diff --git a/docs/badges/coverage-badge.svg b/docs/badges/coverage-badge.svg
index 1024b0e..eb0ef9c 100644
--- a/docs/badges/coverage-badge.svg
+++ b/docs/badges/coverage-badge.svg
@@ -1 +1 @@
-<svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" width="114" height="20" role="img" aria-label="coverage: 88.14%"><title>coverage: 88.14%</title><linearGradient id="s" x2="0" y2="100%"><stop offset="0" stop-color="#bbb" stop-opacity=".1"/><stop offset="1" stop-opacity=".1"/></linearGradient><clipPath id="r"><rect width="114" height="20" rx="3" fill="#fff"/></clipPath><g clip-path="url(#r)"><rect width="61" height="20" fill="#555"/><rect x="61" width="53" height="20" fill="#97ca00"/><rect width="114" height="20" fill="url(#s)"/></g><g fill="#fff" text-anchor="middle" font-family="Verdana,Geneva,DejaVu Sans,sans-serif" text-rendering="geometricPrecision" font-size="110"><text aria-hidden="true" x="315" y="150" fill="#010101" fill-opacity=".3" transform="scale(.1)" textLength="510">coverage</text><text x="315" y="140" transform="scale(.1)" fill="#fff" textLength="510">coverage</text><text aria-hidden="true" x="865" y="150" fill="#010101" fill-opacity=".3" transform="scale(.1)" textLength="430">88.14%</text><text x="865" y="140" transform="scale(.1)" fill="#fff" textLength="430">88.14%</text></g></svg>
\ No newline at end of file
+<svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" width="114" height="20" role="img" aria-label="coverage: 88.97%"><title>coverage: 88.97%</title><linearGradient id="s" x2="0" y2="100%"><stop offset="0" stop-color="#bbb" stop-opacity=".1"/><stop offset="1" stop-opacity=".1"/></linearGradient><clipPath id="r"><rect width="114" height="20" rx="3" fill="#fff"/></clipPath><g clip-path="url(#r)"><rect width="61" height="20" fill="#555"/><rect x="61" width="53" height="20" fill="#97ca00"/><rect width="114" height="20" fill="url(#s)"/></g><g fill="#fff" text-anchor="middle" font-family="Verdana,Geneva,DejaVu Sans,sans-serif" text-rendering="geometricPrecision" font-size="110"><text aria-hidden="true" x="315" y="150" fill="#010101" fill-opacity=".3" transform="scale(.1)" textLength="510">coverage</text><text x="315" y="140" transform="scale(.1)" fill="#fff" textLength="510">coverage</text><text aria-hidden="true" x="865" y="150" fill="#010101" fill-opacity=".3" transform="scale(.1)" textLength="430">88.97%</text><text x="865" y="140" transform="scale(.1)" fill="#fff" textLength="430">88.97%</text></g></svg>
\ No newline at end of file
diff --git a/docs/badges/flake8-badge.svg b/docs/badges/flake8-badge.svg
index 5975b02..cb00fa6 100644
--- a/docs/badges/flake8-badge.svg
+++ b/docs/badges/flake8-badge.svg
@@ -1 +1 @@
-<svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" width="146" height="20" role="img" aria-label="flake8: 1 C, 8941 W, 0 I"><title>flake8: 1 C, 8941 W, 0 I</title><linearGradient id="s" x2="0" y2="100%"><stop offset="0" stop-color="#bbb" stop-opacity=".1"/><stop offset="1" stop-opacity=".1"/></linearGradient><clipPath id="r"><rect width="146" height="20" rx="3" fill="#fff"/></clipPath><g clip-path="url(#r)"><rect width="43" height="20" fill="#555"/><rect x="43" width="103" height="20" fill="#e05d44"/><rect width="146" height="20" fill="url(#s)"/></g><g fill="#fff" text-anchor="middle" font-family="Verdana,Geneva,DejaVu Sans,sans-serif" text-rendering="geometricPrecision" font-size="110"><text aria-hidden="true" x="225" y="150" fill="#010101" fill-opacity=".3" transform="scale(.1)" textLength="330">flake8</text><text x="225" y="140" transform="scale(.1)" fill="#fff" textLength="330">flake8</text><text aria-hidden="true" x="935" y="150" fill="#010101" fill-opacity=".3" transform="scale(.1)" textLength="930">1 C, 8941 W, 0 I</text><text x="935" y="140" transform="scale(.1)" fill="#fff" textLength="930">1 C, 8941 W, 0 I</text></g></svg>
\ No newline at end of file
+<svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" width="146" height="20" role="img" aria-label="flake8: 0 C, 3390 W, 0 I"><title>flake8: 0 C, 3390 W, 0 I</title><linearGradient id="s" x2="0" y2="100%"><stop offset="0" stop-color="#bbb" stop-opacity=".1"/><stop offset="1" stop-opacity=".1"/></linearGradient><clipPath id="r"><rect width="146" height="20" rx="3" fill="#fff"/></clipPath><g clip-path="url(#r)"><rect width="43" height="20" fill="#555"/><rect x="43" width="103" height="20" fill="#fe7d37"/><rect width="146" height="20" fill="url(#s)"/></g><g fill="#fff" text-anchor="middle" font-family="Verdana,Geneva,DejaVu Sans,sans-serif" text-rendering="geometricPrecision" font-size="110"><text aria-hidden="true" x="225" y="150" fill="#010101" fill-opacity=".3" transform="scale(.1)" textLength="330">flake8</text><text x="225" y="140" transform="scale(.1)" fill="#fff" textLength="330">flake8</text><text aria-hidden="true" x="935" y="150" fill="#010101" fill-opacity=".3" transform="scale(.1)" textLength="930">0 C, 3390 W, 0 I</text><text x="935" y="140" transform="scale(.1)" fill="#fff" textLength="930">0 C, 3390 W, 0 I</text></g></svg>
\ No newline at end of file
diff --git a/docs/badges/test-badge.svg b/docs/badges/test-badge.svg
index 63a0abd..51143d6 100644
--- a/docs/badges/test-badge.svg
+++ b/docs/badges/test-badge.svg
@@ -1 +1 @@
-<svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" width="60" height="20" role="img" aria-label="tests: 36"><title>tests: 36</title><linearGradient id="s" x2="0" y2="100%"><stop offset="0" stop-color="#bbb" stop-opacity=".1"/><stop offset="1" stop-opacity=".1"/></linearGradient><clipPath id="r"><rect width="60" height="20" rx="3" fill="#fff"/></clipPath><g clip-path="url(#r)"><rect width="37" height="20" fill="#555"/><rect x="37" width="23" height="20" fill="#4c1"/><rect width="60" height="20" fill="url(#s)"/></g><g fill="#fff" text-anchor="middle" font-family="Verdana,Geneva,DejaVu Sans,sans-serif" text-rendering="geometricPrecision" font-size="110"><text aria-hidden="true" x="195" y="150" fill="#010101" fill-opacity=".3" transform="scale(.1)" textLength="270">tests</text><text x="195" y="140" transform="scale(.1)" fill="#fff" textLength="270">tests</text><text aria-hidden="true" x="475" y="150" fill="#010101" fill-opacity=".3" transform="scale(.1)" textLength="130">36</text><text x="475" y="140" transform="scale(.1)" fill="#fff" textLength="130">36</text></g></svg>
\ No newline at end of file
+<svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" width="60" height="20" role="img" aria-label="tests: 45"><title>tests: 45</title><linearGradient id="s" x2="0" y2="100%"><stop offset="0" stop-color="#bbb" stop-opacity=".1"/><stop offset="1" stop-opacity=".1"/></linearGradient><clipPath id="r"><rect width="60" height="20" rx="3" fill="#fff"/></clipPath><g clip-path="url(#r)"><rect width="37" height="20" fill="#555"/><rect x="37" width="23" height="20" fill="#4c1"/><rect width="60" height="20" fill="url(#s)"/></g><g fill="#fff" text-anchor="middle" font-family="Verdana,Geneva,DejaVu Sans,sans-serif" text-rendering="geometricPrecision" font-size="110"><text aria-hidden="true" x="195" y="150" fill="#010101" fill-opacity=".3" transform="scale(.1)" textLength="270">tests</text><text x="195" y="140" transform="scale(.1)" fill="#fff" textLength="270">tests</text><text aria-hidden="true" x="475" y="150" fill="#010101" fill-opacity=".3" transform="scale(.1)" textLength="130">45</text><text x="475" y="140" transform="scale(.1)" fill="#fff" textLength="130">45</text></g></svg>
\ No newline at end of file
diff --git a/docs/generate_readme_badges.py b/docs/generate_readme_badges.py
index 56f7f5c..b40c359 100644
--- a/docs/generate_readme_badges.py
+++ b/docs/generate_readme_badges.py
@@ -10,71 +10,124 @@
 
 # Documentation will be automatically generated on new version release
 def generate_tests_coverage_badge(cwd: str):
-    run_command([
-        sys.executable, "-m", "coverage", "run", "-m", "unittest",  "discover", "./tests"
-    ],
-        cwd=cwd
+    run_command(
+        [
+            sys.executable,
+            "-m",
+            "coverage",
+            "run",
+            "-m",
+            "unittest",
+            "discover",
+            "./tests",
+        ],
+        cwd=cwd,
     )
-    run_command([
-        sys.executable, "-m", "coverage", "xml", "-o", "./docs/reports/coverage/coverage.xml"
-    ],
-        cwd=cwd
+    run_command(
+        [
+            sys.executable,
+            "-m",
+            "coverage",
+            "xml",
+            "-o",
+            "./docs/reports/coverage/coverage.xml",
+        ],
+        cwd=cwd,
     )
-    run_command([
-        sys.executable, "-m", "coverage", "html", "-d", "./docs/reports/coverage/"
-    ],
-        cwd=cwd
+    run_command(
+        [sys.executable, "-m", "coverage", "html", "-d", "./docs/reports/coverage/"],
+        cwd=cwd,
     )
-    run_command([
-        "genbadge", "coverage", "-i", "./docs/reports/coverage/coverage.xml", "-o", "./docs/badges/coverage-badge.svg"
-    ],
-        cwd=cwd
+    run_command(
+        [
+            "genbadge",
+            "coverage",
+            "-i",
+            "./docs/reports/coverage/coverage.xml",
+            "-o",
+            "./docs/badges/coverage-badge.svg",
+        ],
+        cwd=cwd,
     )
 
 
 def generate_test_badge(cwd: str):
-    test_report_path = pathlib.Path(curr_dir_path / 'reports' / 'junit')
+    test_report_path = pathlib.Path(curr_dir_path / "reports" / "junit")
     shutil.rmtree(test_report_path)
     os.makedirs(test_report_path, exist_ok=True)
-    run_command([
-        sys.executable, "-m", "junitxml.main", "--o", "./docs/reports/junit/junit.xml"
-    ],
-        cwd=cwd
+    run_command(
+        [
+            sys.executable,
+            "-m",
+            "junitxml.main",
+            "--o",
+            "./docs/reports/junit/junit.xml",
+        ],
+        cwd=cwd,
     )
-    run_command([
-        sys.executable, "-m", "junit2htmlreport", "./docs/reports/junit/junit.xml", "./docs/reports/junit/report.html"
-    ],
-        cwd=cwd
+    run_command(
+        [
+            sys.executable,
+            "-m",
+            "junit2htmlreport",
+            "./docs/reports/junit/junit.xml",
+            "./docs/reports/junit/report.html",
+        ],
+        cwd=cwd,
     )
-    run_command([
-        "genbadge", "tests", "-i", "./docs/reports/junit/junit.xml", "-o", "./docs/badges/test-badge.svg"
-    ],
-        cwd=cwd
+    run_command(
+        [
+            "genbadge",
+            "tests",
+            "-i",
+            "./docs/reports/junit/junit.xml",
+            "-o",
+            "./docs/badges/test-badge.svg",
+        ],
+        cwd=cwd,
     )
 
 
 def generate_flake8_badge(cwd: str):
-    run_command([
-        sys.executable, "-m", "flake8", "./rulekit", "--exit-zero", "--format=html", "--htmldir", "./docs/reports/flake8", "--statistics", "--tee", "--output-file", "./docs/reports/flake8/flake8stats.txt"
-    ],
-        cwd=cwd
+    run_command(
+        [
+            sys.executable,
+            "-m",
+            "flake8",
+            "./rulekit",
+            "--exit-zero",
+            "--format=html",
+            "--htmldir",
+            "./docs/reports/flake8",
+            "--statistics",
+            "--tee",
+            "--output-file",
+            "./docs/reports/flake8/flake8stats.txt",
+        ],
+        cwd=cwd,
     )
-    run_command([
-        "genbadge", "flake8", "-i", "./docs/reports/flake8/flake8stats.txt", "-o", "./docs/badges/flake8-badge.svg"
-    ],
-        cwd=cwd
+    run_command(
+        [
+            "genbadge",
+            "flake8",
+            "-i",
+            "./docs/reports/flake8/flake8stats.txt",
+            "-o",
+            "./docs/badges/flake8-badge.svg",
+        ],
+        cwd=cwd,
     )
 
 
 def main():
-    print('Updating badges')
-    cwd = pathlib.Path(curr_dir_path / '..')  # root repo dir
+    print("Updating badges")
+    cwd = pathlib.Path(curr_dir_path / "..")  # root repo dir
 
-    # generate_tests_coverage_badge(cwd)
-    # generate_test_badge(cwd)
+    generate_tests_coverage_badge(cwd)
+    generate_test_badge(cwd)
     generate_flake8_badge(cwd)
 
-    print('Badges generated successfully!')
+    print("Badges generated successfully!")
 
 
 if __name__ == "__main__":
diff --git a/docs/reports/coverage/class_index.html b/docs/reports/coverage/class_index.html
index ba3b712..2a5b9d8 100644
--- a/docs/reports/coverage/class_index.html
+++ b/docs/reports/coverage/class_index.html
@@ -11,7 +11,7 @@
 <header>
     <div class="content">
         <h1>Coverage report:
-            <span class="pc_cov">88%</span>
+            <span class="pc_cov">89%</span>
         </h1>
         <aside id="help_panel_wrapper">
             <input id="help_panel_state" type="checkbox">
@@ -55,7 +55,7 @@ <h2>
         </h2>
         <p class="text">
             <a class="nav" href="https://coverage.readthedocs.io/en/7.6.4">coverage.py v7.6.4</a>,
-            created at 2024-11-08 14:43 +0100
+            created at 2024-11-28 12:33 +0100
         </p>
     </div>
 </header>
@@ -83,42 +83,42 @@ <h2>
             <tr class="region">
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                 <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t38"><data value='RuleGeneratorConfigurator'>RuleGeneratorConfigurator</data></a></td>
-                <td>66</td>
-                <td>14</td>
+                <td>83</td>
+                <td>22</td>
                 <td>0</td>
-                <td class="right" data-ratio="52 66">79%</td>
+                <td class="right" data-ratio="61 83">73%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t166">rulekit\_helpers.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t166"><data value='ExampleSetFactory'>ExampleSetFactory</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t206">rulekit\_helpers.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t206"><data value='ExampleSetFactory'>ExampleSetFactory</data></a></td>
                 <td>65</td>
                 <td>11</td>
                 <td>0</td>
                 <td class="right" data-ratio="54 65">83%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t311">rulekit\_helpers.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t311"><data value='PredictionResultMapper'>PredictionResultMapper</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t351">rulekit\_helpers.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t351"><data value='PredictionResultMapper'>PredictionResultMapper</data></a></td>
                 <td>33</td>
                 <td>4</td>
                 <td>0</td>
                 <td class="right" data-ratio="29 33">88%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t456">rulekit\_helpers.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t456"><data value='ModelSerializer'>ModelSerializer</data></a></td>
-                <td>9</td>
-                <td>0</td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t492">rulekit\_helpers.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t492"><data value='ModelSerializer'>ModelSerializer</data></a></td>
+                <td>11</td>
+                <td>1</td>
                 <td>0</td>
-                <td class="right" data-ratio="9 9">100%</td>
+                <td class="right" data-ratio="10 11">91%</td>
             </tr>
             <tr class="region">
                 <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html">rulekit\_helpers.py</a></td>
                 <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html"><data value=''><span class='no-noun'>(no class)</span></data></a></td>
-                <td>59</td>
+                <td>61</td>
                 <td>0</td>
                 <td>0</td>
-                <td class="right" data-ratio="59 59">100%</td>
+                <td class="right" data-ratio="61 61">100%</td>
             </tr>
             <tr class="region">
                 <td class="name left"><a href="z_a87f2a4bb6695d91__logging_py.html#t1">rulekit\_logging.py</a></td>
@@ -137,16 +137,16 @@ <h2>
                 <td class="right" data-ratio="5 5">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html#t24">rulekit\_operator.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html#t24"><data value='BaseOperator'>BaseOperator</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html#t30">rulekit\_operator.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html#t30"><data value='BaseOperator'>BaseOperator</data></a></td>
                 <td>52</td>
                 <td>10</td>
                 <td>0</td>
                 <td class="right" data-ratio="42 52">81%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html#t196">rulekit\_operator.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html#t196"><data value='ExpertKnowledgeOperator'>ExpertKnowledgeOperator</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html#t202">rulekit\_operator.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html#t202"><data value='ExpertKnowledgeOperator'>ExpertKnowledgeOperator</data></a></td>
                 <td>25</td>
                 <td>1</td>
                 <td>0</td>
@@ -155,10 +155,10 @@ <h2>
             <tr class="region">
                 <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html">rulekit\_operator.py</a></td>
                 <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html"><data value=''><span class='no-noun'>(no class)</span></data></a></td>
-                <td>35</td>
+                <td>44</td>
                 <td>0</td>
                 <td>0</td>
-                <td class="right" data-ratio="35 35">100%</td>
+                <td class="right" data-ratio="44 44">100%</td>
             </tr>
             <tr class="region">
                 <td class="name left"><a href="z_a87f2a4bb6695d91__problem_types_py.html#t4">rulekit\_problem_types.py</a></td>
@@ -185,56 +185,64 @@ <h2>
                 <td class="right" data-ratio="20 23">87%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t22">rulekit\classification.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t22"><data value='ClassificationPredictionMetrics'>ClassificationPredictionMetrics</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t31">rulekit\classification.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t31"><data value='ClassificationPredictionMetrics'>ClassificationPredictionMetrics</data></a></td>
                 <td>0</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="0 0">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t33">rulekit\classification.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t33"><data value='ClassificationParams'>_ClassificationParams</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t42">rulekit\classification.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t42"><data value='ClassificationParams'>_ClassificationParams</data></a></td>
                 <td>0</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="0 0">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t39">rulekit\classification.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t39"><data value='BaseClassifier'>BaseClassifier</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t48">rulekit\classification.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t48"><data value='ClassificationExpertParams'>_ClassificationExpertParams</data></a></td>
+                <td>0</td>
+                <td>0</td>
+                <td>0</td>
+                <td class="right" data-ratio="0 0">100%</td>
+            </tr>
+            <tr class="region">
+                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t52">rulekit\classification.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t52"><data value='BaseClassifier'>BaseClassifier</data></a></td>
                 <td>8</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="8 8">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t47">rulekit\classification.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t47"><data value='MetricTypes'>BaseClassifier.MetricTypes</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t60">rulekit\classification.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t60"><data value='MetricTypes'>BaseClassifier.MetricTypes</data></a></td>
                 <td>0</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="0 0">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t75">rulekit\classification.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t75"><data value='RuleClassifier'>RuleClassifier</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t88">rulekit\classification.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t88"><data value='RuleClassifier'>RuleClassifier</data></a></td>
                 <td>52</td>
-                <td>5</td>
+                <td>3</td>
                 <td>0</td>
-                <td class="right" data-ratio="47 52">90%</td>
+                <td class="right" data-ratio="49 52">94%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t323">rulekit\classification.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t323"><data value='ExpertRuleClassifier'>ExpertRuleClassifier</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t343">rulekit\classification.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t343"><data value='ExpertRuleClassifier'>ExpertRuleClassifier</data></a></td>
                 <td>19</td>
                 <td>2</td>
                 <td>0</td>
                 <td class="right" data-ratio="17 19">89%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t540">rulekit\classification.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t540"><data value='ContrastSetRuleClassifier'>ContrastSetRuleClassifier</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t562">rulekit\classification.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t562"><data value='ContrastSetRuleClassifier'>ContrastSetRuleClassifier</data></a></td>
                 <td>31</td>
                 <td>31</td>
                 <td>0</td>
@@ -243,22 +251,22 @@ <h2>
             <tr class="region">
                 <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html">rulekit\classification.py</a></td>
                 <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html"><data value=''><span class='no-noun'>(no class)</span></data></a></td>
-                <td>63</td>
+                <td>75</td>
                 <td>0</td>
                 <td>0</td>
-                <td class="right" data-ratio="63 63">100%</td>
+                <td class="right" data-ratio="75 75">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_events_py.html#t10">rulekit\events.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_events_py.html#t10"><data value='RuleInductionProgressListener'>RuleInductionProgressListener</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_events_py.html#t14">rulekit\events.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_events_py.html#t14"><data value='RuleInductionProgressListener'>RuleInductionProgressListener</data></a></td>
                 <td>1</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="1 1">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_events_py.html#t53">rulekit\events.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_events_py.html#t53"><data value='CommandListener'>command_listener_factory._CommandListener</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_events_py.html#t61">rulekit\events.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_events_py.html#t61"><data value='CommandListener'>_command_listener_factory._CommandListener</data></a></td>
                 <td>4</td>
                 <td>0</td>
                 <td>0</td>
@@ -267,42 +275,42 @@ <h2>
             <tr class="region">
                 <td class="name left"><a href="z_a87f2a4bb6695d91_events_py.html">rulekit\events.py</a></td>
                 <td class="name left"><a href="z_a87f2a4bb6695d91_events_py.html"><data value=''><span class='no-noun'>(no class)</span></data></a></td>
-                <td>18</td>
+                <td>22</td>
                 <td>0</td>
                 <td>0</td>
-                <td class="right" data-ratio="18 18">100%</td>
+                <td class="right" data-ratio="22 22">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_exceptions_py.html#t7">rulekit\exceptions.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_exceptions_py.html#t7"><data value='RuleKitJavaException'>RuleKitJavaException</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_exceptions_py.html#t8">rulekit\exceptions.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_exceptions_py.html#t8"><data value='RuleKitJavaException'>RuleKitJavaException</data></a></td>
                 <td>5</td>
                 <td>5</td>
                 <td>0</td>
                 <td class="right" data-ratio="0 5">0%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_exceptions_py.html#t47">rulekit\exceptions.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_exceptions_py.html#t47"><data value='RuleKitMisconfigurationException'>RuleKitMisconfigurationException</data></a></td>
-                <td>16</td>
-                <td>16</td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_exceptions_py.html#t48">rulekit\exceptions.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_exceptions_py.html#t48"><data value='RuleKitMisconfigurationException'>RuleKitMisconfigurationException</data></a></td>
+                <td>17</td>
+                <td>17</td>
                 <td>0</td>
-                <td class="right" data-ratio="0 16">0%</td>
+                <td class="right" data-ratio="0 17">0%</td>
             </tr>
             <tr class="region">
                 <td class="name left"><a href="z_a87f2a4bb6695d91_exceptions_py.html">rulekit\exceptions.py</a></td>
                 <td class="name left"><a href="z_a87f2a4bb6695d91_exceptions_py.html"><data value=''><span class='no-noun'>(no class)</span></data></a></td>
-                <td>14</td>
+                <td>15</td>
                 <td>0</td>
                 <td>0</td>
-                <td class="right" data-ratio="14 14">100%</td>
+                <td class="right" data-ratio="15 15">100%</td>
             </tr>
             <tr class="region">
                 <td class="name left"><a href="z_a87f2a4bb6695d91_kaplan_meier_py.html#t7">rulekit\kaplan_meier.py</a></td>
                 <td class="name left"><a href="z_a87f2a4bb6695d91_kaplan_meier_py.html#t7"><data value='KaplanMeierEstimator'>KaplanMeierEstimator</data></a></td>
                 <td>19</td>
-                <td>1</td>
                 <td>0</td>
-                <td class="right" data-ratio="18 19">95%</td>
+                <td>0</td>
+                <td class="right" data-ratio="19 19">100%</td>
             </tr>
             <tr class="region">
                 <td class="name left"><a href="z_a87f2a4bb6695d91_kaplan_meier_py.html">rulekit\kaplan_meier.py</a></td>
@@ -313,16 +321,16 @@ <h2>
                 <td class="right" data-ratio="16 16">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_main_py.html#t19">rulekit\main.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_main_py.html#t19"><data value='JRE_Type'>JRE_Type</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_main_py.html#t21">rulekit\main.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_main_py.html#t21"><data value='JRE_Type'>JRE_Type</data></a></td>
                 <td>0</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="0 0">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_main_py.html#t25">rulekit\main.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_main_py.html#t25"><data value='RuleKit'>RuleKit</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_main_py.html#t27">rulekit\main.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_main_py.html#t27"><data value='RuleKit'>RuleKit</data></a></td>
                 <td>50</td>
                 <td>17</td>
                 <td>0</td>
@@ -331,30 +339,46 @@ <h2>
             <tr class="region">
                 <td class="name left"><a href="z_a87f2a4bb6695d91_main_py.html">rulekit\main.py</a></td>
                 <td class="name left"><a href="z_a87f2a4bb6695d91_main_py.html"><data value=''><span class='no-noun'>(no class)</span></data></a></td>
-                <td>37</td>
+                <td>39</td>
                 <td>0</td>
                 <td>0</td>
-                <td class="right" data-ratio="37 37">100%</td>
+                <td class="right" data-ratio="39 39">100%</td>
+            </tr>
+            <tr class="region">
+                <td class="name left"><a href="z_a87f2a4bb6695d91_params_py.html#t24">rulekit\params.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_params_py.html#t24"><data value='UserMeasure'>_user_defined_measure_factory._UserMeasure</data></a></td>
+                <td>1</td>
+                <td>1</td>
+                <td>0</td>
+                <td class="right" data-ratio="0 1">0%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_params_py.html#t12">rulekit\params.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_params_py.html#t12"><data value='Measures'>Measures</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_params_py.html#t35">rulekit\params.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_params_py.html#t35"><data value='Measures'>Measures</data></a></td>
                 <td>0</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="0 0">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_params_py.html#t96">rulekit\params.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_params_py.html#t96"><data value='ModelsParams'>ModelsParams</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_params_py.html#t121">rulekit\params.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_params_py.html#t121"><data value='ModelsParams'>ModelsParams</data></a></td>
                 <td>0</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="0 0">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_params_py.html#t122">rulekit\params.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_params_py.html#t122"><data value='ContrastSetModelParams'>ContrastSetModelParams</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_params_py.html#t137">rulekit\params.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_params_py.html#t137"><data value='ExpertModelParams'>ExpertModelParams</data></a></td>
+                <td>0</td>
+                <td>0</td>
+                <td>0</td>
+                <td class="right" data-ratio="0 0">100%</td>
+            </tr>
+            <tr class="region">
+                <td class="name left"><a href="z_a87f2a4bb6695d91_params_py.html#t149">rulekit\params.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_params_py.html#t149"><data value='ContrastSetModelParams'>ContrastSetModelParams</data></a></td>
                 <td>0</td>
                 <td>0</td>
                 <td>0</td>
@@ -363,38 +387,46 @@ <h2>
             <tr class="region">
                 <td class="name left"><a href="z_a87f2a4bb6695d91_params_py.html">rulekit\params.py</a></td>
                 <td class="name left"><a href="z_a87f2a4bb6695d91_params_py.html"><data value=''><span class='no-noun'>(no class)</span></data></a></td>
-                <td>73</td>
+                <td>87</td>
+                <td>6</td>
+                <td>0</td>
+                <td class="right" data-ratio="81 87">93%</td>
+            </tr>
+            <tr class="region">
+                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t27">rulekit\regression.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t27"><data value='RegressionModelParams'>_RegressionModelParams</data></a></td>
                 <td>0</td>
                 <td>0</td>
-                <td class="right" data-ratio="73 73">100%</td>
+                <td>0</td>
+                <td class="right" data-ratio="0 0">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t20">rulekit\regression.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t20"><data value='RegressionParams'>_RegressionParams</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t31">rulekit\regression.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t31"><data value='RegressionExpertModelParams'>_RegressionExpertModelParams</data></a></td>
                 <td>0</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="0 0">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t24">rulekit\regression.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t24"><data value='RuleRegressor'>RuleRegressor</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t35">rulekit\regression.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t35"><data value='RuleRegressor'>RuleRegressor</data></a></td>
                 <td>15</td>
                 <td>3</td>
                 <td>0</td>
                 <td class="right" data-ratio="12 15">80%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t169">rulekit\regression.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t169"><data value='ExpertRuleRegressor'>ExpertRuleRegressor</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t180">rulekit\regression.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t180"><data value='ExpertRuleRegressor'>ExpertRuleRegressor</data></a></td>
                 <td>7</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="7 7">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t345">rulekit\regression.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t345"><data value='ContrastSetRuleRegressor'>ContrastSetRuleRegressor</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t356">rulekit\regression.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t356"><data value='ContrastSetRuleRegressor'>ContrastSetRuleRegressor</data></a></td>
                 <td>13</td>
                 <td>13</td>
                 <td>0</td>
@@ -403,54 +435,54 @@ <h2>
             <tr class="region">
                 <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html">rulekit\regression.py</a></td>
                 <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html"><data value=''><span class='no-noun'>(no class)</span></data></a></td>
-                <td>37</td>
+                <td>47</td>
                 <td>0</td>
                 <td>0</td>
-                <td class="right" data-ratio="37 37">100%</td>
+                <td class="right" data-ratio="47 47">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t13">rulekit\rules.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t13"><data value='InductionParameters'>InductionParameters</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t16">rulekit\rules.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t16"><data value='InductionParameters'>InductionParameters</data></a></td>
                 <td>14</td>
                 <td>14</td>
                 <td>0</td>
                 <td class="right" data-ratio="0 14">0%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t61">rulekit\rules.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t61"><data value='BaseRule'>BaseRule</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t64">rulekit\rules.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t64"><data value='BaseRule'>BaseRule</data></a></td>
                 <td>14</td>
                 <td>2</td>
                 <td>0</td>
                 <td class="right" data-ratio="12 14">86%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t130">rulekit\rules.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t130"><data value='ClassificationRule'>ClassificationRule</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t133">rulekit\rules.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t133"><data value='ClassificationRule'>ClassificationRule</data></a></td>
                 <td>3</td>
                 <td>1</td>
                 <td>0</td>
                 <td class="right" data-ratio="2 3">67%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t146">rulekit\rules.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t146"><data value='RegressionRule'>RegressionRule</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t149">rulekit\rules.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t149"><data value='RegressionRule'>RegressionRule</data></a></td>
                 <td>3</td>
                 <td>1</td>
                 <td>0</td>
                 <td class="right" data-ratio="2 3">67%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t163">rulekit\rules.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t163"><data value='SurvivalRule'>SurvivalRule</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t166">rulekit\rules.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t166"><data value='SurvivalRule'>SurvivalRule</data></a></td>
                 <td>3</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="3 3">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t192">rulekit\rules.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t192"><data value='RuleSet'>RuleSet</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t196">rulekit\rules.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t196"><data value='RuleSet'>RuleSet</data></a></td>
                 <td>30</td>
                 <td>3</td>
                 <td>0</td>
@@ -459,10 +491,10 @@ <h2>
             <tr class="region">
                 <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html">rulekit\rules.py</a></td>
                 <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html"><data value=''><span class='no-noun'>(no class)</span></data></a></td>
-                <td>82</td>
+                <td>85</td>
                 <td>0</td>
                 <td>0</td>
-                <td class="right" data-ratio="82 82">100%</td>
+                <td class="right" data-ratio="85 85">100%</td>
             </tr>
             <tr class="region">
                 <td class="name left"><a href="z_a87f2a4bb6695d91_stats_py.html#t5">rulekit\stats.py</a></td>
@@ -489,44 +521,60 @@ <h2>
                 <td class="right" data-ratio="7 7">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t21">rulekit\survival.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t21"><data value='SurvivalModelsParams'>SurvivalModelsParams</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t23">rulekit\survival.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t23"><data value='SurvivalModelsParams'>_SurvivalModelsParams</data></a></td>
                 <td>0</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="0 0">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t42">rulekit\survival.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t42"><data value='SurvivalRules'>SurvivalRules</data></a></td>
-                <td>37</td>
-                <td>22</td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t34">rulekit\survival.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t34"><data value='SurvivalExpertModelParams'>_SurvivalExpertModelParams</data></a></td>
+                <td>0</td>
                 <td>0</td>
-                <td class="right" data-ratio="15 37">41%</td>
+                <td>0</td>
+                <td class="right" data-ratio="0 0">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t234">rulekit\survival.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t234"><data value='ExpertSurvivalRules'>ExpertSurvivalRules</data></a></td>
-                <td>11</td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t38">rulekit\survival.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t38"><data value='BaseSurvivalRulesModel'>_BaseSurvivalRulesModel</data></a></td>
+                <td>1</td>
                 <td>0</td>
                 <td>0</td>
-                <td class="right" data-ratio="11 11">100%</td>
+                <td class="right" data-ratio="1 1">100%</td>
+            </tr>
+            <tr class="region">
+                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t53">rulekit\survival.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t53"><data value='SurvivalRules'>SurvivalRules</data></a></td>
+                <td>38</td>
+                <td>8</td>
+                <td>0</td>
+                <td class="right" data-ratio="30 38">79%</td>
+            </tr>
+            <tr class="region">
+                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t246">rulekit\survival.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t246"><data value='ExpertSurvivalRules'>ExpertSurvivalRules</data></a></td>
+                <td>12</td>
+                <td>0</td>
+                <td>0</td>
+                <td class="right" data-ratio="12 12">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t396">rulekit\survival.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t396"><data value='SurvivalContrastSetModelParams'>SurvivalContrastSetModelParams</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t409">rulekit\survival.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t409"><data value='SurvivalContrastSetModelParams'>_SurvivalContrastSetModelParams</data></a></td>
                 <td>0</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="0 0">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t401">rulekit\survival.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t401"><data value='ContrastSetSurvivalRules'>ContrastSetSurvivalRules</data></a></td>
-                <td>15</td>
-                <td>15</td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t413">rulekit\survival.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t413"><data value='ContrastSetSurvivalRules'>ContrastSetSurvivalRules</data></a></td>
+                <td>16</td>
+                <td>16</td>
                 <td>0</td>
-                <td class="right" data-ratio="0 15">0%</td>
+                <td class="right" data-ratio="0 16">0%</td>
             </tr>
             <tr class="region">
                 <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html">rulekit\survival.py</a></td>
@@ -547,66 +595,66 @@ <h2>
             <tr class="region">
                 <td class="name left"><a href="z_a44f0ac069e85531_test_classifier_py.html#t21">tests\test_classifier.py</a></td>
                 <td class="name left"><a href="z_a44f0ac069e85531_test_classifier_py.html#t21"><data value='TestClassifier'>TestClassifier</data></a></td>
-                <td>92</td>
+                <td>106</td>
                 <td>0</td>
                 <td>0</td>
-                <td class="right" data-ratio="92 92">100%</td>
+                <td class="right" data-ratio="106 106">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a44f0ac069e85531_test_classifier_py.html#t42">tests\test_classifier.py</a></td>
-                <td class="name left"><a href="z_a44f0ac069e85531_test_classifier_py.html#t42"><data value='EventListener'>TestClassifier.test_induction_progress_listener.EventListener</data></a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_classifier_py.html#t43">tests\test_classifier.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_classifier_py.html#t43"><data value='EventListener'>TestClassifier.test_induction_progress_listener.EventListener</data></a></td>
                 <td>6</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="6 6">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a44f0ac069e85531_test_classifier_py.html#t198">tests\test_classifier.py</a></td>
-                <td class="name left"><a href="z_a44f0ac069e85531_test_classifier_py.html#t198"><data value='TestExperClassifier'>TestExperClassifier</data></a></td>
-                <td>28</td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_classifier_py.html#t234">tests\test_classifier.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_classifier_py.html#t234"><data value='TestExperClassifier'>TestExperClassifier</data></a></td>
+                <td>34</td>
                 <td>0</td>
                 <td>0</td>
-                <td class="right" data-ratio="28 28">100%</td>
+                <td class="right" data-ratio="34 34">100%</td>
             </tr>
             <tr class="region">
                 <td class="name left"><a href="z_a44f0ac069e85531_test_classifier_py.html">tests\test_classifier.py</a></td>
                 <td class="name left"><a href="z_a44f0ac069e85531_test_classifier_py.html"><data value=''><span class='no-noun'>(no class)</span></data></a></td>
-                <td>33</td>
+                <td>35</td>
                 <td>1</td>
                 <td>0</td>
-                <td class="right" data-ratio="32 33">97%</td>
+                <td class="right" data-ratio="34 35">97%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a44f0ac069e85531_test_regression_py.html#t18">tests\test_regression.py</a></td>
-                <td class="name left"><a href="z_a44f0ac069e85531_test_regression_py.html#t18"><data value='TestRegressor'>TestRegressor</data></a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_regression_py.html#t21">tests\test_regression.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_regression_py.html#t21"><data value='TestRegressor'>TestRegressor</data></a></td>
                 <td>47</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="47 47">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a44f0ac069e85531_test_regression_py.html#t31">tests\test_regression.py</a></td>
-                <td class="name left"><a href="z_a44f0ac069e85531_test_regression_py.html#t31"><data value='EventListener'>TestRegressor.test_induction_progress_listener.EventListener</data></a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_regression_py.html#t34">tests\test_regression.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_regression_py.html#t34"><data value='EventListener'>TestRegressor.test_induction_progress_listener.EventListener</data></a></td>
                 <td>10</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="10 10">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a44f0ac069e85531_test_regression_py.html#t123">tests\test_regression.py</a></td>
-                <td class="name left"><a href="z_a44f0ac069e85531_test_regression_py.html#t123"><data value='TestExpertRegressor'>TestExpertRegressor</data></a></td>
-                <td>12</td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_regression_py.html#t125">tests\test_regression.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_regression_py.html#t125"><data value='TestExpertRegressor'>TestExpertRegressor</data></a></td>
+                <td>28</td>
                 <td>0</td>
                 <td>0</td>
-                <td class="right" data-ratio="12 12">100%</td>
+                <td class="right" data-ratio="28 28">100%</td>
             </tr>
             <tr class="region">
                 <td class="name left"><a href="z_a44f0ac069e85531_test_regression_py.html">tests\test_regression.py</a></td>
                 <td class="name left"><a href="z_a44f0ac069e85531_test_regression_py.html"><data value=''><span class='no-noun'>(no class)</span></data></a></td>
-                <td>25</td>
+                <td>31</td>
                 <td>1</td>
                 <td>0</td>
-                <td class="right" data-ratio="24 25">96%</td>
+                <td class="right" data-ratio="30 31">97%</td>
             </tr>
             <tr class="region">
                 <td class="name left"><a href="z_a44f0ac069e85531_test_rulekit_py.html#t8">tests\test_rulekit.py</a></td>
@@ -673,48 +721,48 @@ <h2>
                 <td class="right" data-ratio="10 11">91%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a44f0ac069e85531_test_survival_py.html#t15">tests\test_survival.py</a></td>
-                <td class="name left"><a href="z_a44f0ac069e85531_test_survival_py.html#t15"><data value='TestKaplanMeierEstimator'>TestKaplanMeierEstimator</data></a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_survival_py.html#t17">tests\test_survival.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_survival_py.html#t17"><data value='TestKaplanMeierEstimator'>TestKaplanMeierEstimator</data></a></td>
                 <td>9</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="9 9">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a44f0ac069e85531_test_survival_py.html#t54">tests\test_survival.py</a></td>
-                <td class="name left"><a href="z_a44f0ac069e85531_test_survival_py.html#t54"><data value='TestSurvivalRules'>TestSurvivalRules</data></a></td>
-                <td>35</td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_survival_py.html#t59">tests\test_survival.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_survival_py.html#t59"><data value='TestSurvivalRules'>TestSurvivalRules</data></a></td>
+                <td>64</td>
                 <td>0</td>
                 <td>0</td>
-                <td class="right" data-ratio="35 35">100%</td>
+                <td class="right" data-ratio="64 64">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a44f0ac069e85531_test_survival_py.html#t63">tests\test_survival.py</a></td>
-                <td class="name left"><a href="z_a44f0ac069e85531_test_survival_py.html#t63"><data value='EventListener'>TestSurvivalRules.test_induction_progress_listener.EventListener</data></a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_survival_py.html#t67">tests\test_survival.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_survival_py.html#t67"><data value='EventListener'>TestSurvivalRules.test_induction_progress_listener.EventListener</data></a></td>
                 <td>6</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="6 6">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a44f0ac069e85531_test_survival_py.html#t124">tests\test_survival.py</a></td>
-                <td class="name left"><a href="z_a44f0ac069e85531_test_survival_py.html#t124"><data value='TestExpertSurvivalLogRankTree'>TestExpertSurvivalLogRankTree</data></a></td>
-                <td>11</td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_survival_py.html#t187">tests\test_survival.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_survival_py.html#t187"><data value='TestExpertSurvivalRules'>TestExpertSurvivalRules</data></a></td>
+                <td>19</td>
                 <td>0</td>
                 <td>0</td>
-                <td class="right" data-ratio="11 11">100%</td>
+                <td class="right" data-ratio="19 19">100%</td>
             </tr>
             <tr class="region">
                 <td class="name left"><a href="z_a44f0ac069e85531_test_survival_py.html">tests\test_survival.py</a></td>
                 <td class="name left"><a href="z_a44f0ac069e85531_test_survival_py.html"><data value=''><span class='no-noun'>(no class)</span></data></a></td>
-                <td>26</td>
+                <td>32</td>
                 <td>1</td>
                 <td>0</td>
-                <td class="right" data-ratio="25 26">96%</td>
+                <td class="right" data-ratio="31 32">97%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t36">tests\utils.py</a></td>
-                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t36"><data value='ExampleSetWrapper'>ExampleSetWrapper</data></a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t34">tests\utils.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t34"><data value='ExampleSetWrapper'>ExampleSetWrapper</data></a></td>
                 <td>4</td>
                 <td>1</td>
                 <td>0</td>
@@ -745,48 +793,48 @@ <h2>
                 <td class="right" data-ratio="20 20">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t122">tests\utils.py</a></td>
-                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t122"><data value='DataSetConfig'>DataSetConfig</data></a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t120">tests\utils.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t120"><data value='DataSetConfig'>DataSetConfig</data></a></td>
                 <td>4</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="4 4">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t131">tests\utils.py</a></td>
-                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t131"><data value='TestConfig'>TestConfig</data></a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t129">tests\utils.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t129"><data value='TestConfig'>TestConfig</data></a></td>
                 <td>3</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="3 3">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t139">tests\utils.py</a></td>
-                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t139"><data value='TestConfigParser'>TestConfigParser</data></a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t137">tests\utils.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t137"><data value='TestConfigParser'>TestConfigParser</data></a></td>
                 <td>62</td>
                 <td>6</td>
                 <td>0</td>
                 <td class="right" data-ratio="56 62">90%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t255">tests\utils.py</a></td>
-                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t255"><data value='TestCaseFactory'>TestCaseFactory</data></a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t249">tests\utils.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t249"><data value='TestCaseFactory'>TestCaseFactory</data></a></td>
                 <td>50</td>
                 <td>2</td>
                 <td>0</td>
                 <td class="right" data-ratio="48 50">96%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t341">tests\utils.py</a></td>
-                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t341"><data value='TestReportReader'>TestReportReader</data></a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t347">tests\utils.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t347"><data value='TestReportReader'>TestReportReader</data></a></td>
                 <td>20</td>
                 <td>2</td>
                 <td>0</td>
                 <td class="right" data-ratio="18 20">90%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t375">tests\utils.py</a></td>
-                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t375"><data value='TestReportWriter'>TestReportWriter</data></a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t382">tests\utils.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t382"><data value='TestReportWriter'>TestReportWriter</data></a></td>
                 <td>8</td>
                 <td>8</td>
                 <td>0</td>
@@ -795,20 +843,20 @@ <h2>
             <tr class="region">
                 <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html">tests\utils.py</a></td>
                 <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html"><data value=''><span class='no-noun'>(no class)</span></data></a></td>
-                <td>146</td>
-                <td>12</td>
+                <td>147</td>
+                <td>13</td>
                 <td>0</td>
-                <td class="right" data-ratio="134 146">92%</td>
+                <td class="right" data-ratio="134 147">91%</td>
             </tr>
         </tbody>
         <tfoot>
             <tr class="total">
                 <td class="name left">Total</td>
                 <td class="name left">&nbsp;</td>
-                <td>2006</td>
-                <td>238</td>
+                <td>2176</td>
+                <td>240</td>
                 <td>0</td>
-                <td class="right" data-ratio="1768 2006">88%</td>
+                <td class="right" data-ratio="1936 2176">89%</td>
             </tr>
         </tfoot>
     </table>
@@ -820,7 +868,7 @@ <h2>
     <div class="content">
         <p>
             <a class="nav" href="https://coverage.readthedocs.io/en/7.6.4">coverage.py v7.6.4</a>,
-            created at 2024-11-08 14:43 +0100
+            created at 2024-11-28 12:33 +0100
         </p>
     </div>
     <aside class="hidden">
diff --git a/docs/reports/coverage/function_index.html b/docs/reports/coverage/function_index.html
index ff33130..93d7f27 100644
--- a/docs/reports/coverage/function_index.html
+++ b/docs/reports/coverage/function_index.html
@@ -11,7 +11,7 @@
 <header>
     <div class="content">
         <h1>Coverage report:
-            <span class="pc_cov">88%</span>
+            <span class="pc_cov">89%</span>
         </h1>
         <aside id="help_panel_wrapper">
             <input id="help_panel_state" type="checkbox">
@@ -55,7 +55,7 @@ <h2>
         </h2>
         <p class="text">
             <a class="nav" href="https://coverage.readthedocs.io/en/7.6.4">coverage.py v7.6.4</a>,
-            created at 2024-11-08 14:43 +0100
+            created at 2024-11-28 12:33 +0100
         </p>
     </div>
 </header>
@@ -81,220 +81,236 @@ <h2>
                 <td class="right" data-ratio="4 4">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t20">rulekit\_helpers.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t20"><data value='get_rule_generator'>get_rule_generator</data></a></td>
-                <td>4</td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t21">rulekit\_helpers.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t21"><data value='get_rule_generator'>get_rule_generator</data></a></td>
+                <td>3</td>
                 <td>0</td>
                 <td>0</td>
-                <td class="right" data-ratio="4 4">100%</td>
+                <td class="right" data-ratio="3 3">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t42">rulekit\_helpers.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t42"><data value='init__'>RuleGeneratorConfigurator.__init__</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t48">rulekit\_helpers.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t48"><data value='init__'>RuleGeneratorConfigurator.__init__</data></a></td>
                 <td>2</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="2 2">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t46">rulekit\_helpers.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t46"><data value='configure'>RuleGeneratorConfigurator.configure</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t52">rulekit\_helpers.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t52"><data value='configure'>RuleGeneratorConfigurator.configure</data></a></td>
                 <td>4</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="4 4">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t57">rulekit\_helpers.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t57"><data value='configure_expert_parameter'>RuleGeneratorConfigurator._configure_expert_parameter</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t63">rulekit\_helpers.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t63"><data value='configure_expert_parameter'>RuleGeneratorConfigurator._configure_expert_parameter</data></a></td>
                 <td>16</td>
                 <td>7</td>
                 <td>0</td>
                 <td class="right" data-ratio="9 16">56%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t78">rulekit\_helpers.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t78"><data value='configure_simple_parameter'>RuleGeneratorConfigurator._configure_simple_parameter</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t87">rulekit\_helpers.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t87"><data value='configure_simple_parameter'>RuleGeneratorConfigurator._configure_simple_parameter</data></a></td>
                 <td>8</td>
+                <td>1</td>
                 <td>0</td>
+                <td class="right" data-ratio="7 8">88%</td>
+            </tr>
+            <tr class="region">
+                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t97">rulekit\_helpers.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t97"><data value='configure_measure_parameter'>RuleGeneratorConfigurator._configure_measure_parameter</data></a></td>
+                <td>5</td>
+                <td>1</td>
                 <td>0</td>
-                <td class="right" data-ratio="8 8">100%</td>
+                <td class="right" data-ratio="4 5">80%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t88">rulekit\_helpers.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t88"><data value='configure_measure_parameter'>RuleGeneratorConfigurator._configure_measure_parameter</data></a></td>
-                <td>6</td>
-                <td>2</td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t106">rulekit\_helpers.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t106"><data value='configure_user_defined_measure_parameter'>RuleGeneratorConfigurator._configure_user_defined_measure_parameter</data></a></td>
+                <td>4</td>
+                <td>4</td>
                 <td>0</td>
-                <td class="right" data-ratio="4 6">67%</td>
+                <td class="right" data-ratio="0 4">0%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t97">rulekit\_helpers.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t97"><data value='configure_rule_generator'>RuleGeneratorConfigurator._configure_rule_generator</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t119">rulekit\_helpers.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t119"><data value='configure_rule_generator'>RuleGeneratorConfigurator._configure_rule_generator</data></a></td>
                 <td>7</td>
                 <td>1</td>
                 <td>0</td>
                 <td class="right" data-ratio="6 7">86%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t110">rulekit\_helpers.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t110"><data value='validate_rule_generator_parameters'>RuleGeneratorConfigurator._validate_rule_generator_parameters</data></a></td>
-                <td>19</td>
-                <td>3</td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t133">rulekit\_helpers.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t133"><data value='validate_rule_generator_parameters'>RuleGeneratorConfigurator._validate_rule_generator_parameters</data></a></td>
+                <td>20</td>
+                <td>5</td>
                 <td>0</td>
-                <td class="right" data-ratio="16 19">84%</td>
+                <td class="right" data-ratio="15 20">75%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t155">rulekit\_helpers.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t155"><data value='configure_java_logging'>RuleGeneratorConfigurator._configure_java_logging</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t146">rulekit\_helpers.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t146"><data value='are_params_equal'>RuleGeneratorConfigurator._validate_rule_generator_parameters.are_params_equal</data></a></td>
+                <td>13</td>
+                <td>2</td>
+                <td>0</td>
+                <td class="right" data-ratio="11 13">85%</td>
+            </tr>
+            <tr class="region">
+                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t195">rulekit\_helpers.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t195"><data value='configure_java_logging'>RuleGeneratorConfigurator._configure_java_logging</data></a></td>
                 <td>4</td>
                 <td>1</td>
                 <td>0</td>
                 <td class="right" data-ratio="3 4">75%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t172">rulekit\_helpers.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t172"><data value='init__'>ExampleSetFactory.__init__</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t212">rulekit\_helpers.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t212"><data value='init__'>ExampleSetFactory.__init__</data></a></td>
                 <td>7</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="7 7">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t181">rulekit\_helpers.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t181"><data value='make'>ExampleSetFactory.make</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t221">rulekit\_helpers.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t221"><data value='make'>ExampleSetFactory.make</data></a></td>
                 <td>8</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="8 8">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t209">rulekit\_helpers.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t209"><data value='sanitize_y'>ExampleSetFactory._sanitize_y</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t249">rulekit\_helpers.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t249"><data value='sanitize_y'>ExampleSetFactory._sanitize_y</data></a></td>
                 <td>15</td>
                 <td>1</td>
                 <td>0</td>
                 <td class="right" data-ratio="14 15">93%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t233">rulekit\_helpers.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t233"><data value='sanitize_X'>ExampleSetFactory._sanitize_X</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t270">rulekit\_helpers.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t270"><data value='sanitize_X'>ExampleSetFactory._sanitize_X</data></a></td>
                 <td>8</td>
                 <td>1</td>
                 <td>0</td>
                 <td class="right" data-ratio="7 8">88%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t254">rulekit\_helpers.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t254"><data value='validate_X'>ExampleSetFactory._validate_X</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t291">rulekit\_helpers.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t291"><data value='validate_X'>ExampleSetFactory._validate_X</data></a></td>
                 <td>2</td>
                 <td>1</td>
                 <td>0</td>
                 <td class="right" data-ratio="1 2">50%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t261">rulekit\_helpers.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t261"><data value='validate_y'>ExampleSetFactory._validate_y</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t298">rulekit\_helpers.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t298"><data value='validate_y'>ExampleSetFactory._validate_y</data></a></td>
                 <td>2</td>
                 <td>1</td>
                 <td>0</td>
                 <td class="right" data-ratio="1 2">50%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t268">rulekit\_helpers.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t268"><data value='create_example_set'>ExampleSetFactory._create_example_set</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t305">rulekit\_helpers.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t305"><data value='create_example_set'>ExampleSetFactory._create_example_set</data></a></td>
                 <td>15</td>
                 <td>4</td>
                 <td>0</td>
                 <td class="right" data-ratio="11 15">73%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t295">rulekit\_helpers.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t295"><data value='wrap_training_example_set'>ExampleSetFactory._wrap_training_example_set</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t334">rulekit\_helpers.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t334"><data value='wrap_training_example_set'>ExampleSetFactory._wrap_training_example_set</data></a></td>
                 <td>3</td>
                 <td>3</td>
                 <td>0</td>
                 <td class="right" data-ratio="0 3">0%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t302">rulekit\_helpers.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t302"><data value='prepare_data'>ExampleSetFactory._prepare_data</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t342">rulekit\_helpers.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t342"><data value='prepare_data'>ExampleSetFactory._prepare_data</data></a></td>
                 <td>5</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="5 5">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t319">rulekit\_helpers.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t319"><data value='map_confidence'>PredictionResultMapper.map_confidence</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t358">rulekit\_helpers.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t358"><data value='map_confidence'>PredictionResultMapper.map_confidence</data></a></td>
                 <td>6</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="6 6">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t349">rulekit\_helpers.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t349"><data value='map'>PredictionResultMapper.map</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t384">rulekit\_helpers.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t384"><data value='map'>PredictionResultMapper.map</data></a></td>
                 <td>4</td>
                 <td>4</td>
                 <td>0</td>
                 <td class="right" data-ratio="0 4">0%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t367">rulekit\_helpers.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t367"><data value='map_to_nominal'>PredictionResultMapper.map_to_nominal</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t401">rulekit\_helpers.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t401"><data value='map_to_nominal'>PredictionResultMapper.map_to_nominal</data></a></td>
                 <td>2</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="2 2">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t388">rulekit\_helpers.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t388"><data value='map_to_numerical'>PredictionResultMapper.map_to_numerical</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t423">rulekit\_helpers.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t423"><data value='map_to_numerical'>PredictionResultMapper.map_to_numerical</data></a></td>
                 <td>7</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="7 7">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t420">rulekit\_helpers.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t420"><data value='map_survival'>PredictionResultMapper.map_survival</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t455">rulekit\_helpers.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t455"><data value='map_survival'>PredictionResultMapper.map_survival</data></a></td>
                 <td>13</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="13 13">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t452">rulekit\_helpers.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t452"><data value='get_column_by_role'>PredictionResultMapper._get_column_by_role</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t488">rulekit\_helpers.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t488"><data value='get_column_by_role'>PredictionResultMapper._get_column_by_role</data></a></td>
                 <td>1</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="1 1">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t461">rulekit\_helpers.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t461"><data value='serialize'>ModelSerializer.serialize</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t496">rulekit\_helpers.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t496"><data value='serialize'>ModelSerializer.serialize</data></a></td>
                 <td>5</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="5 5">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t474">rulekit\_helpers.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t474"><data value='deserialize'>ModelSerializer.deserialize</data></a></td>
-                <td>4</td>
-                <td>0</td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t509">rulekit\_helpers.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html#t509"><data value='deserialize'>ModelSerializer.deserialize</data></a></td>
+                <td>6</td>
+                <td>1</td>
                 <td>0</td>
-                <td class="right" data-ratio="4 4">100%</td>
+                <td class="right" data-ratio="5 6">83%</td>
             </tr>
             <tr class="region">
                 <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html">rulekit\_helpers.py</a></td>
                 <td class="name left"><a href="z_a87f2a4bb6695d91__helpers_py.html"><data value=''><span class='no-noun'>(no function)</span></data></a></td>
-                <td>55</td>
+                <td>58</td>
                 <td>0</td>
                 <td>0</td>
-                <td class="right" data-ratio="55 55">100%</td>
+                <td class="right" data-ratio="58 58">100%</td>
             </tr>
             <tr class="region">
                 <td class="name left"><a href="z_a87f2a4bb6695d91__logging_py.html#t10">rulekit\_logging.py</a></td>
@@ -321,152 +337,152 @@ <h2>
                 <td class="right" data-ratio="5 5">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html#t30">rulekit\_operator.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html#t30"><data value='init__'>BaseOperator.__init__</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html#t36">rulekit\_operator.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html#t36"><data value='init__'>BaseOperator.__init__</data></a></td>
                 <td>5</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="5 5">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html#t37">rulekit\_operator.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html#t37"><data value='initialize_rulekit'>BaseOperator._initialize_rulekit</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html#t43">rulekit\_operator.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html#t43"><data value='initialize_rulekit'>BaseOperator._initialize_rulekit</data></a></td>
                 <td>2</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="2 2">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html#t41">rulekit\_operator.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html#t41"><data value='map_result'>BaseOperator._map_result</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html#t47">rulekit\_operator.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html#t47"><data value='map_result'>BaseOperator._map_result</data></a></td>
                 <td>1</td>
                 <td>1</td>
                 <td>0</td>
                 <td class="right" data-ratio="0 1">0%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html#t44">rulekit\_operator.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html#t44"><data value='validate_contrast_attribute'>BaseOperator._validate_contrast_attribute</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html#t50">rulekit\_operator.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html#t50"><data value='validate_contrast_attribute'>BaseOperator._validate_contrast_attribute</data></a></td>
                 <td>5</td>
                 <td>3</td>
                 <td>0</td>
                 <td class="right" data-ratio="2 5">40%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html#t58">rulekit\_operator.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html#t58"><data value='fit'>BaseOperator.fit</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html#t64">rulekit\_operator.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html#t64"><data value='fit'>BaseOperator.fit</data></a></td>
                 <td>5</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="5 5">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html#t77">rulekit\_operator.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html#t77"><data value='predict'>BaseOperator.predict</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html#t83">rulekit\_operator.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html#t83"><data value='predict'>BaseOperator.predict</data></a></td>
                 <td>4</td>
                 <td>1</td>
                 <td>0</td>
                 <td class="right" data-ratio="3 4">75%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html#t84">rulekit\_operator.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html#t84"><data value='get_params'>BaseOperator.get_params</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html#t90">rulekit\_operator.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html#t90"><data value='get_params'>BaseOperator.get_params</data></a></td>
                 <td>1</td>
                 <td>1</td>
                 <td>0</td>
                 <td class="right" data-ratio="0 1">0%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html#t98">rulekit\_operator.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html#t98"><data value='set_params'>BaseOperator.set_params</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html#t104">rulekit\_operator.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html#t104"><data value='set_params'>BaseOperator.set_params</data></a></td>
                 <td>7</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="7 7">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html#t112">rulekit\_operator.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html#t112"><data value='get_metadata_routing'>BaseOperator.get_metadata_routing</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html#t118">rulekit\_operator.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html#t118"><data value='get_metadata_routing'>BaseOperator.get_metadata_routing</data></a></td>
                 <td>1</td>
                 <td>1</td>
                 <td>0</td>
                 <td class="right" data-ratio="0 1">0%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html#t123">rulekit\_operator.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html#t123"><data value='get_coverage_matrix'>BaseOperator.get_coverage_matrix</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html#t129">rulekit\_operator.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html#t129"><data value='get_coverage_matrix'>BaseOperator.get_coverage_matrix</data></a></td>
                 <td>11</td>
                 <td>2</td>
                 <td>0</td>
                 <td class="right" data-ratio="9 11">82%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html#t154">rulekit\_operator.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html#t154"><data value='add_event_listener'>BaseOperator.add_event_listener</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html#t160">rulekit\_operator.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html#t160"><data value='add_event_listener'>BaseOperator.add_event_listener</data></a></td>
                 <td>2</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="2 2">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html#t175">rulekit\_operator.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html#t175"><data value='getstate__'>BaseOperator.__getstate__</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html#t181">rulekit\_operator.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html#t181"><data value='getstate__'>BaseOperator.__getstate__</data></a></td>
                 <td>3</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="3 3">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html#t183">rulekit\_operator.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html#t183"><data value='setstate__'>BaseOperator.__setstate__</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html#t189">rulekit\_operator.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html#t189"><data value='setstate__'>BaseOperator.__setstate__</data></a></td>
                 <td>3</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="3 3">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html#t188">rulekit\_operator.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html#t188"><data value='get_rule_generator'>BaseOperator._get_rule_generator</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html#t194">rulekit\_operator.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html#t194"><data value='get_rule_generator'>BaseOperator._get_rule_generator</data></a></td>
                 <td>1</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="1 1">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html#t192">rulekit\_operator.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html#t192"><data value='get_problem_type'>BaseOperator._get_problem_type</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html#t198">rulekit\_operator.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html#t198"><data value='get_problem_type'>BaseOperator._get_problem_type</data></a></td>
                 <td>1</td>
                 <td>1</td>
                 <td>0</td>
                 <td class="right" data-ratio="0 1">0%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html#t200">rulekit\_operator.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html#t200"><data value='fit'>ExpertKnowledgeOperator.fit</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html#t206">rulekit\_operator.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html#t206"><data value='fit'>ExpertKnowledgeOperator.fit</data></a></td>
                 <td>6</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="6 6">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html#t227">rulekit\_operator.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html#t227"><data value='get_rule_generator'>ExpertKnowledgeOperator._get_rule_generator</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html#t233">rulekit\_operator.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html#t233"><data value='get_rule_generator'>ExpertKnowledgeOperator._get_rule_generator</data></a></td>
                 <td>1</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="1 1">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html#t230">rulekit\_operator.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html#t230"><data value='configure_expert_parameters'>ExpertKnowledgeOperator._configure_expert_parameters</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html#t236">rulekit\_operator.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html#t236"><data value='configure_expert_parameters'>ExpertKnowledgeOperator._configure_expert_parameters</data></a></td>
                 <td>11</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="11 11">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html#t259">rulekit\_operator.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html#t259"><data value='sanitize_expert_parameter'>ExpertKnowledgeOperator._sanitize_expert_parameter</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html#t265">rulekit\_operator.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html#t265"><data value='sanitize_expert_parameter'>ExpertKnowledgeOperator._sanitize_expert_parameter</data></a></td>
                 <td>7</td>
                 <td>1</td>
                 <td>0</td>
@@ -475,10 +491,10 @@ <h2>
             <tr class="region">
                 <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html">rulekit\_operator.py</a></td>
                 <td class="name left"><a href="z_a87f2a4bb6695d91__operator_py.html"><data value=''><span class='no-noun'>(no function)</span></data></a></td>
-                <td>35</td>
+                <td>44</td>
                 <td>0</td>
                 <td>0</td>
-                <td class="right" data-ratio="35 35">100%</td>
+                <td class="right" data-ratio="44 44">100%</td>
             </tr>
             <tr class="region">
                 <td class="name left"><a href="z_a87f2a4bb6695d91__problem_types_py.html">rulekit\_problem_types.py</a></td>
@@ -521,256 +537,256 @@ <h2>
                 <td class="right" data-ratio="9 9">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t42">rulekit\classification.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t42"><data value='init__'>BaseClassifier.__init__</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t55">rulekit\classification.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t55"><data value='init__'>BaseClassifier.__init__</data></a></td>
                 <td>3</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="3 3">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t53">rulekit\classification.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t53"><data value='init_classification_rule_performance_classes'>BaseClassifier._init_classification_rule_performance_classes</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t66">rulekit\classification.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t66"><data value='init_classification_rule_performance_classes'>BaseClassifier._init_classification_rule_performance_classes</data></a></td>
                 <td>1</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="1 1">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t58">rulekit\classification.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t58"><data value='calculate_metric'>BaseClassifier._calculate_metric</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t71">rulekit\classification.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t71"><data value='calculate_metric'>BaseClassifier._calculate_metric</data></a></td>
                 <td>3</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="3 3">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t64">rulekit\classification.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t64"><data value='calculate_prediction_metrics'>BaseClassifier._calculate_prediction_metrics</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t77">rulekit\classification.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t77"><data value='calculate_prediction_metrics'>BaseClassifier._calculate_prediction_metrics</data></a></td>
                 <td>1</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="1 1">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t80">rulekit\classification.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t80"><data value='init__'>RuleClassifier.__init__</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t93">rulekit\classification.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t93"><data value='init__'>RuleClassifier.__init__</data></a></td>
                 <td>5</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="5 5">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t169">rulekit\classification.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t169"><data value='map_result'>RuleClassifier._map_result</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t182">rulekit\classification.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t182"><data value='map_result'>RuleClassifier._map_result</data></a></td>
                 <td>4</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="4 4">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t179">rulekit\classification.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t179"><data value='map_confidence'>RuleClassifier._map_confidence</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t192">rulekit\classification.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t192"><data value='map_confidence'>RuleClassifier._map_confidence</data></a></td>
                 <td>1</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="1 1">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t184">rulekit\classification.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t184"><data value='get_unique_label_values'>RuleClassifier._get_unique_label_values</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t197">rulekit\classification.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t197"><data value='get_unique_label_values'>RuleClassifier._get_unique_label_values</data></a></td>
                 <td>6</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="6 6">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t193">rulekit\classification.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t193"><data value='prepare_labels'>RuleClassifier._prepare_labels</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t206">rulekit\classification.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t206"><data value='prepare_labels'>RuleClassifier._prepare_labels</data></a></td>
                 <td>12</td>
                 <td>3</td>
                 <td>0</td>
                 <td class="right" data-ratio="9 12">75%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t211">rulekit\classification.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t211"><data value='fit'>RuleClassifier.fit</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t224">rulekit\classification.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t224"><data value='fit'>RuleClassifier.fit</data></a></td>
                 <td>4</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="4 4">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t229">rulekit\classification.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t229"><data value='predict'>RuleClassifier.predict</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t242">rulekit\classification.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t242"><data value='predict'>RuleClassifier.predict</data></a></td>
                 <td>6</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="6 6">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t259">rulekit\classification.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t259"><data value='predict_proba'>RuleClassifier.predict_proba</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t275">rulekit\classification.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t275"><data value='predict_proba'>RuleClassifier.predict_proba</data></a></td>
                 <td>6</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="6 6">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t289">rulekit\classification.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t289"><data value='score'>RuleClassifier.score</data></a></td>
-                <td>2</td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t309">rulekit\classification.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t309"><data value='score'>RuleClassifier.score</data></a></td>
                 <td>2</td>
                 <td>0</td>
-                <td class="right" data-ratio="0 2">0%</td>
+                <td>0</td>
+                <td class="right" data-ratio="2 2">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t307">rulekit\classification.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t307"><data value='getstate__'>RuleClassifier.__getstate__</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t327">rulekit\classification.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t327"><data value='getstate__'>RuleClassifier.__getstate__</data></a></td>
                 <td>1</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="1 1">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t313">rulekit\classification.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t313"><data value='setstate__'>RuleClassifier.__setstate__</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t333">rulekit\classification.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t333"><data value='setstate__'>RuleClassifier.__setstate__</data></a></td>
                 <td>4</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="4 4">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t319">rulekit\classification.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t319"><data value='get_problem_type'>RuleClassifier._get_problem_type</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t339">rulekit\classification.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t339"><data value='get_problem_type'>RuleClassifier._get_problem_type</data></a></td>
                 <td>1</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="1 1">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t328">rulekit\classification.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t328"><data value='init__'>ExpertRuleClassifier.__init__</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t348">rulekit\classification.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t348"><data value='init__'>ExpertRuleClassifier.__init__</data></a></td>
                 <td>4</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="4 4">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t468">rulekit\classification.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t468"><data value='fit'>ExpertRuleClassifier.fit</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t490">rulekit\classification.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t490"><data value='fit'>ExpertRuleClassifier.fit</data></a></td>
                 <td>10</td>
                 <td>2</td>
                 <td>0</td>
                 <td class="right" data-ratio="8 10">80%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t520">rulekit\classification.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t520"><data value='predict'>ExpertRuleClassifier.predict</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t542">rulekit\classification.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t542"><data value='predict'>ExpertRuleClassifier.predict</data></a></td>
                 <td>1</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="1 1">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t527">rulekit\classification.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t527"><data value='getstate__'>ExpertRuleClassifier.__getstate__</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t549">rulekit\classification.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t549"><data value='getstate__'>ExpertRuleClassifier.__getstate__</data></a></td>
                 <td>1</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="1 1">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t532">rulekit\classification.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t532"><data value='setstate__'>ExpertRuleClassifier.__setstate__</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t554">rulekit\classification.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t554"><data value='setstate__'>ExpertRuleClassifier.__setstate__</data></a></td>
                 <td>2</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="2 2">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t536">rulekit\classification.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t536"><data value='get_problem_type'>ExpertRuleClassifier._get_problem_type</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t558">rulekit\classification.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t558"><data value='get_problem_type'>ExpertRuleClassifier._get_problem_type</data></a></td>
                 <td>1</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="1 1">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t545">rulekit\classification.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t545"><data value='init__'>ContrastSetRuleClassifier.__init__</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t567">rulekit\classification.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t567"><data value='init__'>ContrastSetRuleClassifier.__init__</data></a></td>
                 <td>6</td>
                 <td>6</td>
                 <td>0</td>
                 <td class="right" data-ratio="0 6">0%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t657">rulekit\classification.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t657"><data value='map_result'>ContrastSetRuleClassifier._map_result</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t679">rulekit\classification.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t679"><data value='map_result'>ContrastSetRuleClassifier._map_result</data></a></td>
                 <td>4</td>
                 <td>4</td>
                 <td>0</td>
                 <td class="right" data-ratio="0 4">0%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t667">rulekit\classification.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t667"><data value='get_unique_label_values'>ContrastSetRuleClassifier._get_unique_label_values</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t689">rulekit\classification.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t689"><data value='get_unique_label_values'>ContrastSetRuleClassifier._get_unique_label_values</data></a></td>
                 <td>6</td>
                 <td>6</td>
                 <td>0</td>
                 <td class="right" data-ratio="0 6">0%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t676">rulekit\classification.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t676"><data value='fit'>ContrastSetRuleClassifier.fit</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t698">rulekit\classification.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t698"><data value='fit'>ContrastSetRuleClassifier.fit</data></a></td>
                 <td>5</td>
                 <td>5</td>
                 <td>0</td>
                 <td class="right" data-ratio="0 5">0%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t704">rulekit\classification.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t704"><data value='predict'>ContrastSetRuleClassifier.predict</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t726">rulekit\classification.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t726"><data value='predict'>ContrastSetRuleClassifier.predict</data></a></td>
                 <td>1</td>
                 <td>1</td>
                 <td>0</td>
                 <td class="right" data-ratio="0 1">0%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t728">rulekit\classification.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t728"><data value='predict_proba'>ContrastSetRuleClassifier.predict_proba</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t750">rulekit\classification.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t750"><data value='predict_proba'>ContrastSetRuleClassifier.predict_proba</data></a></td>
                 <td>1</td>
                 <td>1</td>
                 <td>0</td>
                 <td class="right" data-ratio="0 1">0%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t753">rulekit\classification.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t753"><data value='score'>ContrastSetRuleClassifier.score</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t778">rulekit\classification.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t778"><data value='score'>ContrastSetRuleClassifier.score</data></a></td>
                 <td>1</td>
                 <td>1</td>
                 <td>0</td>
                 <td class="right" data-ratio="0 1">0%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t770">rulekit\classification.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t770"><data value='getstate__'>ContrastSetRuleClassifier.__getstate__</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t795">rulekit\classification.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t795"><data value='getstate__'>ContrastSetRuleClassifier.__getstate__</data></a></td>
                 <td>1</td>
                 <td>1</td>
                 <td>0</td>
                 <td class="right" data-ratio="0 1">0%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t777">rulekit\classification.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t777"><data value='setstate__'>ContrastSetRuleClassifier.__setstate__</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t802">rulekit\classification.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t802"><data value='setstate__'>ContrastSetRuleClassifier.__setstate__</data></a></td>
                 <td>5</td>
                 <td>5</td>
                 <td>0</td>
                 <td class="right" data-ratio="0 5">0%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t784">rulekit\classification.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t784"><data value='get_problem_type'>ContrastSetRuleClassifier._get_problem_type</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t809">rulekit\classification.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html#t809"><data value='get_problem_type'>ContrastSetRuleClassifier._get_problem_type</data></a></td>
                 <td>1</td>
                 <td>1</td>
                 <td>0</td>
@@ -779,62 +795,62 @@ <h2>
             <tr class="region">
                 <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html">rulekit\classification.py</a></td>
                 <td class="name left"><a href="z_a87f2a4bb6695d91_classification_py.html"><data value=''><span class='no-noun'>(no function)</span></data></a></td>
-                <td>63</td>
+                <td>75</td>
                 <td>0</td>
                 <td>0</td>
-                <td class="right" data-ratio="63 63">100%</td>
+                <td class="right" data-ratio="75 75">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_events_py.html#t16">rulekit\events.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_events_py.html#t16"><data value='on_new_rule'>RuleInductionProgressListener.on_new_rule</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_events_py.html#t20">rulekit\events.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_events_py.html#t20"><data value='on_new_rule'>RuleInductionProgressListener.on_new_rule</data></a></td>
                 <td>0</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="0 0">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_events_py.html#t23">rulekit\events.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_events_py.html#t23"><data value='on_progress'>RuleInductionProgressListener.on_progress</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_events_py.html#t27">rulekit\events.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_events_py.html#t27"><data value='on_progress'>RuleInductionProgressListener.on_progress</data></a></td>
                 <td>0</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="0 0">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_events_py.html#t37">rulekit\events.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_events_py.html#t37"><data value='should_stop'>RuleInductionProgressListener.should_stop</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_events_py.html#t44">rulekit\events.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_events_py.html#t44"><data value='should_stop'>RuleInductionProgressListener.should_stop</data></a></td>
                 <td>1</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="1 1">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_events_py.html#t48">rulekit\events.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_events_py.html#t48"><data value='command_listener_factory'>command_listener_factory</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_events_py.html#t56">rulekit\events.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_events_py.html#t56"><data value='command_listener_factory'>_command_listener_factory</data></a></td>
                 <td>10</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="10 10">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_events_py.html#t56">rulekit\events.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_events_py.html#t56"><data value='onNewRule'>command_listener_factory._CommandListener.onNewRule</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_events_py.html#t64">rulekit\events.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_events_py.html#t64"><data value='onNewRule'>_command_listener_factory._CommandListener.onNewRule</data></a></td>
                 <td>2</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="2 2">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_events_py.html#t61">rulekit\events.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_events_py.html#t61"><data value='onProgress'>command_listener_factory._CommandListener.onProgress</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_events_py.html#t69">rulekit\events.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_events_py.html#t69"><data value='onProgress'>_command_listener_factory._CommandListener.onProgress</data></a></td>
                 <td>1</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="1 1">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_events_py.html#t65">rulekit\events.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_events_py.html#t65"><data value='isRequestStop'>command_listener_factory._CommandListener.isRequestStop</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_events_py.html#t73">rulekit\events.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_events_py.html#t73"><data value='isRequestStop'>_command_listener_factory._CommandListener.isRequestStop</data></a></td>
                 <td>1</td>
                 <td>0</td>
                 <td>0</td>
@@ -843,62 +859,62 @@ <h2>
             <tr class="region">
                 <td class="name left"><a href="z_a87f2a4bb6695d91_events_py.html">rulekit\events.py</a></td>
                 <td class="name left"><a href="z_a87f2a4bb6695d91_events_py.html"><data value=''><span class='no-noun'>(no function)</span></data></a></td>
-                <td>8</td>
+                <td>12</td>
                 <td>0</td>
                 <td>0</td>
-                <td class="right" data-ratio="8 8">100%</td>
+                <td class="right" data-ratio="12 12">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_exceptions_py.html#t24">rulekit\exceptions.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_exceptions_py.html#t24"><data value='init__'>RuleKitJavaException.__init__</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_exceptions_py.html#t25">rulekit\exceptions.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_exceptions_py.html#t25"><data value='init__'>RuleKitJavaException.__init__</data></a></td>
                 <td>3</td>
                 <td>3</td>
                 <td>0</td>
                 <td class="right" data-ratio="0 3">0%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_exceptions_py.html#t34">rulekit\exceptions.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_exceptions_py.html#t34"><data value='original_exception'>RuleKitJavaException.original_exception</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_exceptions_py.html#t35">rulekit\exceptions.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_exceptions_py.html#t35"><data value='original_exception'>RuleKitJavaException.original_exception</data></a></td>
                 <td>1</td>
                 <td>1</td>
                 <td>0</td>
                 <td class="right" data-ratio="0 1">0%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_exceptions_py.html#t42">rulekit\exceptions.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_exceptions_py.html#t42"><data value='print_java_stack_trace'>RuleKitJavaException.print_java_stack_trace</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_exceptions_py.html#t43">rulekit\exceptions.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_exceptions_py.html#t43"><data value='print_java_stack_trace'>RuleKitJavaException.print_java_stack_trace</data></a></td>
                 <td>1</td>
                 <td>1</td>
                 <td>0</td>
                 <td class="right" data-ratio="0 1">0%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_exceptions_py.html#t52">rulekit\exceptions.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_exceptions_py.html#t52"><data value='init__'>RuleKitMisconfigurationException.__init__</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_exceptions_py.html#t53">rulekit\exceptions.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_exceptions_py.html#t53"><data value='init__'>RuleKitMisconfigurationException.__init__</data></a></td>
                 <td>3</td>
                 <td>3</td>
                 <td>0</td>
                 <td class="right" data-ratio="0 3">0%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_exceptions_py.html#t62">rulekit\exceptions.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_exceptions_py.html#t62"><data value='prepare_message'>RuleKitMisconfigurationException._prepare_message</data></a></td>
-                <td>11</td>
-                <td>11</td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_exceptions_py.html#t65">rulekit\exceptions.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_exceptions_py.html#t65"><data value='prepare_message'>RuleKitMisconfigurationException._prepare_message</data></a></td>
+                <td>12</td>
+                <td>12</td>
                 <td>0</td>
-                <td class="right" data-ratio="0 11">0%</td>
+                <td class="right" data-ratio="0 12">0%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_exceptions_py.html#t87">rulekit\exceptions.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_exceptions_py.html#t87"><data value='java_parameters'>RuleKitMisconfigurationException.java_parameters</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_exceptions_py.html#t93">rulekit\exceptions.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_exceptions_py.html#t93"><data value='java_parameters'>RuleKitMisconfigurationException.java_parameters</data></a></td>
                 <td>1</td>
                 <td>1</td>
                 <td>0</td>
                 <td class="right" data-ratio="0 1">0%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_exceptions_py.html#t96">rulekit\exceptions.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_exceptions_py.html#t96"><data value='python_parameters'>RuleKitMisconfigurationException.python_parameters</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_exceptions_py.html#t102">rulekit\exceptions.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_exceptions_py.html#t102"><data value='python_parameters'>RuleKitMisconfigurationException.python_parameters</data></a></td>
                 <td>1</td>
                 <td>1</td>
                 <td>0</td>
@@ -907,10 +923,10 @@ <h2>
             <tr class="region">
                 <td class="name left"><a href="z_a87f2a4bb6695d91_exceptions_py.html">rulekit\exceptions.py</a></td>
                 <td class="name left"><a href="z_a87f2a4bb6695d91_exceptions_py.html"><data value=''><span class='no-noun'>(no function)</span></data></a></td>
-                <td>14</td>
+                <td>15</td>
                 <td>0</td>
                 <td>0</td>
-                <td class="right" data-ratio="14 14">100%</td>
+                <td class="right" data-ratio="15 15">100%</td>
             </tr>
             <tr class="region">
                 <td class="name left"><a href="z_a87f2a4bb6695d91_kaplan_meier_py.html#t11">rulekit\kaplan_meier.py</a></td>
@@ -921,56 +937,56 @@ <h2>
                 <td class="right" data-ratio="6 6">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_kaplan_meier_py.html#t27">rulekit\kaplan_meier.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_kaplan_meier_py.html#t27"><data value='times'>KaplanMeierEstimator.times</data></a></td>
-                <td>1</td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_kaplan_meier_py.html#t28">rulekit\kaplan_meier.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_kaplan_meier_py.html#t28"><data value='times'>KaplanMeierEstimator.times</data></a></td>
                 <td>1</td>
                 <td>0</td>
-                <td class="right" data-ratio="0 1">0%</td>
+                <td>0</td>
+                <td class="right" data-ratio="1 1">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_kaplan_meier_py.html#t35">rulekit\kaplan_meier.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_kaplan_meier_py.html#t35"><data value='probabilities'>KaplanMeierEstimator.probabilities</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_kaplan_meier_py.html#t36">rulekit\kaplan_meier.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_kaplan_meier_py.html#t36"><data value='probabilities'>KaplanMeierEstimator.probabilities</data></a></td>
                 <td>3</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="3 3">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_kaplan_meier_py.html#t47">rulekit\kaplan_meier.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_kaplan_meier_py.html#t47"><data value='events_count'>KaplanMeierEstimator.events_count</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_kaplan_meier_py.html#t48">rulekit\kaplan_meier.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_kaplan_meier_py.html#t48"><data value='events_count'>KaplanMeierEstimator.events_count</data></a></td>
                 <td>3</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="3 3">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_kaplan_meier_py.html#t59">rulekit\kaplan_meier.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_kaplan_meier_py.html#t59"><data value='at_risk_count'>KaplanMeierEstimator.at_risk_count</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_kaplan_meier_py.html#t60">rulekit\kaplan_meier.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_kaplan_meier_py.html#t60"><data value='at_risk_count'>KaplanMeierEstimator.at_risk_count</data></a></td>
                 <td>3</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="3 3">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_kaplan_meier_py.html#t70">rulekit\kaplan_meier.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_kaplan_meier_py.html#t70"><data value='get_probability_at'>KaplanMeierEstimator.get_probability_at</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_kaplan_meier_py.html#t71">rulekit\kaplan_meier.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_kaplan_meier_py.html#t71"><data value='get_probability_at'>KaplanMeierEstimator.get_probability_at</data></a></td>
                 <td>1</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="1 1">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_kaplan_meier_py.html#t81">rulekit\kaplan_meier.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_kaplan_meier_py.html#t81"><data value='get_events_count_at'>KaplanMeierEstimator.get_events_count_at</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_kaplan_meier_py.html#t82">rulekit\kaplan_meier.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_kaplan_meier_py.html#t82"><data value='get_events_count_at'>KaplanMeierEstimator.get_events_count_at</data></a></td>
                 <td>1</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="1 1">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_kaplan_meier_py.html#t92">rulekit\kaplan_meier.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_kaplan_meier_py.html#t92"><data value='get_risk_set_count_at'>KaplanMeierEstimator.get_risk_set_count_at</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_kaplan_meier_py.html#t93">rulekit\kaplan_meier.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_kaplan_meier_py.html#t93"><data value='get_risk_set_count_at'>KaplanMeierEstimator.get_risk_set_count_at</data></a></td>
                 <td>1</td>
                 <td>0</td>
                 <td>0</td>
@@ -985,56 +1001,56 @@ <h2>
                 <td class="right" data-ratio="16 16">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_main_py.html#t49">rulekit\main.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_main_py.html#t49"><data value='detect_jre_type'>RuleKit._detect_jre_type</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_main_py.html#t51">rulekit\main.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_main_py.html#t51"><data value='detect_jre_type'>RuleKit._detect_jre_type</data></a></td>
                 <td>8</td>
                 <td>3</td>
                 <td>0</td>
                 <td class="right" data-ratio="5 8">62%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_main_py.html#t63">rulekit\main.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_main_py.html#t63"><data value='init'>RuleKit.init</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_main_py.html#t65">rulekit\main.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_main_py.html#t65"><data value='init'>RuleKit.init</data></a></td>
                 <td>22</td>
                 <td>6</td>
                 <td>0</td>
                 <td class="right" data-ratio="16 22">73%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_main_py.html#t130">rulekit\main.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_main_py.html#t130"><data value='setup_logger'>RuleKit._setup_logger</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_main_py.html#t132">rulekit\main.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_main_py.html#t132"><data value='setup_logger'>RuleKit._setup_logger</data></a></td>
                 <td>2</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="2 2">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_main_py.html#t135">rulekit\main.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_main_py.html#t135"><data value='read_versions'>RuleKit._read_versions</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_main_py.html#t137">rulekit\main.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_main_py.html#t137"><data value='read_versions'>RuleKit._read_versions</data></a></td>
                 <td>8</td>
                 <td>4</td>
                 <td>0</td>
                 <td class="right" data-ratio="4 8">50%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_main_py.html#t149">rulekit\main.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_main_py.html#t149"><data value='launch_jvm'>RuleKit._launch_jvm</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_main_py.html#t151">rulekit\main.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_main_py.html#t151"><data value='launch_jvm'>RuleKit._launch_jvm</data></a></td>
                 <td>8</td>
                 <td>3</td>
                 <td>0</td>
                 <td class="right" data-ratio="5 8">62%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_main_py.html#t164">rulekit\main.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_main_py.html#t164"><data value='configure_java_logger'>RuleKit.configure_java_logger</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_main_py.html#t166">rulekit\main.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_main_py.html#t166"><data value='configure_java_logger'>RuleKit.configure_java_logger</data></a></td>
                 <td>1</td>
                 <td>1</td>
                 <td>0</td>
                 <td class="right" data-ratio="0 1">0%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_main_py.html#t184">rulekit\main.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_main_py.html#t184"><data value='get_java_logger_config'>RuleKit.get_java_logger_config</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_main_py.html#t186">rulekit\main.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_main_py.html#t186"><data value='get_java_logger_config'>RuleKit.get_java_logger_config</data></a></td>
                 <td>1</td>
                 <td>0</td>
                 <td>0</td>
@@ -1043,158 +1059,174 @@ <h2>
             <tr class="region">
                 <td class="name left"><a href="z_a87f2a4bb6695d91_main_py.html">rulekit\main.py</a></td>
                 <td class="name left"><a href="z_a87f2a4bb6695d91_main_py.html"><data value=''><span class='no-noun'>(no function)</span></data></a></td>
-                <td>37</td>
+                <td>39</td>
+                <td>0</td>
+                <td>0</td>
+                <td class="right" data-ratio="39 39">100%</td>
+            </tr>
+            <tr class="region">
+                <td class="name left"><a href="z_a87f2a4bb6695d91_params_py.html#t19">rulekit\params.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_params_py.html#t19"><data value='user_defined_measure_factory'>_user_defined_measure_factory</data></a></td>
+                <td>6</td>
+                <td>6</td>
                 <td>0</td>
+                <td class="right" data-ratio="0 6">0%</td>
+            </tr>
+            <tr class="region">
+                <td class="name left"><a href="z_a87f2a4bb6695d91_params_py.html#t27">rulekit\params.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_params_py.html#t27"><data value='getResult'>_user_defined_measure_factory._UserMeasure.getResult</data></a></td>
+                <td>1</td>
+                <td>1</td>
                 <td>0</td>
-                <td class="right" data-ratio="37 37">100%</td>
+                <td class="right" data-ratio="0 1">0%</td>
             </tr>
             <tr class="region">
                 <td class="name left"><a href="z_a87f2a4bb6695d91_params_py.html">rulekit\params.py</a></td>
                 <td class="name left"><a href="z_a87f2a4bb6695d91_params_py.html"><data value=''><span class='no-noun'>(no function)</span></data></a></td>
-                <td>73</td>
+                <td>81</td>
                 <td>0</td>
                 <td>0</td>
-                <td class="right" data-ratio="73 73">100%</td>
+                <td class="right" data-ratio="81 81">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t29">rulekit\regression.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t29"><data value='init__'>RuleRegressor.__init__</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t40">rulekit\regression.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t40"><data value='init__'>RuleRegressor.__init__</data></a></td>
                 <td>2</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="2 2">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t102">rulekit\regression.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t102"><data value='validate_labels'>RuleRegressor._validate_labels</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t113">rulekit\regression.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t113"><data value='validate_labels'>RuleRegressor._validate_labels</data></a></td>
                 <td>5</td>
                 <td>1</td>
                 <td>0</td>
                 <td class="right" data-ratio="4 5">80%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t112">rulekit\regression.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t112"><data value='fit'>RuleRegressor.fit</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t123">rulekit\regression.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t123"><data value='fit'>RuleRegressor.fit</data></a></td>
                 <td>3</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="3 3">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t129">rulekit\regression.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t129"><data value='predict'>RuleRegressor.predict</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t140">rulekit\regression.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t140"><data value='predict'>RuleRegressor.predict</data></a></td>
                 <td>1</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="1 1">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t144">rulekit\regression.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t144"><data value='score'>RuleRegressor.score</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t155">rulekit\regression.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t155"><data value='score'>RuleRegressor.score</data></a></td>
                 <td>2</td>
                 <td>2</td>
                 <td>0</td>
                 <td class="right" data-ratio="0 2">0%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t162">rulekit\regression.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t162"><data value='map_result'>RuleRegressor._map_result</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t173">rulekit\regression.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t173"><data value='map_result'>RuleRegressor._map_result</data></a></td>
                 <td>1</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="1 1">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t165">rulekit\regression.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t165"><data value='get_problem_type'>RuleRegressor._get_problem_type</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t176">rulekit\regression.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t176"><data value='get_problem_type'>RuleRegressor._get_problem_type</data></a></td>
                 <td>1</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="1 1">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t174">rulekit\regression.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t174"><data value='init__'>ExpertRuleRegressor.__init__</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t185">rulekit\regression.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t185"><data value='init__'>ExpertRuleRegressor.__init__</data></a></td>
                 <td>3</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="3 3">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t295">rulekit\regression.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t295"><data value='fit'>ExpertRuleRegressor.fit</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t306">rulekit\regression.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t306"><data value='fit'>ExpertRuleRegressor.fit</data></a></td>
                 <td>2</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="2 2">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t338">rulekit\regression.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t338"><data value='predict'>ExpertRuleRegressor.predict</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t349">rulekit\regression.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t349"><data value='predict'>ExpertRuleRegressor.predict</data></a></td>
                 <td>1</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="1 1">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t341">rulekit\regression.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t341"><data value='get_problem_type'>ExpertRuleRegressor._get_problem_type</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t352">rulekit\regression.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t352"><data value='get_problem_type'>ExpertRuleRegressor._get_problem_type</data></a></td>
                 <td>1</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="1 1">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t350">rulekit\regression.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t350"><data value='init__'>ContrastSetRuleRegressor.__init__</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t361">rulekit\regression.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t361"><data value='init__'>ContrastSetRuleRegressor.__init__</data></a></td>
                 <td>3</td>
                 <td>3</td>
                 <td>0</td>
                 <td class="right" data-ratio="0 3">0%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t447">rulekit\regression.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t447"><data value='fit'>ContrastSetRuleRegressor.fit</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t458">rulekit\regression.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t458"><data value='fit'>ContrastSetRuleRegressor.fit</data></a></td>
                 <td>4</td>
                 <td>4</td>
                 <td>0</td>
                 <td class="right" data-ratio="0 4">0%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t469">rulekit\regression.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t469"><data value='predict'>ContrastSetRuleRegressor.predict</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t480">rulekit\regression.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t480"><data value='predict'>ContrastSetRuleRegressor.predict</data></a></td>
                 <td>1</td>
                 <td>1</td>
                 <td>0</td>
                 <td class="right" data-ratio="0 1">0%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t484">rulekit\regression.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t484"><data value='score'>ContrastSetRuleRegressor.score</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t495">rulekit\regression.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t495"><data value='score'>ContrastSetRuleRegressor.score</data></a></td>
                 <td>1</td>
                 <td>1</td>
                 <td>0</td>
                 <td class="right" data-ratio="0 1">0%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t501">rulekit\regression.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t501"><data value='getstate__'>ContrastSetRuleRegressor.__getstate__</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t512">rulekit\regression.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t512"><data value='getstate__'>ContrastSetRuleRegressor.__getstate__</data></a></td>
                 <td>1</td>
                 <td>1</td>
                 <td>0</td>
                 <td class="right" data-ratio="0 1">0%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t506">rulekit\regression.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t506"><data value='setstate__'>ContrastSetRuleRegressor.__setstate__</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t517">rulekit\regression.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t517"><data value='setstate__'>ContrastSetRuleRegressor.__setstate__</data></a></td>
                 <td>2</td>
                 <td>2</td>
                 <td>0</td>
                 <td class="right" data-ratio="0 2">0%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t510">rulekit\regression.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t510"><data value='get_problem_type'>ContrastSetRuleRegressor._get_problem_type</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t521">rulekit\regression.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html#t521"><data value='get_problem_type'>ContrastSetRuleRegressor._get_problem_type</data></a></td>
                 <td>1</td>
                 <td>1</td>
                 <td>0</td>
@@ -1203,342 +1235,342 @@ <h2>
             <tr class="region">
                 <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html">rulekit\regression.py</a></td>
                 <td class="name left"><a href="z_a87f2a4bb6695d91_regression_py.html"><data value=''><span class='no-noun'>(no function)</span></data></a></td>
-                <td>37</td>
+                <td>47</td>
                 <td>0</td>
                 <td>0</td>
-                <td class="right" data-ratio="37 37">100%</td>
+                <td class="right" data-ratio="47 47">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t17">rulekit\rules.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t17"><data value='init__'>InductionParameters.__init__</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t20">rulekit\rules.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t20"><data value='init__'>InductionParameters.__init__</data></a></td>
                 <td>6</td>
                 <td>6</td>
                 <td>0</td>
                 <td class="right" data-ratio="0 6">0%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t27">rulekit\rules.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t27"><data value='induction_measure'>InductionParameters.induction_measure</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t30">rulekit\rules.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t30"><data value='induction_measure'>InductionParameters.induction_measure</data></a></td>
                 <td>1</td>
                 <td>1</td>
                 <td>0</td>
                 <td class="right" data-ratio="0 1">0%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t35">rulekit\rules.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t35"><data value='pruning_measure'>InductionParameters.pruning_measure</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t38">rulekit\rules.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t38"><data value='pruning_measure'>InductionParameters.pruning_measure</data></a></td>
                 <td>1</td>
                 <td>1</td>
                 <td>0</td>
                 <td class="right" data-ratio="0 1">0%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t43">rulekit\rules.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t43"><data value='voting_measure'>InductionParameters.voting_measure</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t46">rulekit\rules.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t46"><data value='voting_measure'>InductionParameters.voting_measure</data></a></td>
                 <td>1</td>
                 <td>1</td>
                 <td>0</td>
                 <td class="right" data-ratio="0 1">0%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t51">rulekit\rules.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t51"><data value='get_measure_str'>InductionParameters._get_measure_str</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t54">rulekit\rules.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t54"><data value='get_measure_str'>InductionParameters._get_measure_str</data></a></td>
                 <td>4</td>
                 <td>4</td>
                 <td>0</td>
                 <td class="right" data-ratio="0 4">0%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t57">rulekit\rules.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t57"><data value='str__'>InductionParameters.__str__</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t60">rulekit\rules.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t60"><data value='str__'>InductionParameters.__str__</data></a></td>
                 <td>1</td>
                 <td>1</td>
                 <td>0</td>
                 <td class="right" data-ratio="0 1">0%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t64">rulekit\rules.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t64"><data value='init__'>BaseRule.__init__</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t67">rulekit\rules.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t67"><data value='init__'>BaseRule.__init__</data></a></td>
                 <td>2</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="2 2">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t70">rulekit\rules.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t70"><data value='weight'>BaseRule.weight</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t73">rulekit\rules.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t73"><data value='weight'>BaseRule.weight</data></a></td>
                 <td>1</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="1 1">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t75">rulekit\rules.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t75"><data value='weighted_p'>BaseRule.weighted_p</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t78">rulekit\rules.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t78"><data value='weighted_p'>BaseRule.weighted_p</data></a></td>
                 <td>1</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="1 1">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t80">rulekit\rules.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t80"><data value='weighted_n'>BaseRule.weighted_n</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t83">rulekit\rules.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t83"><data value='weighted_n'>BaseRule.weighted_n</data></a></td>
                 <td>1</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="1 1">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t85">rulekit\rules.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t85"><data value='weighted_P'>BaseRule.weighted_P</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t88">rulekit\rules.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t88"><data value='weighted_P'>BaseRule.weighted_P</data></a></td>
                 <td>1</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="1 1">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t90">rulekit\rules.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t90"><data value='weighted_N'>BaseRule.weighted_N</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t93">rulekit\rules.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t93"><data value='weighted_N'>BaseRule.weighted_N</data></a></td>
                 <td>1</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="1 1">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t95">rulekit\rules.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t95"><data value='pvalue'>BaseRule.pvalue</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t98">rulekit\rules.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t98"><data value='pvalue'>BaseRule.pvalue</data></a></td>
                 <td>1</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="1 1">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t100">rulekit\rules.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t100"><data value='stats'>BaseRule.stats</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t103">rulekit\rules.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t103"><data value='stats'>BaseRule.stats</data></a></td>
                 <td>3</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="3 3">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t106">rulekit\rules.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t106"><data value='get_covering_information'>BaseRule.get_covering_information</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t109">rulekit\rules.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t109"><data value='get_covering_information'>BaseRule.get_covering_information</data></a></td>
                 <td>1</td>
                 <td>1</td>
                 <td>0</td>
                 <td class="right" data-ratio="0 1">0%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t121">rulekit\rules.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t121"><data value='print_stats'>BaseRule.print_stats</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t124">rulekit\rules.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t124"><data value='print_stats'>BaseRule.print_stats</data></a></td>
                 <td>1</td>
                 <td>1</td>
                 <td>0</td>
                 <td class="right" data-ratio="0 1">0%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t125">rulekit\rules.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t125"><data value='str__'>BaseRule.__str__</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t128">rulekit\rules.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t128"><data value='str__'>BaseRule.__str__</data></a></td>
                 <td>1</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="1 1">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t134">rulekit\rules.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t134"><data value='init__'>ClassificationRule.__init__</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t137">rulekit\rules.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t137"><data value='init__'>ClassificationRule.__init__</data></a></td>
                 <td>2</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="2 2">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t140">rulekit\rules.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t140"><data value='decision_class'>ClassificationRule.decision_class</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t143">rulekit\rules.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t143"><data value='decision_class'>ClassificationRule.decision_class</data></a></td>
                 <td>1</td>
                 <td>1</td>
                 <td>0</td>
                 <td class="right" data-ratio="0 1">0%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t150">rulekit\rules.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t150"><data value='init__'>RegressionRule.__init__</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t153">rulekit\rules.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t153"><data value='init__'>RegressionRule.__init__</data></a></td>
                 <td>2</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="2 2">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t157">rulekit\rules.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t157"><data value='conclusion_value'>RegressionRule.conclusion_value</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t160">rulekit\rules.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t160"><data value='conclusion_value'>RegressionRule.conclusion_value</data></a></td>
                 <td>1</td>
                 <td>1</td>
                 <td>0</td>
                 <td class="right" data-ratio="0 1">0%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t167">rulekit\rules.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t167"><data value='init__'>SurvivalRule.__init__</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t170">rulekit\rules.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t170"><data value='init__'>SurvivalRule.__init__</data></a></td>
                 <td>2</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="2 2">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t175">rulekit\rules.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t175"><data value='kaplan_meier_estimator'>SurvivalRule.kaplan_meier_estimator</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t178">rulekit\rules.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t178"><data value='kaplan_meier_estimator'>SurvivalRule.kaplan_meier_estimator</data></a></td>
                 <td>1</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="1 1">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t182">rulekit\rules.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t182"><data value='rule_factory'>_rule_factory</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t184">rulekit\rules.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t184"><data value='rule_factory'>_rule_factory</data></a></td>
                 <td>6</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="6 6">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t195">rulekit\rules.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t195"><data value='init__'>RuleSet.__init__</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t199">rulekit\rules.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t199"><data value='init__'>RuleSet.__init__</data></a></td>
                 <td>2</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="2 2">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t201">rulekit\rules.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t201"><data value='total_time'>RuleSet.total_time</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t205">rulekit\rules.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t205"><data value='total_time'>RuleSet.total_time</data></a></td>
                 <td>1</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="1 1">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t206">rulekit\rules.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t206"><data value='growing_time'>RuleSet.growing_time</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t210">rulekit\rules.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t210"><data value='growing_time'>RuleSet.growing_time</data></a></td>
                 <td>1</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="1 1">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t211">rulekit\rules.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t211"><data value='pruning_time'>RuleSet.pruning_time</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t215">rulekit\rules.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t215"><data value='pruning_time'>RuleSet.pruning_time</data></a></td>
                 <td>1</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="1 1">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t216">rulekit\rules.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t216"><data value='is_voting'>RuleSet.is_voting</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t220">rulekit\rules.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t220"><data value='is_voting'>RuleSet.is_voting</data></a></td>
                 <td>1</td>
                 <td>1</td>
                 <td>0</td>
                 <td class="right" data-ratio="0 1">0%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t221">rulekit\rules.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t221"><data value='parameters'>RuleSet.parameters</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t225">rulekit\rules.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t225"><data value='parameters'>RuleSet.parameters</data></a></td>
                 <td>1</td>
                 <td>1</td>
                 <td>0</td>
                 <td class="right" data-ratio="0 1">0%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t226">rulekit\rules.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t226"><data value='stats'>RuleSet.stats</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t230">rulekit\rules.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t230"><data value='stats'>RuleSet.stats</data></a></td>
                 <td>3</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="3 3">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t232">rulekit\rules.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t232"><data value='covering'>RuleSet.covering</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t236">rulekit\rules.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t236"><data value='covering'>RuleSet.covering</data></a></td>
                 <td>7</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="7 7">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t245">rulekit\rules.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t245"><data value='rules'>RuleSet.rules</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t249">rulekit\rules.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t249"><data value='rules'>RuleSet.rules</data></a></td>
                 <td>1</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="1 1">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t252">rulekit\rules.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t252"><data value='calculate_conditions_count'>RuleSet.calculate_conditions_count</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t256">rulekit\rules.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t256"><data value='calculate_conditions_count'>RuleSet.calculate_conditions_count</data></a></td>
                 <td>1</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="1 1">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t261">rulekit\rules.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t261"><data value='calculate_induced_conditions_count'>RuleSet.calculate_induced_conditions_count</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t265">rulekit\rules.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t265"><data value='calculate_induced_conditions_count'>RuleSet.calculate_induced_conditions_count</data></a></td>
                 <td>1</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="1 1">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t270">rulekit\rules.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t270"><data value='calculate_avg_rule_coverage'>RuleSet.calculate_avg_rule_coverage</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t274">rulekit\rules.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t274"><data value='calculate_avg_rule_coverage'>RuleSet.calculate_avg_rule_coverage</data></a></td>
                 <td>1</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="1 1">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t279">rulekit\rules.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t279"><data value='calculate_avg_rule_precision'>RuleSet.calculate_avg_rule_precision</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t283">rulekit\rules.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t283"><data value='calculate_avg_rule_precision'>RuleSet.calculate_avg_rule_precision</data></a></td>
                 <td>1</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="1 1">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t288">rulekit\rules.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t288"><data value='calculate_avg_rule_quality'>RuleSet.calculate_avg_rule_quality</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t292">rulekit\rules.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t292"><data value='calculate_avg_rule_quality'>RuleSet.calculate_avg_rule_quality</data></a></td>
                 <td>1</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="1 1">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t297">rulekit\rules.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t297"><data value='calculate_significance'>RuleSet.calculate_significance</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t301">rulekit\rules.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t301"><data value='calculate_significance'>RuleSet.calculate_significance</data></a></td>
                 <td>2</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="2 2">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t314">rulekit\rules.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t314"><data value='calculate_significance_fdr'>RuleSet.calculate_significance_fdr</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t318">rulekit\rules.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t318"><data value='calculate_significance_fdr'>RuleSet.calculate_significance_fdr</data></a></td>
                 <td>2</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="2 2">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t329">rulekit\rules.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t329"><data value='calculate_significance_fwer'>RuleSet.calculate_significance_fwer</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t333">rulekit\rules.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t333"><data value='calculate_significance_fwer'>RuleSet.calculate_significance_fwer</data></a></td>
                 <td>2</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="2 2">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t344">rulekit\rules.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t344"><data value='str__'>RuleSet.__str__</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t348">rulekit\rules.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html#t348"><data value='str__'>RuleSet.__str__</data></a></td>
                 <td>1</td>
                 <td>1</td>
                 <td>0</td>
@@ -1547,10 +1579,10 @@ <h2>
             <tr class="region">
                 <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html">rulekit\rules.py</a></td>
                 <td class="name left"><a href="z_a87f2a4bb6695d91_rules_py.html"><data value=''><span class='no-noun'>(no function)</span></data></a></td>
-                <td>76</td>
+                <td>79</td>
                 <td>0</td>
                 <td>0</td>
-                <td class="right" data-ratio="76 76">100%</td>
+                <td class="right" data-ratio="79 79">100%</td>
             </tr>
             <tr class="region">
                 <td class="name left"><a href="z_a87f2a4bb6695d91_stats_py.html#t24">rulekit\stats.py</a></td>
@@ -1577,8 +1609,8 @@ <h2>
                 <td class="right" data-ratio="15 15">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_stats_py.html#t113">rulekit\stats.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_stats_py.html#t113"><data value='str__'>RuleSetStatistics.__str__</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_stats_py.html#t114">rulekit\stats.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_stats_py.html#t114"><data value='str__'>RuleSetStatistics.__str__</data></a></td>
                 <td>1</td>
                 <td>1</td>
                 <td>0</td>
@@ -1593,152 +1625,160 @@ <h2>
                 <td class="right" data-ratio="7 7">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t47">rulekit\survival.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t47"><data value='init__'>SurvivalRules.__init__</data></a></td>
-                <td>5</td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t42">rulekit\survival.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t42"><data value='get_train_set_kaplan_meier'>_BaseSurvivalRulesModel.get_train_set_kaplan_meier</data></a></td>
+                <td>1</td>
                 <td>0</td>
                 <td>0</td>
-                <td class="right" data-ratio="5 5">100%</td>
+                <td class="right" data-ratio="1 1">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t107">rulekit\survival.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t107"><data value='set_params'>SurvivalRules.set_params</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t58">rulekit\survival.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t58"><data value='init__'>SurvivalRules.__init__</data></a></td>
+                <td>6</td>
+                <td>0</td>
+                <td>0</td>
+                <td class="right" data-ratio="6 6">100%</td>
+            </tr>
+            <tr class="region">
+                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t119">rulekit\survival.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t119"><data value='set_params'>SurvivalRules.set_params</data></a></td>
                 <td>2</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="2 2">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t116">rulekit\survival.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t116"><data value='append_survival_time_columns'>SurvivalRules._append_survival_time_columns</data></a></td>
-                <td>13</td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t128">rulekit\survival.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t128"><data value='append_survival_time_columns'>SurvivalRules._append_survival_time_columns</data></a></td>
                 <td>13</td>
+                <td>7</td>
                 <td>0</td>
-                <td class="right" data-ratio="0 13">0%</td>
+                <td class="right" data-ratio="6 13">46%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t138">rulekit\survival.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t138"><data value='prepare_survival_attribute'>SurvivalRules._prepare_survival_attribute</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t150">rulekit\survival.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t150"><data value='prepare_survival_attribute'>SurvivalRules._prepare_survival_attribute</data></a></td>
                 <td>5</td>
-                <td>2</td>
+                <td>1</td>
                 <td>0</td>
-                <td class="right" data-ratio="3 5">60%</td>
+                <td class="right" data-ratio="4 5">80%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t149">rulekit\survival.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t149"><data value='fit'>SurvivalRules.fit</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t161">rulekit\survival.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t161"><data value='fit'>SurvivalRules.fit</data></a></td>
                 <td>3</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="3 3">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t171">rulekit\survival.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t171"><data value='predict'>SurvivalRules.predict</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t183">rulekit\survival.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t183"><data value='predict'>SurvivalRules.predict</data></a></td>
                 <td>1</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="1 1">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t188">rulekit\survival.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t188"><data value='score'>SurvivalRules.score</data></a></td>
-                <td>7</td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t200">rulekit\survival.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t200"><data value='score'>SurvivalRules.score</data></a></td>
                 <td>7</td>
                 <td>0</td>
-                <td class="right" data-ratio="0 7">0%</td>
+                <td>0</td>
+                <td class="right" data-ratio="7 7">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t230">rulekit\survival.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t230"><data value='get_problem_type'>SurvivalRules._get_problem_type</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t242">rulekit\survival.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t242"><data value='get_problem_type'>SurvivalRules._get_problem_type</data></a></td>
                 <td>1</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="1 1">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t239">rulekit\survival.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t239"><data value='init__'>ExpertSurvivalRules.__init__</data></a></td>
-                <td>5</td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t251">rulekit\survival.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t251"><data value='init__'>ExpertSurvivalRules.__init__</data></a></td>
+                <td>6</td>
                 <td>0</td>
                 <td>0</td>
-                <td class="right" data-ratio="5 5">100%</td>
+                <td class="right" data-ratio="6 6">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t331">rulekit\survival.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t331"><data value='set_params'>ExpertSurvivalRules.set_params</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t344">rulekit\survival.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t344"><data value='set_params'>ExpertSurvivalRules.set_params</data></a></td>
                 <td>2</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="2 2">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t338">rulekit\survival.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t338"><data value='fit'>ExpertSurvivalRules.fit</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t351">rulekit\survival.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t351"><data value='fit'>ExpertSurvivalRules.fit</data></a></td>
                 <td>2</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="2 2">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t389">rulekit\survival.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t389"><data value='predict'>ExpertSurvivalRules.predict</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t402">rulekit\survival.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t402"><data value='predict'>ExpertSurvivalRules.predict</data></a></td>
                 <td>1</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="1 1">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t392">rulekit\survival.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t392"><data value='get_problem_type'>ExpertSurvivalRules._get_problem_type</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t405">rulekit\survival.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t405"><data value='get_problem_type'>ExpertSurvivalRules._get_problem_type</data></a></td>
                 <td>1</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="1 1">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t406">rulekit\survival.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t406"><data value='init__'>ContrastSetSurvivalRules.__init__</data></a></td>
-                <td>6</td>
-                <td>6</td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t418">rulekit\survival.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t418"><data value='init__'>ContrastSetSurvivalRules.__init__</data></a></td>
+                <td>7</td>
+                <td>7</td>
                 <td>0</td>
-                <td class="right" data-ratio="0 6">0%</td>
+                <td class="right" data-ratio="0 7">0%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t490">rulekit\survival.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t490"><data value='set_params'>ContrastSetSurvivalRules.set_params</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t503">rulekit\survival.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t503"><data value='set_params'>ContrastSetSurvivalRules.set_params</data></a></td>
                 <td>2</td>
                 <td>2</td>
                 <td>0</td>
                 <td class="right" data-ratio="0 2">0%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t496">rulekit\survival.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t496"><data value='fit'>ContrastSetSurvivalRules.fit</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t509">rulekit\survival.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t509"><data value='fit'>ContrastSetSurvivalRules.fit</data></a></td>
                 <td>4</td>
                 <td>4</td>
                 <td>0</td>
                 <td class="right" data-ratio="0 4">0%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t530">rulekit\survival.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t530"><data value='predict'>ContrastSetSurvivalRules.predict</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t543">rulekit\survival.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t543"><data value='predict'>ContrastSetSurvivalRules.predict</data></a></td>
                 <td>1</td>
                 <td>1</td>
                 <td>0</td>
                 <td class="right" data-ratio="0 1">0%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t547">rulekit\survival.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t547"><data value='score'>ContrastSetSurvivalRules.score</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t560">rulekit\survival.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t560"><data value='score'>ContrastSetSurvivalRules.score</data></a></td>
                 <td>1</td>
                 <td>1</td>
                 <td>0</td>
                 <td class="right" data-ratio="0 1">0%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t573">rulekit\survival.py</a></td>
-                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t573"><data value='get_problem_type'>ContrastSetSurvivalRules._get_problem_type</data></a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t586">rulekit\survival.py</a></td>
+                <td class="name left"><a href="z_a87f2a4bb6695d91_survival_py.html#t586"><data value='get_problem_type'>ContrastSetSurvivalRules._get_problem_type</data></a></td>
                 <td>1</td>
                 <td>1</td>
                 <td>0</td>
@@ -1769,212 +1809,252 @@ <h2>
                 <td class="right" data-ratio="10 10">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a44f0ac069e85531_test_classifier_py.html#t38">tests\test_classifier.py</a></td>
-                <td class="name left"><a href="z_a44f0ac069e85531_test_classifier_py.html#t38"><data value='test_induction_progress_listener'>TestClassifier.test_induction_progress_listener</data></a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_classifier_py.html#t39">tests\test_classifier.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_classifier_py.html#t39"><data value='test_induction_progress_listener'>TestClassifier.test_induction_progress_listener</data></a></td>
                 <td>14</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="14 14">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a44f0ac069e85531_test_classifier_py.html#t48">tests\test_classifier.py</a></td>
-                <td class="name left"><a href="z_a44f0ac069e85531_test_classifier_py.html#t48"><data value='on_new_rule'>TestClassifier.test_induction_progress_listener.EventListener.on_new_rule</data></a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_classifier_py.html#t49">tests\test_classifier.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_classifier_py.html#t49"><data value='on_new_rule'>TestClassifier.test_induction_progress_listener.EventListener.on_new_rule</data></a></td>
                 <td>3</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="3 3">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a44f0ac069e85531_test_classifier_py.html#t53">tests\test_classifier.py</a></td>
-                <td class="name left"><a href="z_a44f0ac069e85531_test_classifier_py.html#t53"><data value='on_progress'>TestClassifier.test_induction_progress_listener.EventListener.on_progress</data></a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_classifier_py.html#t54">tests\test_classifier.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_classifier_py.html#t54"><data value='on_progress'>TestClassifier.test_induction_progress_listener.EventListener.on_progress</data></a></td>
                 <td>3</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="3 3">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a44f0ac069e85531_test_classifier_py.html#t71">tests\test_classifier.py</a></td>
-                <td class="name left"><a href="z_a44f0ac069e85531_test_classifier_py.html#t71"><data value='test_getting_examples_coverage'>TestClassifier.test_getting_examples_coverage</data></a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_classifier_py.html#t68">tests\test_classifier.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_classifier_py.html#t68"><data value='test_getting_examples_coverage'>TestClassifier.test_getting_examples_coverage</data></a></td>
                 <td>7</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="7 7">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a44f0ac069e85531_test_classifier_py.html#t85">tests\test_classifier.py</a></td>
-                <td class="name left"><a href="z_a44f0ac069e85531_test_classifier_py.html#t85"><data value='test_classification_metrics'>TestClassifier.test_classification_metrics</data></a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_classifier_py.html#t88">tests\test_classifier.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_classifier_py.html#t88"><data value='test_classification_metrics'>TestClassifier.test_classification_metrics</data></a></td>
                 <td>7</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="7 7">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a44f0ac069e85531_test_classifier_py.html#t97">tests\test_classifier.py</a></td>
-                <td class="name left"><a href="z_a44f0ac069e85531_test_classifier_py.html#t97"><data value='test_classification_predict_proba'>TestClassifier.test_classification_predict_proba</data></a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_classifier_py.html#t102">tests\test_classifier.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_classifier_py.html#t102"><data value='test_score'>TestClassifier.test_score</data></a></td>
+                <td>6</td>
+                <td>0</td>
+                <td>0</td>
+                <td class="right" data-ratio="6 6">100%</td>
+            </tr>
+            <tr class="region">
+                <td class="name left"><a href="z_a44f0ac069e85531_test_classifier_py.html#t114">tests\test_classifier.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_classifier_py.html#t114"><data value='test_fit_on_integer_labels'>TestClassifier.test_fit_on_integer_labels</data></a></td>
+                <td>8</td>
+                <td>0</td>
+                <td>0</td>
+                <td class="right" data-ratio="8 8">100%</td>
+            </tr>
+            <tr class="region">
+                <td class="name left"><a href="z_a44f0ac069e85531_test_classifier_py.html#t132">tests\test_classifier.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_classifier_py.html#t132"><data value='test_classification_predict_proba'>TestClassifier.test_classification_predict_proba</data></a></td>
                 <td>9</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="9 9">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a44f0ac069e85531_test_classifier_py.html#t110">tests\test_classifier.py</a></td>
-                <td class="name left"><a href="z_a44f0ac069e85531_test_classifier_py.html#t110"><data value='test_prediction_results_mapping'>TestClassifier.test_prediction_results_mapping</data></a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_classifier_py.html#t144">tests\test_classifier.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_classifier_py.html#t144"><data value='test_prediction_results_mapping'>TestClassifier.test_prediction_results_mapping</data></a></td>
                 <td>6</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="6 6">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a44f0ac069e85531_test_classifier_py.html#t128">tests\test_classifier.py</a></td>
-                <td class="name left"><a href="z_a44f0ac069e85531_test_classifier_py.html#t128"><data value='test_prediction_on_nominal_values'>TestClassifier.test_prediction_on_nominal_values</data></a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_classifier_py.html#t162">tests\test_classifier.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_classifier_py.html#t162"><data value='test_prediction_on_nominal_values'>TestClassifier.test_prediction_on_nominal_values</data></a></td>
                 <td>6</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="6 6">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a44f0ac069e85531_test_classifier_py.html#t139">tests\test_classifier.py</a></td>
-                <td class="name left"><a href="z_a44f0ac069e85531_test_classifier_py.html#t139"><data value='test_compare_with_java_results'>TestClassifier.test_compare_with_java_results</data></a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_classifier_py.html#t173">tests\test_classifier.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_classifier_py.html#t173"><data value='test_compare_with_java_results'>TestClassifier.test_compare_with_java_results</data></a></td>
                 <td>11</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="11 11">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a44f0ac069e85531_test_classifier_py.html#t154">tests\test_classifier.py</a></td>
-                <td class="name left"><a href="z_a44f0ac069e85531_test_classifier_py.html#t154"><data value='test_predict_proba'>TestClassifier.test_predict_proba</data></a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_classifier_py.html#t189">tests\test_classifier.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_classifier_py.html#t189"><data value='test_predict_proba'>TestClassifier.test_predict_proba</data></a></td>
                 <td>9</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="9 9">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a44f0ac069e85531_test_classifier_py.html#t179">tests\test_classifier.py</a></td>
-                <td class="name left"><a href="z_a44f0ac069e85531_test_classifier_py.html#t179"><data value='test_fit_and_predict_on_boolean_columns'>TestClassifier.test_fit_and_predict_on_boolean_columns</data></a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_classifier_py.html#t214">tests\test_classifier.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_classifier_py.html#t214"><data value='test_fit_and_predict_on_boolean_columns'>TestClassifier.test_fit_and_predict_on_boolean_columns</data></a></td>
                 <td>13</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="13 13">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a44f0ac069e85531_test_classifier_py.html#t200">tests\test_classifier.py</a></td>
-                <td class="name left"><a href="z_a44f0ac069e85531_test_classifier_py.html#t200"><data value='test_compare_with_java_results'>TestExperClassifier.test_compare_with_java_results</data></a></td>
-                <td>11</td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_classifier_py.html#t236">tests\test_classifier.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_classifier_py.html#t236"><data value='test_compare_with_java_results'>TestExperClassifier.test_compare_with_java_results</data></a></td>
+                <td>10</td>
                 <td>0</td>
                 <td>0</td>
-                <td class="right" data-ratio="11 11">100%</td>
+                <td class="right" data-ratio="10 10">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a44f0ac069e85531_test_classifier_py.html#t219">tests\test_classifier.py</a></td>
-                <td class="name left"><a href="z_a44f0ac069e85531_test_classifier_py.html#t219"><data value='test_predict_proba'>TestExperClassifier.test_predict_proba</data></a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_classifier_py.html#t255">tests\test_classifier.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_classifier_py.html#t255"><data value='test_predict_proba'>TestExperClassifier.test_predict_proba</data></a></td>
                 <td>9</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="9 9">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a44f0ac069e85531_test_classifier_py.html#t246">tests\test_classifier.py</a></td>
-                <td class="name left"><a href="z_a44f0ac069e85531_test_classifier_py.html#t246"><data value='test_left_open_intervals_in_expert_induction'>TestExperClassifier.test_left_open_intervals_in_expert_induction</data></a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_classifier_py.html#t284">tests\test_classifier.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_classifier_py.html#t284"><data value='test_left_open_intervals_in_expert_induction'>TestExperClassifier.test_left_open_intervals_in_expert_induction</data></a></td>
                 <td>8</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="8 8">100%</td>
             </tr>
+            <tr class="region">
+                <td class="name left"><a href="z_a44f0ac069e85531_test_classifier_py.html#t326">tests\test_classifier.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_classifier_py.html#t326"><data value='test_refining_conditions_for_nominal_attributes'>TestExperClassifier.test_refining_conditions_for_nominal_attributes</data></a></td>
+                <td>7</td>
+                <td>0</td>
+                <td>0</td>
+                <td class="right" data-ratio="7 7">100%</td>
+            </tr>
             <tr class="region">
                 <td class="name left"><a href="z_a44f0ac069e85531_test_classifier_py.html">tests\test_classifier.py</a></td>
                 <td class="name left"><a href="z_a44f0ac069e85531_test_classifier_py.html"><data value=''><span class='no-noun'>(no function)</span></data></a></td>
-                <td>33</td>
+                <td>35</td>
                 <td>1</td>
                 <td>0</td>
-                <td class="right" data-ratio="32 33">97%</td>
+                <td class="right" data-ratio="34 35">97%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a44f0ac069e85531_test_regression_py.html#t21">tests\test_regression.py</a></td>
-                <td class="name left"><a href="z_a44f0ac069e85531_test_regression_py.html#t21"><data value='setUpClass'>TestRegressor.setUpClass</data></a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_regression_py.html#t24">tests\test_regression.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_regression_py.html#t24"><data value='setUpClass'>TestRegressor.setUpClass</data></a></td>
                 <td>1</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="1 1">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a44f0ac069e85531_test_regression_py.html#t24">tests\test_regression.py</a></td>
-                <td class="name left"><a href="z_a44f0ac069e85531_test_regression_py.html#t24"><data value='test_induction_progress_listener'>TestRegressor.test_induction_progress_listener</data></a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_regression_py.html#t27">tests\test_regression.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_regression_py.html#t27"><data value='test_induction_progress_listener'>TestRegressor.test_induction_progress_listener</data></a></td>
                 <td>17</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="17 17">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a44f0ac069e85531_test_regression_py.html#t37">tests\test_regression.py</a></td>
-                <td class="name left"><a href="z_a44f0ac069e85531_test_regression_py.html#t37"><data value='on_new_rule'>TestRegressor.test_induction_progress_listener.EventListener.on_new_rule</data></a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_regression_py.html#t40">tests\test_regression.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_regression_py.html#t40"><data value='on_new_rule'>TestRegressor.test_induction_progress_listener.EventListener.on_new_rule</data></a></td>
                 <td>3</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="3 3">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a44f0ac069e85531_test_regression_py.html#t42">tests\test_regression.py</a></td>
-                <td class="name left"><a href="z_a44f0ac069e85531_test_regression_py.html#t42"><data value='on_progress'>TestRegressor.test_induction_progress_listener.EventListener.on_progress</data></a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_regression_py.html#t45">tests\test_regression.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_regression_py.html#t45"><data value='on_progress'>TestRegressor.test_induction_progress_listener.EventListener.on_progress</data></a></td>
                 <td>3</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="3 3">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a44f0ac069e85531_test_regression_py.html#t51">tests\test_regression.py</a></td>
-                <td class="name left"><a href="z_a44f0ac069e85531_test_regression_py.html#t51"><data value='should_stop'>TestRegressor.test_induction_progress_listener.EventListener.should_stop</data></a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_regression_py.html#t52">tests\test_regression.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_regression_py.html#t52"><data value='should_stop'>TestRegressor.test_induction_progress_listener.EventListener.should_stop</data></a></td>
                 <td>4</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="4 4">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a44f0ac069e85531_test_regression_py.html#t65">tests\test_regression.py</a></td>
-                <td class="name left"><a href="z_a44f0ac069e85531_test_regression_py.html#t65"><data value='test_compare_with_java_results'>TestRegressor.test_compare_with_java_results</data></a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_regression_py.html#t66">tests\test_regression.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_regression_py.html#t66"><data value='test_compare_with_java_results'>TestRegressor.test_compare_with_java_results</data></a></td>
                 <td>11</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="11 11">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a44f0ac069e85531_test_regression_py.html#t80">tests\test_regression.py</a></td>
-                <td class="name left"><a href="z_a44f0ac069e85531_test_regression_py.html#t80"><data value='test_fit_and_predict_on_boolean_columns'>TestRegressor.test_fit_and_predict_on_boolean_columns</data></a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_regression_py.html#t82">tests\test_regression.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_regression_py.html#t82"><data value='test_fit_and_predict_on_boolean_columns'>TestRegressor.test_fit_and_predict_on_boolean_columns</data></a></td>
                 <td>10</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="10 10">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a44f0ac069e85531_test_regression_py.html#t94">tests\test_regression.py</a></td>
-                <td class="name left"><a href="z_a44f0ac069e85531_test_regression_py.html#t94"><data value='test_cholesterol'>TestRegressor.test_cholesterol</data></a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_regression_py.html#t97">tests\test_regression.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_regression_py.html#t97"><data value='test_cholesterol'>TestRegressor.test_cholesterol</data></a></td>
                 <td>8</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="8 8">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a44f0ac069e85531_test_regression_py.html#t126">tests\test_regression.py</a></td>
-                <td class="name left"><a href="z_a44f0ac069e85531_test_regression_py.html#t126"><data value='setUpClass'>TestExpertRegressor.setUpClass</data></a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_regression_py.html#t128">tests\test_regression.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_regression_py.html#t128"><data value='setUpClass'>TestExpertRegressor.setUpClass</data></a></td>
                 <td>1</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="1 1">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a44f0ac069e85531_test_regression_py.html#t129">tests\test_regression.py</a></td>
-                <td class="name left"><a href="z_a44f0ac069e85531_test_regression_py.html#t129"><data value='test_compare_with_java_results'>TestExpertRegressor.test_compare_with_java_results</data></a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_regression_py.html#t131">tests\test_regression.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_regression_py.html#t131"><data value='test_compare_with_java_results'>TestExpertRegressor.test_compare_with_java_results</data></a></td>
                 <td>11</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="11 11">100%</td>
             </tr>
+            <tr class="region">
+                <td class="name left"><a href="z_a44f0ac069e85531_test_regression_py.html#t157">tests\test_regression.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_regression_py.html#t157"><data value='test_legacy_expert_rules_format'>TestExpertRegressor.test_legacy_expert_rules_format</data></a></td>
+                <td>9</td>
+                <td>0</td>
+                <td>0</td>
+                <td class="right" data-ratio="9 9">100%</td>
+            </tr>
+            <tr class="region">
+                <td class="name left"><a href="z_a44f0ac069e85531_test_regression_py.html#t182">tests\test_regression.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_regression_py.html#t182"><data value='test_refining_conditions_for_nominal_attributes'>TestExpertRegressor.test_refining_conditions_for_nominal_attributes</data></a></td>
+                <td>7</td>
+                <td>0</td>
+                <td>0</td>
+                <td class="right" data-ratio="7 7">100%</td>
+            </tr>
             <tr class="region">
                 <td class="name left"><a href="z_a44f0ac069e85531_test_regression_py.html">tests\test_regression.py</a></td>
                 <td class="name left"><a href="z_a44f0ac069e85531_test_regression_py.html"><data value=''><span class='no-noun'>(no function)</span></data></a></td>
-                <td>25</td>
+                <td>31</td>
                 <td>1</td>
                 <td>0</td>
-                <td class="right" data-ratio="24 25">96%</td>
+                <td class="right" data-ratio="30 31">97%</td>
             </tr>
             <tr class="region">
                 <td class="name left"><a href="z_a44f0ac069e85531_test_rulekit_py.html#t11">tests\test_rulekit.py</a></td>
@@ -2153,72 +2233,72 @@ <h2>
                 <td class="right" data-ratio="10 11">91%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a44f0ac069e85531_test_survival_py.html#t19">tests\test_survival.py</a></td>
-                <td class="name left"><a href="z_a44f0ac069e85531_test_survival_py.html#t19"><data value='setUp'>TestKaplanMeierEstimator.setUp</data></a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_survival_py.html#t21">tests\test_survival.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_survival_py.html#t21"><data value='setUp'>TestKaplanMeierEstimator.setUp</data></a></td>
                 <td>5</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="5 5">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a44f0ac069e85531_test_survival_py.html#t31">tests\test_survival.py</a></td>
-                <td class="name left"><a href="z_a44f0ac069e85531_test_survival_py.html#t31"><data value='test_accessing_probabilities'>TestKaplanMeierEstimator.test_accessing_probabilities</data></a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_survival_py.html#t36">tests\test_survival.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_survival_py.html#t36"><data value='test_accessing_probabilities'>TestKaplanMeierEstimator.test_accessing_probabilities</data></a></td>
                 <td>2</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="2 2">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a44f0ac069e85531_test_survival_py.html#t41">tests\test_survival.py</a></td>
-                <td class="name left"><a href="z_a44f0ac069e85531_test_survival_py.html#t41"><data value='test_accessing_events_count'>TestKaplanMeierEstimator.test_accessing_events_count</data></a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_survival_py.html#t46">tests\test_survival.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_survival_py.html#t46"><data value='test_accessing_events_count'>TestKaplanMeierEstimator.test_accessing_events_count</data></a></td>
                 <td>1</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="1 1">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a44f0ac069e85531_test_survival_py.html#t47">tests\test_survival.py</a></td>
-                <td class="name left"><a href="z_a44f0ac069e85531_test_survival_py.html#t47"><data value='test_accessing_at_risk_count'>TestKaplanMeierEstimator.test_accessing_at_risk_count</data></a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_survival_py.html#t52">tests\test_survival.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_survival_py.html#t52"><data value='test_accessing_at_risk_count'>TestKaplanMeierEstimator.test_accessing_at_risk_count</data></a></td>
                 <td>1</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="1 1">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a44f0ac069e85531_test_survival_py.html#t56">tests\test_survival.py</a></td>
-                <td class="name left"><a href="z_a44f0ac069e85531_test_survival_py.html#t56"><data value='test_induction_progress_listener'>TestSurvivalRules.test_induction_progress_listener</data></a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_survival_py.html#t61">tests\test_survival.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_survival_py.html#t61"><data value='test_induction_progress_listener'>TestSurvivalRules.test_induction_progress_listener</data></a></td>
                 <td>15</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="15 15">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a44f0ac069e85531_test_survival_py.html#t69">tests\test_survival.py</a></td>
-                <td class="name left"><a href="z_a44f0ac069e85531_test_survival_py.html#t69"><data value='on_new_rule'>TestSurvivalRules.test_induction_progress_listener.EventListener.on_new_rule</data></a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_survival_py.html#t73">tests\test_survival.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_survival_py.html#t73"><data value='on_new_rule'>TestSurvivalRules.test_induction_progress_listener.EventListener.on_new_rule</data></a></td>
                 <td>3</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="3 3">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a44f0ac069e85531_test_survival_py.html#t74">tests\test_survival.py</a></td>
-                <td class="name left"><a href="z_a44f0ac069e85531_test_survival_py.html#t74"><data value='on_progress'>TestSurvivalRules.test_induction_progress_listener.EventListener.on_progress</data></a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_survival_py.html#t78">tests\test_survival.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_survival_py.html#t78"><data value='on_progress'>TestSurvivalRules.test_induction_progress_listener.EventListener.on_progress</data></a></td>
                 <td>3</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="3 3">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a44f0ac069e85531_test_survival_py.html#t93">tests\test_survival.py</a></td>
-                <td class="name left"><a href="z_a44f0ac069e85531_test_survival_py.html#t93"><data value='test_compare_with_java_results'>TestSurvivalRules.test_compare_with_java_results</data></a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_survival_py.html#t95">tests\test_survival.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_survival_py.html#t95"><data value='test_compare_with_java_results'>TestSurvivalRules.test_compare_with_java_results</data></a></td>
                 <td>10</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="10 10">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a44f0ac069e85531_test_survival_py.html#t107">tests\test_survival.py</a></td>
-                <td class="name left"><a href="z_a44f0ac069e85531_test_survival_py.html#t107"><data value='test_fit_and_predict_on_boolean_columns'>TestSurvivalRules.test_fit_and_predict_on_boolean_columns</data></a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_survival_py.html#t110">tests\test_survival.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_survival_py.html#t110"><data value='test_fit_and_predict_on_boolean_columns'>TestSurvivalRules.test_fit_and_predict_on_boolean_columns</data></a></td>
                 <td>10</td>
                 <td>0</td>
                 <td>0</td>
@@ -2226,55 +2306,87 @@ <h2>
             </tr>
             <tr class="region">
                 <td class="name left"><a href="z_a44f0ac069e85531_test_survival_py.html#t127">tests\test_survival.py</a></td>
-                <td class="name left"><a href="z_a44f0ac069e85531_test_survival_py.html#t127"><data value='setUpClass'>TestExpertSurvivalLogRankTree.setUpClass</data></a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_survival_py.html#t127"><data value='test_passing_survival_time_column_to_fit_method'>TestSurvivalRules.test_passing_survival_time_column_to_fit_method</data></a></td>
+                <td>10</td>
+                <td>0</td>
+                <td>0</td>
+                <td class="right" data-ratio="10 10">100%</td>
+            </tr>
+            <tr class="region">
+                <td class="name left"><a href="z_a44f0ac069e85531_test_survival_py.html#t147">tests\test_survival.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_survival_py.html#t147"><data value='test_ibs_calculation'>TestSurvivalRules.test_ibs_calculation</data></a></td>
+                <td>10</td>
+                <td>0</td>
+                <td>0</td>
+                <td class="right" data-ratio="10 10">100%</td>
+            </tr>
+            <tr class="region">
+                <td class="name left"><a href="z_a44f0ac069e85531_test_survival_py.html#t165">tests\test_survival.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_survival_py.html#t165"><data value='test_getting_training_dataset_kaplan_meier_estimator'>TestSurvivalRules.test_getting_training_dataset_kaplan_meier_estimator</data></a></td>
+                <td>9</td>
+                <td>0</td>
+                <td>0</td>
+                <td class="right" data-ratio="9 9">100%</td>
+            </tr>
+            <tr class="region">
+                <td class="name left"><a href="z_a44f0ac069e85531_test_survival_py.html#t190">tests\test_survival.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_survival_py.html#t190"><data value='setUpClass'>TestExpertSurvivalRules.setUpClass</data></a></td>
                 <td>1</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="1 1">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a44f0ac069e85531_test_survival_py.html#t130">tests\test_survival.py</a></td>
-                <td class="name left"><a href="z_a44f0ac069e85531_test_survival_py.html#t130"><data value='test_compare_with_java_results'>TestExpertSurvivalLogRankTree.test_compare_with_java_results</data></a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_survival_py.html#t193">tests\test_survival.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_survival_py.html#t193"><data value='test_compare_with_java_results'>TestExpertSurvivalRules.test_compare_with_java_results</data></a></td>
                 <td>10</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="10 10">100%</td>
             </tr>
+            <tr class="region">
+                <td class="name left"><a href="z_a44f0ac069e85531_test_survival_py.html#t216">tests\test_survival.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_test_survival_py.html#t216"><data value='test_refining_conditions_for_nominal_attributes'>TestExpertSurvivalRules.test_refining_conditions_for_nominal_attributes</data></a></td>
+                <td>8</td>
+                <td>0</td>
+                <td>0</td>
+                <td class="right" data-ratio="8 8">100%</td>
+            </tr>
             <tr class="region">
                 <td class="name left"><a href="z_a44f0ac069e85531_test_survival_py.html">tests\test_survival.py</a></td>
                 <td class="name left"><a href="z_a44f0ac069e85531_test_survival_py.html"><data value=''><span class='no-noun'>(no function)</span></data></a></td>
-                <td>26</td>
+                <td>32</td>
                 <td>1</td>
                 <td>0</td>
-                <td class="right" data-ratio="25 26">96%</td>
+                <td class="right" data-ratio="31 32">97%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t30">tests\utils.py</a></td>
-                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t30"><data value='fix_missing_values'>_fix_missing_values</data></a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t28">tests\utils.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t28"><data value='fix_missing_values'>_fix_missing_values</data></a></td>
                 <td>3</td>
                 <td>1</td>
                 <td>0</td>
                 <td class="right" data-ratio="2 3">67%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t38">tests\utils.py</a></td>
-                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t38"><data value='init__'>ExampleSetWrapper.__init__</data></a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t36">tests\utils.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t36"><data value='init__'>ExampleSetWrapper.__init__</data></a></td>
                 <td>3</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="3 3">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t43">tests\utils.py</a></td>
-                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t43"><data value='get_data'>ExampleSetWrapper.get_data</data></a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t41">tests\utils.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t41"><data value='get_data'>ExampleSetWrapper.get_data</data></a></td>
                 <td>1</td>
                 <td>1</td>
                 <td>0</td>
                 <td class="right" data-ratio="0 1">0%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t47">tests\utils.py</a></td>
-                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t47"><data value='load_arff_to_example_set'>load_arff_to_example_set</data></a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t45">tests\utils.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t45"><data value='load_arff_to_example_set'>load_arff_to_example_set</data></a></td>
                 <td>14</td>
                 <td>0</td>
                 <td>0</td>
@@ -2321,252 +2433,252 @@ <h2>
                 <td class="right" data-ratio="3 3">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t114">tests\utils.py</a></td>
-                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t114"><data value='reference_report'>TestCase.reference_report</data></a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t112">tests\utils.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t112"><data value='reference_report'>TestCase.reference_report</data></a></td>
                 <td>5</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="5 5">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t124">tests\utils.py</a></td>
-                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t124"><data value='init__'>DataSetConfig.__init__</data></a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t122">tests\utils.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t122"><data value='init__'>DataSetConfig.__init__</data></a></td>
                 <td>4</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="4 4">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t133">tests\utils.py</a></td>
-                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t133"><data value='init__'>TestConfig.__init__</data></a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t131">tests\utils.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t131"><data value='init__'>TestConfig.__init__</data></a></td>
                 <td>3</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="3 3">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t160">tests\utils.py</a></td>
-                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t160"><data value='init__'>TestConfigParser.__init__</data></a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t158">tests\utils.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t158"><data value='init__'>TestConfigParser.__init__</data></a></td>
                 <td>2</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="2 2">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t164">tests\utils.py</a></td>
-                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t164"><data value='parse_survival_time'>TestConfigParser._parse_survival_time</data></a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t162">tests\utils.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t162"><data value='parse_survival_time'>TestConfigParser._parse_survival_time</data></a></td>
                 <td>4</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="4 4">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t172">tests\utils.py</a></td>
-                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t172"><data value='parse_experts_rules_parameters'>TestConfigParser._parse_experts_rules_parameters</data></a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t169">tests\utils.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t169"><data value='parse_experts_rules_parameters'>TestConfigParser._parse_experts_rules_parameters</data></a></td>
                 <td>7</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="7 7">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t183">tests\utils.py</a></td>
-                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t183"><data value='check_ambigous_data_sets_names'>TestConfigParser._check_ambigous_data_sets_names</data></a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t179">tests\utils.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t179"><data value='check_ambigous_data_sets_names'>TestConfigParser._check_ambigous_data_sets_names</data></a></td>
                 <td>5</td>
                 <td>5</td>
                 <td>0</td>
                 <td class="right" data-ratio="0 5">0%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t190">tests\utils.py</a></td>
-                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t190"><data value='parse_data_set'>TestConfigParser._parse_data_set</data></a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t186">tests\utils.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t186"><data value='parse_data_set'>TestConfigParser._parse_data_set</data></a></td>
                 <td>11</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="11 11">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t205">tests\utils.py</a></td>
-                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t205"><data value='parse_data_sets'>TestConfigParser._parse_data_sets</data></a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t201">tests\utils.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t201"><data value='parse_data_sets'>TestConfigParser._parse_data_sets</data></a></td>
                 <td>5</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="5 5">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t212">tests\utils.py</a></td>
-                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t212"><data value='parse_test_parameters'>TestConfigParser.parse_test_parameters</data></a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t208">tests\utils.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t208"><data value='parse_test_parameters'>TestConfigParser.parse_test_parameters</data></a></td>
                 <td>8</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="8 8">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t224">tests\utils.py</a></td>
-                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t224"><data value='parse_test_parameters_sets'>TestConfigParser._parse_test_parameters_sets</data></a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t221">tests\utils.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t221"><data value='parse_test_parameters_sets'>TestConfigParser._parse_test_parameters_sets</data></a></td>
                 <td>6</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="6 6">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t233">tests\utils.py</a></td>
-                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t233"><data value='parse_test'>TestConfigParser._parse_test</data></a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t229">tests\utils.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t229"><data value='parse_test'>TestConfigParser._parse_test</data></a></td>
                 <td>5</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="5 5">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t242">tests\utils.py</a></td>
-                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t242"><data value='parse'>TestConfigParser.parse</data></a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t236">tests\utils.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t236"><data value='parse'>TestConfigParser.parse</data></a></td>
                 <td>9</td>
                 <td>1</td>
                 <td>0</td>
                 <td class="right" data-ratio="8 9">89%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t257">tests\utils.py</a></td>
-                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t257"><data value='make_test_case'>TestCaseFactory._make_test_case</data></a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t251">tests\utils.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t251"><data value='make_test_case'>TestCaseFactory._make_test_case</data></a></td>
                 <td>9</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="9 9">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t274">tests\utils.py</a></td>
-                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t274"><data value='fix_deprecated_params'>TestCaseFactory._fix_deprecated_params</data></a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t270">tests\utils.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t270"><data value='fix_deprecated_params'>TestCaseFactory._fix_deprecated_params</data></a></td>
                 <td>3</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="3 3">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t279">tests\utils.py</a></td>
-                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t279"><data value='fix_params_typing'>TestCaseFactory._fix_params_typing</data></a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t275">tests\utils.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t275"><data value='fix_params_typing'>TestCaseFactory._fix_params_typing</data></a></td>
                 <td>9</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="9 9">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t290">tests\utils.py</a></td>
-                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t290"><data value='make'>TestCaseFactory.make</data></a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t286">tests\utils.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t286"><data value='make'>TestCaseFactory.make</data></a></td>
                 <td>29</td>
                 <td>2</td>
                 <td>0</td>
                 <td class="right" data-ratio="27 29">93%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t337">tests\utils.py</a></td>
-                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t337"><data value='get_rule_string'>get_rule_string</data></a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t343">tests\utils.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t343"><data value='get_rule_string'>get_rule_string</data></a></td>
                 <td>1</td>
                 <td>1</td>
                 <td>0</td>
                 <td class="right" data-ratio="0 1">0%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t343">tests\utils.py</a></td>
-                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t343"><data value='init__'>TestReportReader.__init__</data></a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t349">tests\utils.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t349"><data value='init__'>TestReportReader.__init__</data></a></td>
                 <td>2</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="2 2">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t347">tests\utils.py</a></td>
-                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t347"><data value='read_rules'>TestReportReader._read_rules</data></a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t353">tests\utils.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t353"><data value='read_rules'>TestReportReader._read_rules</data></a></td>
                 <td>6</td>
                 <td>1</td>
                 <td>0</td>
                 <td class="right" data-ratio="5 6">83%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t356">tests\utils.py</a></td>
-                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t356"><data value='read'>TestReportReader.read</data></a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t362">tests\utils.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t362"><data value='read'>TestReportReader.read</data></a></td>
                 <td>11</td>
                 <td>1</td>
                 <td>0</td>
                 <td class="right" data-ratio="10 11">91%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t371">tests\utils.py</a></td>
-                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t371"><data value='close'>TestReportReader.close</data></a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t378">tests\utils.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t378"><data value='close'>TestReportReader.close</data></a></td>
                 <td>1</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="1 1">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t377">tests\utils.py</a></td>
-                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t377"><data value='init__'>TestReportWriter.__init__</data></a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t384">tests\utils.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t384"><data value='init__'>TestReportWriter.__init__</data></a></td>
                 <td>3</td>
                 <td>3</td>
                 <td>0</td>
                 <td class="right" data-ratio="0 3">0%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t382">tests\utils.py</a></td>
-                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t382"><data value='write'>TestReportWriter.write</data></a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t389">tests\utils.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t389"><data value='write'>TestReportWriter.write</data></a></td>
                 <td>4</td>
                 <td>4</td>
                 <td>0</td>
                 <td class="right" data-ratio="0 4">0%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t388">tests\utils.py</a></td>
-                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t388"><data value='close'>TestReportWriter.close</data></a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t395">tests\utils.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t395"><data value='close'>TestReportWriter.close</data></a></td>
                 <td>1</td>
                 <td>1</td>
                 <td>0</td>
                 <td class="right" data-ratio="0 1">0%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t392">tests\utils.py</a></td>
-                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t392"><data value='get_test_cases'>get_test_cases</data></a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t399">tests\utils.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t399"><data value='get_test_cases'>get_test_cases</data></a></td>
                 <td>5</td>
                 <td>1</td>
                 <td>0</td>
                 <td class="right" data-ratio="4 5">80%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t411">tests\utils.py</a></td>
-                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t411"><data value='get_problem_type_from_test_case_class_name'>_get_problem_type_from_test_case_class_name</data></a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t416">tests\utils.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t416"><data value='get_problem_type_from_test_case_class_name'>_get_problem_type_from_test_case_class_name</data></a></td>
                 <td>8</td>
                 <td>1</td>
                 <td>0</td>
                 <td class="right" data-ratio="7 8">88%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t423">tests\utils.py</a></td>
-                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t423"><data value='assert_rules_are_equals'>assert_rules_are_equals</data></a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t427">tests\utils.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t427"><data value='assert_rules_are_equals'>assert_rules_are_equals</data></a></td>
                 <td>18</td>
                 <td>4</td>
                 <td>0</td>
                 <td class="right" data-ratio="14 18">78%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t424">tests\utils.py</a></td>
-                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t424"><data value='sanitize_rule_string'>assert_rules_are_equals.sanitize_rule_string</data></a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t428">tests\utils.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t428"><data value='sanitize_rule_string'>assert_rules_are_equals.sanitize_rule_string</data></a></td>
                 <td>1</td>
                 <td>0</td>
                 <td>0</td>
                 <td class="right" data-ratio="1 1">100%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t451">tests\utils.py</a></td>
-                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t451"><data value='assert_accuracy_is_greater'>assert_accuracy_is_greater</data></a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t456">tests\utils.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t456"><data value='assert_accuracy_is_greater'>assert_accuracy_is_greater</data></a></td>
                 <td>4</td>
                 <td>1</td>
                 <td>0</td>
                 <td class="right" data-ratio="3 4">75%</td>
             </tr>
             <tr class="region">
-                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t458">tests\utils.py</a></td>
-                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t458"><data value='assert_score_is_greater'>assert_score_is_greater</data></a></td>
-                <td>7</td>
-                <td>2</td>
+                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t463">tests\utils.py</a></td>
+                <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html#t463"><data value='assert_score_is_greater'>assert_score_is_greater</data></a></td>
+                <td>8</td>
+                <td>3</td>
                 <td>0</td>
-                <td class="right" data-ratio="5 7">71%</td>
+                <td class="right" data-ratio="5 8">62%</td>
             </tr>
             <tr class="region">
                 <td class="name left"><a href="z_a44f0ac069e85531_utils_py.html">tests\utils.py</a></td>
@@ -2581,10 +2693,10 @@ <h2>
             <tr class="total">
                 <td class="name left">Total</td>
                 <td class="name left">&nbsp;</td>
-                <td>2006</td>
-                <td>238</td>
+                <td>2176</td>
+                <td>240</td>
                 <td>0</td>
-                <td class="right" data-ratio="1768 2006">88%</td>
+                <td class="right" data-ratio="1936 2176">89%</td>
             </tr>
         </tfoot>
     </table>
@@ -2596,7 +2708,7 @@ <h2>
     <div class="content">
         <p>
             <a class="nav" href="https://coverage.readthedocs.io/en/7.6.4">coverage.py v7.6.4</a>,
-            created at 2024-11-08 14:43 +0100
+            created at 2024-11-28 12:33 +0100
         </p>
     </div>
     <aside class="hidden">
diff --git a/docs/reports/coverage/index.html b/docs/reports/coverage/index.html
index 37ea06e..54b49ba 100644
--- a/docs/reports/coverage/index.html
+++ b/docs/reports/coverage/index.html
@@ -11,7 +11,7 @@
 <header>
     <div class="content">
         <h1>Coverage report:
-            <span class="pc_cov">88%</span>
+            <span class="pc_cov">89%</span>
         </h1>
         <aside id="help_panel_wrapper">
             <input id="help_panel_state" type="checkbox">
@@ -54,7 +54,7 @@ <h2>
         </h2>
         <p class="text">
             <a class="nav" href="https://coverage.readthedocs.io/en/7.6.4">coverage.py v7.6.4</a>,
-            created at 2024-11-08 14:43 +0100
+            created at 2024-11-28 12:33 +0100
         </p>
     </div>
 </header>
@@ -79,10 +79,10 @@ <h2>
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             <tr class="region">
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diff --git a/docs/reports/coverage/z_a44f0ac069e85531_test_classifier_py.html b/docs/reports/coverage/z_a44f0ac069e85531_test_classifier_py.html
index 4bc4611..f0d7e75 100644
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+++ b/docs/reports/coverage/z_a44f0ac069e85531_test_classifier_py.html
@@ -54,8 +54,8 @@ <h1>
             </div>
         </aside>
         <h2>
-            <span class="text">159 statements &nbsp;</span>
-            <button type="button" class="run button_toggle_run" value="run" data-shortcut="r" title="Toggle lines run">158<span class="text"> run</span></button>
+            <span class="text">181 statements &nbsp;</span>
+            <button type="button" class="run button_toggle_run" value="run" data-shortcut="r" title="Toggle lines run">180<span class="text"> run</span></button>
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             &nbsp; &nbsp; &nbsp;
             <a class="nav" href="https://coverage.readthedocs.io/en/7.6.4">coverage.py v7.6.4</a>,
-            created at 2024-11-08 14:43 +0100
+            created at 2024-11-28 12:33 +0100
         </p>
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@@ -90,14 +90,14 @@ <h2>
     <p class="run"><span class="n"><a id="t8" href="#t8">8</a></span><span class="t"><span class="key">from</span> <span class="nam">scipy</span><span class="op">.</span><span class="nam">io</span> <span class="key">import</span> <span class="nam">arff</span>&nbsp;</span><span class="r"></span></p>
     <p class="run"><span class="n"><a id="t9" href="#t9">9</a></span><span class="t"><span class="key">from</span> <span class="nam">sklearn</span> <span class="key">import</span> <span class="nam">metrics</span>&nbsp;</span><span class="r"></span></p>
     <p class="run"><span class="n"><a id="t10" href="#t10">10</a></span><span class="t"><span class="key">from</span> <span class="nam">sklearn</span><span class="op">.</span><span class="nam">datasets</span> <span class="key">import</span> <span class="nam">load_iris</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t11" href="#t11">11</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t12" href="#t12">12</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span> <span class="key">import</span> <span class="nam">classification</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t13" href="#t13">13</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">events</span> <span class="key">import</span> <span class="nam">RuleInductionProgressListener</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t14" href="#t14">14</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">rules</span> <span class="key">import</span> <span class="nam">ClassificationRule</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t15" href="#t15">15</a></span><span class="t"><span class="key">from</span> <span class="nam">tests</span><span class="op">.</span><span class="nam">utils</span> <span class="key">import</span> <span class="nam">assert_accuracy_is_greater</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t16" href="#t16">16</a></span><span class="t"><span class="key">from</span> <span class="nam">tests</span><span class="op">.</span><span class="nam">utils</span> <span class="key">import</span> <span class="nam">assert_rules_are_equals</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t17" href="#t17">17</a></span><span class="t"><span class="key">from</span> <span class="nam">tests</span><span class="op">.</span><span class="nam">utils</span> <span class="key">import</span> <span class="nam">dir_path</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t18" href="#t18">18</a></span><span class="t"><span class="key">from</span> <span class="nam">tests</span><span class="op">.</span><span class="nam">utils</span> <span class="key">import</span> <span class="nam">get_test_cases</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t11" href="#t11">11</a></span><span class="t"><span class="key">from</span> <span class="nam">sklearn</span><span class="op">.</span><span class="nam">preprocessing</span> <span class="key">import</span> <span class="nam">LabelEncoder</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t12" href="#t12">12</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t13" href="#t13">13</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span> <span class="key">import</span> <span class="nam">classification</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t14" href="#t14">14</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">events</span> <span class="key">import</span> <span class="nam">RuleInductionProgressListener</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t15" href="#t15">15</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">params</span> <span class="key">import</span> <span class="nam">Measures</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t16" href="#t16">16</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">rules</span> <span class="key">import</span> <span class="nam">ClassificationRule</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t17" href="#t17">17</a></span><span class="t"><span class="key">from</span> <span class="nam">tests</span><span class="op">.</span><span class="nam">utils</span> <span class="key">import</span> <span class="op">(</span><span class="nam">assert_accuracy_is_greater</span><span class="op">,</span> <span class="nam">assert_rules_are_equals</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t18" href="#t18">18</a></span><span class="t">                         <span class="nam">dir_path</span><span class="op">,</span> <span class="nam">get_test_cases</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t19" href="#t19">19</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t20" href="#t20">20</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
     <p class="run"><span class="n"><a id="t21" href="#t21">21</a></span><span class="t"><span class="key">class</span> <span class="nam">TestClassifier</span><span class="op">(</span><span class="nam">unittest</span><span class="op">.</span><span class="nam">TestCase</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
@@ -114,259 +114,370 @@ <h2>
     <p class="run"><span class="n"><a id="t32" href="#t32">32</a></span><span class="t">        <span class="nam">scikit_accuracy</span> <span class="op">=</span> <span class="nam">metrics</span><span class="op">.</span><span class="nam">accuracy_score</span><span class="op">(</span><span class="nam">y</span><span class="op">,</span> <span class="nam">scikit_prediction</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
     <p class="run"><span class="n"><a id="t33" href="#t33">33</a></span><span class="t">        <span class="nam">rulekit_accuracy</span> <span class="op">=</span> <span class="nam">metrics</span><span class="op">.</span><span class="nam">accuracy_score</span><span class="op">(</span><span class="nam">y</span><span class="op">,</span> <span class="nam">rulekit_prediction</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t34" href="#t34">34</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t35" href="#t35">35</a></span><span class="t">        <span class="key">assert</span> <span class="nam">abs</span><span class="op">(</span><span class="nam">scikit_accuracy</span> <span class="op">-</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t36" href="#t36">36</a></span><span class="t">                   <span class="nam">rulekit_accuracy</span><span class="op">)</span> <span class="op">&lt;</span> <span class="num">0.04</span><span class="op">,</span> <span class="str">'RuleKit model should perform similar to scikit model'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t37" href="#t37">37</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t38" href="#t38">38</a></span><span class="t">    <span class="key">def</span> <span class="nam">test_induction_progress_listener</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t39" href="#t39">39</a></span><span class="t">        <span class="nam">rulekit_clf</span> <span class="op">=</span> <span class="nam">classification</span><span class="op">.</span><span class="nam">RuleClassifier</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t40" href="#t40">40</a></span><span class="t">        <span class="nam">x</span><span class="op">,</span> <span class="nam">y</span> <span class="op">=</span> <span class="nam">load_iris</span><span class="op">(</span><span class="nam">return_X_y</span><span class="op">=</span><span class="key">True</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t41" href="#t41">41</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t42" href="#t42">42</a></span><span class="t">        <span class="key">class</span> <span class="nam">EventListener</span><span class="op">(</span><span class="nam">RuleInductionProgressListener</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t43" href="#t43">43</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t44" href="#t44">44</a></span><span class="t">            <span class="nam">lock</span> <span class="op">=</span> <span class="nam">threading</span><span class="op">.</span><span class="nam">Lock</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t45" href="#t45">45</a></span><span class="t">            <span class="nam">induced_rules_count</span> <span class="op">=</span> <span class="num">0</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t46" href="#t46">46</a></span><span class="t">            <span class="nam">on_progress_calls_count</span> <span class="op">=</span> <span class="num">0</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t47" href="#t47">47</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t48" href="#t48">48</a></span><span class="t">            <span class="key">def</span> <span class="nam">on_new_rule</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">rule</span><span class="op">:</span> <span class="nam">ClassificationRule</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t49" href="#t49">49</a></span><span class="t">                <span class="nam">self</span><span class="op">.</span><span class="nam">lock</span><span class="op">.</span><span class="nam">acquire</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t50" href="#t50">50</a></span><span class="t">                <span class="nam">self</span><span class="op">.</span><span class="nam">induced_rules_count</span> <span class="op">+=</span> <span class="num">1</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t51" href="#t51">51</a></span><span class="t">                <span class="nam">self</span><span class="op">.</span><span class="nam">lock</span><span class="op">.</span><span class="nam">release</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t52" href="#t52">52</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t53" href="#t53">53</a></span><span class="t">            <span class="key">def</span> <span class="nam">on_progress</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t54" href="#t54">54</a></span><span class="t">                <span class="nam">self</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t55" href="#t55">55</a></span><span class="t">                <span class="nam">total_examples_count</span><span class="op">:</span> <span class="nam">int</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t56" href="#t56">56</a></span><span class="t">                <span class="nam">uncovered_examples_count</span><span class="op">:</span> <span class="nam">int</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t57" href="#t57">57</a></span><span class="t">            <span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t58" href="#t58">58</a></span><span class="t">                <span class="nam">self</span><span class="op">.</span><span class="nam">lock</span><span class="op">.</span><span class="nam">acquire</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t59" href="#t59">59</a></span><span class="t">                <span class="nam">self</span><span class="op">.</span><span class="nam">on_progress_calls_count</span> <span class="op">+=</span> <span class="num">1</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t60" href="#t60">60</a></span><span class="t">                <span class="nam">self</span><span class="op">.</span><span class="nam">lock</span><span class="op">.</span><span class="nam">release</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t61" href="#t61">61</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t62" href="#t62">62</a></span><span class="t">        <span class="nam">listener</span> <span class="op">=</span> <span class="nam">EventListener</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t63" href="#t63">63</a></span><span class="t">        <span class="nam">rulekit_clf</span><span class="op">.</span><span class="nam">add_event_listener</span><span class="op">(</span><span class="nam">listener</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t64" href="#t64">64</a></span><span class="t">        <span class="nam">rulekit_clf</span><span class="op">.</span><span class="nam">fit</span><span class="op">(</span><span class="nam">x</span><span class="op">,</span> <span class="nam">y</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t65" href="#t65">65</a></span><span class="t">        <span class="nam">rules_count</span> <span class="op">=</span> <span class="nam">len</span><span class="op">(</span><span class="nam">rulekit_clf</span><span class="op">.</span><span class="nam">model</span><span class="op">.</span><span class="nam">rules</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t66" href="#t66">66</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">assertEqual</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t67" href="#t67">67</a></span><span class="t">            <span class="nam">rules_count</span><span class="op">,</span> <span class="nam">listener</span><span class="op">.</span><span class="nam">induced_rules_count</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t68" href="#t68">68</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t69" href="#t69">69</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">assertEqual</span><span class="op">(</span><span class="nam">rules_count</span><span class="op">,</span> <span class="nam">listener</span><span class="op">.</span><span class="nam">on_progress_calls_count</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t70" href="#t70">70</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t71" href="#t71">71</a></span><span class="t">    <span class="key">def</span> <span class="nam">test_getting_examples_coverage</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t72" href="#t72">72</a></span><span class="t">        <span class="nam">clf</span> <span class="op">=</span> <span class="nam">classification</span><span class="op">.</span><span class="nam">RuleClassifier</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t73" href="#t73">73</a></span><span class="t">        <span class="nam">x</span><span class="op">,</span> <span class="nam">y</span> <span class="op">=</span> <span class="nam">load_iris</span><span class="op">(</span><span class="nam">return_X_y</span><span class="op">=</span><span class="key">True</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t74" href="#t74">74</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t75" href="#t75">75</a></span><span class="t">        <span class="nam">clf</span><span class="op">.</span><span class="nam">fit</span><span class="op">(</span><span class="nam">x</span><span class="op">,</span> <span class="nam">y</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t35" href="#t35">35</a></span><span class="t">        <span class="key">assert</span> <span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t36" href="#t36">36</a></span><span class="t">            <span class="nam">abs</span><span class="op">(</span><span class="nam">scikit_accuracy</span> <span class="op">-</span> <span class="nam">rulekit_accuracy</span><span class="op">)</span> <span class="op">&lt;</span> <span class="num">0.04</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t37" href="#t37">37</a></span><span class="t">        <span class="op">)</span><span class="op">,</span> <span class="str">"RuleKit model should perform similar to scikit model"</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t38" href="#t38">38</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t39" href="#t39">39</a></span><span class="t">    <span class="key">def</span> <span class="nam">test_induction_progress_listener</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t40" href="#t40">40</a></span><span class="t">        <span class="nam">rulekit_clf</span> <span class="op">=</span> <span class="nam">classification</span><span class="op">.</span><span class="nam">RuleClassifier</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t41" href="#t41">41</a></span><span class="t">        <span class="nam">x</span><span class="op">,</span> <span class="nam">y</span> <span class="op">=</span> <span class="nam">load_iris</span><span class="op">(</span><span class="nam">return_X_y</span><span class="op">=</span><span class="key">True</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t42" href="#t42">42</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t43" href="#t43">43</a></span><span class="t">        <span class="key">class</span> <span class="nam">EventListener</span><span class="op">(</span><span class="nam">RuleInductionProgressListener</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t44" href="#t44">44</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t45" href="#t45">45</a></span><span class="t">            <span class="nam">lock</span> <span class="op">=</span> <span class="nam">threading</span><span class="op">.</span><span class="nam">Lock</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t46" href="#t46">46</a></span><span class="t">            <span class="nam">induced_rules_count</span> <span class="op">=</span> <span class="num">0</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t47" href="#t47">47</a></span><span class="t">            <span class="nam">on_progress_calls_count</span> <span class="op">=</span> <span class="num">0</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t48" href="#t48">48</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t49" href="#t49">49</a></span><span class="t">            <span class="key">def</span> <span class="nam">on_new_rule</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">rule</span><span class="op">:</span> <span class="nam">ClassificationRule</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t50" href="#t50">50</a></span><span class="t">                <span class="nam">self</span><span class="op">.</span><span class="nam">lock</span><span class="op">.</span><span class="nam">acquire</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t51" href="#t51">51</a></span><span class="t">                <span class="nam">self</span><span class="op">.</span><span class="nam">induced_rules_count</span> <span class="op">+=</span> <span class="num">1</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t52" href="#t52">52</a></span><span class="t">                <span class="nam">self</span><span class="op">.</span><span class="nam">lock</span><span class="op">.</span><span class="nam">release</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t53" href="#t53">53</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t54" href="#t54">54</a></span><span class="t">            <span class="key">def</span> <span class="nam">on_progress</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t55" href="#t55">55</a></span><span class="t">                <span class="nam">self</span><span class="op">,</span> <span class="nam">total_examples_count</span><span class="op">:</span> <span class="nam">int</span><span class="op">,</span> <span class="nam">uncovered_examples_count</span><span class="op">:</span> <span class="nam">int</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t56" href="#t56">56</a></span><span class="t">            <span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t57" href="#t57">57</a></span><span class="t">                <span class="nam">self</span><span class="op">.</span><span class="nam">lock</span><span class="op">.</span><span class="nam">acquire</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t58" href="#t58">58</a></span><span class="t">                <span class="nam">self</span><span class="op">.</span><span class="nam">on_progress_calls_count</span> <span class="op">+=</span> <span class="num">1</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t59" href="#t59">59</a></span><span class="t">                <span class="nam">self</span><span class="op">.</span><span class="nam">lock</span><span class="op">.</span><span class="nam">release</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t60" href="#t60">60</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t61" href="#t61">61</a></span><span class="t">        <span class="nam">listener</span> <span class="op">=</span> <span class="nam">EventListener</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t62" href="#t62">62</a></span><span class="t">        <span class="nam">rulekit_clf</span><span class="op">.</span><span class="nam">add_event_listener</span><span class="op">(</span><span class="nam">listener</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t63" href="#t63">63</a></span><span class="t">        <span class="nam">rulekit_clf</span><span class="op">.</span><span class="nam">fit</span><span class="op">(</span><span class="nam">x</span><span class="op">,</span> <span class="nam">y</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t64" href="#t64">64</a></span><span class="t">        <span class="nam">rules_count</span> <span class="op">=</span> <span class="nam">len</span><span class="op">(</span><span class="nam">rulekit_clf</span><span class="op">.</span><span class="nam">model</span><span class="op">.</span><span class="nam">rules</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t65" href="#t65">65</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">assertEqual</span><span class="op">(</span><span class="nam">rules_count</span><span class="op">,</span> <span class="nam">listener</span><span class="op">.</span><span class="nam">induced_rules_count</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t66" href="#t66">66</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">assertEqual</span><span class="op">(</span><span class="nam">rules_count</span><span class="op">,</span> <span class="nam">listener</span><span class="op">.</span><span class="nam">on_progress_calls_count</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t67" href="#t67">67</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t68" href="#t68">68</a></span><span class="t">    <span class="key">def</span> <span class="nam">test_getting_examples_coverage</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t69" href="#t69">69</a></span><span class="t">        <span class="nam">clf</span> <span class="op">=</span> <span class="nam">classification</span><span class="op">.</span><span class="nam">RuleClassifier</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t70" href="#t70">70</a></span><span class="t">        <span class="nam">x</span><span class="op">,</span> <span class="nam">y</span> <span class="op">=</span> <span class="nam">load_iris</span><span class="op">(</span><span class="nam">return_X_y</span><span class="op">=</span><span class="key">True</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t71" href="#t71">71</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t72" href="#t72">72</a></span><span class="t">        <span class="nam">clf</span><span class="op">.</span><span class="nam">fit</span><span class="op">(</span><span class="nam">x</span><span class="op">,</span> <span class="nam">y</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t73" href="#t73">73</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t74" href="#t74">74</a></span><span class="t">        <span class="nam">coverage_matrix</span> <span class="op">=</span> <span class="nam">clf</span><span class="op">.</span><span class="nam">get_coverage_matrix</span><span class="op">(</span><span class="nam">x</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t75" href="#t75">75</a></span><span class="t">        <span class="nam">num_rows</span><span class="op">,</span> <span class="nam">num_cols</span> <span class="op">=</span> <span class="nam">coverage_matrix</span><span class="op">.</span><span class="nam">shape</span>&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t76" href="#t76">76</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t77" href="#t77">77</a></span><span class="t">        <span class="nam">coverage_matrix</span> <span class="op">=</span> <span class="nam">clf</span><span class="op">.</span><span class="nam">get_coverage_matrix</span><span class="op">(</span><span class="nam">x</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t78" href="#t78">78</a></span><span class="t">        <span class="nam">num_rows</span><span class="op">,</span> <span class="nam">num_cols</span> <span class="op">=</span> <span class="nam">coverage_matrix</span><span class="op">.</span><span class="nam">shape</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t79" href="#t79">79</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t80" href="#t80">80</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">assertEqual</span><span class="op">(</span><span class="nam">num_rows</span><span class="op">,</span> <span class="nam">len</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t81" href="#t81">81</a></span><span class="t">            <span class="nam">x</span><span class="op">)</span><span class="op">,</span> <span class="str">'Coverage matrix should have as many rows as examples in dataset'</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t82" href="#t82">82</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">assertEqual</span><span class="op">(</span><span class="nam">num_cols</span><span class="op">,</span> <span class="nam">len</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t83" href="#t83">83</a></span><span class="t">            <span class="nam">clf</span><span class="op">.</span><span class="nam">model</span><span class="op">.</span><span class="nam">rules</span><span class="op">)</span><span class="op">,</span> <span class="str">'Coverage matrix should have as many cols as rules in ruleset'</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t84" href="#t84">84</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t85" href="#t85">85</a></span><span class="t">    <span class="key">def</span> <span class="nam">test_classification_metrics</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t86" href="#t86">86</a></span><span class="t">        <span class="nam">clf</span> <span class="op">=</span> <span class="nam">classification</span><span class="op">.</span><span class="nam">RuleClassifier</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t87" href="#t87">87</a></span><span class="t">        <span class="nam">x</span><span class="op">,</span> <span class="nam">y</span> <span class="op">=</span> <span class="nam">load_iris</span><span class="op">(</span><span class="nam">return_X_y</span><span class="op">=</span><span class="key">True</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t88" href="#t88">88</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t89" href="#t89">89</a></span><span class="t">        <span class="nam">clf</span><span class="op">.</span><span class="nam">fit</span><span class="op">(</span><span class="nam">x</span><span class="op">,</span> <span class="nam">y</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t90" href="#t90">90</a></span><span class="t">        <span class="nam">y_pred</span><span class="op">,</span> <span class="nam">m</span> <span class="op">=</span> <span class="nam">clf</span><span class="op">.</span><span class="nam">predict</span><span class="op">(</span><span class="nam">x</span><span class="op">,</span> <span class="nam">return_metrics</span><span class="op">=</span><span class="key">True</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t91" href="#t91">91</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">assertEqual</span><span class="op">(</span><span class="nam">len</span><span class="op">(</span><span class="nam">y_pred</span><span class="op">)</span><span class="op">,</span> <span class="nam">len</span><span class="op">(</span><span class="nam">y</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t92" href="#t92">92</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">assertIsNotNone</span><span class="op">(</span><span class="nam">m</span><span class="op">[</span><span class="str">'rules_per_example'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t93" href="#t93">93</a></span><span class="t">                             <span class="str">'rules_per_example should be calculated'</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t94" href="#t94">94</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">assertIsNotNone</span><span class="op">(</span><span class="nam">m</span><span class="op">[</span><span class="str">'voting_conflicts'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t95" href="#t95">95</a></span><span class="t">                             <span class="str">'rules_per_example should be calculated'</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t96" href="#t96">96</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t97" href="#t97">97</a></span><span class="t">    <span class="key">def</span> <span class="nam">test_classification_predict_proba</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t98" href="#t98">98</a></span><span class="t">        <span class="nam">clf</span> <span class="op">=</span> <span class="nam">classification</span><span class="op">.</span><span class="nam">RuleClassifier</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t99" href="#t99">99</a></span><span class="t">        <span class="nam">x</span><span class="op">,</span> <span class="nam">y</span> <span class="op">=</span> <span class="nam">load_iris</span><span class="op">(</span><span class="nam">return_X_y</span><span class="op">=</span><span class="key">True</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t100" href="#t100">100</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t101" href="#t101">101</a></span><span class="t">        <span class="nam">clf</span><span class="op">.</span><span class="nam">fit</span><span class="op">(</span><span class="nam">x</span><span class="op">,</span> <span class="nam">y</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t102" href="#t102">102</a></span><span class="t">        <span class="nam">confidence_matrix</span><span class="op">,</span> <span class="nam">m</span> <span class="op">=</span> <span class="nam">clf</span><span class="op">.</span><span class="nam">predict_proba</span><span class="op">(</span><span class="nam">x</span><span class="op">,</span> <span class="nam">return_metrics</span><span class="op">=</span><span class="key">True</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t103" href="#t103">103</a></span><span class="t">        <span class="key">for</span> <span class="nam">row</span> <span class="key">in</span> <span class="nam">confidence_matrix</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t104" href="#t104">104</a></span><span class="t">            <span class="nam">sum</span> <span class="op">=</span> <span class="num">0</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t105" href="#t105">105</a></span><span class="t">            <span class="key">for</span> <span class="nam">col</span> <span class="key">in</span> <span class="nam">row</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t106" href="#t106">106</a></span><span class="t">                <span class="nam">sum</span> <span class="op">+=</span> <span class="nam">col</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t107" href="#t107">107</a></span><span class="t">            <span class="nam">self</span><span class="op">.</span><span class="nam">assertAlmostEqual</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t108" href="#t108">108</a></span><span class="t">                <span class="nam">sum</span><span class="op">,</span> <span class="num">1</span><span class="op">,</span> <span class="num">3</span><span class="op">,</span> <span class="str">'Confidence matrix rows should sum to 1'</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t77" href="#t77">77</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">assertEqual</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t78" href="#t78">78</a></span><span class="t">            <span class="nam">num_rows</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t79" href="#t79">79</a></span><span class="t">            <span class="nam">len</span><span class="op">(</span><span class="nam">x</span><span class="op">)</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t80" href="#t80">80</a></span><span class="t">            <span class="str">"Coverage matrix should have as many rows as examples in dataset"</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t81" href="#t81">81</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t82" href="#t82">82</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">assertEqual</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t83" href="#t83">83</a></span><span class="t">            <span class="nam">num_cols</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t84" href="#t84">84</a></span><span class="t">            <span class="nam">len</span><span class="op">(</span><span class="nam">clf</span><span class="op">.</span><span class="nam">model</span><span class="op">.</span><span class="nam">rules</span><span class="op">)</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t85" href="#t85">85</a></span><span class="t">            <span class="str">"Coverage matrix should have as many cols as rules in ruleset"</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t86" href="#t86">86</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t87" href="#t87">87</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t88" href="#t88">88</a></span><span class="t">    <span class="key">def</span> <span class="nam">test_classification_metrics</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t89" href="#t89">89</a></span><span class="t">        <span class="nam">clf</span> <span class="op">=</span> <span class="nam">classification</span><span class="op">.</span><span class="nam">RuleClassifier</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t90" href="#t90">90</a></span><span class="t">        <span class="nam">x</span><span class="op">,</span> <span class="nam">y</span> <span class="op">=</span> <span class="nam">load_iris</span><span class="op">(</span><span class="nam">return_X_y</span><span class="op">=</span><span class="key">True</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t91" href="#t91">91</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t92" href="#t92">92</a></span><span class="t">        <span class="nam">clf</span><span class="op">.</span><span class="nam">fit</span><span class="op">(</span><span class="nam">x</span><span class="op">,</span> <span class="nam">y</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t93" href="#t93">93</a></span><span class="t">        <span class="nam">y_pred</span><span class="op">,</span> <span class="nam">m</span> <span class="op">=</span> <span class="nam">clf</span><span class="op">.</span><span class="nam">predict</span><span class="op">(</span><span class="nam">x</span><span class="op">,</span> <span class="nam">return_metrics</span><span class="op">=</span><span class="key">True</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t94" href="#t94">94</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">assertEqual</span><span class="op">(</span><span class="nam">len</span><span class="op">(</span><span class="nam">y_pred</span><span class="op">)</span><span class="op">,</span> <span class="nam">len</span><span class="op">(</span><span class="nam">y</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t95" href="#t95">95</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">assertIsNotNone</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t96" href="#t96">96</a></span><span class="t">            <span class="nam">m</span><span class="op">[</span><span class="str">"rules_per_example"</span><span class="op">]</span><span class="op">,</span> <span class="str">"rules_per_example should be calculated"</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t97" href="#t97">97</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t98" href="#t98">98</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">assertIsNotNone</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t99" href="#t99">99</a></span><span class="t">            <span class="nam">m</span><span class="op">[</span><span class="str">"voting_conflicts"</span><span class="op">]</span><span class="op">,</span> <span class="str">"rules_per_example should be calculated"</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t100" href="#t100">100</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t101" href="#t101">101</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t102" href="#t102">102</a></span><span class="t">    <span class="key">def</span> <span class="nam">test_score</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t103" href="#t103">103</a></span><span class="t">        <span class="nam">clf</span> <span class="op">=</span> <span class="nam">classification</span><span class="op">.</span><span class="nam">RuleClassifier</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t104" href="#t104">104</a></span><span class="t">        <span class="nam">X</span><span class="op">,</span> <span class="nam">y</span> <span class="op">=</span> <span class="nam">load_iris</span><span class="op">(</span><span class="nam">return_X_y</span><span class="op">=</span><span class="key">True</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t105" href="#t105">105</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t106" href="#t106">106</a></span><span class="t">        <span class="nam">clf</span><span class="op">.</span><span class="nam">fit</span><span class="op">(</span><span class="nam">X</span><span class="op">,</span> <span class="nam">y</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t107" href="#t107">107</a></span><span class="t">        <span class="nam">rulekit_acc</span><span class="op">:</span> <span class="nam">float</span> <span class="op">=</span> <span class="nam">clf</span><span class="op">.</span><span class="nam">score</span><span class="op">(</span><span class="nam">X</span><span class="op">,</span> <span class="nam">y</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t108" href="#t108">108</a></span><span class="t">        <span class="nam">sklearn_acc</span><span class="op">:</span> <span class="nam">float</span> <span class="op">=</span> <span class="nam">metrics</span><span class="op">.</span><span class="nam">accuracy_score</span><span class="op">(</span><span class="nam">y</span><span class="op">,</span> <span class="nam">clf</span><span class="op">.</span><span class="nam">predict</span><span class="op">(</span><span class="nam">X</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t109" href="#t109">109</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t110" href="#t110">110</a></span><span class="t">    <span class="key">def</span> <span class="nam">test_prediction_results_mapping</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t111" href="#t111">111</a></span><span class="t">        <span class="str">"""</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t112" href="#t112">112</a></span><span class="t"><span class="str">        This method tests classifications on numeric labels which possible values does</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t113" href="#t113">113</a></span><span class="t"><span class="str">        not start from 0. RuleKit undehood maps all labels values to integer values starting</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t114" href="#t114">114</a></span><span class="t"><span class="str">        from 0 to N (counting by order of appearance in dataset). Those maped values must be</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t115" href="#t115">115</a></span><span class="t"><span class="str">        later remaped back to actual label value. This test verifies that predict method returns</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t116" href="#t116">116</a></span><span class="t"><span class="str">        correct (remaped) label value.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t117" href="#t117">117</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t118" href="#t118">118</a></span><span class="t">        <span class="nam">clf</span> <span class="op">=</span> <span class="nam">classification</span><span class="op">.</span><span class="nam">RuleClassifier</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t110" href="#t110">110</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">assertAlmostEqual</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t111" href="#t111">111</a></span><span class="t">            <span class="nam">rulekit_acc</span><span class="op">,</span> <span class="nam">sklearn_acc</span><span class="op">,</span> <span class="nam">places</span><span class="op">=</span><span class="num">3</span><span class="op">,</span> <span class="nam">msg</span><span class="op">=</span><span class="str">"Accuracy should be the same"</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t112" href="#t112">112</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t113" href="#t113">113</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t114" href="#t114">114</a></span><span class="t">    <span class="key">def</span> <span class="nam">test_fit_on_integer_labels</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t115" href="#t115">115</a></span><span class="t">        <span class="nam">clf1</span> <span class="op">=</span> <span class="nam">classification</span><span class="op">.</span><span class="nam">RuleClassifier</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t116" href="#t116">116</a></span><span class="t">        <span class="nam">clf2</span> <span class="op">=</span> <span class="nam">classification</span><span class="op">.</span><span class="nam">RuleClassifier</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t117" href="#t117">117</a></span><span class="t">        <span class="nam">X</span><span class="op">,</span> <span class="nam">y_num</span> <span class="op">=</span> <span class="nam">load_iris</span><span class="op">(</span><span class="nam">return_X_y</span><span class="op">=</span><span class="key">True</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t118" href="#t118">118</a></span><span class="t">        <span class="nam">y_str</span><span class="op">:</span> <span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span> <span class="op">=</span> <span class="nam">y_num</span><span class="op">.</span><span class="nam">astype</span><span class="op">(</span><span class="nam">str</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t119" href="#t119">119</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t120" href="#t120">120</a></span><span class="t">        <span class="com"># some trivial dataset - OR (2 = false, 3 = true)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t121" href="#t121">121</a></span><span class="t">        <span class="nam">x</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">array</span><span class="op">(</span><span class="op">[</span><span class="op">[</span><span class="num">0</span><span class="op">,</span> <span class="num">1</span><span class="op">]</span><span class="op">,</span> <span class="op">[</span><span class="num">1</span><span class="op">,</span> <span class="num">1</span><span class="op">]</span><span class="op">,</span> <span class="op">[</span><span class="num">1</span><span class="op">,</span> <span class="num">0</span><span class="op">]</span><span class="op">,</span> <span class="op">[</span><span class="num">0</span><span class="op">,</span> <span class="num">0</span><span class="op">]</span><span class="op">]</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t122" href="#t122">122</a></span><span class="t">        <span class="nam">y</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">array</span><span class="op">(</span><span class="op">[</span><span class="num">0.</span><span class="op">,</span> <span class="num">1.</span><span class="op">,</span> <span class="num">0.</span><span class="op">,</span> <span class="num">0.</span><span class="op">]</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t123" href="#t123">123</a></span><span class="t">        <span class="nam">clf</span><span class="op">.</span><span class="nam">fit</span><span class="op">(</span><span class="nam">x</span><span class="op">,</span> <span class="nam">y</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t124" href="#t124">124</a></span><span class="t">        <span class="nam">prediction</span> <span class="op">=</span> <span class="nam">clf</span><span class="op">.</span><span class="nam">predict</span><span class="op">(</span><span class="nam">x</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t125" href="#t125">125</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t126" href="#t126">126</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">assertEqual</span><span class="op">(</span><span class="nam">y</span><span class="op">.</span><span class="nam">all</span><span class="op">(</span><span class="op">)</span><span class="op">,</span> <span class="nam">prediction</span><span class="op">.</span><span class="nam">all</span><span class="op">(</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t127" href="#t127">127</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t128" href="#t128">128</a></span><span class="t">    <span class="key">def</span> <span class="nam">test_prediction_on_nominal_values</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t129" href="#t129">129</a></span><span class="t">        <span class="nam">clf</span> <span class="op">=</span> <span class="nam">classification</span><span class="op">.</span><span class="nam">RuleClassifier</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t130" href="#t130">130</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t131" href="#t131">131</a></span><span class="t">        <span class="com"># some trivial dataset - AND Gate</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t132" href="#t132">132</a></span><span class="t">        <span class="nam">x</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">array</span><span class="op">(</span><span class="op">[</span><span class="op">[</span><span class="num">0</span><span class="op">,</span> <span class="num">1</span><span class="op">]</span><span class="op">,</span> <span class="op">[</span><span class="num">1</span><span class="op">,</span> <span class="num">1</span><span class="op">]</span><span class="op">,</span> <span class="op">[</span><span class="num">1</span><span class="op">,</span> <span class="num">0</span><span class="op">]</span><span class="op">,</span> <span class="op">[</span><span class="num">0</span><span class="op">,</span> <span class="num">0</span><span class="op">]</span><span class="op">]</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t133" href="#t133">133</a></span><span class="t">        <span class="nam">y</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">array</span><span class="op">(</span><span class="op">[</span><span class="str">'false'</span><span class="op">,</span> <span class="str">'true'</span><span class="op">,</span> <span class="str">'false'</span><span class="op">,</span> <span class="str">'false'</span><span class="op">]</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t134" href="#t134">134</a></span><span class="t">        <span class="nam">clf</span><span class="op">.</span><span class="nam">fit</span><span class="op">(</span><span class="nam">x</span><span class="op">,</span> <span class="nam">y</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t135" href="#t135">135</a></span><span class="t">        <span class="nam">prediction</span> <span class="op">=</span> <span class="nam">clf</span><span class="op">.</span><span class="nam">predict</span><span class="op">(</span><span class="nam">x</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t136" href="#t136">136</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t137" href="#t137">137</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">assertTrue</span><span class="op">(</span><span class="nam">np</span><span class="op">.</span><span class="nam">array_equal</span><span class="op">(</span><span class="nam">y</span><span class="op">,</span> <span class="nam">prediction</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t138" href="#t138">138</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t139" href="#t139">139</a></span><span class="t">    <span class="key">def</span> <span class="nam">test_compare_with_java_results</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t140" href="#t140">140</a></span><span class="t">        <span class="nam">test_cases</span> <span class="op">=</span> <span class="nam">get_test_cases</span><span class="op">(</span><span class="str">'ClassificationSnCTest'</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t141" href="#t141">141</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t142" href="#t142">142</a></span><span class="t">        <span class="key">for</span> <span class="nam">test_case</span> <span class="key">in</span> <span class="nam">test_cases</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t143" href="#t143">143</a></span><span class="t">            <span class="nam">params</span> <span class="op">=</span> <span class="nam">test_case</span><span class="op">.</span><span class="nam">induction_params</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t144" href="#t144">144</a></span><span class="t">            <span class="nam">tree</span> <span class="op">=</span> <span class="nam">classification</span><span class="op">.</span><span class="nam">RuleClassifier</span><span class="op">(</span><span class="op">**</span><span class="nam">params</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t145" href="#t145">145</a></span><span class="t">            <span class="nam">example_set</span> <span class="op">=</span> <span class="nam">test_case</span><span class="op">.</span><span class="nam">example_set</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t146" href="#t146">146</a></span><span class="t">            <span class="nam">tree</span><span class="op">.</span><span class="nam">fit</span><span class="op">(</span><span class="nam">example_set</span><span class="op">.</span><span class="nam">values</span><span class="op">,</span> <span class="nam">example_set</span><span class="op">.</span><span class="nam">labels</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t147" href="#t147">147</a></span><span class="t">            <span class="nam">model</span> <span class="op">=</span> <span class="nam">tree</span><span class="op">.</span><span class="nam">model</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t148" href="#t148">148</a></span><span class="t">            <span class="nam">expected</span> <span class="op">=</span> <span class="nam">test_case</span><span class="op">.</span><span class="nam">reference_report</span><span class="op">.</span><span class="nam">rules</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t149" href="#t149">149</a></span><span class="t">            <span class="nam">actual</span> <span class="op">=</span> <span class="nam">list</span><span class="op">(</span><span class="nam">map</span><span class="op">(</span><span class="nam">str</span><span class="op">,</span> <span class="nam">model</span><span class="op">.</span><span class="nam">rules</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t150" href="#t150">150</a></span><span class="t">            <span class="nam">assert_rules_are_equals</span><span class="op">(</span><span class="nam">expected</span><span class="op">,</span> <span class="nam">actual</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t151" href="#t151">151</a></span><span class="t">            <span class="nam">assert_accuracy_is_greater</span><span class="op">(</span><span class="nam">tree</span><span class="op">.</span><span class="nam">predict</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t152" href="#t152">152</a></span><span class="t">                <span class="nam">example_set</span><span class="op">.</span><span class="nam">values</span><span class="op">)</span><span class="op">,</span> <span class="nam">example_set</span><span class="op">.</span><span class="nam">labels</span><span class="op">,</span> <span class="num">0.9</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t120" href="#t120">120</a></span><span class="t">        <span class="nam">clf1</span><span class="op">.</span><span class="nam">fit</span><span class="op">(</span><span class="nam">X</span><span class="op">,</span> <span class="nam">y_num</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t121" href="#t121">121</a></span><span class="t">        <span class="nam">clf2</span><span class="op">.</span><span class="nam">fit</span><span class="op">(</span><span class="nam">X</span><span class="op">,</span> <span class="nam">y_str</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t122" href="#t122">122</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t123" href="#t123">123</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">assertTrue</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t124" href="#t124">124</a></span><span class="t">            <span class="nam">isinstance</span><span class="op">(</span><span class="nam">clf1</span><span class="op">.</span><span class="nam">predict</span><span class="op">(</span><span class="nam">X</span><span class="op">)</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="op">,</span> <span class="nam">float</span><span class="op">)</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t125" href="#t125">125</a></span><span class="t">            <span class="str">"Predictions should be of the same type as labels in the training set"</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t126" href="#t126">126</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t127" href="#t127">127</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">assertTrue</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t128" href="#t128">128</a></span><span class="t">            <span class="nam">isinstance</span><span class="op">(</span><span class="nam">clf2</span><span class="op">.</span><span class="nam">predict</span><span class="op">(</span><span class="nam">X</span><span class="op">)</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="op">,</span> <span class="nam">str</span><span class="op">)</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t129" href="#t129">129</a></span><span class="t">            <span class="str">"Predictions should be of the same type as labels in the training set"</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t130" href="#t130">130</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t131" href="#t131">131</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t132" href="#t132">132</a></span><span class="t">    <span class="key">def</span> <span class="nam">test_classification_predict_proba</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t133" href="#t133">133</a></span><span class="t">        <span class="nam">clf</span> <span class="op">=</span> <span class="nam">classification</span><span class="op">.</span><span class="nam">RuleClassifier</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t134" href="#t134">134</a></span><span class="t">        <span class="nam">x</span><span class="op">,</span> <span class="nam">y</span> <span class="op">=</span> <span class="nam">load_iris</span><span class="op">(</span><span class="nam">return_X_y</span><span class="op">=</span><span class="key">True</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t135" href="#t135">135</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t136" href="#t136">136</a></span><span class="t">        <span class="nam">clf</span><span class="op">.</span><span class="nam">fit</span><span class="op">(</span><span class="nam">x</span><span class="op">,</span> <span class="nam">y</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t137" href="#t137">137</a></span><span class="t">        <span class="nam">confidence_matrix</span><span class="op">,</span> <span class="nam">m</span> <span class="op">=</span> <span class="nam">clf</span><span class="op">.</span><span class="nam">predict_proba</span><span class="op">(</span><span class="nam">x</span><span class="op">,</span> <span class="nam">return_metrics</span><span class="op">=</span><span class="key">True</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t138" href="#t138">138</a></span><span class="t">        <span class="key">for</span> <span class="nam">row</span> <span class="key">in</span> <span class="nam">confidence_matrix</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t139" href="#t139">139</a></span><span class="t">            <span class="nam">sum</span> <span class="op">=</span> <span class="num">0</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t140" href="#t140">140</a></span><span class="t">            <span class="key">for</span> <span class="nam">col</span> <span class="key">in</span> <span class="nam">row</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t141" href="#t141">141</a></span><span class="t">                <span class="nam">sum</span> <span class="op">+=</span> <span class="nam">col</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t142" href="#t142">142</a></span><span class="t">            <span class="nam">self</span><span class="op">.</span><span class="nam">assertAlmostEqual</span><span class="op">(</span><span class="nam">sum</span><span class="op">,</span> <span class="num">1</span><span class="op">,</span> <span class="num">3</span><span class="op">,</span> <span class="str">"Confidence matrix rows should sum to 1"</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t143" href="#t143">143</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t144" href="#t144">144</a></span><span class="t">    <span class="key">def</span> <span class="nam">test_prediction_results_mapping</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t145" href="#t145">145</a></span><span class="t">        <span class="str">"""</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t146" href="#t146">146</a></span><span class="t"><span class="str">        This method tests classifications on numeric labels which possible values does</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t147" href="#t147">147</a></span><span class="t"><span class="str">        not start from 0. RuleKit undehood maps all labels values to integer values starting</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t148" href="#t148">148</a></span><span class="t"><span class="str">        from 0 to N (counting by order of appearance in dataset). Those maped values must be</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t149" href="#t149">149</a></span><span class="t"><span class="str">        later remaped back to actual label value. This test verifies that predict method returns</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t150" href="#t150">150</a></span><span class="t"><span class="str">        correct (remaped) label value.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t151" href="#t151">151</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t152" href="#t152">152</a></span><span class="t">        <span class="nam">clf</span> <span class="op">=</span> <span class="nam">classification</span><span class="op">.</span><span class="nam">RuleClassifier</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t153" href="#t153">153</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t154" href="#t154">154</a></span><span class="t">    <span class="key">def</span> <span class="nam">test_predict_proba</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t155" href="#t155">155</a></span><span class="t">        <span class="nam">test_case</span> <span class="op">=</span> <span class="nam">get_test_cases</span><span class="op">(</span><span class="str">'ClassificationSnCTest'</span><span class="op">)</span><span class="op">[</span><span class="num">0</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t156" href="#t156">156</a></span><span class="t">        <span class="nam">params</span> <span class="op">=</span> <span class="nam">test_case</span><span class="op">.</span><span class="nam">induction_params</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t157" href="#t157">157</a></span><span class="t">        <span class="nam">clf</span> <span class="op">=</span> <span class="nam">classification</span><span class="op">.</span><span class="nam">RuleClassifier</span><span class="op">(</span><span class="op">**</span><span class="nam">params</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t158" href="#t158">158</a></span><span class="t">        <span class="nam">example_set</span> <span class="op">=</span> <span class="nam">test_case</span><span class="op">.</span><span class="nam">example_set</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t159" href="#t159">159</a></span><span class="t">        <span class="nam">clf</span><span class="op">.</span><span class="nam">fit</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t160" href="#t160">160</a></span><span class="t">            <span class="nam">example_set</span><span class="op">.</span><span class="nam">values</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t161" href="#t161">161</a></span><span class="t">            <span class="nam">example_set</span><span class="op">.</span><span class="nam">labels</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t162" href="#t162">162</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t163" href="#t163">163</a></span><span class="t">        <span class="nam">res</span> <span class="op">=</span> <span class="nam">clf</span><span class="op">.</span><span class="nam">predict_proba</span><span class="op">(</span><span class="nam">example_set</span><span class="op">.</span><span class="nam">values</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t164" href="#t164">164</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">assertEqual</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t165" href="#t165">165</a></span><span class="t">            <span class="nam">res</span><span class="op">.</span><span class="nam">shape</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t166" href="#t166">166</a></span><span class="t">            <span class="nam">example_set</span><span class="op">.</span><span class="nam">values</span><span class="op">.</span><span class="nam">shape</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t167" href="#t167">167</a></span><span class="t">            <span class="str">'Should have as many rows as the original dataset'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t168" href="#t168">168</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t169" href="#t169">169</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">assertEqual</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t170" href="#t170">170</a></span><span class="t">            <span class="nam">res</span><span class="op">.</span><span class="nam">shape</span><span class="op">[</span><span class="num">1</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t171" href="#t171">171</a></span><span class="t">            <span class="nam">np</span><span class="op">.</span><span class="nam">unique</span><span class="op">(</span><span class="nam">example_set</span><span class="op">.</span><span class="nam">labels</span><span class="op">)</span><span class="op">.</span><span class="nam">shape</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t172" href="#t172">172</a></span><span class="t">            <span class="str">'Should have as many columns as there are classes in the dataset'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t173" href="#t173">173</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t174" href="#t174">174</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">assertTrue</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t175" href="#t175">175</a></span><span class="t">            <span class="nam">res</span><span class="op">.</span><span class="nam">max</span><span class="op">(</span><span class="op">)</span> <span class="op">&lt;=</span> <span class="num">1</span> <span class="key">and</span> <span class="nam">res</span><span class="op">.</span><span class="nam">min</span><span class="op">(</span><span class="op">)</span> <span class="op">>=</span> <span class="num">0</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t176" href="#t176">176</a></span><span class="t">            <span class="str">'Predicted probabilities should be in range [0, 1]'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t177" href="#t177">177</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t178" href="#t178">178</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t179" href="#t179">179</a></span><span class="t">    <span class="key">def</span> <span class="nam">test_fit_and_predict_on_boolean_columns</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t180" href="#t180">180</a></span><span class="t">        <span class="nam">test_case</span> <span class="op">=</span> <span class="nam">get_test_cases</span><span class="op">(</span><span class="str">'ClassificationSnCTest'</span><span class="op">)</span><span class="op">[</span><span class="num">0</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t181" href="#t181">181</a></span><span class="t">        <span class="nam">params</span> <span class="op">=</span> <span class="nam">test_case</span><span class="op">.</span><span class="nam">induction_params</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t182" href="#t182">182</a></span><span class="t">        <span class="nam">clf</span> <span class="op">=</span> <span class="nam">classification</span><span class="op">.</span><span class="nam">RuleClassifier</span><span class="op">(</span><span class="op">**</span><span class="nam">params</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t183" href="#t183">183</a></span><span class="t">        <span class="nam">X</span><span class="op">,</span> <span class="nam">y</span> <span class="op">=</span> <span class="nam">test_case</span><span class="op">.</span><span class="nam">example_set</span><span class="op">.</span><span class="nam">values</span><span class="op">,</span> <span class="nam">test_case</span><span class="op">.</span><span class="nam">example_set</span><span class="op">.</span><span class="nam">labels</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t184" href="#t184">184</a></span><span class="t">        <span class="nam">X</span><span class="op">[</span><span class="str">'boolean_column'</span><span class="op">]</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">random</span><span class="op">.</span><span class="nam">randint</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t185" href="#t185">185</a></span><span class="t">            <span class="nam">low</span><span class="op">=</span><span class="num">0</span><span class="op">,</span> <span class="nam">high</span><span class="op">=</span><span class="num">2</span><span class="op">,</span> <span class="nam">size</span><span class="op">=</span><span class="nam">X</span><span class="op">.</span><span class="nam">shape</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="op">)</span><span class="op">.</span><span class="nam">astype</span><span class="op">(</span><span class="nam">bool</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t186" href="#t186">186</a></span><span class="t">        <span class="nam">clf</span><span class="op">.</span><span class="nam">fit</span><span class="op">(</span><span class="nam">X</span><span class="op">,</span> <span class="nam">y</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t187" href="#t187">187</a></span><span class="t">        <span class="nam">clf</span><span class="op">.</span><span class="nam">predict</span><span class="op">(</span><span class="nam">X</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t154" href="#t154">154</a></span><span class="t">        <span class="com"># some trivial dataset - OR (2 = false, 3 = true)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t155" href="#t155">155</a></span><span class="t">        <span class="nam">x</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">array</span><span class="op">(</span><span class="op">[</span><span class="op">[</span><span class="num">0</span><span class="op">,</span> <span class="num">1</span><span class="op">]</span><span class="op">,</span> <span class="op">[</span><span class="num">1</span><span class="op">,</span> <span class="num">1</span><span class="op">]</span><span class="op">,</span> <span class="op">[</span><span class="num">1</span><span class="op">,</span> <span class="num">0</span><span class="op">]</span><span class="op">,</span> <span class="op">[</span><span class="num">0</span><span class="op">,</span> <span class="num">0</span><span class="op">]</span><span class="op">]</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t156" href="#t156">156</a></span><span class="t">        <span class="nam">y</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">array</span><span class="op">(</span><span class="op">[</span><span class="num">0.0</span><span class="op">,</span> <span class="num">1.0</span><span class="op">,</span> <span class="num">0.0</span><span class="op">,</span> <span class="num">0.0</span><span class="op">]</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t157" href="#t157">157</a></span><span class="t">        <span class="nam">clf</span><span class="op">.</span><span class="nam">fit</span><span class="op">(</span><span class="nam">x</span><span class="op">,</span> <span class="nam">y</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t158" href="#t158">158</a></span><span class="t">        <span class="nam">prediction</span> <span class="op">=</span> <span class="nam">clf</span><span class="op">.</span><span class="nam">predict</span><span class="op">(</span><span class="nam">x</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t159" href="#t159">159</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t160" href="#t160">160</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">assertEqual</span><span class="op">(</span><span class="nam">y</span><span class="op">.</span><span class="nam">all</span><span class="op">(</span><span class="op">)</span><span class="op">,</span> <span class="nam">prediction</span><span class="op">.</span><span class="nam">all</span><span class="op">(</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t161" href="#t161">161</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t162" href="#t162">162</a></span><span class="t">    <span class="key">def</span> <span class="nam">test_prediction_on_nominal_values</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t163" href="#t163">163</a></span><span class="t">        <span class="nam">clf</span> <span class="op">=</span> <span class="nam">classification</span><span class="op">.</span><span class="nam">RuleClassifier</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t164" href="#t164">164</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t165" href="#t165">165</a></span><span class="t">        <span class="com"># some trivial dataset - AND Gate</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t166" href="#t166">166</a></span><span class="t">        <span class="nam">x</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">array</span><span class="op">(</span><span class="op">[</span><span class="op">[</span><span class="num">0</span><span class="op">,</span> <span class="num">1</span><span class="op">]</span><span class="op">,</span> <span class="op">[</span><span class="num">1</span><span class="op">,</span> <span class="num">1</span><span class="op">]</span><span class="op">,</span> <span class="op">[</span><span class="num">1</span><span class="op">,</span> <span class="num">0</span><span class="op">]</span><span class="op">,</span> <span class="op">[</span><span class="num">0</span><span class="op">,</span> <span class="num">0</span><span class="op">]</span><span class="op">]</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t167" href="#t167">167</a></span><span class="t">        <span class="nam">y</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">array</span><span class="op">(</span><span class="op">[</span><span class="str">"false"</span><span class="op">,</span> <span class="str">"true"</span><span class="op">,</span> <span class="str">"false"</span><span class="op">,</span> <span class="str">"false"</span><span class="op">]</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t168" href="#t168">168</a></span><span class="t">        <span class="nam">clf</span><span class="op">.</span><span class="nam">fit</span><span class="op">(</span><span class="nam">x</span><span class="op">,</span> <span class="nam">y</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t169" href="#t169">169</a></span><span class="t">        <span class="nam">prediction</span> <span class="op">=</span> <span class="nam">clf</span><span class="op">.</span><span class="nam">predict</span><span class="op">(</span><span class="nam">x</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t170" href="#t170">170</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t171" href="#t171">171</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">assertTrue</span><span class="op">(</span><span class="nam">np</span><span class="op">.</span><span class="nam">array_equal</span><span class="op">(</span><span class="nam">y</span><span class="op">,</span> <span class="nam">prediction</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t172" href="#t172">172</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t173" href="#t173">173</a></span><span class="t">    <span class="key">def</span> <span class="nam">test_compare_with_java_results</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t174" href="#t174">174</a></span><span class="t">        <span class="nam">test_cases</span> <span class="op">=</span> <span class="nam">get_test_cases</span><span class="op">(</span><span class="str">"ClassificationSnCTest"</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t175" href="#t175">175</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t176" href="#t176">176</a></span><span class="t">        <span class="key">for</span> <span class="nam">test_case</span> <span class="key">in</span> <span class="nam">test_cases</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t177" href="#t177">177</a></span><span class="t">            <span class="nam">params</span> <span class="op">=</span> <span class="nam">test_case</span><span class="op">.</span><span class="nam">induction_params</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t178" href="#t178">178</a></span><span class="t">            <span class="nam">tree</span> <span class="op">=</span> <span class="nam">classification</span><span class="op">.</span><span class="nam">RuleClassifier</span><span class="op">(</span><span class="op">**</span><span class="nam">params</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t179" href="#t179">179</a></span><span class="t">            <span class="nam">example_set</span> <span class="op">=</span> <span class="nam">test_case</span><span class="op">.</span><span class="nam">example_set</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t180" href="#t180">180</a></span><span class="t">            <span class="nam">tree</span><span class="op">.</span><span class="nam">fit</span><span class="op">(</span><span class="nam">example_set</span><span class="op">.</span><span class="nam">values</span><span class="op">,</span> <span class="nam">example_set</span><span class="op">.</span><span class="nam">labels</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t181" href="#t181">181</a></span><span class="t">            <span class="nam">model</span> <span class="op">=</span> <span class="nam">tree</span><span class="op">.</span><span class="nam">model</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t182" href="#t182">182</a></span><span class="t">            <span class="nam">expected</span> <span class="op">=</span> <span class="nam">test_case</span><span class="op">.</span><span class="nam">reference_report</span><span class="op">.</span><span class="nam">rules</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t183" href="#t183">183</a></span><span class="t">            <span class="nam">actual</span> <span class="op">=</span> <span class="nam">list</span><span class="op">(</span><span class="nam">map</span><span class="op">(</span><span class="nam">str</span><span class="op">,</span> <span class="nam">model</span><span class="op">.</span><span class="nam">rules</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t184" href="#t184">184</a></span><span class="t">            <span class="nam">assert_rules_are_equals</span><span class="op">(</span><span class="nam">expected</span><span class="op">,</span> <span class="nam">actual</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t185" href="#t185">185</a></span><span class="t">            <span class="nam">assert_accuracy_is_greater</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t186" href="#t186">186</a></span><span class="t">                <span class="nam">tree</span><span class="op">.</span><span class="nam">predict</span><span class="op">(</span><span class="nam">example_set</span><span class="op">.</span><span class="nam">values</span><span class="op">)</span><span class="op">,</span> <span class="nam">example_set</span><span class="op">.</span><span class="nam">labels</span><span class="op">,</span> <span class="num">0.9</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t187" href="#t187">187</a></span><span class="t">            <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t188" href="#t188">188</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t189" href="#t189">189</a></span><span class="t">        <span class="nam">y</span> <span class="op">=</span> <span class="nam">y</span><span class="op">.</span><span class="nam">astype</span><span class="op">(</span><span class="nam">bool</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t190" href="#t190">190</a></span><span class="t">        <span class="nam">clf</span><span class="op">.</span><span class="nam">fit</span><span class="op">(</span><span class="nam">X</span><span class="op">,</span> <span class="nam">y</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t191" href="#t191">191</a></span><span class="t">        <span class="nam">clf</span><span class="op">.</span><span class="nam">predict</span><span class="op">(</span><span class="nam">X</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t192" href="#t192">192</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t193" href="#t193">193</a></span><span class="t">        <span class="nam">y</span> <span class="op">=</span> <span class="nam">pd</span><span class="op">.</span><span class="nam">Series</span><span class="op">(</span><span class="nam">y</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t194" href="#t194">194</a></span><span class="t">        <span class="nam">clf</span><span class="op">.</span><span class="nam">fit</span><span class="op">(</span><span class="nam">X</span><span class="op">,</span> <span class="nam">y</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t195" href="#t195">195</a></span><span class="t">        <span class="nam">clf</span><span class="op">.</span><span class="nam">predict</span><span class="op">(</span><span class="nam">X</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t196" href="#t196">196</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t197" href="#t197">197</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t198" href="#t198">198</a></span><span class="t"><span class="key">class</span> <span class="nam">TestExperClassifier</span><span class="op">(</span><span class="nam">unittest</span><span class="op">.</span><span class="nam">TestCase</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t199" href="#t199">199</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t200" href="#t200">200</a></span><span class="t">    <span class="key">def</span> <span class="nam">test_compare_with_java_results</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t201" href="#t201">201</a></span><span class="t">        <span class="nam">test_cases</span> <span class="op">=</span> <span class="nam">get_test_cases</span><span class="op">(</span><span class="str">'ClassificationExpertSnCTest'</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t202" href="#t202">202</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t203" href="#t203">203</a></span><span class="t">        <span class="key">for</span> <span class="nam">test_case</span> <span class="key">in</span> <span class="nam">test_cases</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t204" href="#t204">204</a></span><span class="t">            <span class="nam">params</span> <span class="op">=</span> <span class="nam">test_case</span><span class="op">.</span><span class="nam">induction_params</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t205" href="#t205">205</a></span><span class="t">            <span class="nam">clf</span> <span class="op">=</span> <span class="nam">classification</span><span class="op">.</span><span class="nam">ExpertRuleClassifier</span><span class="op">(</span><span class="op">**</span><span class="nam">params</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t206" href="#t206">206</a></span><span class="t">            <span class="nam">example_set</span> <span class="op">=</span> <span class="nam">test_case</span><span class="op">.</span><span class="nam">example_set</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t207" href="#t207">207</a></span><span class="t">            <span class="nam">clf</span><span class="op">.</span><span class="nam">fit</span><span class="op">(</span><span class="nam">example_set</span><span class="op">.</span><span class="nam">values</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t208" href="#t208">208</a></span><span class="t">                    <span class="nam">example_set</span><span class="op">.</span><span class="nam">labels</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t209" href="#t209">209</a></span><span class="t">                    <span class="nam">expert_rules</span><span class="op">=</span><span class="nam">test_case</span><span class="op">.</span><span class="nam">knowledge</span><span class="op">.</span><span class="nam">expert_rules</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t210" href="#t210">210</a></span><span class="t">                    <span class="nam">expert_preferred_conditions</span><span class="op">=</span><span class="nam">test_case</span><span class="op">.</span><span class="nam">knowledge</span><span class="op">.</span><span class="nam">expert_preferred_conditions</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t211" href="#t211">211</a></span><span class="t">                    <span class="nam">expert_forbidden_conditions</span><span class="op">=</span><span class="nam">test_case</span><span class="op">.</span><span class="nam">knowledge</span><span class="op">.</span><span class="nam">expert_forbidden_conditions</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t212" href="#t212">212</a></span><span class="t">            <span class="nam">model</span> <span class="op">=</span> <span class="nam">clf</span><span class="op">.</span><span class="nam">model</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t213" href="#t213">213</a></span><span class="t">            <span class="nam">expected</span> <span class="op">=</span> <span class="nam">test_case</span><span class="op">.</span><span class="nam">reference_report</span><span class="op">.</span><span class="nam">rules</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t214" href="#t214">214</a></span><span class="t">            <span class="nam">actual</span> <span class="op">=</span> <span class="nam">list</span><span class="op">(</span><span class="nam">map</span><span class="op">(</span><span class="nam">str</span><span class="op">,</span> <span class="nam">model</span><span class="op">.</span><span class="nam">rules</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t215" href="#t215">215</a></span><span class="t">            <span class="nam">assert_rules_are_equals</span><span class="op">(</span><span class="nam">expected</span><span class="op">,</span> <span class="nam">actual</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t216" href="#t216">216</a></span><span class="t">            <span class="nam">assert_accuracy_is_greater</span><span class="op">(</span><span class="nam">clf</span><span class="op">.</span><span class="nam">predict</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t217" href="#t217">217</a></span><span class="t">                <span class="nam">example_set</span><span class="op">.</span><span class="nam">values</span><span class="op">)</span><span class="op">,</span> <span class="nam">example_set</span><span class="op">.</span><span class="nam">labels</span><span class="op">,</span> <span class="num">0.75</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t218" href="#t218">218</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t219" href="#t219">219</a></span><span class="t">    <span class="key">def</span> <span class="nam">test_predict_proba</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t220" href="#t220">220</a></span><span class="t">        <span class="nam">test_case</span> <span class="op">=</span> <span class="nam">get_test_cases</span><span class="op">(</span><span class="str">'ClassificationExpertSnCTest'</span><span class="op">)</span><span class="op">[</span><span class="num">0</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t221" href="#t221">221</a></span><span class="t">        <span class="nam">params</span> <span class="op">=</span> <span class="nam">test_case</span><span class="op">.</span><span class="nam">induction_params</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t222" href="#t222">222</a></span><span class="t">        <span class="nam">clf</span> <span class="op">=</span> <span class="nam">classification</span><span class="op">.</span><span class="nam">ExpertRuleClassifier</span><span class="op">(</span><span class="op">**</span><span class="nam">params</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t223" href="#t223">223</a></span><span class="t">        <span class="nam">example_set</span> <span class="op">=</span> <span class="nam">test_case</span><span class="op">.</span><span class="nam">example_set</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t224" href="#t224">224</a></span><span class="t">        <span class="nam">clf</span><span class="op">.</span><span class="nam">fit</span><span class="op">(</span><span class="nam">example_set</span><span class="op">.</span><span class="nam">values</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t225" href="#t225">225</a></span><span class="t">                <span class="nam">example_set</span><span class="op">.</span><span class="nam">labels</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t226" href="#t226">226</a></span><span class="t">                <span class="nam">expert_rules</span><span class="op">=</span><span class="nam">test_case</span><span class="op">.</span><span class="nam">knowledge</span><span class="op">.</span><span class="nam">expert_rules</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t227" href="#t227">227</a></span><span class="t">                <span class="nam">expert_preferred_conditions</span><span class="op">=</span><span class="nam">test_case</span><span class="op">.</span><span class="nam">knowledge</span><span class="op">.</span><span class="nam">expert_preferred_conditions</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t228" href="#t228">228</a></span><span class="t">                <span class="nam">expert_forbidden_conditions</span><span class="op">=</span><span class="nam">test_case</span><span class="op">.</span><span class="nam">knowledge</span><span class="op">.</span><span class="nam">expert_forbidden_conditions</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t229" href="#t229">229</a></span><span class="t">        <span class="nam">res</span> <span class="op">=</span> <span class="nam">clf</span><span class="op">.</span><span class="nam">predict_proba</span><span class="op">(</span><span class="nam">example_set</span><span class="op">.</span><span class="nam">values</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t230" href="#t230">230</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">assertEqual</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t231" href="#t231">231</a></span><span class="t">            <span class="nam">res</span><span class="op">.</span><span class="nam">shape</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t232" href="#t232">232</a></span><span class="t">            <span class="nam">example_set</span><span class="op">.</span><span class="nam">values</span><span class="op">.</span><span class="nam">shape</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t233" href="#t233">233</a></span><span class="t">            <span class="str">'Should have as many rows as the original dataset'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t234" href="#t234">234</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t235" href="#t235">235</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">assertEqual</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t236" href="#t236">236</a></span><span class="t">            <span class="nam">res</span><span class="op">.</span><span class="nam">shape</span><span class="op">[</span><span class="num">1</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t237" href="#t237">237</a></span><span class="t">            <span class="nam">np</span><span class="op">.</span><span class="nam">unique</span><span class="op">(</span><span class="nam">example_set</span><span class="op">.</span><span class="nam">labels</span><span class="op">)</span><span class="op">.</span><span class="nam">shape</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t238" href="#t238">238</a></span><span class="t">            <span class="str">'Should have as many columns as there are classes in the dataset'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t239" href="#t239">239</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t240" href="#t240">240</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">assertTrue</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t241" href="#t241">241</a></span><span class="t">            <span class="nam">res</span><span class="op">.</span><span class="nam">max</span><span class="op">(</span><span class="op">)</span> <span class="op">&lt;=</span> <span class="num">1</span> <span class="key">and</span> <span class="nam">res</span><span class="op">.</span><span class="nam">min</span><span class="op">(</span><span class="op">)</span> <span class="op">>=</span> <span class="num">0</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t242" href="#t242">242</a></span><span class="t">            <span class="str">'Predicted probabilities should be in range [0, 1]'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t243" href="#t243">243</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t244" href="#t244">244</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t245" href="#t245">245</a></span><span class="t">    <span class="com"># Issue #17</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t246" href="#t246">246</a></span><span class="t">    <span class="key">def</span> <span class="nam">test_left_open_intervals_in_expert_induction</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t247" href="#t247">247</a></span><span class="t">        <span class="nam">df</span> <span class="op">=</span> <span class="nam">pd</span><span class="op">.</span><span class="nam">DataFrame</span><span class="op">(</span><span class="nam">arff</span><span class="op">.</span><span class="nam">loadarff</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t248" href="#t248">248</a></span><span class="t">            <span class="str">f'{dir_path}/resources/data/seismic-bumps-train-minimal.arff'</span><span class="op">)</span><span class="op">[</span><span class="num">0</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t249" href="#t249">249</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t250" href="#t250">250</a></span><span class="t">        <span class="nam">X</span> <span class="op">=</span> <span class="nam">df</span><span class="op">.</span><span class="nam">drop</span><span class="op">(</span><span class="str">'class'</span><span class="op">,</span> <span class="nam">axis</span><span class="op">=</span><span class="num">1</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t251" href="#t251">251</a></span><span class="t">        <span class="nam">y</span> <span class="op">=</span> <span class="nam">df</span><span class="op">[</span><span class="str">'class'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t252" href="#t252">252</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t253" href="#t253">253</a></span><span class="t">        <span class="nam">expert_rules</span> <span class="op">=</span> <span class="op">[</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t254" href="#t254">254</a></span><span class="t">            <span class="op">(</span><span class="str">'rule-0'</span><span class="op">,</span> <span class="str">'IF [[gimpuls = &lt;-inf, 750)]] THEN class = {0}'</span><span class="op">)</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t255" href="#t255">255</a></span><span class="t">            <span class="op">(</span><span class="str">'rule-1'</span><span class="op">,</span> <span class="str">'IF [[gimpuls = (750, inf)]] THEN class = {1}'</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t256" href="#t256">256</a></span><span class="t">        <span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t257" href="#t257">257</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t258" href="#t258">258</a></span><span class="t">        <span class="nam">expert_preferred_conditions</span> <span class="op">=</span> <span class="op">[</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t259" href="#t259">259</a></span><span class="t">            <span class="op">(</span><span class="str">'preferred-condition-0'</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t260" href="#t260">260</a></span><span class="t">             <span class="str">'1: IF [[seismic = {a}]] THEN class = {0}'</span><span class="op">)</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t261" href="#t261">261</a></span><span class="t">            <span class="op">(</span><span class="str">'preferred-attribute-0'</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t262" href="#t262">262</a></span><span class="t">             <span class="str">'1: IF [[gimpuls = Any]] THEN class = {1}'</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t263" href="#t263">263</a></span><span class="t">        <span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t264" href="#t264">264</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t265" href="#t265">265</a></span><span class="t">        <span class="nam">expert_forbidden_conditions</span> <span class="op">=</span> <span class="op">[</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t266" href="#t266">266</a></span><span class="t">            <span class="op">(</span><span class="str">'forb-attribute-0'</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t267" href="#t267">267</a></span><span class="t">             <span class="str">'1: IF [[seismoacoustic  = Any]] THEN class = {0}'</span><span class="op">)</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t268" href="#t268">268</a></span><span class="t">            <span class="op">(</span><span class="str">'forb-attribute-1'</span><span class="op">,</span> <span class="str">'inf: IF [[ghazard  = Any]] THEN class = {1}'</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t269" href="#t269">269</a></span><span class="t">        <span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t270" href="#t270">270</a></span><span class="t">        <span class="nam">clf</span> <span class="op">=</span> <span class="nam">classification</span><span class="op">.</span><span class="nam">ExpertRuleClassifier</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t271" href="#t271">271</a></span><span class="t">            <span class="nam">minsupp_new</span><span class="op">=</span><span class="num">8</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t272" href="#t272">272</a></span><span class="t">            <span class="nam">max_growing</span><span class="op">=</span><span class="num">0</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t273" href="#t273">273</a></span><span class="t">            <span class="nam">extend_using_preferred</span><span class="op">=</span><span class="key">True</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t274" href="#t274">274</a></span><span class="t">            <span class="nam">extend_using_automatic</span><span class="op">=</span><span class="key">True</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t275" href="#t275">275</a></span><span class="t">            <span class="nam">induce_using_preferred</span><span class="op">=</span><span class="key">True</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t276" href="#t276">276</a></span><span class="t">            <span class="nam">induce_using_automatic</span><span class="op">=</span><span class="key">True</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t189" href="#t189">189</a></span><span class="t">    <span class="key">def</span> <span class="nam">test_predict_proba</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t190" href="#t190">190</a></span><span class="t">        <span class="nam">test_case</span> <span class="op">=</span> <span class="nam">get_test_cases</span><span class="op">(</span><span class="str">"ClassificationSnCTest"</span><span class="op">)</span><span class="op">[</span><span class="num">0</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t191" href="#t191">191</a></span><span class="t">        <span class="nam">params</span> <span class="op">=</span> <span class="nam">test_case</span><span class="op">.</span><span class="nam">induction_params</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t192" href="#t192">192</a></span><span class="t">        <span class="nam">clf</span> <span class="op">=</span> <span class="nam">classification</span><span class="op">.</span><span class="nam">RuleClassifier</span><span class="op">(</span><span class="op">**</span><span class="nam">params</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t193" href="#t193">193</a></span><span class="t">        <span class="nam">example_set</span> <span class="op">=</span> <span class="nam">test_case</span><span class="op">.</span><span class="nam">example_set</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t194" href="#t194">194</a></span><span class="t">        <span class="nam">clf</span><span class="op">.</span><span class="nam">fit</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t195" href="#t195">195</a></span><span class="t">            <span class="nam">example_set</span><span class="op">.</span><span class="nam">values</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t196" href="#t196">196</a></span><span class="t">            <span class="nam">example_set</span><span class="op">.</span><span class="nam">labels</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t197" href="#t197">197</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t198" href="#t198">198</a></span><span class="t">        <span class="nam">res</span> <span class="op">=</span> <span class="nam">clf</span><span class="op">.</span><span class="nam">predict_proba</span><span class="op">(</span><span class="nam">example_set</span><span class="op">.</span><span class="nam">values</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t199" href="#t199">199</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">assertEqual</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t200" href="#t200">200</a></span><span class="t">            <span class="nam">res</span><span class="op">.</span><span class="nam">shape</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t201" href="#t201">201</a></span><span class="t">            <span class="nam">example_set</span><span class="op">.</span><span class="nam">values</span><span class="op">.</span><span class="nam">shape</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t202" href="#t202">202</a></span><span class="t">            <span class="str">"Should have as many rows as the original dataset"</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t203" href="#t203">203</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t204" href="#t204">204</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">assertEqual</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t205" href="#t205">205</a></span><span class="t">            <span class="nam">res</span><span class="op">.</span><span class="nam">shape</span><span class="op">[</span><span class="num">1</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t206" href="#t206">206</a></span><span class="t">            <span class="nam">np</span><span class="op">.</span><span class="nam">unique</span><span class="op">(</span><span class="nam">example_set</span><span class="op">.</span><span class="nam">labels</span><span class="op">)</span><span class="op">.</span><span class="nam">shape</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t207" href="#t207">207</a></span><span class="t">            <span class="str">"Should have as many columns as there are classes in the dataset"</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t208" href="#t208">208</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t209" href="#t209">209</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">assertTrue</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t210" href="#t210">210</a></span><span class="t">            <span class="nam">res</span><span class="op">.</span><span class="nam">max</span><span class="op">(</span><span class="op">)</span> <span class="op">&lt;=</span> <span class="num">1</span> <span class="key">and</span> <span class="nam">res</span><span class="op">.</span><span class="nam">min</span><span class="op">(</span><span class="op">)</span> <span class="op">>=</span> <span class="num">0</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t211" href="#t211">211</a></span><span class="t">            <span class="str">"Predicted probabilities should be in range [0, 1]"</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t212" href="#t212">212</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t213" href="#t213">213</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t214" href="#t214">214</a></span><span class="t">    <span class="key">def</span> <span class="nam">test_fit_and_predict_on_boolean_columns</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t215" href="#t215">215</a></span><span class="t">        <span class="nam">test_case</span> <span class="op">=</span> <span class="nam">get_test_cases</span><span class="op">(</span><span class="str">"ClassificationSnCTest"</span><span class="op">)</span><span class="op">[</span><span class="num">0</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t216" href="#t216">216</a></span><span class="t">        <span class="nam">params</span> <span class="op">=</span> <span class="nam">test_case</span><span class="op">.</span><span class="nam">induction_params</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t217" href="#t217">217</a></span><span class="t">        <span class="nam">clf</span> <span class="op">=</span> <span class="nam">classification</span><span class="op">.</span><span class="nam">RuleClassifier</span><span class="op">(</span><span class="op">**</span><span class="nam">params</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t218" href="#t218">218</a></span><span class="t">        <span class="nam">X</span><span class="op">,</span> <span class="nam">y</span> <span class="op">=</span> <span class="nam">test_case</span><span class="op">.</span><span class="nam">example_set</span><span class="op">.</span><span class="nam">values</span><span class="op">,</span> <span class="nam">test_case</span><span class="op">.</span><span class="nam">example_set</span><span class="op">.</span><span class="nam">labels</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t219" href="#t219">219</a></span><span class="t">        <span class="nam">X</span><span class="op">[</span><span class="str">"boolean_column"</span><span class="op">]</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">random</span><span class="op">.</span><span class="nam">randint</span><span class="op">(</span><span class="nam">low</span><span class="op">=</span><span class="num">0</span><span class="op">,</span> <span class="nam">high</span><span class="op">=</span><span class="num">2</span><span class="op">,</span> <span class="nam">size</span><span class="op">=</span><span class="nam">X</span><span class="op">.</span><span class="nam">shape</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="op">)</span><span class="op">.</span><span class="nam">astype</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t220" href="#t220">220</a></span><span class="t">            <span class="nam">bool</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t221" href="#t221">221</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t222" href="#t222">222</a></span><span class="t">        <span class="nam">clf</span><span class="op">.</span><span class="nam">fit</span><span class="op">(</span><span class="nam">X</span><span class="op">,</span> <span class="nam">y</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t223" href="#t223">223</a></span><span class="t">        <span class="nam">clf</span><span class="op">.</span><span class="nam">predict</span><span class="op">(</span><span class="nam">X</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t224" href="#t224">224</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t225" href="#t225">225</a></span><span class="t">        <span class="nam">y</span> <span class="op">=</span> <span class="nam">y</span><span class="op">.</span><span class="nam">astype</span><span class="op">(</span><span class="nam">bool</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t226" href="#t226">226</a></span><span class="t">        <span class="nam">clf</span><span class="op">.</span><span class="nam">fit</span><span class="op">(</span><span class="nam">X</span><span class="op">,</span> <span class="nam">y</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t227" href="#t227">227</a></span><span class="t">        <span class="nam">clf</span><span class="op">.</span><span class="nam">predict</span><span class="op">(</span><span class="nam">X</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t228" href="#t228">228</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t229" href="#t229">229</a></span><span class="t">        <span class="nam">y</span> <span class="op">=</span> <span class="nam">pd</span><span class="op">.</span><span class="nam">Series</span><span class="op">(</span><span class="nam">y</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t230" href="#t230">230</a></span><span class="t">        <span class="nam">clf</span><span class="op">.</span><span class="nam">fit</span><span class="op">(</span><span class="nam">X</span><span class="op">,</span> <span class="nam">y</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t231" href="#t231">231</a></span><span class="t">        <span class="nam">clf</span><span class="op">.</span><span class="nam">predict</span><span class="op">(</span><span class="nam">X</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t232" href="#t232">232</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t233" href="#t233">233</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t234" href="#t234">234</a></span><span class="t"><span class="key">class</span> <span class="nam">TestExperClassifier</span><span class="op">(</span><span class="nam">unittest</span><span class="op">.</span><span class="nam">TestCase</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t235" href="#t235">235</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t236" href="#t236">236</a></span><span class="t">    <span class="key">def</span> <span class="nam">test_compare_with_java_results</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t237" href="#t237">237</a></span><span class="t">        <span class="nam">test_cases</span> <span class="op">=</span> <span class="nam">get_test_cases</span><span class="op">(</span><span class="str">"ClassificationExpertSnCTest"</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t238" href="#t238">238</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t239" href="#t239">239</a></span><span class="t">        <span class="key">for</span> <span class="nam">test_case</span> <span class="key">in</span> <span class="nam">test_cases</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t240" href="#t240">240</a></span><span class="t">            <span class="nam">params</span> <span class="op">=</span> <span class="nam">test_case</span><span class="op">.</span><span class="nam">induction_params</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t241" href="#t241">241</a></span><span class="t">            <span class="nam">clf</span> <span class="op">=</span> <span class="nam">classification</span><span class="op">.</span><span class="nam">ExpertRuleClassifier</span><span class="op">(</span><span class="op">**</span><span class="nam">params</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t242" href="#t242">242</a></span><span class="t">            <span class="nam">example_set</span> <span class="op">=</span> <span class="nam">test_case</span><span class="op">.</span><span class="nam">example_set</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t243" href="#t243">243</a></span><span class="t">            <span class="nam">clf</span><span class="op">.</span><span class="nam">fit</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t244" href="#t244">244</a></span><span class="t">                <span class="nam">example_set</span><span class="op">.</span><span class="nam">values</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t245" href="#t245">245</a></span><span class="t">                <span class="nam">example_set</span><span class="op">.</span><span class="nam">labels</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t246" href="#t246">246</a></span><span class="t">                <span class="nam">expert_rules</span><span class="op">=</span><span class="nam">test_case</span><span class="op">.</span><span class="nam">knowledge</span><span class="op">.</span><span class="nam">expert_rules</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t247" href="#t247">247</a></span><span class="t">                <span class="nam">expert_preferred_conditions</span><span class="op">=</span><span class="nam">test_case</span><span class="op">.</span><span class="nam">knowledge</span><span class="op">.</span><span class="nam">expert_preferred_conditions</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t248" href="#t248">248</a></span><span class="t">                <span class="nam">expert_forbidden_conditions</span><span class="op">=</span><span class="nam">test_case</span><span class="op">.</span><span class="nam">knowledge</span><span class="op">.</span><span class="nam">expert_forbidden_conditions</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t249" href="#t249">249</a></span><span class="t">            <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t250" href="#t250">250</a></span><span class="t">            <span class="nam">model</span> <span class="op">=</span> <span class="nam">clf</span><span class="op">.</span><span class="nam">model</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t251" href="#t251">251</a></span><span class="t">            <span class="nam">expected</span> <span class="op">=</span> <span class="nam">test_case</span><span class="op">.</span><span class="nam">reference_report</span><span class="op">.</span><span class="nam">rules</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t252" href="#t252">252</a></span><span class="t">            <span class="nam">actual</span> <span class="op">=</span> <span class="nam">list</span><span class="op">(</span><span class="nam">map</span><span class="op">(</span><span class="nam">str</span><span class="op">,</span> <span class="nam">model</span><span class="op">.</span><span class="nam">rules</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t253" href="#t253">253</a></span><span class="t">            <span class="nam">assert_rules_are_equals</span><span class="op">(</span><span class="nam">expected</span><span class="op">,</span> <span class="nam">actual</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t254" href="#t254">254</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t255" href="#t255">255</a></span><span class="t">    <span class="key">def</span> <span class="nam">test_predict_proba</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t256" href="#t256">256</a></span><span class="t">        <span class="nam">test_case</span> <span class="op">=</span> <span class="nam">get_test_cases</span><span class="op">(</span><span class="str">"ClassificationExpertSnCTest"</span><span class="op">)</span><span class="op">[</span><span class="num">0</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t257" href="#t257">257</a></span><span class="t">        <span class="nam">params</span> <span class="op">=</span> <span class="nam">test_case</span><span class="op">.</span><span class="nam">induction_params</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t258" href="#t258">258</a></span><span class="t">        <span class="nam">clf</span> <span class="op">=</span> <span class="nam">classification</span><span class="op">.</span><span class="nam">ExpertRuleClassifier</span><span class="op">(</span><span class="op">**</span><span class="nam">params</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t259" href="#t259">259</a></span><span class="t">        <span class="nam">example_set</span> <span class="op">=</span> <span class="nam">test_case</span><span class="op">.</span><span class="nam">example_set</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t260" href="#t260">260</a></span><span class="t">        <span class="nam">clf</span><span class="op">.</span><span class="nam">fit</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t261" href="#t261">261</a></span><span class="t">            <span class="nam">example_set</span><span class="op">.</span><span class="nam">values</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t262" href="#t262">262</a></span><span class="t">            <span class="nam">example_set</span><span class="op">.</span><span class="nam">labels</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t263" href="#t263">263</a></span><span class="t">            <span class="nam">expert_rules</span><span class="op">=</span><span class="nam">test_case</span><span class="op">.</span><span class="nam">knowledge</span><span class="op">.</span><span class="nam">expert_rules</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t264" href="#t264">264</a></span><span class="t">            <span class="nam">expert_preferred_conditions</span><span class="op">=</span><span class="nam">test_case</span><span class="op">.</span><span class="nam">knowledge</span><span class="op">.</span><span class="nam">expert_preferred_conditions</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t265" href="#t265">265</a></span><span class="t">            <span class="nam">expert_forbidden_conditions</span><span class="op">=</span><span class="nam">test_case</span><span class="op">.</span><span class="nam">knowledge</span><span class="op">.</span><span class="nam">expert_forbidden_conditions</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t266" href="#t266">266</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t267" href="#t267">267</a></span><span class="t">        <span class="nam">res</span> <span class="op">=</span> <span class="nam">clf</span><span class="op">.</span><span class="nam">predict_proba</span><span class="op">(</span><span class="nam">example_set</span><span class="op">.</span><span class="nam">values</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t268" href="#t268">268</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">assertEqual</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t269" href="#t269">269</a></span><span class="t">            <span class="nam">res</span><span class="op">.</span><span class="nam">shape</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t270" href="#t270">270</a></span><span class="t">            <span class="nam">example_set</span><span class="op">.</span><span class="nam">values</span><span class="op">.</span><span class="nam">shape</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t271" href="#t271">271</a></span><span class="t">            <span class="str">"Should have as many rows as the original dataset"</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t272" href="#t272">272</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t273" href="#t273">273</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">assertEqual</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t274" href="#t274">274</a></span><span class="t">            <span class="nam">res</span><span class="op">.</span><span class="nam">shape</span><span class="op">[</span><span class="num">1</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t275" href="#t275">275</a></span><span class="t">            <span class="nam">np</span><span class="op">.</span><span class="nam">unique</span><span class="op">(</span><span class="nam">example_set</span><span class="op">.</span><span class="nam">labels</span><span class="op">)</span><span class="op">.</span><span class="nam">shape</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t276" href="#t276">276</a></span><span class="t">            <span class="str">"Should have as many columns as there are classes in the dataset"</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t277" href="#t277">277</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t278" href="#t278">278</a></span><span class="t">        <span class="nam">clf</span><span class="op">.</span><span class="nam">fit</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t279" href="#t279">279</a></span><span class="t">            <span class="nam">X</span><span class="op">,</span> <span class="nam">y</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t280" href="#t280">280</a></span><span class="t">            <span class="nam">expert_rules</span><span class="op">=</span><span class="nam">expert_rules</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t281" href="#t281">281</a></span><span class="t">            <span class="nam">expert_preferred_conditions</span><span class="op">=</span><span class="nam">expert_preferred_conditions</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t282" href="#t282">282</a></span><span class="t">            <span class="nam">expert_forbidden_conditions</span><span class="op">=</span><span class="nam">expert_forbidden_conditions</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t283" href="#t283">283</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t284" href="#t284">284</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t285" href="#t285">285</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t286" href="#t286">286</a></span><span class="t"><span class="key">if</span> <span class="nam">__name__</span> <span class="op">==</span> <span class="str">'__main__'</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t287" href="#t287">287</a></span><span class="t">    <span class="nam">unittest</span><span class="op">.</span><span class="nam">main</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t278" href="#t278">278</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">assertTrue</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t279" href="#t279">279</a></span><span class="t">            <span class="nam">res</span><span class="op">.</span><span class="nam">max</span><span class="op">(</span><span class="op">)</span> <span class="op">&lt;=</span> <span class="num">1</span> <span class="key">and</span> <span class="nam">res</span><span class="op">.</span><span class="nam">min</span><span class="op">(</span><span class="op">)</span> <span class="op">>=</span> <span class="num">0</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t280" href="#t280">280</a></span><span class="t">            <span class="str">"Predicted probabilities should be in range [0, 1]"</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t281" href="#t281">281</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t282" href="#t282">282</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t283" href="#t283">283</a></span><span class="t">    <span class="com"># Issue #17</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t284" href="#t284">284</a></span><span class="t">    <span class="key">def</span> <span class="nam">test_left_open_intervals_in_expert_induction</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t285" href="#t285">285</a></span><span class="t">        <span class="nam">df</span> <span class="op">=</span> <span class="nam">pd</span><span class="op">.</span><span class="nam">DataFrame</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t286" href="#t286">286</a></span><span class="t">            <span class="nam">arff</span><span class="op">.</span><span class="nam">loadarff</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t287" href="#t287">287</a></span><span class="t">                <span class="str">f"{dir_path}/resources/data/seismic-bumps-train-minimal.arff"</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t288" href="#t288">288</a></span><span class="t">            <span class="op">)</span><span class="op">[</span><span class="num">0</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t289" href="#t289">289</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t290" href="#t290">290</a></span><span class="t">        <span class="nam">X</span> <span class="op">=</span> <span class="nam">df</span><span class="op">.</span><span class="nam">drop</span><span class="op">(</span><span class="str">"class"</span><span class="op">,</span> <span class="nam">axis</span><span class="op">=</span><span class="num">1</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t291" href="#t291">291</a></span><span class="t">        <span class="nam">y</span> <span class="op">=</span> <span class="nam">df</span><span class="op">[</span><span class="str">"class"</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t292" href="#t292">292</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t293" href="#t293">293</a></span><span class="t">        <span class="nam">expert_rules</span> <span class="op">=</span> <span class="op">[</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t294" href="#t294">294</a></span><span class="t">            <span class="op">(</span><span class="str">"rule-0"</span><span class="op">,</span> <span class="str">"IF [[gimpuls = &lt;-inf, 750)]] THEN class = {0}"</span><span class="op">)</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t295" href="#t295">295</a></span><span class="t">            <span class="op">(</span><span class="str">"rule-1"</span><span class="op">,</span> <span class="str">"IF [[gimpuls = (750, inf)]] THEN class = {1}"</span><span class="op">)</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t296" href="#t296">296</a></span><span class="t">        <span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t297" href="#t297">297</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t298" href="#t298">298</a></span><span class="t">        <span class="nam">expert_preferred_conditions</span> <span class="op">=</span> <span class="op">[</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t299" href="#t299">299</a></span><span class="t">            <span class="op">(</span><span class="str">"preferred-condition-0"</span><span class="op">,</span> <span class="str">"1: IF [[seismic = {a}]] THEN class = {0}"</span><span class="op">)</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t300" href="#t300">300</a></span><span class="t">            <span class="op">(</span><span class="str">"preferred-attribute-0"</span><span class="op">,</span> <span class="str">"1: IF [[gimpuls = Any]] THEN class = {1}"</span><span class="op">)</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t301" href="#t301">301</a></span><span class="t">        <span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t302" href="#t302">302</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t303" href="#t303">303</a></span><span class="t">        <span class="nam">expert_forbidden_conditions</span> <span class="op">=</span> <span class="op">[</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t304" href="#t304">304</a></span><span class="t">            <span class="op">(</span><span class="str">"forb-attribute-0"</span><span class="op">,</span> <span class="str">"1: IF [[seismoacoustic  = Any]] THEN class = {0}"</span><span class="op">)</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t305" href="#t305">305</a></span><span class="t">            <span class="op">(</span><span class="str">"forb-attribute-1"</span><span class="op">,</span> <span class="str">"inf: IF [[ghazard  = Any]] THEN class = {1}"</span><span class="op">)</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t306" href="#t306">306</a></span><span class="t">        <span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t307" href="#t307">307</a></span><span class="t">        <span class="nam">clf</span> <span class="op">=</span> <span class="nam">classification</span><span class="op">.</span><span class="nam">ExpertRuleClassifier</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t308" href="#t308">308</a></span><span class="t">            <span class="nam">minsupp_new</span><span class="op">=</span><span class="num">8</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t309" href="#t309">309</a></span><span class="t">            <span class="nam">max_growing</span><span class="op">=</span><span class="num">0</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t310" href="#t310">310</a></span><span class="t">            <span class="nam">extend_using_preferred</span><span class="op">=</span><span class="key">True</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t311" href="#t311">311</a></span><span class="t">            <span class="nam">extend_using_automatic</span><span class="op">=</span><span class="key">True</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t312" href="#t312">312</a></span><span class="t">            <span class="nam">induce_using_preferred</span><span class="op">=</span><span class="key">True</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t313" href="#t313">313</a></span><span class="t">            <span class="nam">induce_using_automatic</span><span class="op">=</span><span class="key">True</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t314" href="#t314">314</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t315" href="#t315">315</a></span><span class="t">        <span class="nam">clf</span><span class="op">.</span><span class="nam">fit</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t316" href="#t316">316</a></span><span class="t">            <span class="nam">X</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t317" href="#t317">317</a></span><span class="t">            <span class="nam">y</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t318" href="#t318">318</a></span><span class="t">            <span class="nam">expert_rules</span><span class="op">=</span><span class="nam">expert_rules</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t319" href="#t319">319</a></span><span class="t">            <span class="nam">expert_preferred_conditions</span><span class="op">=</span><span class="nam">expert_preferred_conditions</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t320" href="#t320">320</a></span><span class="t">            <span class="nam">expert_forbidden_conditions</span><span class="op">=</span><span class="nam">expert_forbidden_conditions</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t321" href="#t321">321</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t322" href="#t322">322</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t323" href="#t323">323</a></span><span class="t">    <span class="com"># @unittest.skip(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t324" href="#t324">324</a></span><span class="t">    <span class="com">#     "Skipped due to known bug https://bitbucket.org/polsl-a/rules/issues/126"</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t325" href="#t325">325</a></span><span class="t">    <span class="com"># )</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t326" href="#t326">326</a></span><span class="t">    <span class="key">def</span> <span class="nam">test_refining_conditions_for_nominal_attributes</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t327" href="#t327">327</a></span><span class="t">        <span class="nam">df</span><span class="op">:</span> <span class="nam">pd</span><span class="op">.</span><span class="nam">DataFrame</span> <span class="op">=</span> <span class="nam">pd</span><span class="op">.</span><span class="nam">read_csv</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t328" href="#t328">328</a></span><span class="t">            <span class="nam">os</span><span class="op">.</span><span class="nam">path</span><span class="op">.</span><span class="nam">join</span><span class="op">(</span><span class="nam">dir_path</span><span class="op">,</span> <span class="str">"additional_resources"</span><span class="op">,</span> <span class="str">"salary.csv"</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t329" href="#t329">329</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t330" href="#t330">330</a></span><span class="t">        <span class="nam">X</span><span class="op">,</span> <span class="nam">y</span> <span class="op">=</span> <span class="nam">df</span><span class="op">.</span><span class="nam">drop</span><span class="op">(</span><span class="str">"Salary"</span><span class="op">,</span> <span class="nam">axis</span><span class="op">=</span><span class="num">1</span><span class="op">)</span><span class="op">,</span> <span class="nam">df</span><span class="op">[</span><span class="str">"Salary"</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t331" href="#t331">331</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t332" href="#t332">332</a></span><span class="t">        <span class="com"># Run experiment using python API</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t333" href="#t333">333</a></span><span class="t">        <span class="nam">clf</span> <span class="op">=</span> <span class="nam">classification</span><span class="op">.</span><span class="nam">ExpertRuleClassifier</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t334" href="#t334">334</a></span><span class="t">            <span class="nam">induction_measure</span><span class="op">=</span><span class="nam">Measures</span><span class="op">.</span><span class="nam">C2</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t335" href="#t335">335</a></span><span class="t">            <span class="nam">pruning_measure</span><span class="op">=</span><span class="nam">Measures</span><span class="op">.</span><span class="nam">C2</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t336" href="#t336">336</a></span><span class="t">            <span class="nam">voting_measure</span><span class="op">=</span><span class="nam">Measures</span><span class="op">.</span><span class="nam">C2</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t337" href="#t337">337</a></span><span class="t">            <span class="nam">complementary_conditions</span><span class="op">=</span><span class="key">True</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t338" href="#t338">338</a></span><span class="t">            <span class="nam">extend_using_preferred</span><span class="op">=</span><span class="key">False</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t339" href="#t339">339</a></span><span class="t">            <span class="nam">extend_using_automatic</span><span class="op">=</span><span class="key">False</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t340" href="#t340">340</a></span><span class="t">            <span class="nam">induce_using_preferred</span><span class="op">=</span><span class="key">False</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t341" href="#t341">341</a></span><span class="t">            <span class="nam">induce_using_automatic</span><span class="op">=</span><span class="key">False</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t342" href="#t342">342</a></span><span class="t">            <span class="nam">preferred_conditions_per_rule</span><span class="op">=</span><span class="num">0</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t343" href="#t343">343</a></span><span class="t">            <span class="nam">preferred_attributes_per_rule</span><span class="op">=</span><span class="num">0</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t344" href="#t344">344</a></span><span class="t">            <span class="nam">consider_other_classes</span><span class="op">=</span><span class="key">False</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t345" href="#t345">345</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t346" href="#t346">346</a></span><span class="t">        <span class="nam">clf</span><span class="op">.</span><span class="nam">fit</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t347" href="#t347">347</a></span><span class="t">            <span class="nam">X</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t348" href="#t348">348</a></span><span class="t">            <span class="nam">y</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t349" href="#t349">349</a></span><span class="t">            <span class="nam">expert_rules</span><span class="op">=</span><span class="op">[</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t350" href="#t350">350</a></span><span class="t">                <span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t351" href="#t351">351</a></span><span class="t">                    <span class="str">"expert_rules-1"</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t352" href="#t352">352</a></span><span class="t">                    <span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t353" href="#t353">353</a></span><span class="t">                        <span class="str">"IF Age = (-inf, 33.0) AND Job Title @= {Software Engineer} THEN "</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t354" href="#t354">354</a></span><span class="t">                        <span class="str">"Salary = {below average}"</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t355" href="#t355">355</a></span><span class="t">                    <span class="op">)</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t356" href="#t356">356</a></span><span class="t">                <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t357" href="#t357">357</a></span><span class="t">            <span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t358" href="#t358">358</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t359" href="#t359">359</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">assertEqual</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t360" href="#t360">360</a></span><span class="t">            <span class="op">[</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t361" href="#t361">361</a></span><span class="t">                <span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t362" href="#t362">362</a></span><span class="t">                    <span class="str">"IF [[Age = (-inf, 33)]] AND [[Job Title = {Software Engineer}]] THEN "</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t363" href="#t363">363</a></span><span class="t">                    <span class="str">"Salary = {below average}"</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t364" href="#t364">364</a></span><span class="t">                <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t365" href="#t365">365</a></span><span class="t">            <span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t366" href="#t366">366</a></span><span class="t">            <span class="op">[</span><span class="nam">str</span><span class="op">(</span><span class="nam">r</span><span class="op">)</span> <span class="key">for</span> <span class="nam">r</span> <span class="key">in</span> <span class="nam">clf</span><span class="op">.</span><span class="nam">model</span><span class="op">.</span><span class="nam">rules</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t367" href="#t367">367</a></span><span class="t">            <span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t368" href="#t368">368</a></span><span class="t">                <span class="str">"Ruleset should contain only a single rule configured by expert with "</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t369" href="#t369">369</a></span><span class="t">                <span class="str">"a refined condition"</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t370" href="#t370">370</a></span><span class="t">            <span class="op">)</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t371" href="#t371">371</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t372" href="#t372">372</a></span><span class="t">        <span class="nam">clf</span><span class="op">.</span><span class="nam">fit</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t373" href="#t373">373</a></span><span class="t">            <span class="nam">X</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t374" href="#t374">374</a></span><span class="t">            <span class="nam">y</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t375" href="#t375">375</a></span><span class="t">            <span class="nam">expert_rules</span><span class="op">=</span><span class="op">[</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t376" href="#t376">376</a></span><span class="t">                <span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t377" href="#t377">377</a></span><span class="t">                    <span class="str">"expert_rules-1"</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t378" href="#t378">378</a></span><span class="t">                    <span class="str">"IF Age = (-inf, 33.0) AND Job Title @= Any THEN Salary = {below average}"</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t379" href="#t379">379</a></span><span class="t">                <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t380" href="#t380">380</a></span><span class="t">            <span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t381" href="#t381">381</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t382" href="#t382">382</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">assertEqual</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t383" href="#t383">383</a></span><span class="t">            <span class="op">[</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t384" href="#t384">384</a></span><span class="t">                <span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t385" href="#t385">385</a></span><span class="t">                    <span class="str">"IF [[Age = (-inf, 33)]] AND [[Job Title = {Marketing Analyst}]] "</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t386" href="#t386">386</a></span><span class="t">                    <span class="str">"THEN Salary = {below average}"</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t387" href="#t387">387</a></span><span class="t">                <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t388" href="#t388">388</a></span><span class="t">            <span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t389" href="#t389">389</a></span><span class="t">            <span class="op">[</span><span class="nam">str</span><span class="op">(</span><span class="nam">r</span><span class="op">)</span> <span class="key">for</span> <span class="nam">r</span> <span class="key">in</span> <span class="nam">clf</span><span class="op">.</span><span class="nam">model</span><span class="op">.</span><span class="nam">rules</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t390" href="#t390">390</a></span><span class="t">            <span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t391" href="#t391">391</a></span><span class="t">                <span class="str">"Ruleset should contain only a single rule configured by expert with "</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t392" href="#t392">392</a></span><span class="t">                <span class="str">"a refined condition"</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t393" href="#t393">393</a></span><span class="t">            <span class="op">)</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t394" href="#t394">394</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t395" href="#t395">395</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t396" href="#t396">396</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t397" href="#t397">397</a></span><span class="t"><span class="key">if</span> <span class="nam">__name__</span> <span class="op">==</span> <span class="str">"__main__"</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t398" href="#t398">398</a></span><span class="t">    <span class="nam">unittest</span><span class="op">.</span><span class="nam">main</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
 </main>
 <footer>
     <div class="content">
@@ -376,7 +487,7 @@ <h2>
             <a class="nav" href="z_a44f0ac069e85531_test_regression_py.html">&#xbb; next</a>
             &nbsp; &nbsp; &nbsp;
             <a class="nav" href="https://coverage.readthedocs.io/en/7.6.4">coverage.py v7.6.4</a>,
-            created at 2024-11-08 14:43 +0100
+            created at 2024-11-28 12:33 +0100
         </p>
     </div>
 </footer>
diff --git a/docs/reports/coverage/z_a44f0ac069e85531_test_regression_py.html b/docs/reports/coverage/z_a44f0ac069e85531_test_regression_py.html
index be3e020..7543b22 100644
--- a/docs/reports/coverage/z_a44f0ac069e85531_test_regression_py.html
+++ b/docs/reports/coverage/z_a44f0ac069e85531_test_regression_py.html
@@ -54,8 +54,8 @@ <h1>
             </div>
         </aside>
         <h2>
-            <span class="text">94 statements &nbsp;</span>
-            <button type="button" class="run button_toggle_run" value="run" data-shortcut="r" title="Toggle lines run">93<span class="text"> run</span></button>
+            <span class="text">116 statements &nbsp;</span>
+            <button type="button" class="run button_toggle_run" value="run" data-shortcut="r" title="Toggle lines run">115<span class="text"> run</span></button>
             <button type="button" class="mis show_mis button_toggle_mis" value="mis" data-shortcut="m" title="Toggle lines missing">1<span class="text"> missing</span></button>
             <button type="button" class="exc show_exc button_toggle_exc" value="exc" data-shortcut="x" title="Toggle lines excluded">0<span class="text"> excluded</span></button>
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@@ -65,7 +65,7 @@ <h2>
             <a id="nextFileLink" class="nav" href="z_a44f0ac069e85531_test_rulekit_py.html">&#xbb; next</a>
             &nbsp; &nbsp; &nbsp;
             <a class="nav" href="https://coverage.readthedocs.io/en/7.6.4">coverage.py v7.6.4</a>,
-            created at 2024-11-08 14:43 +0100
+            created at 2024-11-28 11:55 +0100
         </p>
         <aside class="hidden">
             <button type="button" class="button_next_chunk" data-shortcut="j"></button>
@@ -93,143 +93,213 @@ <h2>
     <p class="run"><span class="n"><a id="t11" href="#t11">11</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">main</span> <span class="key">import</span> <span class="nam">RuleKit</span>&nbsp;</span><span class="r"></span></p>
     <p class="run"><span class="n"><a id="t12" href="#t12">12</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">params</span> <span class="key">import</span> <span class="nam">Measures</span>&nbsp;</span><span class="r"></span></p>
     <p class="run"><span class="n"><a id="t13" href="#t13">13</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">rules</span> <span class="key">import</span> <span class="nam">RegressionRule</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t14" href="#t14">14</a></span><span class="t"><span class="key">from</span> <span class="nam">tests</span><span class="op">.</span><span class="nam">utils</span> <span class="key">import</span> <span class="op">(</span><span class="nam">assert_rules_are_equals</span><span class="op">,</span> <span class="nam">assert_score_is_greater</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t15" href="#t15">15</a></span><span class="t">                         <span class="nam">dir_path</span><span class="op">,</span> <span class="nam">get_test_cases</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t16" href="#t16">16</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t17" href="#t17">17</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t18" href="#t18">18</a></span><span class="t"><span class="key">class</span> <span class="nam">TestRegressor</span><span class="op">(</span><span class="nam">unittest</span><span class="op">.</span><span class="nam">TestCase</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t14" href="#t14">14</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">rules</span> <span class="key">import</span> <span class="nam">RuleSet</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t15" href="#t15">15</a></span><span class="t"><span class="key">from</span> <span class="nam">tests</span><span class="op">.</span><span class="nam">utils</span> <span class="key">import</span> <span class="nam">assert_rules_are_equals</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t16" href="#t16">16</a></span><span class="t"><span class="key">from</span> <span class="nam">tests</span><span class="op">.</span><span class="nam">utils</span> <span class="key">import</span> <span class="nam">assert_score_is_greater</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t17" href="#t17">17</a></span><span class="t"><span class="key">from</span> <span class="nam">tests</span><span class="op">.</span><span class="nam">utils</span> <span class="key">import</span> <span class="nam">dir_path</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t18" href="#t18">18</a></span><span class="t"><span class="key">from</span> <span class="nam">tests</span><span class="op">.</span><span class="nam">utils</span> <span class="key">import</span> <span class="nam">get_test_cases</span>&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t19" href="#t19">19</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t20" href="#t20">20</a></span><span class="t">    <span class="op">@</span><span class="nam">classmethod</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t21" href="#t21">21</a></span><span class="t">    <span class="key">def</span> <span class="nam">setUpClass</span><span class="op">(</span><span class="nam">cls</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t22" href="#t22">22</a></span><span class="t">        <span class="nam">RuleKit</span><span class="op">.</span><span class="nam">init</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t23" href="#t23">23</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t24" href="#t24">24</a></span><span class="t">    <span class="key">def</span> <span class="nam">test_induction_progress_listener</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t25" href="#t25">25</a></span><span class="t">        <span class="nam">test_case</span> <span class="op">=</span> <span class="nam">get_test_cases</span><span class="op">(</span><span class="str">'RegressionSnCTest'</span><span class="op">)</span><span class="op">[</span><span class="num">0</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t20" href="#t20">20</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t21" href="#t21">21</a></span><span class="t"><span class="key">class</span> <span class="nam">TestRegressor</span><span class="op">(</span><span class="nam">unittest</span><span class="op">.</span><span class="nam">TestCase</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t22" href="#t22">22</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t23" href="#t23">23</a></span><span class="t">    <span class="op">@</span><span class="nam">classmethod</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t24" href="#t24">24</a></span><span class="t">    <span class="key">def</span> <span class="nam">setUpClass</span><span class="op">(</span><span class="nam">cls</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t25" href="#t25">25</a></span><span class="t">        <span class="nam">RuleKit</span><span class="op">.</span><span class="nam">init</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t26" href="#t26">26</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t27" href="#t27">27</a></span><span class="t">        <span class="nam">reg</span> <span class="op">=</span> <span class="nam">regression</span><span class="op">.</span><span class="nam">RuleRegressor</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t28" href="#t28">28</a></span><span class="t">        <span class="nam">example_set</span> <span class="op">=</span> <span class="nam">test_case</span><span class="op">.</span><span class="nam">example_set</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t29" href="#t29">29</a></span><span class="t">        <span class="nam">MAX_RULES</span> <span class="op">=</span> <span class="num">3</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t30" href="#t30">30</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t31" href="#t31">31</a></span><span class="t">        <span class="key">class</span> <span class="nam">EventListener</span><span class="op">(</span><span class="nam">RuleInductionProgressListener</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t32" href="#t32">32</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t33" href="#t33">33</a></span><span class="t">            <span class="nam">lock</span> <span class="op">=</span> <span class="nam">threading</span><span class="op">.</span><span class="nam">Lock</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t34" href="#t34">34</a></span><span class="t">            <span class="nam">induced_rules_count</span> <span class="op">=</span> <span class="num">0</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t35" href="#t35">35</a></span><span class="t">            <span class="nam">on_progress_calls_count</span> <span class="op">=</span> <span class="num">0</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t36" href="#t36">36</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t37" href="#t37">37</a></span><span class="t">            <span class="key">def</span> <span class="nam">on_new_rule</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">rule</span><span class="op">:</span> <span class="nam">RegressionRule</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t38" href="#t38">38</a></span><span class="t">                <span class="nam">self</span><span class="op">.</span><span class="nam">lock</span><span class="op">.</span><span class="nam">acquire</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t39" href="#t39">39</a></span><span class="t">                <span class="nam">self</span><span class="op">.</span><span class="nam">induced_rules_count</span> <span class="op">+=</span> <span class="num">1</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t40" href="#t40">40</a></span><span class="t">                <span class="nam">self</span><span class="op">.</span><span class="nam">lock</span><span class="op">.</span><span class="nam">release</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t41" href="#t41">41</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t42" href="#t42">42</a></span><span class="t">            <span class="key">def</span> <span class="nam">on_progress</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t43" href="#t43">43</a></span><span class="t">                <span class="nam">self</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t44" href="#t44">44</a></span><span class="t">                <span class="nam">total_examples_count</span><span class="op">:</span> <span class="nam">int</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t45" href="#t45">45</a></span><span class="t">                <span class="nam">uncovered_examples_count</span><span class="op">:</span> <span class="nam">int</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t46" href="#t46">46</a></span><span class="t">            <span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t47" href="#t47">47</a></span><span class="t">                <span class="nam">self</span><span class="op">.</span><span class="nam">lock</span><span class="op">.</span><span class="nam">acquire</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t48" href="#t48">48</a></span><span class="t">                <span class="nam">self</span><span class="op">.</span><span class="nam">on_progress_calls_count</span> <span class="op">+=</span> <span class="num">1</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t49" href="#t49">49</a></span><span class="t">                <span class="nam">self</span><span class="op">.</span><span class="nam">lock</span><span class="op">.</span><span class="nam">release</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t50" href="#t50">50</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t51" href="#t51">51</a></span><span class="t">            <span class="key">def</span> <span class="nam">should_stop</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">bool</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t52" href="#t52">52</a></span><span class="t">                <span class="nam">self</span><span class="op">.</span><span class="nam">lock</span><span class="op">.</span><span class="nam">acquire</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t53" href="#t53">53</a></span><span class="t">                <span class="nam">should_stop</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">induced_rules_count</span> <span class="op">==</span> <span class="nam">MAX_RULES</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t54" href="#t54">54</a></span><span class="t">                <span class="nam">self</span><span class="op">.</span><span class="nam">lock</span><span class="op">.</span><span class="nam">release</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t55" href="#t55">55</a></span><span class="t">                <span class="key">return</span> <span class="nam">should_stop</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t56" href="#t56">56</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t57" href="#t57">57</a></span><span class="t">        <span class="nam">listener</span> <span class="op">=</span> <span class="nam">EventListener</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t58" href="#t58">58</a></span><span class="t">        <span class="nam">reg</span><span class="op">.</span><span class="nam">add_event_listener</span><span class="op">(</span><span class="nam">listener</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t59" href="#t59">59</a></span><span class="t">        <span class="nam">reg</span><span class="op">.</span><span class="nam">fit</span><span class="op">(</span><span class="nam">example_set</span><span class="op">.</span><span class="nam">values</span><span class="op">,</span> <span class="nam">example_set</span><span class="op">.</span><span class="nam">labels</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t60" href="#t60">60</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t61" href="#t61">61</a></span><span class="t">        <span class="nam">rules_count</span> <span class="op">=</span> <span class="nam">len</span><span class="op">(</span><span class="nam">reg</span><span class="op">.</span><span class="nam">model</span><span class="op">.</span><span class="nam">rules</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t62" href="#t62">62</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">assertEqual</span><span class="op">(</span><span class="nam">rules_count</span><span class="op">,</span> <span class="nam">MAX_RULES</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t63" href="#t63">63</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">assertEqual</span><span class="op">(</span><span class="nam">rules_count</span><span class="op">,</span> <span class="nam">listener</span><span class="op">.</span><span class="nam">on_progress_calls_count</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t64" href="#t64">64</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t65" href="#t65">65</a></span><span class="t">    <span class="key">def</span> <span class="nam">test_compare_with_java_results</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t66" href="#t66">66</a></span><span class="t">        <span class="nam">test_cases</span> <span class="op">=</span> <span class="nam">get_test_cases</span><span class="op">(</span><span class="str">'RegressionSnCTest'</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t67" href="#t67">67</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t68" href="#t68">68</a></span><span class="t">        <span class="key">for</span> <span class="nam">test_case</span> <span class="key">in</span> <span class="nam">test_cases</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t69" href="#t69">69</a></span><span class="t">            <span class="nam">params</span> <span class="op">=</span> <span class="nam">test_case</span><span class="op">.</span><span class="nam">induction_params</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t70" href="#t70">70</a></span><span class="t">            <span class="nam">tree</span> <span class="op">=</span> <span class="nam">regression</span><span class="op">.</span><span class="nam">RuleRegressor</span><span class="op">(</span><span class="op">**</span><span class="nam">params</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t71" href="#t71">71</a></span><span class="t">            <span class="nam">example_set</span> <span class="op">=</span> <span class="nam">test_case</span><span class="op">.</span><span class="nam">example_set</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t72" href="#t72">72</a></span><span class="t">            <span class="nam">tree</span><span class="op">.</span><span class="nam">fit</span><span class="op">(</span><span class="nam">example_set</span><span class="op">.</span><span class="nam">values</span><span class="op">,</span> <span class="nam">example_set</span><span class="op">.</span><span class="nam">labels</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t73" href="#t73">73</a></span><span class="t">            <span class="nam">model</span> <span class="op">=</span> <span class="nam">tree</span><span class="op">.</span><span class="nam">model</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t74" href="#t74">74</a></span><span class="t">            <span class="nam">expected</span> <span class="op">=</span> <span class="nam">test_case</span><span class="op">.</span><span class="nam">reference_report</span><span class="op">.</span><span class="nam">rules</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t75" href="#t75">75</a></span><span class="t">            <span class="nam">actual</span> <span class="op">=</span> <span class="op">[</span><span class="nam">str</span><span class="op">(</span><span class="nam">r</span><span class="op">)</span> <span class="key">for</span> <span class="nam">r</span> <span class="key">in</span> <span class="nam">model</span><span class="op">.</span><span class="nam">rules</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t76" href="#t76">76</a></span><span class="t">            <span class="nam">assert_rules_are_equals</span><span class="op">(</span><span class="nam">expected</span><span class="op">,</span> <span class="nam">actual</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t77" href="#t77">77</a></span><span class="t">            <span class="nam">assert_score_is_greater</span><span class="op">(</span><span class="nam">tree</span><span class="op">.</span><span class="nam">predict</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t78" href="#t78">78</a></span><span class="t">                <span class="nam">example_set</span><span class="op">.</span><span class="nam">values</span><span class="op">)</span><span class="op">,</span> <span class="nam">example_set</span><span class="op">.</span><span class="nam">labels</span><span class="op">,</span> <span class="num">0.7</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t79" href="#t79">79</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t80" href="#t80">80</a></span><span class="t">    <span class="key">def</span> <span class="nam">test_fit_and_predict_on_boolean_columns</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t81" href="#t81">81</a></span><span class="t">        <span class="nam">test_case</span> <span class="op">=</span> <span class="nam">get_test_cases</span><span class="op">(</span><span class="str">'RegressionSnCTest'</span><span class="op">)</span><span class="op">[</span><span class="num">0</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t82" href="#t82">82</a></span><span class="t">        <span class="nam">params</span> <span class="op">=</span> <span class="nam">test_case</span><span class="op">.</span><span class="nam">induction_params</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t83" href="#t83">83</a></span><span class="t">        <span class="nam">clf</span> <span class="op">=</span> <span class="nam">regression</span><span class="op">.</span><span class="nam">RuleRegressor</span><span class="op">(</span><span class="op">**</span><span class="nam">params</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t84" href="#t84">84</a></span><span class="t">        <span class="nam">X</span><span class="op">,</span> <span class="nam">y</span> <span class="op">=</span> <span class="nam">test_case</span><span class="op">.</span><span class="nam">example_set</span><span class="op">.</span><span class="nam">values</span><span class="op">,</span> <span class="nam">test_case</span><span class="op">.</span><span class="nam">example_set</span><span class="op">.</span><span class="nam">labels</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t85" href="#t85">85</a></span><span class="t">        <span class="nam">X</span><span class="op">[</span><span class="str">'boolean_column'</span><span class="op">]</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">random</span><span class="op">.</span><span class="nam">randint</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t86" href="#t86">86</a></span><span class="t">            <span class="nam">low</span><span class="op">=</span><span class="num">0</span><span class="op">,</span> <span class="nam">high</span><span class="op">=</span><span class="num">2</span><span class="op">,</span> <span class="nam">size</span><span class="op">=</span><span class="nam">X</span><span class="op">.</span><span class="nam">shape</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="op">)</span><span class="op">.</span><span class="nam">astype</span><span class="op">(</span><span class="nam">bool</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t87" href="#t87">87</a></span><span class="t">        <span class="nam">clf</span><span class="op">.</span><span class="nam">fit</span><span class="op">(</span><span class="nam">X</span><span class="op">,</span> <span class="nam">y</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t88" href="#t88">88</a></span><span class="t">        <span class="nam">clf</span><span class="op">.</span><span class="nam">predict</span><span class="op">(</span><span class="nam">X</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t89" href="#t89">89</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t90" href="#t90">90</a></span><span class="t">        <span class="nam">y</span> <span class="op">=</span> <span class="nam">pd</span><span class="op">.</span><span class="nam">Series</span><span class="op">(</span><span class="nam">y</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t91" href="#t91">91</a></span><span class="t">        <span class="nam">clf</span><span class="op">.</span><span class="nam">fit</span><span class="op">(</span><span class="nam">X</span><span class="op">,</span> <span class="nam">y</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t92" href="#t92">92</a></span><span class="t">        <span class="nam">clf</span><span class="op">.</span><span class="nam">predict</span><span class="op">(</span><span class="nam">X</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t93" href="#t93">93</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t94" href="#t94">94</a></span><span class="t">    <span class="key">def</span> <span class="nam">test_cholesterol</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t95" href="#t95">95</a></span><span class="t">        <span class="nam">resources_dir</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="nam">os</span><span class="op">.</span><span class="nam">path</span><span class="op">.</span><span class="nam">join</span><span class="op">(</span><span class="nam">dir_path</span><span class="op">,</span> <span class="str">'additional_resources'</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t96" href="#t96">96</a></span><span class="t">        <span class="nam">df</span><span class="op">:</span> <span class="nam">pd</span><span class="op">.</span><span class="nam">DataFrame</span> <span class="op">=</span> <span class="nam">read_arff</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t97" href="#t97">97</a></span><span class="t">            <span class="nam">os</span><span class="op">.</span><span class="nam">path</span><span class="op">.</span><span class="nam">join</span><span class="op">(</span><span class="nam">resources_dir</span><span class="op">,</span> <span class="str">'cholesterol.arff'</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t98" href="#t98">98</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t99" href="#t99">99</a></span><span class="t">        <span class="nam">X</span><span class="op">,</span> <span class="nam">y</span> <span class="op">=</span> <span class="nam">df</span><span class="op">.</span><span class="nam">drop</span><span class="op">(</span><span class="str">'class'</span><span class="op">,</span> <span class="nam">axis</span><span class="op">=</span><span class="num">1</span><span class="op">)</span><span class="op">,</span> <span class="nam">df</span><span class="op">[</span><span class="str">'class'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t100" href="#t100">100</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t101" href="#t101">101</a></span><span class="t">        <span class="com"># Run experiment using python API</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t102" href="#t102">102</a></span><span class="t">        <span class="nam">reg</span> <span class="op">=</span> <span class="nam">regression</span><span class="op">.</span><span class="nam">RuleRegressor</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t103" href="#t103">103</a></span><span class="t">            <span class="nam">minsupp_new</span><span class="op">=</span><span class="num">0.05</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t104" href="#t104">104</a></span><span class="t">            <span class="nam">max_uncovered_fraction</span><span class="op">=</span><span class="num">0.0</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t105" href="#t105">105</a></span><span class="t">            <span class="nam">max_growing</span><span class="op">=</span><span class="num">0.0</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t106" href="#t106">106</a></span><span class="t">            <span class="nam">induction_measure</span><span class="op">=</span><span class="nam">Measures</span><span class="op">.</span><span class="nam">Accuracy</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t107" href="#t107">107</a></span><span class="t">            <span class="nam">pruning_measure</span><span class="op">=</span><span class="nam">Measures</span><span class="op">.</span><span class="nam">Accuracy</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t108" href="#t108">108</a></span><span class="t">            <span class="nam">voting_measure</span><span class="op">=</span><span class="nam">Measures</span><span class="op">.</span><span class="nam">Accuracy</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t109" href="#t109">109</a></span><span class="t">            <span class="nam">ignore_missing</span><span class="op">=</span><span class="key">False</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t110" href="#t110">110</a></span><span class="t">            <span class="nam">select_best_candidate</span><span class="op">=</span><span class="key">False</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t111" href="#t111">111</a></span><span class="t">            <span class="nam">complementary_conditions</span><span class="op">=</span><span class="key">True</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t112" href="#t112">112</a></span><span class="t">            <span class="nam">max_rule_count</span><span class="op">=</span><span class="num">0</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t113" href="#t113">113</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t114" href="#t114">114</a></span><span class="t">        <span class="nam">reg</span><span class="op">.</span><span class="nam">fit</span><span class="op">(</span><span class="nam">X</span><span class="op">,</span> <span class="nam">y</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t115" href="#t115">115</a></span><span class="t">        <span class="nam">actual_rules</span><span class="op">:</span> <span class="nam">list</span><span class="op">[</span><span class="nam">str</span><span class="op">]</span> <span class="op">=</span> <span class="nam">list</span><span class="op">(</span><span class="nam">map</span><span class="op">(</span><span class="nam">str</span><span class="op">,</span> <span class="nam">reg</span><span class="op">.</span><span class="nam">model</span><span class="op">.</span><span class="nam">rules</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t116" href="#t116">116</a></span><span class="t">        <span class="nam">expected_rules</span><span class="op">:</span> <span class="nam">list</span><span class="op">[</span><span class="nam">str</span><span class="op">]</span> <span class="op">=</span> <span class="op">[</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t117" href="#t117">117</a></span><span class="t">            <span class="str">'IF trestbps = (-inf, 149) THEN class = {244.84} [192.73,296.96]'</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t118" href="#t118">118</a></span><span class="t">            <span class="str">'IF trestbps = &lt;122, inf) THEN class = {250.80} [201.79,299.80]'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t119" href="#t119">119</a></span><span class="t">        <span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t120" href="#t120">120</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">assertEqual</span><span class="op">(</span><span class="nam">actual_rules</span><span class="op">,</span> <span class="nam">expected_rules</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t121" href="#t121">121</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t122" href="#t122">122</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t123" href="#t123">123</a></span><span class="t"><span class="key">class</span> <span class="nam">TestExpertRegressor</span><span class="op">(</span><span class="nam">unittest</span><span class="op">.</span><span class="nam">TestCase</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t27" href="#t27">27</a></span><span class="t">    <span class="key">def</span> <span class="nam">test_induction_progress_listener</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t28" href="#t28">28</a></span><span class="t">        <span class="nam">test_case</span> <span class="op">=</span> <span class="nam">get_test_cases</span><span class="op">(</span><span class="str">"RegressionSnCTest"</span><span class="op">)</span><span class="op">[</span><span class="num">0</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t29" href="#t29">29</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t30" href="#t30">30</a></span><span class="t">        <span class="nam">reg</span> <span class="op">=</span> <span class="nam">regression</span><span class="op">.</span><span class="nam">RuleRegressor</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t31" href="#t31">31</a></span><span class="t">        <span class="nam">example_set</span> <span class="op">=</span> <span class="nam">test_case</span><span class="op">.</span><span class="nam">example_set</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t32" href="#t32">32</a></span><span class="t">        <span class="nam">MAX_RULES</span> <span class="op">=</span> <span class="num">3</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t33" href="#t33">33</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t34" href="#t34">34</a></span><span class="t">        <span class="key">class</span> <span class="nam">EventListener</span><span class="op">(</span><span class="nam">RuleInductionProgressListener</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t35" href="#t35">35</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t36" href="#t36">36</a></span><span class="t">            <span class="nam">lock</span> <span class="op">=</span> <span class="nam">threading</span><span class="op">.</span><span class="nam">Lock</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t37" href="#t37">37</a></span><span class="t">            <span class="nam">induced_rules_count</span> <span class="op">=</span> <span class="num">0</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t38" href="#t38">38</a></span><span class="t">            <span class="nam">on_progress_calls_count</span> <span class="op">=</span> <span class="num">0</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t39" href="#t39">39</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t40" href="#t40">40</a></span><span class="t">            <span class="key">def</span> <span class="nam">on_new_rule</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">rule</span><span class="op">:</span> <span class="nam">RegressionRule</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t41" href="#t41">41</a></span><span class="t">                <span class="nam">self</span><span class="op">.</span><span class="nam">lock</span><span class="op">.</span><span class="nam">acquire</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t42" href="#t42">42</a></span><span class="t">                <span class="nam">self</span><span class="op">.</span><span class="nam">induced_rules_count</span> <span class="op">+=</span> <span class="num">1</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t43" href="#t43">43</a></span><span class="t">                <span class="nam">self</span><span class="op">.</span><span class="nam">lock</span><span class="op">.</span><span class="nam">release</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t44" href="#t44">44</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t45" href="#t45">45</a></span><span class="t">            <span class="key">def</span> <span class="nam">on_progress</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t46" href="#t46">46</a></span><span class="t">                <span class="nam">self</span><span class="op">,</span> <span class="nam">total_examples_count</span><span class="op">:</span> <span class="nam">int</span><span class="op">,</span> <span class="nam">uncovered_examples_count</span><span class="op">:</span> <span class="nam">int</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t47" href="#t47">47</a></span><span class="t">            <span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t48" href="#t48">48</a></span><span class="t">                <span class="nam">self</span><span class="op">.</span><span class="nam">lock</span><span class="op">.</span><span class="nam">acquire</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t49" href="#t49">49</a></span><span class="t">                <span class="nam">self</span><span class="op">.</span><span class="nam">on_progress_calls_count</span> <span class="op">+=</span> <span class="num">1</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t50" href="#t50">50</a></span><span class="t">                <span class="nam">self</span><span class="op">.</span><span class="nam">lock</span><span class="op">.</span><span class="nam">release</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t51" href="#t51">51</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t52" href="#t52">52</a></span><span class="t">            <span class="key">def</span> <span class="nam">should_stop</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">bool</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t53" href="#t53">53</a></span><span class="t">                <span class="nam">self</span><span class="op">.</span><span class="nam">lock</span><span class="op">.</span><span class="nam">acquire</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t54" href="#t54">54</a></span><span class="t">                <span class="nam">should_stop</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">induced_rules_count</span> <span class="op">==</span> <span class="nam">MAX_RULES</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t55" href="#t55">55</a></span><span class="t">                <span class="nam">self</span><span class="op">.</span><span class="nam">lock</span><span class="op">.</span><span class="nam">release</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t56" href="#t56">56</a></span><span class="t">                <span class="key">return</span> <span class="nam">should_stop</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t57" href="#t57">57</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t58" href="#t58">58</a></span><span class="t">        <span class="nam">listener</span> <span class="op">=</span> <span class="nam">EventListener</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t59" href="#t59">59</a></span><span class="t">        <span class="nam">reg</span><span class="op">.</span><span class="nam">add_event_listener</span><span class="op">(</span><span class="nam">listener</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t60" href="#t60">60</a></span><span class="t">        <span class="nam">reg</span><span class="op">.</span><span class="nam">fit</span><span class="op">(</span><span class="nam">example_set</span><span class="op">.</span><span class="nam">values</span><span class="op">,</span> <span class="nam">example_set</span><span class="op">.</span><span class="nam">labels</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t61" href="#t61">61</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t62" href="#t62">62</a></span><span class="t">        <span class="nam">rules_count</span> <span class="op">=</span> <span class="nam">len</span><span class="op">(</span><span class="nam">reg</span><span class="op">.</span><span class="nam">model</span><span class="op">.</span><span class="nam">rules</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t63" href="#t63">63</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">assertEqual</span><span class="op">(</span><span class="nam">rules_count</span><span class="op">,</span> <span class="nam">MAX_RULES</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t64" href="#t64">64</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">assertEqual</span><span class="op">(</span><span class="nam">rules_count</span><span class="op">,</span> <span class="nam">listener</span><span class="op">.</span><span class="nam">on_progress_calls_count</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t65" href="#t65">65</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t66" href="#t66">66</a></span><span class="t">    <span class="key">def</span> <span class="nam">test_compare_with_java_results</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t67" href="#t67">67</a></span><span class="t">        <span class="nam">test_cases</span> <span class="op">=</span> <span class="nam">get_test_cases</span><span class="op">(</span><span class="str">"RegressionSnCTest"</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t68" href="#t68">68</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t69" href="#t69">69</a></span><span class="t">        <span class="key">for</span> <span class="nam">test_case</span> <span class="key">in</span> <span class="nam">test_cases</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t70" href="#t70">70</a></span><span class="t">            <span class="nam">params</span> <span class="op">=</span> <span class="nam">test_case</span><span class="op">.</span><span class="nam">induction_params</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t71" href="#t71">71</a></span><span class="t">            <span class="nam">tree</span> <span class="op">=</span> <span class="nam">regression</span><span class="op">.</span><span class="nam">RuleRegressor</span><span class="op">(</span><span class="op">**</span><span class="nam">params</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t72" href="#t72">72</a></span><span class="t">            <span class="nam">example_set</span> <span class="op">=</span> <span class="nam">test_case</span><span class="op">.</span><span class="nam">example_set</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t73" href="#t73">73</a></span><span class="t">            <span class="nam">tree</span><span class="op">.</span><span class="nam">fit</span><span class="op">(</span><span class="nam">example_set</span><span class="op">.</span><span class="nam">values</span><span class="op">,</span> <span class="nam">example_set</span><span class="op">.</span><span class="nam">labels</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t74" href="#t74">74</a></span><span class="t">            <span class="nam">model</span> <span class="op">=</span> <span class="nam">tree</span><span class="op">.</span><span class="nam">model</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t75" href="#t75">75</a></span><span class="t">            <span class="nam">expected</span> <span class="op">=</span> <span class="nam">test_case</span><span class="op">.</span><span class="nam">reference_report</span><span class="op">.</span><span class="nam">rules</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t76" href="#t76">76</a></span><span class="t">            <span class="nam">actual</span> <span class="op">=</span> <span class="op">[</span><span class="nam">str</span><span class="op">(</span><span class="nam">r</span><span class="op">)</span> <span class="key">for</span> <span class="nam">r</span> <span class="key">in</span> <span class="nam">model</span><span class="op">.</span><span class="nam">rules</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t77" href="#t77">77</a></span><span class="t">            <span class="nam">assert_rules_are_equals</span><span class="op">(</span><span class="nam">expected</span><span class="op">,</span> <span class="nam">actual</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t78" href="#t78">78</a></span><span class="t">            <span class="nam">assert_score_is_greater</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t79" href="#t79">79</a></span><span class="t">                <span class="nam">tree</span><span class="op">.</span><span class="nam">predict</span><span class="op">(</span><span class="nam">example_set</span><span class="op">.</span><span class="nam">values</span><span class="op">)</span><span class="op">,</span> <span class="nam">example_set</span><span class="op">.</span><span class="nam">labels</span><span class="op">,</span> <span class="num">0.7</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t80" href="#t80">80</a></span><span class="t">            <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t81" href="#t81">81</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t82" href="#t82">82</a></span><span class="t">    <span class="key">def</span> <span class="nam">test_fit_and_predict_on_boolean_columns</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t83" href="#t83">83</a></span><span class="t">        <span class="nam">test_case</span> <span class="op">=</span> <span class="nam">get_test_cases</span><span class="op">(</span><span class="str">"RegressionSnCTest"</span><span class="op">)</span><span class="op">[</span><span class="num">0</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t84" href="#t84">84</a></span><span class="t">        <span class="nam">params</span> <span class="op">=</span> <span class="nam">test_case</span><span class="op">.</span><span class="nam">induction_params</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t85" href="#t85">85</a></span><span class="t">        <span class="nam">clf</span> <span class="op">=</span> <span class="nam">regression</span><span class="op">.</span><span class="nam">RuleRegressor</span><span class="op">(</span><span class="op">**</span><span class="nam">params</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t86" href="#t86">86</a></span><span class="t">        <span class="nam">X</span><span class="op">,</span> <span class="nam">y</span> <span class="op">=</span> <span class="nam">test_case</span><span class="op">.</span><span class="nam">example_set</span><span class="op">.</span><span class="nam">values</span><span class="op">,</span> <span class="nam">test_case</span><span class="op">.</span><span class="nam">example_set</span><span class="op">.</span><span class="nam">labels</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t87" href="#t87">87</a></span><span class="t">        <span class="nam">X</span><span class="op">[</span><span class="str">"boolean_column"</span><span class="op">]</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">random</span><span class="op">.</span><span class="nam">randint</span><span class="op">(</span><span class="nam">low</span><span class="op">=</span><span class="num">0</span><span class="op">,</span> <span class="nam">high</span><span class="op">=</span><span class="num">2</span><span class="op">,</span> <span class="nam">size</span><span class="op">=</span><span class="nam">X</span><span class="op">.</span><span class="nam">shape</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="op">)</span><span class="op">.</span><span class="nam">astype</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t88" href="#t88">88</a></span><span class="t">            <span class="nam">bool</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t89" href="#t89">89</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t90" href="#t90">90</a></span><span class="t">        <span class="nam">clf</span><span class="op">.</span><span class="nam">fit</span><span class="op">(</span><span class="nam">X</span><span class="op">,</span> <span class="nam">y</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t91" href="#t91">91</a></span><span class="t">        <span class="nam">clf</span><span class="op">.</span><span class="nam">predict</span><span class="op">(</span><span class="nam">X</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t92" href="#t92">92</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t93" href="#t93">93</a></span><span class="t">        <span class="nam">y</span> <span class="op">=</span> <span class="nam">pd</span><span class="op">.</span><span class="nam">Series</span><span class="op">(</span><span class="nam">y</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t94" href="#t94">94</a></span><span class="t">        <span class="nam">clf</span><span class="op">.</span><span class="nam">fit</span><span class="op">(</span><span class="nam">X</span><span class="op">,</span> <span class="nam">y</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t95" href="#t95">95</a></span><span class="t">        <span class="nam">clf</span><span class="op">.</span><span class="nam">predict</span><span class="op">(</span><span class="nam">X</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t96" href="#t96">96</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t97" href="#t97">97</a></span><span class="t">    <span class="key">def</span> <span class="nam">test_cholesterol</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t98" href="#t98">98</a></span><span class="t">        <span class="nam">resources_dir</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="nam">os</span><span class="op">.</span><span class="nam">path</span><span class="op">.</span><span class="nam">join</span><span class="op">(</span><span class="nam">dir_path</span><span class="op">,</span> <span class="str">"additional_resources"</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t99" href="#t99">99</a></span><span class="t">        <span class="nam">df</span><span class="op">:</span> <span class="nam">pd</span><span class="op">.</span><span class="nam">DataFrame</span> <span class="op">=</span> <span class="nam">read_arff</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t100" href="#t100">100</a></span><span class="t">            <span class="nam">os</span><span class="op">.</span><span class="nam">path</span><span class="op">.</span><span class="nam">join</span><span class="op">(</span><span class="nam">resources_dir</span><span class="op">,</span> <span class="str">"cholesterol.arff"</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t101" href="#t101">101</a></span><span class="t">        <span class="nam">X</span><span class="op">,</span> <span class="nam">y</span> <span class="op">=</span> <span class="nam">df</span><span class="op">.</span><span class="nam">drop</span><span class="op">(</span><span class="str">"class"</span><span class="op">,</span> <span class="nam">axis</span><span class="op">=</span><span class="num">1</span><span class="op">)</span><span class="op">,</span> <span class="nam">df</span><span class="op">[</span><span class="str">"class"</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t102" href="#t102">102</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t103" href="#t103">103</a></span><span class="t">        <span class="com"># Run experiment using python API</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t104" href="#t104">104</a></span><span class="t">        <span class="nam">reg</span> <span class="op">=</span> <span class="nam">regression</span><span class="op">.</span><span class="nam">RuleRegressor</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t105" href="#t105">105</a></span><span class="t">            <span class="nam">minsupp_new</span><span class="op">=</span><span class="num">0.05</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t106" href="#t106">106</a></span><span class="t">            <span class="nam">max_uncovered_fraction</span><span class="op">=</span><span class="num">0.0</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t107" href="#t107">107</a></span><span class="t">            <span class="nam">max_growing</span><span class="op">=</span><span class="num">0.0</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t108" href="#t108">108</a></span><span class="t">            <span class="nam">induction_measure</span><span class="op">=</span><span class="nam">Measures</span><span class="op">.</span><span class="nam">Accuracy</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t109" href="#t109">109</a></span><span class="t">            <span class="nam">pruning_measure</span><span class="op">=</span><span class="nam">Measures</span><span class="op">.</span><span class="nam">Accuracy</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t110" href="#t110">110</a></span><span class="t">            <span class="nam">voting_measure</span><span class="op">=</span><span class="nam">Measures</span><span class="op">.</span><span class="nam">Accuracy</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t111" href="#t111">111</a></span><span class="t">            <span class="nam">ignore_missing</span><span class="op">=</span><span class="key">False</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t112" href="#t112">112</a></span><span class="t">            <span class="nam">select_best_candidate</span><span class="op">=</span><span class="key">False</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t113" href="#t113">113</a></span><span class="t">            <span class="nam">complementary_conditions</span><span class="op">=</span><span class="key">True</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t114" href="#t114">114</a></span><span class="t">            <span class="nam">max_rule_count</span><span class="op">=</span><span class="num">0</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t115" href="#t115">115</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t116" href="#t116">116</a></span><span class="t">        <span class="nam">reg</span><span class="op">.</span><span class="nam">fit</span><span class="op">(</span><span class="nam">X</span><span class="op">,</span> <span class="nam">y</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t117" href="#t117">117</a></span><span class="t">        <span class="nam">actual_rules</span><span class="op">:</span> <span class="nam">list</span><span class="op">[</span><span class="nam">str</span><span class="op">]</span> <span class="op">=</span> <span class="nam">list</span><span class="op">(</span><span class="nam">map</span><span class="op">(</span><span class="nam">str</span><span class="op">,</span> <span class="nam">reg</span><span class="op">.</span><span class="nam">model</span><span class="op">.</span><span class="nam">rules</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t118" href="#t118">118</a></span><span class="t">        <span class="nam">expected_rules</span><span class="op">:</span> <span class="nam">list</span><span class="op">[</span><span class="nam">str</span><span class="op">]</span> <span class="op">=</span> <span class="op">[</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t119" href="#t119">119</a></span><span class="t">            <span class="str">"IF trestbps = (-inf, 149) THEN class = {244.84} [192.73,296.96]"</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t120" href="#t120">120</a></span><span class="t">            <span class="str">"IF trestbps = &lt;122, inf) THEN class = {250.80} [201.79,299.80]"</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t121" href="#t121">121</a></span><span class="t">        <span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t122" href="#t122">122</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">assertEqual</span><span class="op">(</span><span class="nam">actual_rules</span><span class="op">,</span> <span class="nam">expected_rules</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t123" href="#t123">123</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t124" href="#t124">124</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t125" href="#t125">125</a></span><span class="t">    <span class="op">@</span><span class="nam">classmethod</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t126" href="#t126">126</a></span><span class="t">    <span class="key">def</span> <span class="nam">setUpClass</span><span class="op">(</span><span class="nam">cls</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t127" href="#t127">127</a></span><span class="t">        <span class="nam">RuleKit</span><span class="op">.</span><span class="nam">init</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t128" href="#t128">128</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t129" href="#t129">129</a></span><span class="t">    <span class="key">def</span> <span class="nam">test_compare_with_java_results</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t130" href="#t130">130</a></span><span class="t">        <span class="nam">test_cases</span> <span class="op">=</span> <span class="nam">get_test_cases</span><span class="op">(</span><span class="str">'RegressionExpertSnCTest'</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t131" href="#t131">131</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t132" href="#t132">132</a></span><span class="t">        <span class="key">for</span> <span class="nam">test_case</span> <span class="key">in</span> <span class="nam">test_cases</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t133" href="#t133">133</a></span><span class="t">            <span class="nam">params</span> <span class="op">=</span> <span class="nam">test_case</span><span class="op">.</span><span class="nam">induction_params</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t134" href="#t134">134</a></span><span class="t">            <span class="nam">tree</span> <span class="op">=</span> <span class="nam">regression</span><span class="op">.</span><span class="nam">ExpertRuleRegressor</span><span class="op">(</span><span class="op">**</span><span class="nam">params</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t135" href="#t135">135</a></span><span class="t">            <span class="nam">example_set</span> <span class="op">=</span> <span class="nam">test_case</span><span class="op">.</span><span class="nam">example_set</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t136" href="#t136">136</a></span><span class="t">            <span class="nam">tree</span><span class="op">.</span><span class="nam">fit</span><span class="op">(</span><span class="nam">example_set</span><span class="op">.</span><span class="nam">values</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t137" href="#t137">137</a></span><span class="t">                     <span class="nam">example_set</span><span class="op">.</span><span class="nam">labels</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t138" href="#t138">138</a></span><span class="t">                     <span class="nam">expert_rules</span><span class="op">=</span><span class="nam">test_case</span><span class="op">.</span><span class="nam">knowledge</span><span class="op">.</span><span class="nam">expert_rules</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t139" href="#t139">139</a></span><span class="t">                     <span class="nam">expert_preferred_conditions</span><span class="op">=</span><span class="nam">test_case</span><span class="op">.</span><span class="nam">knowledge</span><span class="op">.</span><span class="nam">expert_preferred_conditions</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t140" href="#t140">140</a></span><span class="t">                     <span class="nam">expert_forbidden_conditions</span><span class="op">=</span><span class="nam">test_case</span><span class="op">.</span><span class="nam">knowledge</span><span class="op">.</span><span class="nam">expert_forbidden_conditions</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t141" href="#t141">141</a></span><span class="t">            <span class="nam">model</span> <span class="op">=</span> <span class="nam">tree</span><span class="op">.</span><span class="nam">model</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t142" href="#t142">142</a></span><span class="t">            <span class="nam">expected</span> <span class="op">=</span> <span class="nam">test_case</span><span class="op">.</span><span class="nam">reference_report</span><span class="op">.</span><span class="nam">rules</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t143" href="#t143">143</a></span><span class="t">            <span class="nam">actual</span> <span class="op">=</span> <span class="op">[</span><span class="nam">str</span><span class="op">(</span><span class="nam">r</span><span class="op">)</span> <span class="key">for</span> <span class="nam">r</span> <span class="key">in</span> <span class="nam">model</span><span class="op">.</span><span class="nam">rules</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t144" href="#t144">144</a></span><span class="t">            <span class="nam">assert_rules_are_equals</span><span class="op">(</span><span class="nam">expected</span><span class="op">,</span> <span class="nam">actual</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t145" href="#t145">145</a></span><span class="t">            <span class="nam">assert_score_is_greater</span><span class="op">(</span><span class="nam">tree</span><span class="op">.</span><span class="nam">predict</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t146" href="#t146">146</a></span><span class="t">                <span class="nam">example_set</span><span class="op">.</span><span class="nam">values</span><span class="op">)</span><span class="op">,</span> <span class="nam">example_set</span><span class="op">.</span><span class="nam">labels</span><span class="op">,</span> <span class="num">0.66</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t147" href="#t147">147</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t148" href="#t148">148</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t149" href="#t149">149</a></span><span class="t"><span class="key">if</span> <span class="nam">__name__</span> <span class="op">==</span> <span class="str">'__main__'</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t150" href="#t150">150</a></span><span class="t">    <span class="nam">unittest</span><span class="op">.</span><span class="nam">main</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t125" href="#t125">125</a></span><span class="t"><span class="key">class</span> <span class="nam">TestExpertRegressor</span><span class="op">(</span><span class="nam">unittest</span><span class="op">.</span><span class="nam">TestCase</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t126" href="#t126">126</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t127" href="#t127">127</a></span><span class="t">    <span class="op">@</span><span class="nam">classmethod</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t128" href="#t128">128</a></span><span class="t">    <span class="key">def</span> <span class="nam">setUpClass</span><span class="op">(</span><span class="nam">cls</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t129" href="#t129">129</a></span><span class="t">        <span class="nam">RuleKit</span><span class="op">.</span><span class="nam">init</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t130" href="#t130">130</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t131" href="#t131">131</a></span><span class="t">    <span class="key">def</span> <span class="nam">test_compare_with_java_results</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t132" href="#t132">132</a></span><span class="t">        <span class="nam">test_cases</span> <span class="op">=</span> <span class="nam">get_test_cases</span><span class="op">(</span><span class="str">"RegressionExpertSnCTest"</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t133" href="#t133">133</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t134" href="#t134">134</a></span><span class="t">        <span class="key">for</span> <span class="nam">test_case</span> <span class="key">in</span> <span class="nam">test_cases</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t135" href="#t135">135</a></span><span class="t">            <span class="nam">params</span> <span class="op">=</span> <span class="nam">test_case</span><span class="op">.</span><span class="nam">induction_params</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t136" href="#t136">136</a></span><span class="t">            <span class="nam">tree</span> <span class="op">=</span> <span class="nam">regression</span><span class="op">.</span><span class="nam">ExpertRuleRegressor</span><span class="op">(</span><span class="op">**</span><span class="nam">params</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t137" href="#t137">137</a></span><span class="t">            <span class="nam">example_set</span> <span class="op">=</span> <span class="nam">test_case</span><span class="op">.</span><span class="nam">example_set</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t138" href="#t138">138</a></span><span class="t">            <span class="nam">tree</span><span class="op">.</span><span class="nam">fit</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t139" href="#t139">139</a></span><span class="t">                <span class="nam">example_set</span><span class="op">.</span><span class="nam">values</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t140" href="#t140">140</a></span><span class="t">                <span class="nam">example_set</span><span class="op">.</span><span class="nam">labels</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t141" href="#t141">141</a></span><span class="t">                <span class="nam">expert_rules</span><span class="op">=</span><span class="nam">test_case</span><span class="op">.</span><span class="nam">knowledge</span><span class="op">.</span><span class="nam">expert_rules</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t142" href="#t142">142</a></span><span class="t">                <span class="nam">expert_preferred_conditions</span><span class="op">=</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t143" href="#t143">143</a></span><span class="t">                    <span class="nam">test_case</span><span class="op">.</span><span class="nam">knowledge</span><span class="op">.</span><span class="nam">expert_preferred_conditions</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t144" href="#t144">144</a></span><span class="t">                <span class="op">)</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t145" href="#t145">145</a></span><span class="t">                <span class="nam">expert_forbidden_conditions</span><span class="op">=</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t146" href="#t146">146</a></span><span class="t">                    <span class="nam">test_case</span><span class="op">.</span><span class="nam">knowledge</span><span class="op">.</span><span class="nam">expert_forbidden_conditions</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t147" href="#t147">147</a></span><span class="t">                <span class="op">)</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t148" href="#t148">148</a></span><span class="t">            <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t149" href="#t149">149</a></span><span class="t">            <span class="nam">model</span> <span class="op">=</span> <span class="nam">tree</span><span class="op">.</span><span class="nam">model</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t150" href="#t150">150</a></span><span class="t">            <span class="nam">expected</span> <span class="op">=</span> <span class="nam">test_case</span><span class="op">.</span><span class="nam">reference_report</span><span class="op">.</span><span class="nam">rules</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t151" href="#t151">151</a></span><span class="t">            <span class="nam">actual</span> <span class="op">=</span> <span class="op">[</span><span class="nam">str</span><span class="op">(</span><span class="nam">r</span><span class="op">)</span> <span class="key">for</span> <span class="nam">r</span> <span class="key">in</span> <span class="nam">model</span><span class="op">.</span><span class="nam">rules</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t152" href="#t152">152</a></span><span class="t">            <span class="nam">assert_rules_are_equals</span><span class="op">(</span><span class="nam">expected</span><span class="op">,</span> <span class="nam">actual</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t153" href="#t153">153</a></span><span class="t">            <span class="nam">assert_score_is_greater</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t154" href="#t154">154</a></span><span class="t">                <span class="nam">tree</span><span class="op">.</span><span class="nam">predict</span><span class="op">(</span><span class="nam">example_set</span><span class="op">.</span><span class="nam">values</span><span class="op">)</span><span class="op">,</span> <span class="nam">example_set</span><span class="op">.</span><span class="nam">labels</span><span class="op">,</span> <span class="num">0.66</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t155" href="#t155">155</a></span><span class="t">            <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t156" href="#t156">156</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t157" href="#t157">157</a></span><span class="t">    <span class="key">def</span> <span class="nam">test_legacy_expert_rules_format</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t158" href="#t158">158</a></span><span class="t">        <span class="str">"""Test if the legacy expert rules format is still supported.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t159" href="#t159">159</a></span><span class="t"><span class="str">        In legacy format rules strings contains conclusion in the form</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t160" href="#t160">160</a></span><span class="t"><span class="str">        of "label_attr = {NaN}". In new format conclusion part should be empty</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t161" href="#t161">161</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t162" href="#t162">162</a></span><span class="t">        <span class="nam">df</span><span class="op">:</span> <span class="nam">pd</span><span class="op">.</span><span class="nam">DataFrame</span> <span class="op">=</span> <span class="nam">read_arff</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t163" href="#t163">163</a></span><span class="t">            <span class="nam">os</span><span class="op">.</span><span class="nam">path</span><span class="op">.</span><span class="nam">join</span><span class="op">(</span><span class="nam">dir_path</span><span class="op">,</span> <span class="str">"additional_resources"</span><span class="op">,</span> <span class="str">"cholesterol.arff"</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t164" href="#t164">164</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t165" href="#t165">165</a></span><span class="t">        <span class="nam">X</span><span class="op">,</span> <span class="nam">y</span> <span class="op">=</span> <span class="nam">df</span><span class="op">.</span><span class="nam">drop</span><span class="op">(</span><span class="str">"class"</span><span class="op">,</span> <span class="nam">axis</span><span class="op">=</span><span class="num">1</span><span class="op">)</span><span class="op">,</span> <span class="nam">df</span><span class="op">[</span><span class="str">"class"</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t166" href="#t166">166</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t167" href="#t167">167</a></span><span class="t">        <span class="com"># Run experiment using python API</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t168" href="#t168">168</a></span><span class="t">        <span class="nam">reg</span> <span class="op">=</span> <span class="nam">regression</span><span class="op">.</span><span class="nam">ExpertRuleRegressor</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t169" href="#t169">169</a></span><span class="t">            <span class="nam">mean_based_regression</span><span class="op">=</span><span class="key">True</span><span class="op">,</span> <span class="nam">extend_using_automatic</span><span class="op">=</span><span class="key">True</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t170" href="#t170">170</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t171" href="#t171">171</a></span><span class="t">        <span class="nam">expert_rule</span> <span class="op">=</span> <span class="str">"IF trestbps &lt; 149 THEN class = {NaN}"</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t172" href="#t172">172</a></span><span class="t">        <span class="nam">legacy_ruleset</span><span class="op">:</span> <span class="nam">RuleSet</span><span class="op">[</span><span class="nam">RegressionRule</span><span class="op">]</span> <span class="op">=</span> <span class="nam">reg</span><span class="op">.</span><span class="nam">fit</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t173" href="#t173">173</a></span><span class="t">            <span class="nam">X</span><span class="op">,</span> <span class="nam">y</span><span class="op">,</span> <span class="nam">expert_rules</span><span class="op">=</span><span class="op">[</span><span class="op">(</span><span class="str">"0"</span><span class="op">,</span> <span class="nam">expert_rule</span><span class="op">)</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t174" href="#t174">174</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t175" href="#t175">175</a></span><span class="t">        <span class="nam">new_format_ruleset</span><span class="op">:</span> <span class="nam">RuleSet</span><span class="op">[</span><span class="nam">RegressionRule</span><span class="op">]</span> <span class="op">=</span> <span class="nam">reg</span><span class="op">.</span><span class="nam">fit</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t176" href="#t176">176</a></span><span class="t">            <span class="nam">X</span><span class="op">,</span> <span class="nam">y</span><span class="op">,</span> <span class="nam">expert_rules</span><span class="op">=</span><span class="op">[</span><span class="op">(</span><span class="str">"rule-0"</span><span class="op">,</span> <span class="nam">expert_rule</span><span class="op">.</span><span class="nam">split</span><span class="op">(</span><span class="str">"class"</span><span class="op">)</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="op">)</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t177" href="#t177">177</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t178" href="#t178">178</a></span><span class="t">        <span class="nam">legacy_rules</span><span class="op">:</span> <span class="nam">list</span><span class="op">[</span><span class="nam">str</span><span class="op">]</span> <span class="op">=</span> <span class="nam">list</span><span class="op">(</span><span class="nam">map</span><span class="op">(</span><span class="nam">str</span><span class="op">,</span> <span class="nam">legacy_ruleset</span><span class="op">.</span><span class="nam">rules</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t179" href="#t179">179</a></span><span class="t">        <span class="nam">new_format_rules</span><span class="op">:</span> <span class="nam">list</span><span class="op">[</span><span class="nam">str</span><span class="op">]</span> <span class="op">=</span> <span class="nam">list</span><span class="op">(</span><span class="nam">map</span><span class="op">(</span><span class="nam">str</span><span class="op">,</span> <span class="nam">new_format_ruleset</span><span class="op">.</span><span class="nam">rules</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t180" href="#t180">180</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">assertEqual</span><span class="op">(</span><span class="nam">legacy_rules</span><span class="op">,</span> <span class="nam">new_format_rules</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t181" href="#t181">181</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t182" href="#t182">182</a></span><span class="t">    <span class="key">def</span> <span class="nam">test_refining_conditions_for_nominal_attributes</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t183" href="#t183">183</a></span><span class="t">        <span class="nam">df</span><span class="op">:</span> <span class="nam">pd</span><span class="op">.</span><span class="nam">DataFrame</span> <span class="op">=</span> <span class="nam">read_arff</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t184" href="#t184">184</a></span><span class="t">            <span class="nam">os</span><span class="op">.</span><span class="nam">path</span><span class="op">.</span><span class="nam">join</span><span class="op">(</span><span class="nam">dir_path</span><span class="op">,</span> <span class="str">"additional_resources"</span><span class="op">,</span> <span class="str">"cholesterol.arff"</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t185" href="#t185">185</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t186" href="#t186">186</a></span><span class="t">        <span class="nam">X</span><span class="op">,</span> <span class="nam">y</span> <span class="op">=</span> <span class="nam">df</span><span class="op">.</span><span class="nam">drop</span><span class="op">(</span><span class="str">"class"</span><span class="op">,</span> <span class="nam">axis</span><span class="op">=</span><span class="num">1</span><span class="op">)</span><span class="op">,</span> <span class="nam">df</span><span class="op">[</span><span class="str">"class"</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t187" href="#t187">187</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t188" href="#t188">188</a></span><span class="t">        <span class="com"># Run experiment using python API</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t189" href="#t189">189</a></span><span class="t">        <span class="nam">clf</span> <span class="op">=</span> <span class="nam">regression</span><span class="op">.</span><span class="nam">ExpertRuleRegressor</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t190" href="#t190">190</a></span><span class="t">            <span class="nam">induction_measure</span><span class="op">=</span><span class="nam">Measures</span><span class="op">.</span><span class="nam">C2</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t191" href="#t191">191</a></span><span class="t">            <span class="nam">pruning_measure</span><span class="op">=</span><span class="nam">Measures</span><span class="op">.</span><span class="nam">C2</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t192" href="#t192">192</a></span><span class="t">            <span class="nam">voting_measure</span><span class="op">=</span><span class="nam">Measures</span><span class="op">.</span><span class="nam">C2</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t193" href="#t193">193</a></span><span class="t">            <span class="nam">complementary_conditions</span><span class="op">=</span><span class="key">True</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t194" href="#t194">194</a></span><span class="t">            <span class="nam">extend_using_preferred</span><span class="op">=</span><span class="key">False</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t195" href="#t195">195</a></span><span class="t">            <span class="nam">extend_using_automatic</span><span class="op">=</span><span class="key">False</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t196" href="#t196">196</a></span><span class="t">            <span class="nam">induce_using_preferred</span><span class="op">=</span><span class="key">False</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t197" href="#t197">197</a></span><span class="t">            <span class="nam">induce_using_automatic</span><span class="op">=</span><span class="key">False</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t198" href="#t198">198</a></span><span class="t">            <span class="nam">preferred_conditions_per_rule</span><span class="op">=</span><span class="num">0</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t199" href="#t199">199</a></span><span class="t">            <span class="nam">preferred_attributes_per_rule</span><span class="op">=</span><span class="num">0</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t200" href="#t200">200</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t201" href="#t201">201</a></span><span class="t">        <span class="nam">clf</span><span class="op">.</span><span class="nam">fit</span><span class="op">(</span><span class="nam">X</span><span class="op">,</span> <span class="nam">y</span><span class="op">,</span> <span class="nam">expert_rules</span><span class="op">=</span><span class="op">[</span><span class="op">(</span><span class="str">"expert_rules-1"</span><span class="op">,</span> <span class="str">"IF sex @= {1} THEN"</span><span class="op">)</span><span class="op">]</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t202" href="#t202">202</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">assertEqual</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t203" href="#t203">203</a></span><span class="t">            <span class="op">[</span><span class="str">"IF [[sex = {1}]] THEN class = {239.60} [197.06,282.15]"</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t204" href="#t204">204</a></span><span class="t">            <span class="op">[</span><span class="nam">str</span><span class="op">(</span><span class="nam">r</span><span class="op">)</span> <span class="key">for</span> <span class="nam">r</span> <span class="key">in</span> <span class="nam">clf</span><span class="op">.</span><span class="nam">model</span><span class="op">.</span><span class="nam">rules</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t205" href="#t205">205</a></span><span class="t">            <span class="str">"Ruleset should contain only a single rule configured by expert"</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t206" href="#t206">206</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t207" href="#t207">207</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t208" href="#t208">208</a></span><span class="t">        <span class="nam">clf</span><span class="op">.</span><span class="nam">fit</span><span class="op">(</span><span class="nam">X</span><span class="op">,</span> <span class="nam">y</span><span class="op">,</span> <span class="nam">expert_rules</span><span class="op">=</span><span class="op">[</span><span class="op">(</span><span class="str">"expert_rules-1"</span><span class="op">,</span> <span class="str">"IF sex @= Any THEN"</span><span class="op">)</span><span class="op">]</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t209" href="#t209">209</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">assertEqual</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t210" href="#t210">210</a></span><span class="t">            <span class="op">[</span><span class="str">"IF [[sex = {1}]] THEN class = {239.60} [197.06,282.15]"</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t211" href="#t211">211</a></span><span class="t">            <span class="op">[</span><span class="nam">str</span><span class="op">(</span><span class="nam">r</span><span class="op">)</span> <span class="key">for</span> <span class="nam">r</span> <span class="key">in</span> <span class="nam">clf</span><span class="op">.</span><span class="nam">model</span><span class="op">.</span><span class="nam">rules</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t212" href="#t212">212</a></span><span class="t">            <span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t213" href="#t213">213</a></span><span class="t">                <span class="str">"Ruleset should contain only a single rule configured by expert with "</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t214" href="#t214">214</a></span><span class="t">                <span class="str">"a refined condition"</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t215" href="#t215">215</a></span><span class="t">            <span class="op">)</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t216" href="#t216">216</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t217" href="#t217">217</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t218" href="#t218">218</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t219" href="#t219">219</a></span><span class="t"><span class="key">if</span> <span class="nam">__name__</span> <span class="op">==</span> <span class="str">"__main__"</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t220" href="#t220">220</a></span><span class="t">    <span class="nam">unittest</span><span class="op">.</span><span class="nam">main</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
 </main>
 <footer>
     <div class="content">
@@ -239,7 +309,7 @@ <h2>
             <a class="nav" href="z_a44f0ac069e85531_test_rulekit_py.html">&#xbb; next</a>
             &nbsp; &nbsp; &nbsp;
             <a class="nav" href="https://coverage.readthedocs.io/en/7.6.4">coverage.py v7.6.4</a>,
-            created at 2024-11-08 14:43 +0100
+            created at 2024-11-28 11:55 +0100
         </p>
     </div>
 </footer>
diff --git a/docs/reports/coverage/z_a44f0ac069e85531_test_survival_py.html b/docs/reports/coverage/z_a44f0ac069e85531_test_survival_py.html
index 64a315c..f980afe 100644
--- a/docs/reports/coverage/z_a44f0ac069e85531_test_survival_py.html
+++ b/docs/reports/coverage/z_a44f0ac069e85531_test_survival_py.html
@@ -54,8 +54,8 @@ <h1>
             </div>
         </aside>
         <h2>
-            <span class="text">87 statements &nbsp;</span>
-            <button type="button" class="run button_toggle_run" value="run" data-shortcut="r" title="Toggle lines run">86<span class="text"> run</span></button>
+            <span class="text">130 statements &nbsp;</span>
+            <button type="button" class="run button_toggle_run" value="run" data-shortcut="r" title="Toggle lines run">129<span class="text"> run</span></button>
             <button type="button" class="mis show_mis button_toggle_mis" value="mis" data-shortcut="m" title="Toggle lines missing">1<span class="text"> missing</span></button>
             <button type="button" class="exc show_exc button_toggle_exc" value="exc" data-shortcut="x" title="Toggle lines excluded">0<span class="text"> excluded</span></button>
         </h2>
@@ -65,7 +65,7 @@ <h2>
             <a id="nextFileLink" class="nav" href="z_a44f0ac069e85531_utils_py.html">&#xbb; next</a>
             &nbsp; &nbsp; &nbsp;
             <a class="nav" href="https://coverage.readthedocs.io/en/7.6.4">coverage.py v7.6.4</a>,
-            created at 2024-11-08 14:43 +0100
+            created at 2024-11-28 12:23 +0100
         </p>
         <aside class="hidden">
             <button type="button" class="button_next_chunk" data-shortcut="j"></button>
@@ -80,156 +80,260 @@ <h2>
     </div>
 </header>
 <main id="source">
-    <p class="run"><span class="n"><a id="t1" href="#t1">1</a></span><span class="t"><span class="key">import</span> <span class="nam">threading</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t2" href="#t2">2</a></span><span class="t"><span class="key">import</span> <span class="nam">unittest</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t3" href="#t3">3</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t4" href="#t4">4</a></span><span class="t"><span class="key">import</span> <span class="nam">numpy</span> <span class="key">as</span> <span class="nam">np</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t5" href="#t5">5</a></span><span class="t"><span class="key">import</span> <span class="nam">pandas</span> <span class="key">as</span> <span class="nam">pd</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t6" href="#t6">6</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t7" href="#t7">7</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span> <span class="key">import</span> <span class="nam">survival</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t8" href="#t8">8</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">events</span> <span class="key">import</span> <span class="nam">RuleInductionProgressListener</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t9" href="#t9">9</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">kaplan_meier</span> <span class="key">import</span> <span class="nam">KaplanMeierEstimator</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t10" href="#t10">10</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">main</span> <span class="key">import</span> <span class="nam">RuleKit</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t11" href="#t11">11</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">rules</span> <span class="key">import</span> <span class="nam">SurvivalRule</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t12" href="#t12">12</a></span><span class="t"><span class="key">from</span> <span class="nam">tests</span><span class="op">.</span><span class="nam">utils</span> <span class="key">import</span> <span class="nam">assert_rules_are_equals</span><span class="op">,</span> <span class="nam">get_test_cases</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t13" href="#t13">13</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t14" href="#t14">14</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t15" href="#t15">15</a></span><span class="t"><span class="key">class</span> <span class="nam">TestKaplanMeierEstimator</span><span class="op">(</span><span class="nam">unittest</span><span class="op">.</span><span class="nam">TestCase</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t1" href="#t1">1</a></span><span class="t"><span class="key">import</span> <span class="nam">os</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t2" href="#t2">2</a></span><span class="t"><span class="key">import</span> <span class="nam">threading</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t3" href="#t3">3</a></span><span class="t"><span class="key">import</span> <span class="nam">unittest</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t4" href="#t4">4</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t5" href="#t5">5</a></span><span class="t"><span class="key">import</span> <span class="nam">numpy</span> <span class="key">as</span> <span class="nam">np</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t6" href="#t6">6</a></span><span class="t"><span class="key">import</span> <span class="nam">pandas</span> <span class="key">as</span> <span class="nam">pd</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t7" href="#t7">7</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t8" href="#t8">8</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span> <span class="key">import</span> <span class="nam">survival</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t9" href="#t9">9</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">arff</span> <span class="key">import</span> <span class="nam">read_arff</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t10" href="#t10">10</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">events</span> <span class="key">import</span> <span class="nam">RuleInductionProgressListener</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t11" href="#t11">11</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">kaplan_meier</span> <span class="key">import</span> <span class="nam">KaplanMeierEstimator</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t12" href="#t12">12</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">main</span> <span class="key">import</span> <span class="nam">RuleKit</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t13" href="#t13">13</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">rules</span> <span class="key">import</span> <span class="nam">SurvivalRule</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t14" href="#t14">14</a></span><span class="t"><span class="key">from</span> <span class="nam">tests</span><span class="op">.</span><span class="nam">utils</span> <span class="key">import</span> <span class="nam">assert_rules_are_equals</span><span class="op">,</span> <span class="nam">dir_path</span><span class="op">,</span> <span class="nam">get_test_cases</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t15" href="#t15">15</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t16" href="#t16">16</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t17" href="#t17">17</a></span><span class="t">    <span class="nam">survival_rules</span><span class="op">:</span> <span class="nam">survival</span><span class="op">.</span><span class="nam">SurvivalRules</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t17" href="#t17">17</a></span><span class="t"><span class="key">class</span> <span class="nam">TestKaplanMeierEstimator</span><span class="op">(</span><span class="nam">unittest</span><span class="op">.</span><span class="nam">TestCase</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t18" href="#t18">18</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t19" href="#t19">19</a></span><span class="t">    <span class="key">def</span> <span class="nam">setUp</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t20" href="#t20">20</a></span><span class="t">        <span class="nam">test_case</span> <span class="op">=</span> <span class="nam">get_test_cases</span><span class="op">(</span><span class="str">'SurvivalLogRankSnCTest'</span><span class="op">)</span><span class="op">[</span><span class="num">0</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t21" href="#t21">21</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t22" href="#t22">22</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">survival_rules</span> <span class="op">=</span> <span class="nam">survival</span><span class="op">.</span><span class="nam">SurvivalRules</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t23" href="#t23">23</a></span><span class="t">            <span class="nam">survival_time_attr</span><span class="op">=</span><span class="nam">test_case</span><span class="op">.</span><span class="nam">survival_time</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t24" href="#t24">24</a></span><span class="t">        <span class="nam">example_set</span> <span class="op">=</span> <span class="nam">test_case</span><span class="op">.</span><span class="nam">example_set</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t25" href="#t25">25</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">survival_rules</span><span class="op">.</span><span class="nam">fit</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t26" href="#t26">26</a></span><span class="t">            <span class="nam">example_set</span><span class="op">.</span><span class="nam">values</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t27" href="#t27">27</a></span><span class="t">            <span class="nam">example_set</span><span class="op">.</span><span class="nam">labels</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t28" href="#t28">28</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t29" href="#t29">29</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">km</span><span class="op">:</span> <span class="nam">KaplanMeierEstimator</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">survival_rules</span><span class="op">.</span><span class="nam">model</span><span class="op">.</span><span class="nam">rules</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="op">.</span><span class="nam">kaplan_meier_estimator</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t30" href="#t30">30</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t31" href="#t31">31</a></span><span class="t">    <span class="key">def</span> <span class="nam">test_accessing_probabilities</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t32" href="#t32">32</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">assertTrue</span><span class="op">(</span><span class="nam">all</span><span class="op">(</span><span class="op">[</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t33" href="#t33">33</a></span><span class="t">            <span class="nam">p</span> <span class="op">>=</span> <span class="num">0.0</span> <span class="key">and</span> <span class="nam">p</span> <span class="op">&lt;=</span> <span class="num">1.0</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t34" href="#t34">34</a></span><span class="t">            <span class="key">for</span> <span class="nam">p</span> <span class="key">in</span> <span class="nam">self</span><span class="op">.</span><span class="nam">km</span><span class="op">.</span><span class="nam">probabilities</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t35" href="#t35">35</a></span><span class="t">        <span class="op">]</span><span class="op">)</span><span class="op">,</span> <span class="str">'All probabilities should be in range [0, 1]'</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t36" href="#t36">36</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">assertTrue</span><span class="op">(</span><span class="nam">all</span><span class="op">(</span><span class="op">[</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t37" href="#t37">37</a></span><span class="t">            <span class="nam">isinstance</span><span class="op">(</span><span class="nam">p</span><span class="op">,</span> <span class="nam">float</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t38" href="#t38">38</a></span><span class="t">            <span class="key">for</span> <span class="nam">p</span> <span class="key">in</span> <span class="nam">self</span><span class="op">.</span><span class="nam">km</span><span class="op">.</span><span class="nam">probabilities</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t39" href="#t39">39</a></span><span class="t">        <span class="op">]</span><span class="op">)</span><span class="op">,</span> <span class="str">'All probabilities should be Pythonic floats'</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t40" href="#t40">40</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t41" href="#t41">41</a></span><span class="t">    <span class="key">def</span> <span class="nam">test_accessing_events_count</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t42" href="#t42">42</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">assertTrue</span><span class="op">(</span><span class="nam">all</span><span class="op">(</span><span class="op">[</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t43" href="#t43">43</a></span><span class="t">            <span class="nam">isinstance</span><span class="op">(</span><span class="nam">p</span><span class="op">,</span> <span class="nam">np</span><span class="op">.</span><span class="nam">int_</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t44" href="#t44">44</a></span><span class="t">            <span class="key">for</span> <span class="nam">p</span> <span class="key">in</span> <span class="nam">self</span><span class="op">.</span><span class="nam">km</span><span class="op">.</span><span class="nam">events_count</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t45" href="#t45">45</a></span><span class="t">        <span class="op">]</span><span class="op">)</span><span class="op">,</span> <span class="str">'All event counts should be Pythonic integers'</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t46" href="#t46">46</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t47" href="#t47">47</a></span><span class="t">    <span class="key">def</span> <span class="nam">test_accessing_at_risk_count</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t48" href="#t48">48</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">assertTrue</span><span class="op">(</span><span class="nam">all</span><span class="op">(</span><span class="op">[</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t49" href="#t49">49</a></span><span class="t">            <span class="nam">isinstance</span><span class="op">(</span><span class="nam">p</span><span class="op">,</span> <span class="nam">np</span><span class="op">.</span><span class="nam">int_</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t50" href="#t50">50</a></span><span class="t">            <span class="key">for</span> <span class="nam">p</span> <span class="key">in</span> <span class="nam">self</span><span class="op">.</span><span class="nam">km</span><span class="op">.</span><span class="nam">at_risk_count</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t51" href="#t51">51</a></span><span class="t">        <span class="op">]</span><span class="op">)</span><span class="op">,</span> <span class="str">'All risk count should be Pythonic integers'</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t52" href="#t52">52</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t53" href="#t53">53</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t54" href="#t54">54</a></span><span class="t"><span class="key">class</span> <span class="nam">TestSurvivalRules</span><span class="op">(</span><span class="nam">unittest</span><span class="op">.</span><span class="nam">TestCase</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t55" href="#t55">55</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t56" href="#t56">56</a></span><span class="t">    <span class="key">def</span> <span class="nam">test_induction_progress_listener</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t57" href="#t57">57</a></span><span class="t">        <span class="nam">test_case</span> <span class="op">=</span> <span class="nam">get_test_cases</span><span class="op">(</span><span class="str">'SurvivalLogRankSnCTest'</span><span class="op">)</span><span class="op">[</span><span class="num">0</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t19" href="#t19">19</a></span><span class="t">    <span class="nam">survival_rules</span><span class="op">:</span> <span class="nam">survival</span><span class="op">.</span><span class="nam">SurvivalRules</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t20" href="#t20">20</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t21" href="#t21">21</a></span><span class="t">    <span class="key">def</span> <span class="nam">setUp</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t22" href="#t22">22</a></span><span class="t">        <span class="nam">test_case</span> <span class="op">=</span> <span class="nam">get_test_cases</span><span class="op">(</span><span class="str">"SurvivalLogRankSnCTest"</span><span class="op">)</span><span class="op">[</span><span class="num">0</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t23" href="#t23">23</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t24" href="#t24">24</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">survival_rules</span> <span class="op">=</span> <span class="nam">survival</span><span class="op">.</span><span class="nam">SurvivalRules</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t25" href="#t25">25</a></span><span class="t">            <span class="nam">survival_time_attr</span><span class="op">=</span><span class="nam">test_case</span><span class="op">.</span><span class="nam">survival_time</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t26" href="#t26">26</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t27" href="#t27">27</a></span><span class="t">        <span class="nam">example_set</span> <span class="op">=</span> <span class="nam">test_case</span><span class="op">.</span><span class="nam">example_set</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t28" href="#t28">28</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">survival_rules</span><span class="op">.</span><span class="nam">fit</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t29" href="#t29">29</a></span><span class="t">            <span class="nam">example_set</span><span class="op">.</span><span class="nam">values</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t30" href="#t30">30</a></span><span class="t">            <span class="nam">example_set</span><span class="op">.</span><span class="nam">labels</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t31" href="#t31">31</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t32" href="#t32">32</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">km</span><span class="op">:</span> <span class="nam">KaplanMeierEstimator</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">survival_rules</span><span class="op">.</span><span class="nam">model</span><span class="op">.</span><span class="nam">rules</span><span class="op">[</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t33" href="#t33">33</a></span><span class="t">            <span class="num">0</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t34" href="#t34">34</a></span><span class="t">        <span class="op">]</span><span class="op">.</span><span class="nam">kaplan_meier_estimator</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t35" href="#t35">35</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t36" href="#t36">36</a></span><span class="t">    <span class="key">def</span> <span class="nam">test_accessing_probabilities</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t37" href="#t37">37</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">assertTrue</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t38" href="#t38">38</a></span><span class="t">            <span class="nam">all</span><span class="op">(</span><span class="op">[</span><span class="nam">p</span> <span class="op">>=</span> <span class="num">0.0</span> <span class="key">and</span> <span class="nam">p</span> <span class="op">&lt;=</span> <span class="num">1.0</span> <span class="key">for</span> <span class="nam">p</span> <span class="key">in</span> <span class="nam">self</span><span class="op">.</span><span class="nam">km</span><span class="op">.</span><span class="nam">probabilities</span><span class="op">]</span><span class="op">)</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t39" href="#t39">39</a></span><span class="t">            <span class="str">"All probabilities should be in range [0, 1]"</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t40" href="#t40">40</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t41" href="#t41">41</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">assertTrue</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t42" href="#t42">42</a></span><span class="t">            <span class="nam">all</span><span class="op">(</span><span class="op">[</span><span class="nam">isinstance</span><span class="op">(</span><span class="nam">p</span><span class="op">,</span> <span class="nam">float</span><span class="op">)</span> <span class="key">for</span> <span class="nam">p</span> <span class="key">in</span> <span class="nam">self</span><span class="op">.</span><span class="nam">km</span><span class="op">.</span><span class="nam">probabilities</span><span class="op">]</span><span class="op">)</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t43" href="#t43">43</a></span><span class="t">            <span class="str">"All probabilities should be Pythonic floats"</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t44" href="#t44">44</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t45" href="#t45">45</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t46" href="#t46">46</a></span><span class="t">    <span class="key">def</span> <span class="nam">test_accessing_events_count</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t47" href="#t47">47</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">assertTrue</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t48" href="#t48">48</a></span><span class="t">            <span class="nam">all</span><span class="op">(</span><span class="op">[</span><span class="nam">isinstance</span><span class="op">(</span><span class="nam">p</span><span class="op">,</span> <span class="nam">np</span><span class="op">.</span><span class="nam">int_</span><span class="op">)</span> <span class="key">for</span> <span class="nam">p</span> <span class="key">in</span> <span class="nam">self</span><span class="op">.</span><span class="nam">km</span><span class="op">.</span><span class="nam">events_count</span><span class="op">]</span><span class="op">)</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t49" href="#t49">49</a></span><span class="t">            <span class="str">"All event counts should be Pythonic integers"</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t50" href="#t50">50</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t51" href="#t51">51</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t52" href="#t52">52</a></span><span class="t">    <span class="key">def</span> <span class="nam">test_accessing_at_risk_count</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t53" href="#t53">53</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">assertTrue</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t54" href="#t54">54</a></span><span class="t">            <span class="nam">all</span><span class="op">(</span><span class="op">[</span><span class="nam">isinstance</span><span class="op">(</span><span class="nam">p</span><span class="op">,</span> <span class="nam">np</span><span class="op">.</span><span class="nam">int_</span><span class="op">)</span> <span class="key">for</span> <span class="nam">p</span> <span class="key">in</span> <span class="nam">self</span><span class="op">.</span><span class="nam">km</span><span class="op">.</span><span class="nam">at_risk_count</span><span class="op">]</span><span class="op">)</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t55" href="#t55">55</a></span><span class="t">            <span class="str">"All risk count should be Pythonic integers"</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t56" href="#t56">56</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t57" href="#t57">57</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t58" href="#t58">58</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t59" href="#t59">59</a></span><span class="t">        <span class="nam">surv</span> <span class="op">=</span> <span class="nam">survival</span><span class="op">.</span><span class="nam">SurvivalRules</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t60" href="#t60">60</a></span><span class="t">            <span class="nam">survival_time_attr</span><span class="op">=</span><span class="nam">test_case</span><span class="op">.</span><span class="nam">survival_time</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t61" href="#t61">61</a></span><span class="t">        <span class="nam">example_set</span> <span class="op">=</span> <span class="nam">test_case</span><span class="op">.</span><span class="nam">example_set</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t62" href="#t62">62</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t63" href="#t63">63</a></span><span class="t">        <span class="key">class</span> <span class="nam">EventListener</span><span class="op">(</span><span class="nam">RuleInductionProgressListener</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t64" href="#t64">64</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t65" href="#t65">65</a></span><span class="t">            <span class="nam">lock</span> <span class="op">=</span> <span class="nam">threading</span><span class="op">.</span><span class="nam">Lock</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t66" href="#t66">66</a></span><span class="t">            <span class="nam">induced_rules_count</span> <span class="op">=</span> <span class="num">0</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t67" href="#t67">67</a></span><span class="t">            <span class="nam">on_progress_calls_count</span> <span class="op">=</span> <span class="num">0</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t59" href="#t59">59</a></span><span class="t"><span class="key">class</span> <span class="nam">TestSurvivalRules</span><span class="op">(</span><span class="nam">unittest</span><span class="op">.</span><span class="nam">TestCase</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t60" href="#t60">60</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t61" href="#t61">61</a></span><span class="t">    <span class="key">def</span> <span class="nam">test_induction_progress_listener</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t62" href="#t62">62</a></span><span class="t">        <span class="nam">test_case</span> <span class="op">=</span> <span class="nam">get_test_cases</span><span class="op">(</span><span class="str">"SurvivalLogRankSnCTest"</span><span class="op">)</span><span class="op">[</span><span class="num">0</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t63" href="#t63">63</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t64" href="#t64">64</a></span><span class="t">        <span class="nam">surv</span> <span class="op">=</span> <span class="nam">survival</span><span class="op">.</span><span class="nam">SurvivalRules</span><span class="op">(</span><span class="nam">survival_time_attr</span><span class="op">=</span><span class="nam">test_case</span><span class="op">.</span><span class="nam">survival_time</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t65" href="#t65">65</a></span><span class="t">        <span class="nam">example_set</span> <span class="op">=</span> <span class="nam">test_case</span><span class="op">.</span><span class="nam">example_set</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t66" href="#t66">66</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t67" href="#t67">67</a></span><span class="t">        <span class="key">class</span> <span class="nam">EventListener</span><span class="op">(</span><span class="nam">RuleInductionProgressListener</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t68" href="#t68">68</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t69" href="#t69">69</a></span><span class="t">            <span class="key">def</span> <span class="nam">on_new_rule</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">rule</span><span class="op">:</span> <span class="nam">SurvivalRule</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t70" href="#t70">70</a></span><span class="t">                <span class="nam">self</span><span class="op">.</span><span class="nam">lock</span><span class="op">.</span><span class="nam">acquire</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t71" href="#t71">71</a></span><span class="t">                <span class="nam">self</span><span class="op">.</span><span class="nam">induced_rules_count</span> <span class="op">+=</span> <span class="num">1</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t72" href="#t72">72</a></span><span class="t">                <span class="nam">self</span><span class="op">.</span><span class="nam">lock</span><span class="op">.</span><span class="nam">release</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t73" href="#t73">73</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t74" href="#t74">74</a></span><span class="t">            <span class="key">def</span> <span class="nam">on_progress</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t75" href="#t75">75</a></span><span class="t">                <span class="nam">self</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t76" href="#t76">76</a></span><span class="t">                <span class="nam">total_examples_count</span><span class="op">:</span> <span class="nam">int</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t77" href="#t77">77</a></span><span class="t">                <span class="nam">uncovered_examples_count</span><span class="op">:</span> <span class="nam">int</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t78" href="#t78">78</a></span><span class="t">            <span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t79" href="#t79">79</a></span><span class="t">                <span class="nam">self</span><span class="op">.</span><span class="nam">lock</span><span class="op">.</span><span class="nam">acquire</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t80" href="#t80">80</a></span><span class="t">                <span class="nam">self</span><span class="op">.</span><span class="nam">on_progress_calls_count</span> <span class="op">+=</span> <span class="num">1</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t81" href="#t81">81</a></span><span class="t">                <span class="nam">self</span><span class="op">.</span><span class="nam">lock</span><span class="op">.</span><span class="nam">release</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t82" href="#t82">82</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t83" href="#t83">83</a></span><span class="t">        <span class="nam">listener</span> <span class="op">=</span> <span class="nam">EventListener</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t84" href="#t84">84</a></span><span class="t">        <span class="nam">surv</span><span class="op">.</span><span class="nam">add_event_listener</span><span class="op">(</span><span class="nam">listener</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t85" href="#t85">85</a></span><span class="t">        <span class="nam">surv</span><span class="op">.</span><span class="nam">fit</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t86" href="#t86">86</a></span><span class="t">            <span class="nam">example_set</span><span class="op">.</span><span class="nam">values</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t87" href="#t87">87</a></span><span class="t">            <span class="nam">example_set</span><span class="op">.</span><span class="nam">labels</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t88" href="#t88">88</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t89" href="#t89">89</a></span><span class="t">        <span class="nam">rules_count</span> <span class="op">=</span> <span class="nam">len</span><span class="op">(</span><span class="nam">surv</span><span class="op">.</span><span class="nam">model</span><span class="op">.</span><span class="nam">rules</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t90" href="#t90">90</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">assertEqual</span><span class="op">(</span><span class="nam">rules_count</span><span class="op">,</span> <span class="nam">listener</span><span class="op">.</span><span class="nam">induced_rules_count</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t91" href="#t91">91</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">assertEqual</span><span class="op">(</span><span class="nam">rules_count</span><span class="op">,</span> <span class="nam">listener</span><span class="op">.</span><span class="nam">on_progress_calls_count</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t92" href="#t92">92</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t93" href="#t93">93</a></span><span class="t">    <span class="key">def</span> <span class="nam">test_compare_with_java_results</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t94" href="#t94">94</a></span><span class="t">        <span class="nam">test_cases</span> <span class="op">=</span> <span class="nam">get_test_cases</span><span class="op">(</span><span class="str">'SurvivalLogRankSnCTest'</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t95" href="#t95">95</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t96" href="#t96">96</a></span><span class="t">        <span class="key">for</span> <span class="nam">test_case</span> <span class="key">in</span> <span class="nam">test_cases</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t97" href="#t97">97</a></span><span class="t">            <span class="nam">params</span> <span class="op">=</span> <span class="nam">test_case</span><span class="op">.</span><span class="nam">induction_params</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t98" href="#t98">98</a></span><span class="t">            <span class="nam">tree</span> <span class="op">=</span> <span class="nam">survival</span><span class="op">.</span><span class="nam">SurvivalRules</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t99" href="#t99">99</a></span><span class="t">                <span class="op">**</span><span class="nam">params</span><span class="op">,</span> <span class="nam">survival_time_attr</span><span class="op">=</span><span class="nam">test_case</span><span class="op">.</span><span class="nam">survival_time</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t100" href="#t100">100</a></span><span class="t">            <span class="nam">example_set</span> <span class="op">=</span> <span class="nam">test_case</span><span class="op">.</span><span class="nam">example_set</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t101" href="#t101">101</a></span><span class="t">            <span class="nam">tree</span><span class="op">.</span><span class="nam">fit</span><span class="op">(</span><span class="nam">example_set</span><span class="op">.</span><span class="nam">values</span><span class="op">,</span> <span class="nam">example_set</span><span class="op">.</span><span class="nam">labels</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t102" href="#t102">102</a></span><span class="t">            <span class="nam">model</span> <span class="op">=</span> <span class="nam">tree</span><span class="op">.</span><span class="nam">model</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t103" href="#t103">103</a></span><span class="t">            <span class="nam">expected</span> <span class="op">=</span> <span class="nam">test_case</span><span class="op">.</span><span class="nam">reference_report</span><span class="op">.</span><span class="nam">rules</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t104" href="#t104">104</a></span><span class="t">            <span class="nam">actual</span> <span class="op">=</span> <span class="nam">list</span><span class="op">(</span><span class="nam">map</span><span class="op">(</span><span class="nam">str</span><span class="op">,</span> <span class="nam">model</span><span class="op">.</span><span class="nam">rules</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t105" href="#t105">105</a></span><span class="t">            <span class="nam">assert_rules_are_equals</span><span class="op">(</span><span class="nam">expected</span><span class="op">,</span> <span class="nam">actual</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t106" href="#t106">106</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t107" href="#t107">107</a></span><span class="t">    <span class="key">def</span> <span class="nam">test_fit_and_predict_on_boolean_columns</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t108" href="#t108">108</a></span><span class="t">        <span class="nam">test_case</span> <span class="op">=</span> <span class="nam">get_test_cases</span><span class="op">(</span><span class="str">'SurvivalLogRankSnCTest'</span><span class="op">)</span><span class="op">[</span><span class="num">0</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t109" href="#t109">109</a></span><span class="t">        <span class="nam">params</span> <span class="op">=</span> <span class="nam">test_case</span><span class="op">.</span><span class="nam">induction_params</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t110" href="#t110">110</a></span><span class="t">        <span class="nam">clf</span> <span class="op">=</span> <span class="nam">survival</span><span class="op">.</span><span class="nam">SurvivalRules</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t111" href="#t111">111</a></span><span class="t">            <span class="op">**</span><span class="nam">params</span><span class="op">,</span> <span class="nam">survival_time_attr</span><span class="op">=</span><span class="nam">test_case</span><span class="op">.</span><span class="nam">survival_time</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t112" href="#t112">112</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t113" href="#t113">113</a></span><span class="t">        <span class="nam">X</span><span class="op">,</span> <span class="nam">y</span> <span class="op">=</span> <span class="nam">test_case</span><span class="op">.</span><span class="nam">example_set</span><span class="op">.</span><span class="nam">values</span><span class="op">,</span> <span class="nam">test_case</span><span class="op">.</span><span class="nam">example_set</span><span class="op">.</span><span class="nam">labels</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t114" href="#t114">114</a></span><span class="t">        <span class="nam">X</span><span class="op">[</span><span class="str">'boolean_column'</span><span class="op">]</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">random</span><span class="op">.</span><span class="nam">randint</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t115" href="#t115">115</a></span><span class="t">            <span class="nam">low</span><span class="op">=</span><span class="num">0</span><span class="op">,</span> <span class="nam">high</span><span class="op">=</span><span class="num">2</span><span class="op">,</span> <span class="nam">size</span><span class="op">=</span><span class="nam">X</span><span class="op">.</span><span class="nam">shape</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="op">)</span><span class="op">.</span><span class="nam">astype</span><span class="op">(</span><span class="nam">bool</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t116" href="#t116">116</a></span><span class="t">        <span class="nam">clf</span><span class="op">.</span><span class="nam">fit</span><span class="op">(</span><span class="nam">X</span><span class="op">,</span> <span class="nam">y</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t117" href="#t117">117</a></span><span class="t">        <span class="nam">clf</span><span class="op">.</span><span class="nam">predict</span><span class="op">(</span><span class="nam">X</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t118" href="#t118">118</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t119" href="#t119">119</a></span><span class="t">        <span class="nam">y</span> <span class="op">=</span> <span class="nam">pd</span><span class="op">.</span><span class="nam">Series</span><span class="op">(</span><span class="nam">y</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t69" href="#t69">69</a></span><span class="t">            <span class="nam">lock</span> <span class="op">=</span> <span class="nam">threading</span><span class="op">.</span><span class="nam">Lock</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t70" href="#t70">70</a></span><span class="t">            <span class="nam">induced_rules_count</span> <span class="op">=</span> <span class="num">0</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t71" href="#t71">71</a></span><span class="t">            <span class="nam">on_progress_calls_count</span> <span class="op">=</span> <span class="num">0</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t72" href="#t72">72</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t73" href="#t73">73</a></span><span class="t">            <span class="key">def</span> <span class="nam">on_new_rule</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">rule</span><span class="op">:</span> <span class="nam">SurvivalRule</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t74" href="#t74">74</a></span><span class="t">                <span class="nam">self</span><span class="op">.</span><span class="nam">lock</span><span class="op">.</span><span class="nam">acquire</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t75" href="#t75">75</a></span><span class="t">                <span class="nam">self</span><span class="op">.</span><span class="nam">induced_rules_count</span> <span class="op">+=</span> <span class="num">1</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t76" href="#t76">76</a></span><span class="t">                <span class="nam">self</span><span class="op">.</span><span class="nam">lock</span><span class="op">.</span><span class="nam">release</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t77" href="#t77">77</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t78" href="#t78">78</a></span><span class="t">            <span class="key">def</span> <span class="nam">on_progress</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t79" href="#t79">79</a></span><span class="t">                <span class="nam">self</span><span class="op">,</span> <span class="nam">total_examples_count</span><span class="op">:</span> <span class="nam">int</span><span class="op">,</span> <span class="nam">uncovered_examples_count</span><span class="op">:</span> <span class="nam">int</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t80" href="#t80">80</a></span><span class="t">            <span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t81" href="#t81">81</a></span><span class="t">                <span class="nam">self</span><span class="op">.</span><span class="nam">lock</span><span class="op">.</span><span class="nam">acquire</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t82" href="#t82">82</a></span><span class="t">                <span class="nam">self</span><span class="op">.</span><span class="nam">on_progress_calls_count</span> <span class="op">+=</span> <span class="num">1</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t83" href="#t83">83</a></span><span class="t">                <span class="nam">self</span><span class="op">.</span><span class="nam">lock</span><span class="op">.</span><span class="nam">release</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t84" href="#t84">84</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t85" href="#t85">85</a></span><span class="t">        <span class="nam">listener</span> <span class="op">=</span> <span class="nam">EventListener</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t86" href="#t86">86</a></span><span class="t">        <span class="nam">surv</span><span class="op">.</span><span class="nam">add_event_listener</span><span class="op">(</span><span class="nam">listener</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t87" href="#t87">87</a></span><span class="t">        <span class="nam">surv</span><span class="op">.</span><span class="nam">fit</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t88" href="#t88">88</a></span><span class="t">            <span class="nam">example_set</span><span class="op">.</span><span class="nam">values</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t89" href="#t89">89</a></span><span class="t">            <span class="nam">example_set</span><span class="op">.</span><span class="nam">labels</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t90" href="#t90">90</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t91" href="#t91">91</a></span><span class="t">        <span class="nam">rules_count</span> <span class="op">=</span> <span class="nam">len</span><span class="op">(</span><span class="nam">surv</span><span class="op">.</span><span class="nam">model</span><span class="op">.</span><span class="nam">rules</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t92" href="#t92">92</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">assertEqual</span><span class="op">(</span><span class="nam">rules_count</span><span class="op">,</span> <span class="nam">listener</span><span class="op">.</span><span class="nam">induced_rules_count</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t93" href="#t93">93</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">assertEqual</span><span class="op">(</span><span class="nam">rules_count</span><span class="op">,</span> <span class="nam">listener</span><span class="op">.</span><span class="nam">on_progress_calls_count</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t94" href="#t94">94</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t95" href="#t95">95</a></span><span class="t">    <span class="key">def</span> <span class="nam">test_compare_with_java_results</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t96" href="#t96">96</a></span><span class="t">        <span class="nam">test_cases</span> <span class="op">=</span> <span class="nam">get_test_cases</span><span class="op">(</span><span class="str">"SurvivalLogRankSnCTest"</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t97" href="#t97">97</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t98" href="#t98">98</a></span><span class="t">        <span class="key">for</span> <span class="nam">test_case</span> <span class="key">in</span> <span class="nam">test_cases</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t99" href="#t99">99</a></span><span class="t">            <span class="nam">params</span> <span class="op">=</span> <span class="nam">test_case</span><span class="op">.</span><span class="nam">induction_params</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t100" href="#t100">100</a></span><span class="t">            <span class="nam">tree</span> <span class="op">=</span> <span class="nam">survival</span><span class="op">.</span><span class="nam">SurvivalRules</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t101" href="#t101">101</a></span><span class="t">                <span class="op">**</span><span class="nam">params</span><span class="op">,</span> <span class="nam">survival_time_attr</span><span class="op">=</span><span class="nam">test_case</span><span class="op">.</span><span class="nam">survival_time</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t102" href="#t102">102</a></span><span class="t">            <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t103" href="#t103">103</a></span><span class="t">            <span class="nam">example_set</span> <span class="op">=</span> <span class="nam">test_case</span><span class="op">.</span><span class="nam">example_set</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t104" href="#t104">104</a></span><span class="t">            <span class="nam">tree</span><span class="op">.</span><span class="nam">fit</span><span class="op">(</span><span class="nam">example_set</span><span class="op">.</span><span class="nam">values</span><span class="op">,</span> <span class="nam">example_set</span><span class="op">.</span><span class="nam">labels</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t105" href="#t105">105</a></span><span class="t">            <span class="nam">model</span> <span class="op">=</span> <span class="nam">tree</span><span class="op">.</span><span class="nam">model</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t106" href="#t106">106</a></span><span class="t">            <span class="nam">expected</span> <span class="op">=</span> <span class="nam">test_case</span><span class="op">.</span><span class="nam">reference_report</span><span class="op">.</span><span class="nam">rules</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t107" href="#t107">107</a></span><span class="t">            <span class="nam">actual</span> <span class="op">=</span> <span class="nam">list</span><span class="op">(</span><span class="nam">map</span><span class="op">(</span><span class="nam">str</span><span class="op">,</span> <span class="nam">model</span><span class="op">.</span><span class="nam">rules</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t108" href="#t108">108</a></span><span class="t">            <span class="nam">assert_rules_are_equals</span><span class="op">(</span><span class="nam">expected</span><span class="op">,</span> <span class="nam">actual</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t109" href="#t109">109</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t110" href="#t110">110</a></span><span class="t">    <span class="key">def</span> <span class="nam">test_fit_and_predict_on_boolean_columns</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t111" href="#t111">111</a></span><span class="t">        <span class="nam">test_case</span> <span class="op">=</span> <span class="nam">get_test_cases</span><span class="op">(</span><span class="str">"SurvivalLogRankSnCTest"</span><span class="op">)</span><span class="op">[</span><span class="num">0</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t112" href="#t112">112</a></span><span class="t">        <span class="nam">params</span> <span class="op">=</span> <span class="nam">test_case</span><span class="op">.</span><span class="nam">induction_params</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t113" href="#t113">113</a></span><span class="t">        <span class="nam">clf</span> <span class="op">=</span> <span class="nam">survival</span><span class="op">.</span><span class="nam">SurvivalRules</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t114" href="#t114">114</a></span><span class="t">            <span class="op">**</span><span class="nam">params</span><span class="op">,</span> <span class="nam">survival_time_attr</span><span class="op">=</span><span class="nam">test_case</span><span class="op">.</span><span class="nam">survival_time</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t115" href="#t115">115</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t116" href="#t116">116</a></span><span class="t">        <span class="nam">X</span><span class="op">,</span> <span class="nam">y</span> <span class="op">=</span> <span class="nam">test_case</span><span class="op">.</span><span class="nam">example_set</span><span class="op">.</span><span class="nam">values</span><span class="op">,</span> <span class="nam">test_case</span><span class="op">.</span><span class="nam">example_set</span><span class="op">.</span><span class="nam">labels</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t117" href="#t117">117</a></span><span class="t">        <span class="nam">X</span><span class="op">[</span><span class="str">"boolean_column"</span><span class="op">]</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">random</span><span class="op">.</span><span class="nam">randint</span><span class="op">(</span><span class="nam">low</span><span class="op">=</span><span class="num">0</span><span class="op">,</span> <span class="nam">high</span><span class="op">=</span><span class="num">2</span><span class="op">,</span> <span class="nam">size</span><span class="op">=</span><span class="nam">X</span><span class="op">.</span><span class="nam">shape</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="op">)</span><span class="op">.</span><span class="nam">astype</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t118" href="#t118">118</a></span><span class="t">            <span class="nam">bool</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t119" href="#t119">119</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
     <p class="run"><span class="n"><a id="t120" href="#t120">120</a></span><span class="t">        <span class="nam">clf</span><span class="op">.</span><span class="nam">fit</span><span class="op">(</span><span class="nam">X</span><span class="op">,</span> <span class="nam">y</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t121" href="#t121">121</a></span><span class="t">        <span class="nam">p</span> <span class="op">=</span> <span class="nam">clf</span><span class="op">.</span><span class="nam">predict</span><span class="op">(</span><span class="nam">X</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t121" href="#t121">121</a></span><span class="t">        <span class="nam">clf</span><span class="op">.</span><span class="nam">predict</span><span class="op">(</span><span class="nam">X</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t122" href="#t122">122</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t123" href="#t123">123</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t124" href="#t124">124</a></span><span class="t"><span class="key">class</span> <span class="nam">TestExpertSurvivalLogRankTree</span><span class="op">(</span><span class="nam">unittest</span><span class="op">.</span><span class="nam">TestCase</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t125" href="#t125">125</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t126" href="#t126">126</a></span><span class="t">    <span class="op">@</span> <span class="nam">classmethod</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t127" href="#t127">127</a></span><span class="t">    <span class="key">def</span> <span class="nam">setUpClass</span><span class="op">(</span><span class="nam">cls</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t128" href="#t128">128</a></span><span class="t">        <span class="nam">RuleKit</span><span class="op">.</span><span class="nam">init</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t129" href="#t129">129</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t130" href="#t130">130</a></span><span class="t">    <span class="key">def</span> <span class="nam">test_compare_with_java_results</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t131" href="#t131">131</a></span><span class="t">        <span class="nam">test_cases</span> <span class="op">=</span> <span class="nam">get_test_cases</span><span class="op">(</span><span class="str">'SurvivalLogRankExpertSnCTest'</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t132" href="#t132">132</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t133" href="#t133">133</a></span><span class="t">        <span class="key">for</span> <span class="nam">test_case</span> <span class="key">in</span> <span class="nam">test_cases</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t134" href="#t134">134</a></span><span class="t">            <span class="nam">params</span> <span class="op">=</span> <span class="nam">test_case</span><span class="op">.</span><span class="nam">induction_params</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t135" href="#t135">135</a></span><span class="t">            <span class="nam">tree</span> <span class="op">=</span> <span class="nam">survival</span><span class="op">.</span><span class="nam">ExpertSurvivalRules</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t136" href="#t136">136</a></span><span class="t">                <span class="op">**</span><span class="nam">params</span><span class="op">,</span> <span class="nam">ignore_missing</span><span class="op">=</span><span class="key">True</span><span class="op">,</span> <span class="nam">survival_time_attr</span><span class="op">=</span><span class="nam">test_case</span><span class="op">.</span><span class="nam">survival_time</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t137" href="#t137">137</a></span><span class="t">            <span class="nam">example_set</span> <span class="op">=</span> <span class="nam">test_case</span><span class="op">.</span><span class="nam">example_set</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t138" href="#t138">138</a></span><span class="t">            <span class="nam">tree</span><span class="op">.</span><span class="nam">fit</span><span class="op">(</span><span class="nam">example_set</span><span class="op">.</span><span class="nam">values</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t139" href="#t139">139</a></span><span class="t">                     <span class="nam">example_set</span><span class="op">.</span><span class="nam">labels</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t140" href="#t140">140</a></span><span class="t">                     <span class="nam">expert_rules</span><span class="op">=</span><span class="nam">test_case</span><span class="op">.</span><span class="nam">knowledge</span><span class="op">.</span><span class="nam">expert_rules</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t141" href="#t141">141</a></span><span class="t">                     <span class="nam">expert_preferred_conditions</span><span class="op">=</span><span class="nam">test_case</span><span class="op">.</span><span class="nam">knowledge</span><span class="op">.</span><span class="nam">expert_preferred_conditions</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t142" href="#t142">142</a></span><span class="t">                     <span class="nam">expert_forbidden_conditions</span><span class="op">=</span><span class="nam">test_case</span><span class="op">.</span><span class="nam">knowledge</span><span class="op">.</span><span class="nam">expert_forbidden_conditions</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t143" href="#t143">143</a></span><span class="t">            <span class="nam">model</span> <span class="op">=</span> <span class="nam">tree</span><span class="op">.</span><span class="nam">model</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t144" href="#t144">144</a></span><span class="t">            <span class="nam">expected</span> <span class="op">=</span> <span class="nam">test_case</span><span class="op">.</span><span class="nam">reference_report</span><span class="op">.</span><span class="nam">rules</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t145" href="#t145">145</a></span><span class="t">            <span class="nam">actual</span> <span class="op">=</span> <span class="nam">list</span><span class="op">(</span><span class="nam">map</span><span class="op">(</span><span class="nam">str</span><span class="op">,</span> <span class="nam">model</span><span class="op">.</span><span class="nam">rules</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t146" href="#t146">146</a></span><span class="t">            <span class="nam">assert_rules_are_equals</span><span class="op">(</span><span class="nam">expected</span><span class="op">,</span> <span class="nam">actual</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t147" href="#t147">147</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t148" href="#t148">148</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t149" href="#t149">149</a></span><span class="t"><span class="key">if</span> <span class="nam">__name__</span> <span class="op">==</span> <span class="str">'__main__'</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t150" href="#t150">150</a></span><span class="t">    <span class="nam">unittest</span><span class="op">.</span><span class="nam">main</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t123" href="#t123">123</a></span><span class="t">        <span class="nam">y</span> <span class="op">=</span> <span class="nam">pd</span><span class="op">.</span><span class="nam">Series</span><span class="op">(</span><span class="nam">y</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t124" href="#t124">124</a></span><span class="t">        <span class="nam">clf</span><span class="op">.</span><span class="nam">fit</span><span class="op">(</span><span class="nam">X</span><span class="op">,</span> <span class="nam">y</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t125" href="#t125">125</a></span><span class="t">        <span class="nam">clf</span><span class="op">.</span><span class="nam">predict</span><span class="op">(</span><span class="nam">X</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t126" href="#t126">126</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t127" href="#t127">127</a></span><span class="t">    <span class="key">def</span> <span class="nam">test_passing_survival_time_column_to_fit_method</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t128" href="#t128">128</a></span><span class="t">        <span class="nam">test_case</span> <span class="op">=</span> <span class="nam">get_test_cases</span><span class="op">(</span><span class="str">"SurvivalLogRankSnCTest"</span><span class="op">)</span><span class="op">[</span><span class="num">0</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t129" href="#t129">129</a></span><span class="t">        <span class="nam">params</span> <span class="op">=</span> <span class="nam">test_case</span><span class="op">.</span><span class="nam">induction_params</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t130" href="#t130">130</a></span><span class="t">        <span class="nam">surv1</span> <span class="op">=</span> <span class="nam">survival</span><span class="op">.</span><span class="nam">SurvivalRules</span><span class="op">(</span><span class="op">**</span><span class="nam">params</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t131" href="#t131">131</a></span><span class="t">        <span class="nam">surv2</span> <span class="op">=</span> <span class="nam">survival</span><span class="op">.</span><span class="nam">SurvivalRules</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t132" href="#t132">132</a></span><span class="t">            <span class="op">**</span><span class="nam">params</span><span class="op">,</span> <span class="nam">survival_time_attr</span><span class="op">=</span><span class="nam">test_case</span><span class="op">.</span><span class="nam">survival_time</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t133" href="#t133">133</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t134" href="#t134">134</a></span><span class="t">        <span class="nam">X</span><span class="op">,</span> <span class="nam">y</span> <span class="op">=</span> <span class="nam">test_case</span><span class="op">.</span><span class="nam">example_set</span><span class="op">.</span><span class="nam">values</span><span class="op">,</span> <span class="nam">test_case</span><span class="op">.</span><span class="nam">example_set</span><span class="op">.</span><span class="nam">labels</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t135" href="#t135">135</a></span><span class="t">        <span class="nam">survival_time_col</span><span class="op">:</span> <span class="nam">pd</span><span class="op">.</span><span class="nam">Series</span> <span class="op">=</span> <span class="nam">X</span><span class="op">[</span><span class="nam">test_case</span><span class="op">.</span><span class="nam">survival_time</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t136" href="#t136">136</a></span><span class="t">        <span class="nam">X_without_time_col</span><span class="op">:</span> <span class="nam">pd</span><span class="op">.</span><span class="nam">DataFrame</span> <span class="op">=</span> <span class="nam">X</span><span class="op">.</span><span class="nam">drop</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t137" href="#t137">137</a></span><span class="t">            <span class="nam">columns</span><span class="op">=</span><span class="op">[</span><span class="nam">test_case</span><span class="op">.</span><span class="nam">survival_time</span><span class="op">]</span><span class="op">,</span> <span class="nam">axis</span><span class="op">=</span><span class="num">1</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t138" href="#t138">138</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t139" href="#t139">139</a></span><span class="t">        <span class="nam">surv1</span><span class="op">.</span><span class="nam">fit</span><span class="op">(</span><span class="nam">X_without_time_col</span><span class="op">,</span> <span class="nam">y</span><span class="op">,</span> <span class="nam">survival_time</span><span class="op">=</span><span class="nam">survival_time_col</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t140" href="#t140">140</a></span><span class="t">        <span class="nam">surv2</span><span class="op">.</span><span class="nam">fit</span><span class="op">(</span><span class="nam">X</span><span class="op">,</span> <span class="nam">y</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t141" href="#t141">141</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t142" href="#t142">142</a></span><span class="t">        <span class="nam">assert_rules_are_equals</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t143" href="#t143">143</a></span><span class="t">            <span class="op">[</span><span class="nam">str</span><span class="op">(</span><span class="nam">r</span><span class="op">)</span> <span class="key">for</span> <span class="nam">r</span> <span class="key">in</span> <span class="nam">surv1</span><span class="op">.</span><span class="nam">model</span><span class="op">.</span><span class="nam">rules</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t144" href="#t144">144</a></span><span class="t">            <span class="op">[</span><span class="nam">str</span><span class="op">(</span><span class="nam">r</span><span class="op">)</span> <span class="key">for</span> <span class="nam">r</span> <span class="key">in</span> <span class="nam">surv2</span><span class="op">.</span><span class="nam">model</span><span class="op">.</span><span class="nam">rules</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t145" href="#t145">145</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t146" href="#t146">146</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t147" href="#t147">147</a></span><span class="t">    <span class="key">def</span> <span class="nam">test_ibs_calculation</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t148" href="#t148">148</a></span><span class="t">        <span class="nam">test_case</span> <span class="op">=</span> <span class="nam">get_test_cases</span><span class="op">(</span><span class="str">"SurvivalLogRankSnCTest"</span><span class="op">)</span><span class="op">[</span><span class="num">0</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t149" href="#t149">149</a></span><span class="t">        <span class="nam">params</span> <span class="op">=</span> <span class="nam">test_case</span><span class="op">.</span><span class="nam">induction_params</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t150" href="#t150">150</a></span><span class="t">        <span class="nam">surv</span> <span class="op">=</span> <span class="nam">survival</span><span class="op">.</span><span class="nam">SurvivalRules</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t151" href="#t151">151</a></span><span class="t">            <span class="op">**</span><span class="nam">params</span><span class="op">,</span> <span class="nam">survival_time_attr</span><span class="op">=</span><span class="nam">test_case</span><span class="op">.</span><span class="nam">survival_time</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t152" href="#t152">152</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t153" href="#t153">153</a></span><span class="t">        <span class="nam">X</span><span class="op">,</span> <span class="nam">y</span> <span class="op">=</span> <span class="nam">test_case</span><span class="op">.</span><span class="nam">example_set</span><span class="op">.</span><span class="nam">values</span><span class="op">,</span> <span class="nam">test_case</span><span class="op">.</span><span class="nam">example_set</span><span class="op">.</span><span class="nam">labels</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t154" href="#t154">154</a></span><span class="t">        <span class="nam">survival_time_col</span><span class="op">:</span> <span class="nam">pd</span><span class="op">.</span><span class="nam">Series</span> <span class="op">=</span> <span class="nam">X</span><span class="op">[</span><span class="nam">test_case</span><span class="op">.</span><span class="nam">survival_time</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t155" href="#t155">155</a></span><span class="t">        <span class="nam">X_without_time_col</span><span class="op">:</span> <span class="nam">pd</span><span class="op">.</span><span class="nam">DataFrame</span> <span class="op">=</span> <span class="nam">X</span><span class="op">.</span><span class="nam">drop</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t156" href="#t156">156</a></span><span class="t">            <span class="nam">columns</span><span class="op">=</span><span class="op">[</span><span class="nam">test_case</span><span class="op">.</span><span class="nam">survival_time</span><span class="op">]</span><span class="op">,</span> <span class="nam">axis</span><span class="op">=</span><span class="num">1</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t157" href="#t157">157</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t158" href="#t158">158</a></span><span class="t">        <span class="nam">surv</span><span class="op">.</span><span class="nam">fit</span><span class="op">(</span><span class="nam">X</span><span class="op">,</span> <span class="nam">y</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t159" href="#t159">159</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t160" href="#t160">160</a></span><span class="t">        <span class="nam">ibs</span><span class="op">:</span> <span class="nam">float</span> <span class="op">=</span> <span class="nam">surv</span><span class="op">.</span><span class="nam">score</span><span class="op">(</span><span class="nam">X</span><span class="op">,</span> <span class="nam">y</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t161" href="#t161">161</a></span><span class="t">        <span class="nam">ibs2</span><span class="op">:</span> <span class="nam">float</span> <span class="op">=</span> <span class="nam">surv</span><span class="op">.</span><span class="nam">score</span><span class="op">(</span><span class="nam">X_without_time_col</span><span class="op">,</span> <span class="nam">y</span><span class="op">,</span> <span class="nam">survival_time</span><span class="op">=</span><span class="nam">survival_time_col</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t162" href="#t162">162</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t163" href="#t163">163</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">assertEqual</span><span class="op">(</span><span class="nam">ibs</span><span class="op">,</span> <span class="nam">ibs2</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t164" href="#t164">164</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t165" href="#t165">165</a></span><span class="t">    <span class="key">def</span> <span class="nam">test_getting_training_dataset_kaplan_meier_estimator</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t166" href="#t166">166</a></span><span class="t">        <span class="nam">test_case</span> <span class="op">=</span> <span class="nam">get_test_cases</span><span class="op">(</span><span class="str">"SurvivalLogRankSnCTest"</span><span class="op">)</span><span class="op">[</span><span class="num">0</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t167" href="#t167">167</a></span><span class="t">        <span class="nam">params</span> <span class="op">=</span> <span class="nam">test_case</span><span class="op">.</span><span class="nam">induction_params</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t168" href="#t168">168</a></span><span class="t">        <span class="nam">surv</span> <span class="op">=</span> <span class="nam">survival</span><span class="op">.</span><span class="nam">SurvivalRules</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t169" href="#t169">169</a></span><span class="t">            <span class="op">**</span><span class="nam">params</span><span class="op">,</span> <span class="nam">survival_time_attr</span><span class="op">=</span><span class="nam">test_case</span><span class="op">.</span><span class="nam">survival_time</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t170" href="#t170">170</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t171" href="#t171">171</a></span><span class="t">        <span class="nam">example_set</span> <span class="op">=</span> <span class="nam">test_case</span><span class="op">.</span><span class="nam">example_set</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t172" href="#t172">172</a></span><span class="t">        <span class="nam">unique_times_counts</span><span class="op">:</span> <span class="nam">int</span> <span class="op">=</span> <span class="nam">example_set</span><span class="op">.</span><span class="nam">values</span><span class="op">[</span><span class="nam">test_case</span><span class="op">.</span><span class="nam">survival_time</span><span class="op">]</span><span class="op">.</span><span class="nam">nunique</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t173" href="#t173">173</a></span><span class="t">        <span class="nam">surv</span><span class="op">.</span><span class="nam">fit</span><span class="op">(</span><span class="nam">example_set</span><span class="op">.</span><span class="nam">values</span><span class="op">,</span> <span class="nam">example_set</span><span class="op">.</span><span class="nam">labels</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t174" href="#t174">174</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t175" href="#t175">175</a></span><span class="t">        <span class="nam">training_km</span><span class="op">:</span> <span class="nam">KaplanMeierEstimator</span> <span class="op">=</span> <span class="nam">surv</span><span class="op">.</span><span class="nam">get_train_set_kaplan_meier</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t176" href="#t176">176</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">assertTrue</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t177" href="#t177">177</a></span><span class="t">            <span class="nam">training_km</span> <span class="key">is</span> <span class="key">not</span> <span class="key">None</span> <span class="key">and</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">training_km</span><span class="op">,</span> <span class="nam">KaplanMeierEstimator</span><span class="op">)</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t178" href="#t178">178</a></span><span class="t">            <span class="str">"Should return KaplanMeierEstimator instance fitted on whole training set"</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t179" href="#t179">179</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t180" href="#t180">180</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">assertEqual</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t181" href="#t181">181</a></span><span class="t">            <span class="nam">len</span><span class="op">(</span><span class="nam">training_km</span><span class="op">.</span><span class="nam">times</span><span class="op">)</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t182" href="#t182">182</a></span><span class="t">            <span class="nam">unique_times_counts</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t183" href="#t183">183</a></span><span class="t">            <span class="str">"Estimator should contain probabilities for each unique time from the dataset"</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t184" href="#t184">184</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t185" href="#t185">185</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t186" href="#t186">186</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t187" href="#t187">187</a></span><span class="t"><span class="key">class</span> <span class="nam">TestExpertSurvivalRules</span><span class="op">(</span><span class="nam">unittest</span><span class="op">.</span><span class="nam">TestCase</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t188" href="#t188">188</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t189" href="#t189">189</a></span><span class="t">    <span class="op">@</span><span class="nam">classmethod</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t190" href="#t190">190</a></span><span class="t">    <span class="key">def</span> <span class="nam">setUpClass</span><span class="op">(</span><span class="nam">cls</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t191" href="#t191">191</a></span><span class="t">        <span class="nam">RuleKit</span><span class="op">.</span><span class="nam">init</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t192" href="#t192">192</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t193" href="#t193">193</a></span><span class="t">    <span class="key">def</span> <span class="nam">test_compare_with_java_results</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t194" href="#t194">194</a></span><span class="t">        <span class="nam">test_cases</span> <span class="op">=</span> <span class="nam">get_test_cases</span><span class="op">(</span><span class="str">"SurvivalLogRankExpertSnCTest"</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t195" href="#t195">195</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t196" href="#t196">196</a></span><span class="t">        <span class="key">for</span> <span class="nam">test_case</span> <span class="key">in</span> <span class="nam">test_cases</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t197" href="#t197">197</a></span><span class="t">            <span class="nam">params</span> <span class="op">=</span> <span class="nam">test_case</span><span class="op">.</span><span class="nam">induction_params</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t198" href="#t198">198</a></span><span class="t">            <span class="nam">surv</span> <span class="op">=</span> <span class="nam">survival</span><span class="op">.</span><span class="nam">ExpertSurvivalRules</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t199" href="#t199">199</a></span><span class="t">                <span class="op">**</span><span class="nam">params</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t200" href="#t200">200</a></span><span class="t">                <span class="nam">ignore_missing</span><span class="op">=</span><span class="key">True</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t201" href="#t201">201</a></span><span class="t">                <span class="nam">survival_time_attr</span><span class="op">=</span><span class="nam">test_case</span><span class="op">.</span><span class="nam">survival_time</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t202" href="#t202">202</a></span><span class="t">            <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t203" href="#t203">203</a></span><span class="t">            <span class="nam">example_set</span> <span class="op">=</span> <span class="nam">test_case</span><span class="op">.</span><span class="nam">example_set</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t204" href="#t204">204</a></span><span class="t">            <span class="nam">surv</span><span class="op">.</span><span class="nam">fit</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t205" href="#t205">205</a></span><span class="t">                <span class="nam">example_set</span><span class="op">.</span><span class="nam">values</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t206" href="#t206">206</a></span><span class="t">                <span class="nam">example_set</span><span class="op">.</span><span class="nam">labels</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t207" href="#t207">207</a></span><span class="t">                <span class="nam">expert_rules</span><span class="op">=</span><span class="nam">test_case</span><span class="op">.</span><span class="nam">knowledge</span><span class="op">.</span><span class="nam">expert_rules</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t208" href="#t208">208</a></span><span class="t">                <span class="nam">expert_preferred_conditions</span><span class="op">=</span><span class="nam">test_case</span><span class="op">.</span><span class="nam">knowledge</span><span class="op">.</span><span class="nam">expert_preferred_conditions</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t209" href="#t209">209</a></span><span class="t">                <span class="nam">expert_forbidden_conditions</span><span class="op">=</span><span class="nam">test_case</span><span class="op">.</span><span class="nam">knowledge</span><span class="op">.</span><span class="nam">expert_forbidden_conditions</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t210" href="#t210">210</a></span><span class="t">            <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t211" href="#t211">211</a></span><span class="t">            <span class="nam">model</span> <span class="op">=</span> <span class="nam">surv</span><span class="op">.</span><span class="nam">model</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t212" href="#t212">212</a></span><span class="t">            <span class="nam">expected</span> <span class="op">=</span> <span class="nam">test_case</span><span class="op">.</span><span class="nam">reference_report</span><span class="op">.</span><span class="nam">rules</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t213" href="#t213">213</a></span><span class="t">            <span class="nam">actual</span> <span class="op">=</span> <span class="nam">list</span><span class="op">(</span><span class="nam">map</span><span class="op">(</span><span class="nam">str</span><span class="op">,</span> <span class="nam">model</span><span class="op">.</span><span class="nam">rules</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t214" href="#t214">214</a></span><span class="t">            <span class="nam">assert_rules_are_equals</span><span class="op">(</span><span class="nam">expected</span><span class="op">,</span> <span class="nam">actual</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t215" href="#t215">215</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t216" href="#t216">216</a></span><span class="t">    <span class="key">def</span> <span class="nam">test_refining_conditions_for_nominal_attributes</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t217" href="#t217">217</a></span><span class="t">        <span class="nam">df</span><span class="op">:</span> <span class="nam">pd</span><span class="op">.</span><span class="nam">DataFrame</span> <span class="op">=</span> <span class="nam">read_arff</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t218" href="#t218">218</a></span><span class="t">            <span class="nam">os</span><span class="op">.</span><span class="nam">path</span><span class="op">.</span><span class="nam">join</span><span class="op">(</span><span class="nam">dir_path</span><span class="op">,</span> <span class="str">"resources"</span><span class="op">,</span> <span class="str">"data"</span><span class="op">,</span> <span class="str">"bmt-train-0.arff"</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t219" href="#t219">219</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t220" href="#t220">220</a></span><span class="t">        <span class="nam">X</span><span class="op">,</span> <span class="nam">y</span> <span class="op">=</span> <span class="nam">df</span><span class="op">.</span><span class="nam">drop</span><span class="op">(</span><span class="str">"survival_status"</span><span class="op">,</span> <span class="nam">axis</span><span class="op">=</span><span class="num">1</span><span class="op">)</span><span class="op">,</span> <span class="nam">df</span><span class="op">[</span><span class="str">"survival_status"</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t221" href="#t221">221</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t222" href="#t222">222</a></span><span class="t">        <span class="com"># Run experiment using python API</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t223" href="#t223">223</a></span><span class="t">        <span class="nam">clf</span> <span class="op">=</span> <span class="nam">survival</span><span class="op">.</span><span class="nam">ExpertSurvivalRules</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t224" href="#t224">224</a></span><span class="t">            <span class="nam">complementary_conditions</span><span class="op">=</span><span class="key">True</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t225" href="#t225">225</a></span><span class="t">            <span class="nam">extend_using_preferred</span><span class="op">=</span><span class="key">False</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t226" href="#t226">226</a></span><span class="t">            <span class="nam">extend_using_automatic</span><span class="op">=</span><span class="key">False</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t227" href="#t227">227</a></span><span class="t">            <span class="nam">induce_using_preferred</span><span class="op">=</span><span class="key">False</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t228" href="#t228">228</a></span><span class="t">            <span class="nam">induce_using_automatic</span><span class="op">=</span><span class="key">False</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t229" href="#t229">229</a></span><span class="t">            <span class="nam">preferred_conditions_per_rule</span><span class="op">=</span><span class="num">0</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t230" href="#t230">230</a></span><span class="t">            <span class="nam">preferred_attributes_per_rule</span><span class="op">=</span><span class="num">0</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t231" href="#t231">231</a></span><span class="t">            <span class="nam">survival_time_attr</span><span class="op">=</span><span class="str">"survival_time"</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t232" href="#t232">232</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t233" href="#t233">233</a></span><span class="t">        <span class="nam">clf</span><span class="op">.</span><span class="nam">fit</span><span class="op">(</span><span class="nam">X</span><span class="op">,</span> <span class="nam">y</span><span class="op">,</span> <span class="nam">expert_rules</span><span class="op">=</span><span class="op">[</span><span class="op">(</span><span class="str">"expert_rules-1"</span><span class="op">,</span> <span class="str">"IF CMVstatus @= {1} THEN"</span><span class="op">)</span><span class="op">]</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t234" href="#t234">234</a></span><span class="t">        <span class="nam">r</span> <span class="op">=</span> <span class="op">[</span><span class="nam">str</span><span class="op">(</span><span class="nam">r</span><span class="op">)</span> <span class="key">for</span> <span class="nam">r</span> <span class="key">in</span> <span class="nam">clf</span><span class="op">.</span><span class="nam">model</span><span class="op">.</span><span class="nam">rules</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t235" href="#t235">235</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t236" href="#t236">236</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">assertEqual</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t237" href="#t237">237</a></span><span class="t">            <span class="op">[</span><span class="str">"IF [[CMVstatus = {1}]] THEN "</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t238" href="#t238">238</a></span><span class="t">            <span class="op">[</span><span class="nam">str</span><span class="op">(</span><span class="nam">r</span><span class="op">)</span> <span class="key">for</span> <span class="nam">r</span> <span class="key">in</span> <span class="nam">clf</span><span class="op">.</span><span class="nam">model</span><span class="op">.</span><span class="nam">rules</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t239" href="#t239">239</a></span><span class="t">            <span class="str">"Ruleset should contain only a single rule configured by expert"</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t240" href="#t240">240</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t241" href="#t241">241</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t242" href="#t242">242</a></span><span class="t">        <span class="nam">clf</span><span class="op">.</span><span class="nam">fit</span><span class="op">(</span><span class="nam">X</span><span class="op">,</span> <span class="nam">y</span><span class="op">,</span> <span class="nam">expert_rules</span><span class="op">=</span><span class="op">[</span><span class="op">(</span><span class="str">"expert_rules-1"</span><span class="op">,</span> <span class="str">"IF CMVstatus @= Any THEN"</span><span class="op">)</span><span class="op">]</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t243" href="#t243">243</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">assertEqual</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t244" href="#t244">244</a></span><span class="t">            <span class="op">[</span><span class="str">"IF [[CMVstatus = !{1}]] THEN "</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t245" href="#t245">245</a></span><span class="t">            <span class="op">[</span><span class="nam">str</span><span class="op">(</span><span class="nam">r</span><span class="op">)</span> <span class="key">for</span> <span class="nam">r</span> <span class="key">in</span> <span class="nam">clf</span><span class="op">.</span><span class="nam">model</span><span class="op">.</span><span class="nam">rules</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t246" href="#t246">246</a></span><span class="t">            <span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t247" href="#t247">247</a></span><span class="t">                <span class="str">"Ruleset should contain only a single rule configured by expert with "</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t248" href="#t248">248</a></span><span class="t">                <span class="str">"a refined condition"</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t249" href="#t249">249</a></span><span class="t">            <span class="op">)</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t250" href="#t250">250</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t251" href="#t251">251</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t252" href="#t252">252</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t253" href="#t253">253</a></span><span class="t"><span class="key">if</span> <span class="nam">__name__</span> <span class="op">==</span> <span class="str">"__main__"</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t254" href="#t254">254</a></span><span class="t">    <span class="nam">unittest</span><span class="op">.</span><span class="nam">main</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
 </main>
 <footer>
     <div class="content">
@@ -239,7 +343,7 @@ <h2>
             <a class="nav" href="z_a44f0ac069e85531_utils_py.html">&#xbb; next</a>
             &nbsp; &nbsp; &nbsp;
             <a class="nav" href="https://coverage.readthedocs.io/en/7.6.4">coverage.py v7.6.4</a>,
-            created at 2024-11-08 14:43 +0100
+            created at 2024-11-28 12:23 +0100
         </p>
     </div>
 </footer>
diff --git a/docs/reports/coverage/z_a44f0ac069e85531_utils_py.html b/docs/reports/coverage/z_a44f0ac069e85531_utils_py.html
index 44cfda9..9f1a0f6 100644
--- a/docs/reports/coverage/z_a44f0ac069e85531_utils_py.html
+++ b/docs/reports/coverage/z_a44f0ac069e85531_utils_py.html
@@ -54,9 +54,9 @@ <h1>
             </div>
         </aside>
         <h2>
-            <span class="text">322 statements &nbsp;</span>
+            <span class="text">323 statements &nbsp;</span>
             <button type="button" class="run button_toggle_run" value="run" data-shortcut="r" title="Toggle lines run">291<span class="text"> run</span></button>
-            <button type="button" class="mis show_mis button_toggle_mis" value="mis" data-shortcut="m" title="Toggle lines missing">31<span class="text"> missing</span></button>
+            <button type="button" class="mis show_mis button_toggle_mis" value="mis" data-shortcut="m" title="Toggle lines missing">32<span class="text"> missing</span></button>
             <button type="button" class="exc show_exc button_toggle_exc" value="exc" data-shortcut="x" title="Toggle lines excluded">0<span class="text"> excluded</span></button>
         </h2>
         <p class="text">
@@ -65,7 +65,7 @@ <h2>
             <a id="nextFileLink" class="nav" href="index.html">&#xbb; next</a>
             &nbsp; &nbsp; &nbsp;
             <a class="nav" href="https://coverage.readthedocs.io/en/7.6.4">coverage.py v7.6.4</a>,
-            created at 2024-11-05 13:43 +0100
+            created at 2024-11-28 11:55 +0100
         </p>
         <aside class="hidden">
             <button type="button" class="button_next_chunk" data-shortcut="j"></button>
@@ -96,38 +96,38 @@ <h2>
     <p class="pln"><span class="n"><a id="t14" href="#t14">14</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
     <p class="run"><span class="n"><a id="t15" href="#t15">15</a></span><span class="t"><span class="nam">dir_path</span> <span class="op">=</span> <span class="nam">os</span><span class="op">.</span><span class="nam">path</span><span class="op">.</span><span class="nam">dirname</span><span class="op">(</span><span class="nam">os</span><span class="op">.</span><span class="nam">path</span><span class="op">.</span><span class="nam">realpath</span><span class="op">(</span><span class="nam">__file__</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t16" href="#t16">16</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t17" href="#t17">17</a></span><span class="t"><span class="nam">TEST_CONFIG_PATH</span> <span class="op">=</span> <span class="str">f'{dir_path}/resources/config'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t18" href="#t18">18</a></span><span class="t"><span class="nam">REPORTS_IN_DIRECTORY_PATH</span> <span class="op">=</span> <span class="str">f'{dir_path}/resources/reports'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t19" href="#t19">19</a></span><span class="t"><span class="nam">DATA_IN_DIRECTORY_PATH</span> <span class="op">=</span> <span class="str">f'{dir_path}/resources/'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t20" href="#t20">20</a></span><span class="t"><span class="nam">REPORTS_OUT_DIRECTORY_PATH</span> <span class="op">=</span> <span class="str">f'{dir_path}/test_out'</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t17" href="#t17">17</a></span><span class="t"><span class="nam">TEST_CONFIG_PATH</span> <span class="op">=</span> <span class="str">f"{dir_path}/resources/config"</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t18" href="#t18">18</a></span><span class="t"><span class="nam">REPORTS_IN_DIRECTORY_PATH</span> <span class="op">=</span> <span class="str">f"{dir_path}/resources/reports"</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t19" href="#t19">19</a></span><span class="t"><span class="nam">DATA_IN_DIRECTORY_PATH</span> <span class="op">=</span> <span class="str">f"{dir_path}/resources/"</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t20" href="#t20">20</a></span><span class="t"><span class="nam">REPORTS_OUT_DIRECTORY_PATH</span> <span class="op">=</span> <span class="str">f"{dir_path}/test_out"</span>&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t21" href="#t21">21</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t22" href="#t22">22</a></span><span class="t"><span class="nam">REPORTS_SECTIONS_HEADERS</span> <span class="op">=</span> <span class="op">{</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t23" href="#t23">23</a></span><span class="t">    <span class="str">'RULES'</span><span class="op">:</span> <span class="str">'RULES'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t24" href="#t24">24</a></span><span class="t"><span class="op">}</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t25" href="#t25">25</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t26" href="#t26">26</a></span><span class="t"><span class="nam">DATASETS_PATH</span> <span class="op">=</span> <span class="str">'/resources/data'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t27" href="#t27">27</a></span><span class="t"><span class="nam">EXPERIMENTS_PATH</span> <span class="op">=</span> <span class="str">'/resources/config'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t28" href="#t28">28</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t29" href="#t29">29</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t30" href="#t30">30</a></span><span class="t"><span class="key">def</span> <span class="nam">_fix_missing_values</span><span class="op">(</span><span class="nam">column</span><span class="op">)</span> <span class="op">-></span> <span class="key">None</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t31" href="#t31">31</a></span><span class="t">    <span class="key">for</span> <span class="nam">i</span><span class="op">,</span> <span class="nam">value</span> <span class="key">in</span> <span class="nam">enumerate</span><span class="op">(</span><span class="nam">column</span><span class="op">.</span><span class="nam">values</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t32" href="#t32">32</a></span><span class="t">        <span class="key">if</span> <span class="nam">value</span> <span class="op">==</span> <span class="str">b'?'</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t33" href="#t33">33</a></span><span class="t">            <span class="nam">column</span><span class="op">.</span><span class="nam">values</span><span class="op">[</span><span class="nam">i</span><span class="op">]</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t34" href="#t34">34</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t22" href="#t22">22</a></span><span class="t"><span class="nam">REPORTS_SECTIONS_HEADERS</span> <span class="op">=</span> <span class="op">{</span><span class="str">"RULES"</span><span class="op">:</span> <span class="str">"RULES"</span><span class="op">}</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t23" href="#t23">23</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t24" href="#t24">24</a></span><span class="t"><span class="nam">DATASETS_PATH</span> <span class="op">=</span> <span class="str">"/resources/data"</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t25" href="#t25">25</a></span><span class="t"><span class="nam">EXPERIMENTS_PATH</span> <span class="op">=</span> <span class="str">"/resources/config"</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t26" href="#t26">26</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t27" href="#t27">27</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t28" href="#t28">28</a></span><span class="t"><span class="key">def</span> <span class="nam">_fix_missing_values</span><span class="op">(</span><span class="nam">column</span><span class="op">)</span> <span class="op">-></span> <span class="key">None</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t29" href="#t29">29</a></span><span class="t">    <span class="key">for</span> <span class="nam">i</span><span class="op">,</span> <span class="nam">value</span> <span class="key">in</span> <span class="nam">enumerate</span><span class="op">(</span><span class="nam">column</span><span class="op">.</span><span class="nam">values</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t30" href="#t30">30</a></span><span class="t">        <span class="key">if</span> <span class="nam">value</span> <span class="op">==</span> <span class="str">b"?"</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t31" href="#t31">31</a></span><span class="t">            <span class="nam">column</span><span class="op">.</span><span class="nam">values</span><span class="op">[</span><span class="nam">i</span><span class="op">]</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t32" href="#t32">32</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t33" href="#t33">33</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t34" href="#t34">34</a></span><span class="t"><span class="key">class</span> <span class="nam">ExampleSetWrapper</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t35" href="#t35">35</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t36" href="#t36">36</a></span><span class="t"><span class="key">class</span> <span class="nam">ExampleSetWrapper</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t37" href="#t37">37</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t38" href="#t38">38</a></span><span class="t">    <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">values</span><span class="op">,</span> <span class="nam">labels</span><span class="op">,</span> <span class="nam">problem_type</span><span class="op">:</span> <span class="nam">ProblemType</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t39" href="#t39">39</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">values</span> <span class="op">=</span> <span class="nam">values</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t40" href="#t40">40</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">labels</span> <span class="op">=</span> <span class="nam">labels</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t41" href="#t41">41</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">example_set</span> <span class="op">=</span> <span class="nam">ExampleSetFactory</span><span class="op">(</span><span class="nam">problem_type</span><span class="op">)</span><span class="op">.</span><span class="nam">make</span><span class="op">(</span><span class="nam">values</span><span class="op">,</span> <span class="nam">labels</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t42" href="#t42">42</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t43" href="#t43">43</a></span><span class="t">    <span class="key">def</span> <span class="nam">get_data</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">tuple</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t44" href="#t44">44</a></span><span class="t">        <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">values</span><span class="op">,</span> <span class="nam">self</span><span class="op">.</span><span class="nam">labels</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t45" href="#t45">45</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t46" href="#t46">46</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t47" href="#t47">47</a></span><span class="t"><span class="key">def</span> <span class="nam">load_arff_to_example_set</span><span class="op">(</span><span class="nam">path</span><span class="op">:</span> <span class="nam">str</span><span class="op">,</span> <span class="nam">label_attribute</span><span class="op">:</span> <span class="nam">str</span><span class="op">,</span> <span class="nam">problem_type</span><span class="op">:</span> <span class="nam">ProblemType</span><span class="op">)</span> <span class="op">-></span> <span class="nam">ExampleSetWrapper</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t48" href="#t48">48</a></span><span class="t">    <span class="key">with</span> <span class="nam">open</span><span class="op">(</span><span class="nam">path</span><span class="op">,</span> <span class="str">'r'</span><span class="op">)</span> <span class="key">as</span> <span class="nam">file</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t36" href="#t36">36</a></span><span class="t">    <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">values</span><span class="op">,</span> <span class="nam">labels</span><span class="op">,</span> <span class="nam">problem_type</span><span class="op">:</span> <span class="nam">ProblemType</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t37" href="#t37">37</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">values</span> <span class="op">=</span> <span class="nam">values</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t38" href="#t38">38</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">labels</span> <span class="op">=</span> <span class="nam">labels</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t39" href="#t39">39</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">example_set</span> <span class="op">=</span> <span class="nam">ExampleSetFactory</span><span class="op">(</span><span class="nam">problem_type</span><span class="op">)</span><span class="op">.</span><span class="nam">make</span><span class="op">(</span><span class="nam">values</span><span class="op">,</span> <span class="nam">labels</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t40" href="#t40">40</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t41" href="#t41">41</a></span><span class="t">    <span class="key">def</span> <span class="nam">get_data</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">tuple</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t42" href="#t42">42</a></span><span class="t">        <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">values</span><span class="op">,</span> <span class="nam">self</span><span class="op">.</span><span class="nam">labels</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t43" href="#t43">43</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t44" href="#t44">44</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t45" href="#t45">45</a></span><span class="t"><span class="key">def</span> <span class="nam">load_arff_to_example_set</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t46" href="#t46">46</a></span><span class="t">    <span class="nam">path</span><span class="op">:</span> <span class="nam">str</span><span class="op">,</span> <span class="nam">label_attribute</span><span class="op">:</span> <span class="nam">str</span><span class="op">,</span> <span class="nam">problem_type</span><span class="op">:</span> <span class="nam">ProblemType</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t47" href="#t47">47</a></span><span class="t"><span class="op">)</span> <span class="op">-></span> <span class="nam">ExampleSetWrapper</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t48" href="#t48">48</a></span><span class="t">    <span class="key">with</span> <span class="nam">open</span><span class="op">(</span><span class="nam">path</span><span class="op">,</span> <span class="str">"r"</span><span class="op">)</span> <span class="key">as</span> <span class="nam">file</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
     <p class="run"><span class="n"><a id="t49" href="#t49">49</a></span><span class="t">        <span class="nam">content</span> <span class="op">=</span> <span class="nam">file</span><span class="op">.</span><span class="nam">read</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">replace</span><span class="op">(</span><span class="str">'"'</span><span class="op">,</span> <span class="str">"'"</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
     <p class="run"><span class="n"><a id="t50" href="#t50">50</a></span><span class="t">        <span class="nam">arff_file</span> <span class="op">=</span> <span class="nam">io</span><span class="op">.</span><span class="nam">StringIO</span><span class="op">(</span><span class="nam">content</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
     <p class="run"><span class="n"><a id="t51" href="#t51">51</a></span><span class="t">    <span class="nam">arff_data_frame</span> <span class="op">=</span> <span class="nam">read_arff</span><span class="op">(</span><span class="nam">arff_file</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
@@ -147,7 +147,7 @@ <h2>
     <p class="pln"><span class="n"><a id="t65" href="#t65">65</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t66" href="#t66">66</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
     <p class="run"><span class="n"><a id="t67" href="#t67">67</a></span><span class="t"><span class="key">def</span> <span class="nam">get_dataset_path</span><span class="op">(</span><span class="nam">name</span><span class="op">:</span> <span class="nam">str</span><span class="op">)</span> <span class="op">-></span> <span class="nam">str</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t68" href="#t68">68</a></span><span class="t">    <span class="key">return</span> <span class="str">f'{DATASETS_PATH}/{name}'</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t68" href="#t68">68</a></span><span class="t">    <span class="key">return</span> <span class="str">f"{DATASETS_PATH}/{name}"</span>&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t69" href="#t69">69</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t70" href="#t70">70</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
     <p class="run"><span class="n"><a id="t71" href="#t71">71</a></span><span class="t"><span class="key">class</span> <span class="nam">Knowledge</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
@@ -186,367 +186,376 @@ <h2>
     <p class="run"><span class="n"><a id="t104" href="#t104">104</a></span><span class="t">    <span class="key">def</span> <span class="nam">example_set</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">ExampleSetWrapper</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
     <p class="run"><span class="n"><a id="t105" href="#t105">105</a></span><span class="t">        <span class="key">if</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_example_set</span> <span class="key">is</span> <span class="key">None</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
     <p class="run"><span class="n"><a id="t106" href="#t106">106</a></span><span class="t">            <span class="nam">self</span><span class="op">.</span><span class="nam">_example_set</span> <span class="op">=</span> <span class="nam">load_arff_to_example_set</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t107" href="#t107">107</a></span><span class="t">                <span class="nam">self</span><span class="op">.</span><span class="nam">data_set_file_path</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t108" href="#t108">108</a></span><span class="t">                <span class="nam">self</span><span class="op">.</span><span class="nam">label_attribute</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t109" href="#t109">109</a></span><span class="t">                <span class="nam">self</span><span class="op">.</span><span class="nam">problem_type</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t110" href="#t110">110</a></span><span class="t">            <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t111" href="#t111">111</a></span><span class="t">        <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_example_set</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t112" href="#t112">112</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t113" href="#t113">113</a></span><span class="t">    <span class="op">@</span><span class="nam">property</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t114" href="#t114">114</a></span><span class="t">    <span class="key">def</span> <span class="nam">reference_report</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">TestReport</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t115" href="#t115">115</a></span><span class="t">        <span class="key">if</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_reference_report</span> <span class="key">is</span> <span class="key">None</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t116" href="#t116">116</a></span><span class="t">            <span class="nam">reader</span> <span class="op">=</span> <span class="nam">TestReportReader</span><span class="op">(</span><span class="str">f'{self.report_file_path}.txt'</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t117" href="#t117">117</a></span><span class="t">            <span class="nam">self</span><span class="op">.</span><span class="nam">_reference_report</span> <span class="op">=</span> <span class="nam">reader</span><span class="op">.</span><span class="nam">read</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t118" href="#t118">118</a></span><span class="t">            <span class="nam">reader</span><span class="op">.</span><span class="nam">close</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t119" href="#t119">119</a></span><span class="t">        <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_reference_report</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t120" href="#t120">120</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t107" href="#t107">107</a></span><span class="t">                <span class="nam">self</span><span class="op">.</span><span class="nam">data_set_file_path</span><span class="op">,</span> <span class="nam">self</span><span class="op">.</span><span class="nam">label_attribute</span><span class="op">,</span> <span class="nam">self</span><span class="op">.</span><span class="nam">problem_type</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t108" href="#t108">108</a></span><span class="t">            <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t109" href="#t109">109</a></span><span class="t">        <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_example_set</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t110" href="#t110">110</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t111" href="#t111">111</a></span><span class="t">    <span class="op">@</span><span class="nam">property</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t112" href="#t112">112</a></span><span class="t">    <span class="key">def</span> <span class="nam">reference_report</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">TestReport</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t113" href="#t113">113</a></span><span class="t">        <span class="key">if</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_reference_report</span> <span class="key">is</span> <span class="key">None</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t114" href="#t114">114</a></span><span class="t">            <span class="nam">reader</span> <span class="op">=</span> <span class="nam">TestReportReader</span><span class="op">(</span><span class="str">f"{self.report_file_path}.txt"</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t115" href="#t115">115</a></span><span class="t">            <span class="nam">self</span><span class="op">.</span><span class="nam">_reference_report</span> <span class="op">=</span> <span class="nam">reader</span><span class="op">.</span><span class="nam">read</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t116" href="#t116">116</a></span><span class="t">            <span class="nam">reader</span><span class="op">.</span><span class="nam">close</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t117" href="#t117">117</a></span><span class="t">        <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_reference_report</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t118" href="#t118">118</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t119" href="#t119">119</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t120" href="#t120">120</a></span><span class="t"><span class="key">class</span> <span class="nam">DataSetConfig</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t121" href="#t121">121</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t122" href="#t122">122</a></span><span class="t"><span class="key">class</span> <span class="nam">DataSetConfig</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t123" href="#t123">123</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t124" href="#t124">124</a></span><span class="t">    <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t125" href="#t125">125</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">name</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t126" href="#t126">126</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">label_attribute</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t127" href="#t127">127</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">train_file_name</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t128" href="#t128">128</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">survival_time</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t129" href="#t129">129</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t122" href="#t122">122</a></span><span class="t">    <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t123" href="#t123">123</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">name</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t124" href="#t124">124</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">label_attribute</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t125" href="#t125">125</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">train_file_name</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t126" href="#t126">126</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">survival_time</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t127" href="#t127">127</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t128" href="#t128">128</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t129" href="#t129">129</a></span><span class="t"><span class="key">class</span> <span class="nam">TestConfig</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t130" href="#t130">130</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t131" href="#t131">131</a></span><span class="t"><span class="key">class</span> <span class="nam">TestConfig</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t132" href="#t132">132</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t133" href="#t133">133</a></span><span class="t">    <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t134" href="#t134">134</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">name</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t135" href="#t135">135</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">parameter_configs</span><span class="op">:</span> <span class="nam">dict</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">dict</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">object</span><span class="op">]</span><span class="op">]</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t136" href="#t136">136</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">datasets</span><span class="op">:</span> <span class="nam">list</span><span class="op">[</span><span class="nam">DataSetConfig</span><span class="op">]</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t137" href="#t137">137</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t138" href="#t138">138</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t139" href="#t139">139</a></span><span class="t"><span class="key">class</span> <span class="nam">TestConfigParser</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t140" href="#t140">140</a></span><span class="t">    <span class="nam">TEST_KEY</span> <span class="op">=</span> <span class="str">'test'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t141" href="#t141">141</a></span><span class="t">    <span class="nam">NAME_KEY</span> <span class="op">=</span> <span class="str">'name'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t142" href="#t142">142</a></span><span class="t">    <span class="nam">IN_FILE_KEY</span> <span class="op">=</span> <span class="str">'in_file'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t143" href="#t143">143</a></span><span class="t">    <span class="nam">TRAINING_KEY</span> <span class="op">=</span> <span class="str">'training'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t144" href="#t144">144</a></span><span class="t">    <span class="nam">TRAIN_KEY</span> <span class="op">=</span> <span class="str">'train'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t145" href="#t145">145</a></span><span class="t">    <span class="nam">LABEL_KEY</span> <span class="op">=</span> <span class="str">'label'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t146" href="#t146">146</a></span><span class="t">    <span class="nam">DATASET_KEY</span> <span class="op">=</span> <span class="str">'dataset'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t147" href="#t147">147</a></span><span class="t">    <span class="nam">DATASETS_KEY</span> <span class="op">=</span> <span class="str">'datasets'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t148" href="#t148">148</a></span><span class="t">    <span class="nam">PARAM_KEY</span> <span class="op">=</span> <span class="str">'param'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t149" href="#t149">149</a></span><span class="t">    <span class="nam">PARAMETERS_SET_KEY</span> <span class="op">=</span> <span class="str">'parameter_sets'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t150" href="#t150">150</a></span><span class="t">    <span class="nam">PARAMETERS_KEY</span> <span class="op">=</span> <span class="str">'parameter_set'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t151" href="#t151">151</a></span><span class="t">    <span class="nam">ENTRY_KEY</span> <span class="op">=</span> <span class="str">'entry'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t152" href="#t152">152</a></span><span class="t">    <span class="nam">SURVIVAL_TIME_ROLE</span> <span class="op">=</span> <span class="str">'survival_time'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t153" href="#t153">153</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t154" href="#t154">154</a></span><span class="t">    <span class="nam">EXPERTS_RULES_PARAMETERS_NAMES</span> <span class="op">=</span> <span class="op">[</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t155" href="#t155">155</a></span><span class="t">        <span class="str">'expert_rules'</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t156" href="#t156">156</a></span><span class="t">        <span class="str">'expert_preferred_conditions'</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t157" href="#t157">157</a></span><span class="t">        <span class="str">'expert_forbidden_conditions'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t158" href="#t158">158</a></span><span class="t">    <span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t159" href="#t159">159</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t160" href="#t160">160</a></span><span class="t">    <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t161" href="#t161">161</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">tests_configs</span><span class="op">:</span> <span class="nam">dict</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">TestConfig</span><span class="op">]</span> <span class="op">=</span> <span class="op">{</span><span class="op">}</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t162" href="#t162">162</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">root</span><span class="op">:</span> <span class="nam">ElementTree</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t163" href="#t163">163</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t164" href="#t164">164</a></span><span class="t">    <span class="key">def</span> <span class="nam">_parse_survival_time</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">element</span><span class="op">)</span> <span class="op">-></span> <span class="nam">Union</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="key">None</span><span class="op">]</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t165" href="#t165">165</a></span><span class="t">        <span class="nam">survival_time_element</span> <span class="op">=</span> <span class="nam">element</span><span class="op">.</span><span class="nam">find</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t166" href="#t166">166</a></span><span class="t">            <span class="nam">TestConfigParser</span><span class="op">.</span><span class="nam">SURVIVAL_TIME_ROLE</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t167" href="#t167">167</a></span><span class="t">        <span class="key">if</span> <span class="nam">element</span><span class="op">.</span><span class="nam">find</span><span class="op">(</span><span class="nam">TestConfigParser</span><span class="op">.</span><span class="nam">SURVIVAL_TIME_ROLE</span><span class="op">)</span> <span class="key">is</span> <span class="key">not</span> <span class="key">None</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t168" href="#t168">168</a></span><span class="t">            <span class="key">return</span> <span class="nam">survival_time_element</span><span class="op">.</span><span class="nam">text</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t169" href="#t169">169</a></span><span class="t">        <span class="key">else</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t170" href="#t170">170</a></span><span class="t">            <span class="key">return</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t171" href="#t171">171</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t172" href="#t172">172</a></span><span class="t">    <span class="key">def</span> <span class="nam">_parse_experts_rules_parameters</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">elements</span><span class="op">)</span> <span class="op">-></span> <span class="nam">list</span><span class="op">[</span><span class="nam">tuple</span><span class="op">]</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t173" href="#t173">173</a></span><span class="t">        <span class="nam">expert_rules</span> <span class="op">=</span> <span class="op">[</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t174" href="#t174">174</a></span><span class="t">        <span class="key">for</span> <span class="nam">element</span> <span class="key">in</span> <span class="nam">elements</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t175" href="#t175">175</a></span><span class="t">            <span class="nam">rule_name</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="nam">element</span><span class="op">.</span><span class="nam">attrib</span><span class="op">[</span><span class="str">'name'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t176" href="#t176">176</a></span><span class="t">            <span class="nam">rule_content</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="nam">element</span><span class="op">.</span><span class="nam">text</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t177" href="#t177">177</a></span><span class="t">            <span class="com"># RuleKit originally used XML for specifying parameters and uses special xml characters</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t178" href="#t178">178</a></span><span class="t">            <span class="nam">rule_content</span> <span class="op">=</span> <span class="nam">rule_content</span><span class="op">.</span><span class="nam">replace</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t179" href="#t179">179</a></span><span class="t">                <span class="str">'&amp;lt;'</span><span class="op">,</span> <span class="str">'&lt;'</span><span class="op">)</span><span class="op">.</span><span class="nam">replace</span><span class="op">(</span><span class="str">'&amp;gt;'</span><span class="op">,</span> <span class="str">'>'</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t180" href="#t180">180</a></span><span class="t">            <span class="nam">expert_rules</span><span class="op">.</span><span class="nam">append</span><span class="op">(</span><span class="op">(</span><span class="nam">rule_name</span><span class="op">,</span> <span class="nam">rule_content</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t181" href="#t181">181</a></span><span class="t">        <span class="key">return</span> <span class="nam">expert_rules</span> <span class="key">if</span> <span class="nam">len</span><span class="op">(</span><span class="nam">expert_rules</span><span class="op">)</span> <span class="op">></span> <span class="num">0</span> <span class="key">else</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t182" href="#t182">182</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t183" href="#t183">183</a></span><span class="t">    <span class="key">def</span> <span class="nam">_check_ambigous_data_sets_names</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">data_sets_configs</span><span class="op">:</span> <span class="nam">list</span><span class="op">[</span><span class="nam">DataSetConfig</span><span class="op">]</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t184" href="#t184">184</a></span><span class="t">        <span class="nam">dictionary</span> <span class="op">=</span> <span class="op">{</span><span class="op">}</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t185" href="#t185">185</a></span><span class="t">        <span class="key">for</span> <span class="nam">element</span> <span class="key">in</span> <span class="nam">data_sets_configs</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t186" href="#t186">186</a></span><span class="t">            <span class="nam">dictionary</span><span class="op">[</span><span class="nam">element</span><span class="op">.</span><span class="nam">name</span><span class="op">]</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t187" href="#t187">187</a></span><span class="t">        <span class="key">if</span> <span class="nam">len</span><span class="op">(</span><span class="nam">dictionary</span><span class="op">.</span><span class="nam">keys</span><span class="op">(</span><span class="op">)</span><span class="op">)</span> <span class="op">&lt;</span> <span class="nam">len</span><span class="op">(</span><span class="nam">data_sets_configs</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t188" href="#t188">188</a></span><span class="t">            <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span><span class="str">'Datasets are ambigous'</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t189" href="#t189">189</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t190" href="#t190">190</a></span><span class="t">    <span class="key">def</span> <span class="nam">_parse_data_set</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">element</span><span class="op">)</span> <span class="op">-></span> <span class="nam">DataSetConfig</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t191" href="#t191">191</a></span><span class="t">        <span class="nam">data_set_config</span> <span class="op">=</span> <span class="nam">DataSetConfig</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t192" href="#t192">192</a></span><span class="t">        <span class="nam">data_set_config</span><span class="op">.</span><span class="nam">label_attribute</span> <span class="op">=</span> <span class="nam">element</span><span class="op">.</span><span class="nam">find</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t193" href="#t193">193</a></span><span class="t">            <span class="nam">TestConfigParser</span><span class="op">.</span><span class="nam">LABEL_KEY</span><span class="op">)</span><span class="op">.</span><span class="nam">text</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t194" href="#t194">194</a></span><span class="t">        <span class="nam">train_element</span> <span class="op">=</span> <span class="nam">element</span><span class="op">.</span><span class="nam">find</span><span class="op">(</span><span class="nam">TestConfigParser</span><span class="op">.</span><span class="nam">TRAINING_KEY</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t195" href="#t195">195</a></span><span class="t">        <span class="nam">train_element</span> <span class="op">=</span> <span class="nam">train_element</span><span class="op">.</span><span class="nam">find</span><span class="op">(</span><span class="nam">TestConfigParser</span><span class="op">.</span><span class="nam">TRAIN_KEY</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t196" href="#t196">196</a></span><span class="t">        <span class="nam">data_set_config</span><span class="op">.</span><span class="nam">train_file_name</span> <span class="op">=</span> <span class="nam">train_element</span><span class="op">.</span><span class="nam">find</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t197" href="#t197">197</a></span><span class="t">            <span class="nam">TestConfigParser</span><span class="op">.</span><span class="nam">IN_FILE_KEY</span><span class="op">)</span><span class="op">.</span><span class="nam">text</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t198" href="#t198">198</a></span><span class="t">        <span class="nam">data_set_config</span><span class="op">.</span><span class="nam">name</span> <span class="op">=</span> <span class="nam">element</span><span class="op">.</span><span class="nam">attrib</span><span class="op">.</span><span class="nam">get</span><span class="op">(</span><span class="str">'name'</span><span class="op">,</span> <span class="key">None</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t199" href="#t199">199</a></span><span class="t">        <span class="key">if</span> <span class="nam">data_set_config</span><span class="op">.</span><span class="nam">name</span> <span class="key">is</span> <span class="key">None</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t200" href="#t200">200</a></span><span class="t">            <span class="nam">file_name</span> <span class="op">=</span> <span class="nam">os</span><span class="op">.</span><span class="nam">path</span><span class="op">.</span><span class="nam">basename</span><span class="op">(</span><span class="nam">data_set_config</span><span class="op">.</span><span class="nam">train_file_name</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t201" href="#t201">201</a></span><span class="t">            <span class="nam">data_set_config</span><span class="op">.</span><span class="nam">name</span> <span class="op">=</span> <span class="nam">file_name</span><span class="op">.</span><span class="nam">split</span><span class="op">(</span><span class="str">'.'</span><span class="op">)</span><span class="op">[</span><span class="num">0</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t202" href="#t202">202</a></span><span class="t">        <span class="nam">data_set_config</span><span class="op">.</span><span class="nam">survival_time</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_parse_survival_time</span><span class="op">(</span><span class="nam">element</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t203" href="#t203">203</a></span><span class="t">        <span class="key">return</span> <span class="nam">data_set_config</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t204" href="#t204">204</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t205" href="#t205">205</a></span><span class="t">    <span class="key">def</span> <span class="nam">_parse_data_sets</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">element</span><span class="op">)</span> <span class="op">-></span> <span class="nam">list</span><span class="op">[</span><span class="nam">DataSetConfig</span><span class="op">]</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t206" href="#t206">206</a></span><span class="t">        <span class="nam">data_set_configs</span> <span class="op">=</span> <span class="op">[</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t207" href="#t207">207</a></span><span class="t">        <span class="nam">node</span> <span class="op">=</span> <span class="nam">element</span><span class="op">.</span><span class="nam">find</span><span class="op">(</span><span class="nam">TestConfigParser</span><span class="op">.</span><span class="nam">DATASETS_KEY</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t208" href="#t208">208</a></span><span class="t">        <span class="key">for</span> <span class="nam">element</span> <span class="key">in</span> <span class="nam">node</span><span class="op">.</span><span class="nam">findall</span><span class="op">(</span><span class="nam">TestConfigParser</span><span class="op">.</span><span class="nam">DATASET_KEY</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t209" href="#t209">209</a></span><span class="t">            <span class="nam">data_set_configs</span><span class="op">.</span><span class="nam">append</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">_parse_data_set</span><span class="op">(</span><span class="nam">element</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t210" href="#t210">210</a></span><span class="t">        <span class="key">return</span> <span class="nam">data_set_configs</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t211" href="#t211">211</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t212" href="#t212">212</a></span><span class="t">    <span class="key">def</span> <span class="nam">parse_test_parameters</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">element</span><span class="op">)</span> <span class="op">-></span> <span class="nam">dict</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">object</span><span class="op">]</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t213" href="#t213">213</a></span><span class="t">        <span class="nam">params</span> <span class="op">=</span> <span class="op">{</span><span class="op">}</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t214" href="#t214">214</a></span><span class="t">        <span class="key">for</span> <span class="nam">param_node</span> <span class="key">in</span> <span class="nam">element</span><span class="op">.</span><span class="nam">findall</span><span class="op">(</span><span class="nam">TestConfigParser</span><span class="op">.</span><span class="nam">PARAM_KEY</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t215" href="#t215">215</a></span><span class="t">            <span class="nam">name</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="nam">param_node</span><span class="op">.</span><span class="nam">attrib</span><span class="op">[</span><span class="str">'name'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t216" href="#t216">216</a></span><span class="t">            <span class="key">if</span> <span class="nam">name</span> <span class="key">in</span> <span class="nam">TestConfigParser</span><span class="op">.</span><span class="nam">EXPERTS_RULES_PARAMETERS_NAMES</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t217" href="#t217">217</a></span><span class="t">                <span class="nam">value</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_parse_experts_rules_parameters</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t218" href="#t218">218</a></span><span class="t">                    <span class="nam">param_node</span><span class="op">.</span><span class="nam">findall</span><span class="op">(</span><span class="nam">TestConfigParser</span><span class="op">.</span><span class="nam">ENTRY_KEY</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t219" href="#t219">219</a></span><span class="t">            <span class="key">else</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t220" href="#t220">220</a></span><span class="t">                <span class="nam">value</span> <span class="op">=</span> <span class="nam">param_node</span><span class="op">.</span><span class="nam">text</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t221" href="#t221">221</a></span><span class="t">            <span class="nam">params</span><span class="op">[</span><span class="nam">name</span><span class="op">]</span> <span class="op">=</span> <span class="nam">value</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t222" href="#t222">222</a></span><span class="t">        <span class="key">return</span> <span class="nam">params</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t223" href="#t223">223</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t224" href="#t224">224</a></span><span class="t">    <span class="key">def</span> <span class="nam">_parse_test_parameters_sets</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">element</span><span class="op">)</span> <span class="op">-></span> <span class="nam">dict</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">dict</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">object</span><span class="op">]</span><span class="op">]</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t225" href="#t225">225</a></span><span class="t">        <span class="nam">parameters_sets</span> <span class="op">=</span> <span class="op">{</span><span class="op">}</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t226" href="#t226">226</a></span><span class="t">        <span class="nam">params_sets_node</span> <span class="op">=</span> <span class="nam">element</span><span class="op">.</span><span class="nam">findall</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t227" href="#t227">227</a></span><span class="t">            <span class="nam">TestConfigParser</span><span class="op">.</span><span class="nam">PARAMETERS_SET_KEY</span><span class="op">)</span><span class="op">[</span><span class="num">0</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t228" href="#t228">228</a></span><span class="t">        <span class="key">for</span> <span class="nam">param_set</span> <span class="key">in</span> <span class="nam">params_sets_node</span><span class="op">.</span><span class="nam">findall</span><span class="op">(</span><span class="nam">TestConfigParser</span><span class="op">.</span><span class="nam">PARAMETERS_KEY</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t229" href="#t229">229</a></span><span class="t">            <span class="nam">name</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="nam">param_set</span><span class="op">.</span><span class="nam">attrib</span><span class="op">[</span><span class="str">'name'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t230" href="#t230">230</a></span><span class="t">            <span class="nam">parameters_sets</span><span class="op">[</span><span class="nam">name</span><span class="op">]</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">parse_test_parameters</span><span class="op">(</span><span class="nam">param_set</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t231" href="#t231">231</a></span><span class="t">        <span class="key">return</span> <span class="nam">parameters_sets</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t232" href="#t232">232</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t233" href="#t233">233</a></span><span class="t">    <span class="key">def</span> <span class="nam">_parse_test</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">element</span><span class="op">)</span> <span class="op">-></span> <span class="nam">TestConfig</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t234" href="#t234">234</a></span><span class="t">        <span class="nam">test_config</span> <span class="op">=</span> <span class="nam">TestConfig</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t235" href="#t235">235</a></span><span class="t">        <span class="nam">test_config</span><span class="op">.</span><span class="nam">parameter_configs</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_parse_test_parameters_sets</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t236" href="#t236">236</a></span><span class="t">            <span class="nam">element</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t237" href="#t237">237</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t238" href="#t238">238</a></span><span class="t">        <span class="nam">test_config</span><span class="op">.</span><span class="nam">datasets</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_parse_data_sets</span><span class="op">(</span><span class="nam">element</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t239" href="#t239">239</a></span><span class="t">        <span class="nam">test_config</span><span class="op">.</span><span class="nam">name</span> <span class="op">=</span> <span class="nam">element</span><span class="op">.</span><span class="nam">attrib</span><span class="op">[</span><span class="str">'name'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t240" href="#t240">240</a></span><span class="t">        <span class="key">return</span> <span class="nam">test_config</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t241" href="#t241">241</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t242" href="#t242">242</a></span><span class="t">    <span class="key">def</span> <span class="nam">parse</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">file_path</span><span class="op">:</span> <span class="nam">str</span><span class="op">)</span> <span class="op">-></span> <span class="nam">dict</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">TestConfig</span><span class="op">]</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t243" href="#t243">243</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">tests_configs</span> <span class="op">=</span> <span class="op">{</span><span class="op">}</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t244" href="#t244">244</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">root</span> <span class="op">=</span> <span class="nam">ElementTree</span><span class="op">.</span><span class="nam">parse</span><span class="op">(</span><span class="nam">file_path</span><span class="op">)</span><span class="op">.</span><span class="nam">getroot</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t245" href="#t245">245</a></span><span class="t">        <span class="key">if</span> <span class="nam">self</span><span class="op">.</span><span class="nam">root</span><span class="op">.</span><span class="nam">tag</span> <span class="op">==</span> <span class="str">'test'</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t246" href="#t246">246</a></span><span class="t">            <span class="nam">test_elements</span> <span class="op">=</span> <span class="op">[</span><span class="nam">self</span><span class="op">.</span><span class="nam">root</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t247" href="#t247">247</a></span><span class="t">        <span class="key">else</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t248" href="#t248">248</a></span><span class="t">            <span class="nam">test_elements</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">root</span><span class="op">.</span><span class="nam">findall</span><span class="op">(</span><span class="nam">TestConfigParser</span><span class="op">.</span><span class="nam">TEST_KEY</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t249" href="#t249">249</a></span><span class="t">        <span class="key">for</span> <span class="nam">test_element</span> <span class="key">in</span> <span class="nam">test_elements</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t250" href="#t250">250</a></span><span class="t">            <span class="nam">test_config</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_parse_test</span><span class="op">(</span><span class="nam">test_element</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t251" href="#t251">251</a></span><span class="t">            <span class="nam">self</span><span class="op">.</span><span class="nam">tests_configs</span><span class="op">[</span><span class="nam">test_config</span><span class="op">.</span><span class="nam">name</span><span class="op">]</span> <span class="op">=</span> <span class="nam">test_config</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t252" href="#t252">252</a></span><span class="t">        <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">tests_configs</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t253" href="#t253">253</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t254" href="#t254">254</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t255" href="#t255">255</a></span><span class="t"><span class="key">class</span> <span class="nam">TestCaseFactory</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t256" href="#t256">256</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t257" href="#t257">257</a></span><span class="t">    <span class="key">def</span> <span class="nam">_make_test_case</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t258" href="#t258">258</a></span><span class="t">            <span class="nam">self</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t259" href="#t259">259</a></span><span class="t">            <span class="nam">test_case_name</span><span class="op">:</span> <span class="nam">str</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t260" href="#t260">260</a></span><span class="t">            <span class="nam">params</span><span class="op">:</span> <span class="nam">dict</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">object</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t261" href="#t261">261</a></span><span class="t">            <span class="nam">data_set_config</span><span class="op">:</span> <span class="nam">DataSetConfig</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t262" href="#t262">262</a></span><span class="t">            <span class="nam">problem_type</span><span class="op">:</span> <span class="nam">ProblemType</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t263" href="#t263">263</a></span><span class="t">    <span class="op">)</span> <span class="op">-></span> <span class="nam">TestCase</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t264" href="#t264">264</a></span><span class="t">        <span class="nam">test_case</span> <span class="op">=</span> <span class="nam">TestCase</span><span class="op">(</span><span class="nam">problem_type</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t265" href="#t265">265</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_fix_params_typing</span><span class="op">(</span><span class="nam">params</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t266" href="#t266">266</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_fix_deprecated_params</span><span class="op">(</span><span class="nam">params</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t267" href="#t267">267</a></span><span class="t">        <span class="nam">test_case</span><span class="op">.</span><span class="nam">induction_params</span> <span class="op">=</span> <span class="nam">params</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t268" href="#t268">268</a></span><span class="t">        <span class="nam">test_case</span><span class="op">.</span><span class="nam">data_set_file_path</span> <span class="op">=</span> <span class="str">f'{DATA_IN_DIRECTORY_PATH}/{data_set_config.train_file_name}'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t269" href="#t269">269</a></span><span class="t">        <span class="nam">test_case</span><span class="op">.</span><span class="nam">label_attribute</span> <span class="op">=</span> <span class="nam">data_set_config</span><span class="op">.</span><span class="nam">label_attribute</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t270" href="#t270">270</a></span><span class="t">        <span class="nam">test_case</span><span class="op">.</span><span class="nam">name</span> <span class="op">=</span> <span class="nam">test_case_name</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t271" href="#t271">271</a></span><span class="t">        <span class="nam">test_case</span><span class="op">.</span><span class="nam">param_config</span> <span class="op">=</span> <span class="nam">params</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t272" href="#t272">272</a></span><span class="t">        <span class="key">return</span> <span class="nam">test_case</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t273" href="#t273">273</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t274" href="#t274">274</a></span><span class="t">    <span class="key">def</span> <span class="nam">_fix_deprecated_params</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">params</span><span class="op">:</span> <span class="nam">dict</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">object</span><span class="op">]</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t275" href="#t275">275</a></span><span class="t">        <span class="nam">deprecated_minsupp_new_name</span> <span class="op">=</span> <span class="str">'min_rule_covered'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t276" href="#t276">276</a></span><span class="t">        <span class="key">if</span> <span class="nam">deprecated_minsupp_new_name</span> <span class="key">in</span> <span class="nam">params</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t277" href="#t277">277</a></span><span class="t">            <span class="nam">params</span><span class="op">[</span><span class="str">'minsupp_new'</span><span class="op">]</span> <span class="op">=</span> <span class="nam">params</span><span class="op">.</span><span class="nam">pop</span><span class="op">(</span><span class="nam">deprecated_minsupp_new_name</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t278" href="#t278">278</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t279" href="#t279">279</a></span><span class="t">    <span class="key">def</span> <span class="nam">_fix_params_typing</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">params</span><span class="op">:</span> <span class="nam">dict</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t280" href="#t280">280</a></span><span class="t">        <span class="key">for</span> <span class="nam">key</span><span class="op">,</span> <span class="nam">value</span> <span class="key">in</span> <span class="nam">params</span><span class="op">.</span><span class="nam">items</span><span class="op">(</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t281" href="#t281">281</a></span><span class="t">            <span class="key">if</span> <span class="nam">value</span> <span class="op">==</span> <span class="str">'false'</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t282" href="#t282">282</a></span><span class="t">                <span class="nam">params</span><span class="op">[</span><span class="nam">key</span><span class="op">]</span> <span class="op">=</span> <span class="key">False</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t283" href="#t283">283</a></span><span class="t">                <span class="key">continue</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t284" href="#t284">284</a></span><span class="t">            <span class="key">if</span> <span class="nam">value</span> <span class="op">==</span> <span class="str">'true'</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t285" href="#t285">285</a></span><span class="t">                <span class="nam">params</span><span class="op">[</span><span class="nam">key</span><span class="op">]</span> <span class="op">=</span> <span class="key">True</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t286" href="#t286">286</a></span><span class="t">                <span class="key">continue</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t287" href="#t287">287</a></span><span class="t">            <span class="key">if</span> <span class="key">not</span> <span class="str">'measure'</span> <span class="key">in</span> <span class="nam">key</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t288" href="#t288">288</a></span><span class="t">                <span class="nam">params</span><span class="op">[</span><span class="nam">key</span><span class="op">]</span> <span class="op">=</span> <span class="nam">int</span><span class="op">(</span><span class="nam">float</span><span class="op">(</span><span class="nam">value</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t289" href="#t289">289</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t290" href="#t290">290</a></span><span class="t">    <span class="key">def</span> <span class="nam">make</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t291" href="#t291">291</a></span><span class="t">        <span class="nam">self</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t292" href="#t292">292</a></span><span class="t">        <span class="nam">tests_configs</span><span class="op">:</span> <span class="nam">dict</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">TestConfig</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t293" href="#t293">293</a></span><span class="t">        <span class="nam">report_dir_path</span><span class="op">:</span> <span class="nam">str</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t294" href="#t294">294</a></span><span class="t">        <span class="nam">problem_type</span><span class="op">:</span> <span class="nam">ProblemType</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t295" href="#t295">295</a></span><span class="t">    <span class="op">)</span> <span class="op">-></span> <span class="nam">list</span><span class="op">[</span><span class="nam">TestCase</span><span class="op">]</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t296" href="#t296">296</a></span><span class="t">        <span class="nam">test_cases</span> <span class="op">=</span> <span class="op">[</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t297" href="#t297">297</a></span><span class="t">        <span class="key">for</span> <span class="nam">key</span> <span class="key">in</span> <span class="nam">tests_configs</span><span class="op">.</span><span class="nam">keys</span><span class="op">(</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t298" href="#t298">298</a></span><span class="t">            <span class="nam">test_config</span> <span class="op">=</span> <span class="nam">tests_configs</span><span class="op">[</span><span class="nam">key</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t299" href="#t299">299</a></span><span class="t">            <span class="key">for</span> <span class="nam">config_name</span> <span class="key">in</span> <span class="nam">test_config</span><span class="op">.</span><span class="nam">parameter_configs</span><span class="op">.</span><span class="nam">keys</span><span class="op">(</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t300" href="#t300">300</a></span><span class="t">                <span class="key">for</span> <span class="nam">data_set_config</span> <span class="key">in</span> <span class="nam">test_config</span><span class="op">.</span><span class="nam">datasets</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t301" href="#t301">301</a></span><span class="t">                    <span class="nam">params</span> <span class="op">=</span> <span class="nam">test_config</span><span class="op">.</span><span class="nam">parameter_configs</span><span class="op">[</span><span class="nam">config_name</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t302" href="#t302">302</a></span><span class="t">                    <span class="nam">test_case_name</span> <span class="op">=</span> <span class="str">f'{key}.{config_name}.{data_set_config.name}'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t303" href="#t303">303</a></span><span class="t">                    <span class="nam">test_config</span><span class="op">.</span><span class="nam">parameter_configs</span><span class="op">[</span><span class="nam">config_name</span><span class="op">]</span><span class="op">.</span><span class="nam">pop</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t304" href="#t304">304</a></span><span class="t">                        <span class="str">'use_expert'</span><span class="op">,</span> <span class="key">None</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t305" href="#t305">305</a></span><span class="t">                    <span class="nam">expert_rules</span> <span class="op">=</span> <span class="nam">test_config</span><span class="op">.</span><span class="nam">parameter_configs</span><span class="op">[</span><span class="nam">config_name</span><span class="op">]</span><span class="op">.</span><span class="nam">pop</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t306" href="#t306">306</a></span><span class="t">                        <span class="str">'expert_rules'</span><span class="op">,</span> <span class="key">None</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t307" href="#t307">307</a></span><span class="t">                    <span class="nam">preferred_conditions</span> <span class="op">=</span> <span class="nam">test_config</span><span class="op">.</span><span class="nam">parameter_configs</span><span class="op">[</span><span class="nam">config_name</span><span class="op">]</span><span class="op">.</span><span class="nam">pop</span><span class="op">(</span><span class="str">'expert_preferred_conditions'</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t308" href="#t308">308</a></span><span class="t">                                                                                          <span class="key">None</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t309" href="#t309">309</a></span><span class="t">                    <span class="nam">forbidden_conditions</span> <span class="op">=</span> <span class="nam">test_config</span><span class="op">.</span><span class="nam">parameter_configs</span><span class="op">[</span><span class="nam">config_name</span><span class="op">]</span><span class="op">.</span><span class="nam">pop</span><span class="op">(</span><span class="str">'expert_forbidden_conditions'</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t310" href="#t310">310</a></span><span class="t">                                                                                          <span class="key">None</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t311" href="#t311">311</a></span><span class="t">                    <span class="nam">test_case</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_make_test_case</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t312" href="#t312">312</a></span><span class="t">                        <span class="nam">test_case_name</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t313" href="#t313">313</a></span><span class="t">                        <span class="nam">test_config</span><span class="op">.</span><span class="nam">parameter_configs</span><span class="op">[</span><span class="nam">config_name</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t314" href="#t314">314</a></span><span class="t">                        <span class="nam">data_set_config</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t315" href="#t315">315</a></span><span class="t">                        <span class="nam">problem_type</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t316" href="#t316">316</a></span><span class="t">                    <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t317" href="#t317">317</a></span><span class="t">                    <span class="key">if</span> <span class="str">'use_report'</span> <span class="key">in</span> <span class="nam">params</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t318" href="#t318">318</a></span><span class="t">                        <span class="nam">report_file_name</span> <span class="op">=</span> <span class="nam">params</span><span class="op">[</span><span class="str">'use_report'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t319" href="#t319">319</a></span><span class="t">                        <span class="nam">test_case</span><span class="op">.</span><span class="nam">using_existing_report_file</span> <span class="op">=</span> <span class="key">True</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t320" href="#t320">320</a></span><span class="t">                    <span class="key">else</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t321" href="#t321">321</a></span><span class="t">                        <span class="nam">report_file_name</span> <span class="op">=</span> <span class="nam">test_case_name</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t322" href="#t322">322</a></span><span class="t">                    <span class="nam">report_path</span> <span class="op">=</span> <span class="str">f'{report_dir_path}/{report_file_name}'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t323" href="#t323">323</a></span><span class="t">                    <span class="nam">test_case</span><span class="op">.</span><span class="nam">report_file_path</span> <span class="op">=</span> <span class="nam">report_path</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t324" href="#t324">324</a></span><span class="t">                    <span class="nam">test_case</span><span class="op">.</span><span class="nam">survival_time</span> <span class="op">=</span> <span class="nam">data_set_config</span><span class="op">.</span><span class="nam">survival_time</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t325" href="#t325">325</a></span><span class="t">                    <span class="key">if</span> <span class="nam">expert_rules</span> <span class="key">is</span> <span class="key">not</span> <span class="key">None</span> <span class="key">or</span> <span class="nam">preferred_conditions</span> <span class="key">is</span> <span class="key">not</span> <span class="key">None</span> <span class="key">or</span> <span class="nam">forbidden_conditions</span> <span class="key">is</span> <span class="key">not</span> <span class="key">None</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t326" href="#t326">326</a></span><span class="t">                        <span class="nam">test_case</span><span class="op">.</span><span class="nam">knowledge</span> <span class="op">=</span> <span class="nam">Knowledge</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t327" href="#t327">327</a></span><span class="t">                        <span class="key">if</span> <span class="nam">expert_rules</span> <span class="key">is</span> <span class="key">not</span> <span class="key">None</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t328" href="#t328">328</a></span><span class="t">                            <span class="nam">test_case</span><span class="op">.</span><span class="nam">knowledge</span><span class="op">.</span><span class="nam">expert_rules</span> <span class="op">=</span> <span class="nam">expert_rules</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t329" href="#t329">329</a></span><span class="t">                        <span class="key">if</span> <span class="nam">forbidden_conditions</span> <span class="key">is</span> <span class="key">not</span> <span class="key">None</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t330" href="#t330">330</a></span><span class="t">                            <span class="nam">test_case</span><span class="op">.</span><span class="nam">knowledge</span><span class="op">.</span><span class="nam">expert_forbidden_conditions</span> <span class="op">=</span> <span class="nam">forbidden_conditions</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t331" href="#t331">331</a></span><span class="t">                        <span class="key">if</span> <span class="nam">preferred_conditions</span> <span class="key">is</span> <span class="key">not</span> <span class="key">None</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t332" href="#t332">332</a></span><span class="t">                            <span class="nam">test_case</span><span class="op">.</span><span class="nam">knowledge</span><span class="op">.</span><span class="nam">expert_preferred_conditions</span> <span class="op">=</span> <span class="nam">preferred_conditions</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t333" href="#t333">333</a></span><span class="t">                    <span class="nam">test_cases</span><span class="op">.</span><span class="nam">append</span><span class="op">(</span><span class="nam">test_case</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t334" href="#t334">334</a></span><span class="t">        <span class="key">return</span> <span class="nam">test_cases</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t335" href="#t335">335</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t336" href="#t336">336</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t337" href="#t337">337</a></span><span class="t"><span class="key">def</span> <span class="nam">get_rule_string</span><span class="op">(</span><span class="nam">rule</span><span class="op">)</span> <span class="op">-></span> <span class="nam">str</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t338" href="#t338">338</a></span><span class="t">    <span class="key">return</span> <span class="nam">re</span><span class="op">.</span><span class="nam">sub</span><span class="op">(</span><span class="str">r'(\\[[^\\]]*\\]$)|(\\([^\\)]*\\)$)'</span><span class="op">,</span> <span class="str">''</span><span class="op">,</span> <span class="nam">str</span><span class="op">(</span><span class="nam">rule</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t339" href="#t339">339</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t340" href="#t340">340</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t341" href="#t341">341</a></span><span class="t"><span class="key">class</span> <span class="nam">TestReportReader</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t131" href="#t131">131</a></span><span class="t">    <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t132" href="#t132">132</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">name</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t133" href="#t133">133</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">parameter_configs</span><span class="op">:</span> <span class="nam">dict</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">dict</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">object</span><span class="op">]</span><span class="op">]</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t134" href="#t134">134</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">datasets</span><span class="op">:</span> <span class="nam">list</span><span class="op">[</span><span class="nam">DataSetConfig</span><span class="op">]</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t135" href="#t135">135</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t136" href="#t136">136</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t137" href="#t137">137</a></span><span class="t"><span class="key">class</span> <span class="nam">TestConfigParser</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t138" href="#t138">138</a></span><span class="t">    <span class="nam">TEST_KEY</span> <span class="op">=</span> <span class="str">"test"</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t139" href="#t139">139</a></span><span class="t">    <span class="nam">NAME_KEY</span> <span class="op">=</span> <span class="str">"name"</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t140" href="#t140">140</a></span><span class="t">    <span class="nam">IN_FILE_KEY</span> <span class="op">=</span> <span class="str">"in_file"</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t141" href="#t141">141</a></span><span class="t">    <span class="nam">TRAINING_KEY</span> <span class="op">=</span> <span class="str">"training"</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t142" href="#t142">142</a></span><span class="t">    <span class="nam">TRAIN_KEY</span> <span class="op">=</span> <span class="str">"train"</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t143" href="#t143">143</a></span><span class="t">    <span class="nam">LABEL_KEY</span> <span class="op">=</span> <span class="str">"label"</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t144" href="#t144">144</a></span><span class="t">    <span class="nam">DATASET_KEY</span> <span class="op">=</span> <span class="str">"dataset"</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t145" href="#t145">145</a></span><span class="t">    <span class="nam">DATASETS_KEY</span> <span class="op">=</span> <span class="str">"datasets"</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t146" href="#t146">146</a></span><span class="t">    <span class="nam">PARAM_KEY</span> <span class="op">=</span> <span class="str">"param"</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t147" href="#t147">147</a></span><span class="t">    <span class="nam">PARAMETERS_SET_KEY</span> <span class="op">=</span> <span class="str">"parameter_sets"</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t148" href="#t148">148</a></span><span class="t">    <span class="nam">PARAMETERS_KEY</span> <span class="op">=</span> <span class="str">"parameter_set"</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t149" href="#t149">149</a></span><span class="t">    <span class="nam">ENTRY_KEY</span> <span class="op">=</span> <span class="str">"entry"</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t150" href="#t150">150</a></span><span class="t">    <span class="nam">SURVIVAL_TIME_ROLE</span> <span class="op">=</span> <span class="str">"survival_time"</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t151" href="#t151">151</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t152" href="#t152">152</a></span><span class="t">    <span class="nam">EXPERTS_RULES_PARAMETERS_NAMES</span> <span class="op">=</span> <span class="op">[</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t153" href="#t153">153</a></span><span class="t">        <span class="str">"expert_rules"</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t154" href="#t154">154</a></span><span class="t">        <span class="str">"expert_preferred_conditions"</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t155" href="#t155">155</a></span><span class="t">        <span class="str">"expert_forbidden_conditions"</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t156" href="#t156">156</a></span><span class="t">    <span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t157" href="#t157">157</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t158" href="#t158">158</a></span><span class="t">    <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t159" href="#t159">159</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">tests_configs</span><span class="op">:</span> <span class="nam">dict</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">TestConfig</span><span class="op">]</span> <span class="op">=</span> <span class="op">{</span><span class="op">}</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t160" href="#t160">160</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">root</span><span class="op">:</span> <span class="nam">ElementTree</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t161" href="#t161">161</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t162" href="#t162">162</a></span><span class="t">    <span class="key">def</span> <span class="nam">_parse_survival_time</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">element</span><span class="op">)</span> <span class="op">-></span> <span class="nam">Union</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="key">None</span><span class="op">]</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t163" href="#t163">163</a></span><span class="t">        <span class="nam">survival_time_element</span> <span class="op">=</span> <span class="nam">element</span><span class="op">.</span><span class="nam">find</span><span class="op">(</span><span class="nam">TestConfigParser</span><span class="op">.</span><span class="nam">SURVIVAL_TIME_ROLE</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t164" href="#t164">164</a></span><span class="t">        <span class="key">if</span> <span class="nam">element</span><span class="op">.</span><span class="nam">find</span><span class="op">(</span><span class="nam">TestConfigParser</span><span class="op">.</span><span class="nam">SURVIVAL_TIME_ROLE</span><span class="op">)</span> <span class="key">is</span> <span class="key">not</span> <span class="key">None</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t165" href="#t165">165</a></span><span class="t">            <span class="key">return</span> <span class="nam">survival_time_element</span><span class="op">.</span><span class="nam">text</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t166" href="#t166">166</a></span><span class="t">        <span class="key">else</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t167" href="#t167">167</a></span><span class="t">            <span class="key">return</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t168" href="#t168">168</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t169" href="#t169">169</a></span><span class="t">    <span class="key">def</span> <span class="nam">_parse_experts_rules_parameters</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">elements</span><span class="op">)</span> <span class="op">-></span> <span class="nam">list</span><span class="op">[</span><span class="nam">tuple</span><span class="op">]</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t170" href="#t170">170</a></span><span class="t">        <span class="nam">expert_rules</span> <span class="op">=</span> <span class="op">[</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t171" href="#t171">171</a></span><span class="t">        <span class="key">for</span> <span class="nam">element</span> <span class="key">in</span> <span class="nam">elements</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t172" href="#t172">172</a></span><span class="t">            <span class="nam">rule_name</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="nam">element</span><span class="op">.</span><span class="nam">attrib</span><span class="op">[</span><span class="str">"name"</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t173" href="#t173">173</a></span><span class="t">            <span class="nam">rule_content</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="nam">element</span><span class="op">.</span><span class="nam">text</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t174" href="#t174">174</a></span><span class="t">            <span class="com"># RuleKit originally used XML for specifying parameters and uses special xml characters</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t175" href="#t175">175</a></span><span class="t">            <span class="nam">rule_content</span> <span class="op">=</span> <span class="nam">rule_content</span><span class="op">.</span><span class="nam">replace</span><span class="op">(</span><span class="str">"&amp;lt;"</span><span class="op">,</span> <span class="str">"&lt;"</span><span class="op">)</span><span class="op">.</span><span class="nam">replace</span><span class="op">(</span><span class="str">"&amp;gt;"</span><span class="op">,</span> <span class="str">">"</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t176" href="#t176">176</a></span><span class="t">            <span class="nam">expert_rules</span><span class="op">.</span><span class="nam">append</span><span class="op">(</span><span class="op">(</span><span class="nam">rule_name</span><span class="op">,</span> <span class="nam">rule_content</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t177" href="#t177">177</a></span><span class="t">        <span class="key">return</span> <span class="nam">expert_rules</span> <span class="key">if</span> <span class="nam">len</span><span class="op">(</span><span class="nam">expert_rules</span><span class="op">)</span> <span class="op">></span> <span class="num">0</span> <span class="key">else</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t178" href="#t178">178</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t179" href="#t179">179</a></span><span class="t">    <span class="key">def</span> <span class="nam">_check_ambigous_data_sets_names</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">data_sets_configs</span><span class="op">:</span> <span class="nam">list</span><span class="op">[</span><span class="nam">DataSetConfig</span><span class="op">]</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t180" href="#t180">180</a></span><span class="t">        <span class="nam">dictionary</span> <span class="op">=</span> <span class="op">{</span><span class="op">}</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t181" href="#t181">181</a></span><span class="t">        <span class="key">for</span> <span class="nam">element</span> <span class="key">in</span> <span class="nam">data_sets_configs</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t182" href="#t182">182</a></span><span class="t">            <span class="nam">dictionary</span><span class="op">[</span><span class="nam">element</span><span class="op">.</span><span class="nam">name</span><span class="op">]</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t183" href="#t183">183</a></span><span class="t">        <span class="key">if</span> <span class="nam">len</span><span class="op">(</span><span class="nam">dictionary</span><span class="op">.</span><span class="nam">keys</span><span class="op">(</span><span class="op">)</span><span class="op">)</span> <span class="op">&lt;</span> <span class="nam">len</span><span class="op">(</span><span class="nam">data_sets_configs</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t184" href="#t184">184</a></span><span class="t">            <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span><span class="str">"Datasets are ambigous"</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t185" href="#t185">185</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t186" href="#t186">186</a></span><span class="t">    <span class="key">def</span> <span class="nam">_parse_data_set</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">element</span><span class="op">)</span> <span class="op">-></span> <span class="nam">DataSetConfig</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t187" href="#t187">187</a></span><span class="t">        <span class="nam">data_set_config</span> <span class="op">=</span> <span class="nam">DataSetConfig</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t188" href="#t188">188</a></span><span class="t">        <span class="nam">data_set_config</span><span class="op">.</span><span class="nam">label_attribute</span> <span class="op">=</span> <span class="nam">element</span><span class="op">.</span><span class="nam">find</span><span class="op">(</span><span class="nam">TestConfigParser</span><span class="op">.</span><span class="nam">LABEL_KEY</span><span class="op">)</span><span class="op">.</span><span class="nam">text</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t189" href="#t189">189</a></span><span class="t">        <span class="nam">train_element</span> <span class="op">=</span> <span class="nam">element</span><span class="op">.</span><span class="nam">find</span><span class="op">(</span><span class="nam">TestConfigParser</span><span class="op">.</span><span class="nam">TRAINING_KEY</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t190" href="#t190">190</a></span><span class="t">        <span class="nam">train_element</span> <span class="op">=</span> <span class="nam">train_element</span><span class="op">.</span><span class="nam">find</span><span class="op">(</span><span class="nam">TestConfigParser</span><span class="op">.</span><span class="nam">TRAIN_KEY</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t191" href="#t191">191</a></span><span class="t">        <span class="nam">data_set_config</span><span class="op">.</span><span class="nam">train_file_name</span> <span class="op">=</span> <span class="nam">train_element</span><span class="op">.</span><span class="nam">find</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t192" href="#t192">192</a></span><span class="t">            <span class="nam">TestConfigParser</span><span class="op">.</span><span class="nam">IN_FILE_KEY</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t193" href="#t193">193</a></span><span class="t">        <span class="op">)</span><span class="op">.</span><span class="nam">text</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t194" href="#t194">194</a></span><span class="t">        <span class="nam">data_set_config</span><span class="op">.</span><span class="nam">name</span> <span class="op">=</span> <span class="nam">element</span><span class="op">.</span><span class="nam">attrib</span><span class="op">.</span><span class="nam">get</span><span class="op">(</span><span class="str">"name"</span><span class="op">,</span> <span class="key">None</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t195" href="#t195">195</a></span><span class="t">        <span class="key">if</span> <span class="nam">data_set_config</span><span class="op">.</span><span class="nam">name</span> <span class="key">is</span> <span class="key">None</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t196" href="#t196">196</a></span><span class="t">            <span class="nam">file_name</span> <span class="op">=</span> <span class="nam">os</span><span class="op">.</span><span class="nam">path</span><span class="op">.</span><span class="nam">basename</span><span class="op">(</span><span class="nam">data_set_config</span><span class="op">.</span><span class="nam">train_file_name</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t197" href="#t197">197</a></span><span class="t">            <span class="nam">data_set_config</span><span class="op">.</span><span class="nam">name</span> <span class="op">=</span> <span class="nam">file_name</span><span class="op">.</span><span class="nam">split</span><span class="op">(</span><span class="str">"."</span><span class="op">)</span><span class="op">[</span><span class="num">0</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t198" href="#t198">198</a></span><span class="t">        <span class="nam">data_set_config</span><span class="op">.</span><span class="nam">survival_time</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_parse_survival_time</span><span class="op">(</span><span class="nam">element</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t199" href="#t199">199</a></span><span class="t">        <span class="key">return</span> <span class="nam">data_set_config</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t200" href="#t200">200</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t201" href="#t201">201</a></span><span class="t">    <span class="key">def</span> <span class="nam">_parse_data_sets</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">element</span><span class="op">)</span> <span class="op">-></span> <span class="nam">list</span><span class="op">[</span><span class="nam">DataSetConfig</span><span class="op">]</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t202" href="#t202">202</a></span><span class="t">        <span class="nam">data_set_configs</span> <span class="op">=</span> <span class="op">[</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t203" href="#t203">203</a></span><span class="t">        <span class="nam">node</span> <span class="op">=</span> <span class="nam">element</span><span class="op">.</span><span class="nam">find</span><span class="op">(</span><span class="nam">TestConfigParser</span><span class="op">.</span><span class="nam">DATASETS_KEY</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t204" href="#t204">204</a></span><span class="t">        <span class="key">for</span> <span class="nam">element</span> <span class="key">in</span> <span class="nam">node</span><span class="op">.</span><span class="nam">findall</span><span class="op">(</span><span class="nam">TestConfigParser</span><span class="op">.</span><span class="nam">DATASET_KEY</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t205" href="#t205">205</a></span><span class="t">            <span class="nam">data_set_configs</span><span class="op">.</span><span class="nam">append</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">_parse_data_set</span><span class="op">(</span><span class="nam">element</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t206" href="#t206">206</a></span><span class="t">        <span class="key">return</span> <span class="nam">data_set_configs</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t207" href="#t207">207</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t208" href="#t208">208</a></span><span class="t">    <span class="key">def</span> <span class="nam">parse_test_parameters</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">element</span><span class="op">)</span> <span class="op">-></span> <span class="nam">dict</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">object</span><span class="op">]</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t209" href="#t209">209</a></span><span class="t">        <span class="nam">params</span> <span class="op">=</span> <span class="op">{</span><span class="op">}</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t210" href="#t210">210</a></span><span class="t">        <span class="key">for</span> <span class="nam">param_node</span> <span class="key">in</span> <span class="nam">element</span><span class="op">.</span><span class="nam">findall</span><span class="op">(</span><span class="nam">TestConfigParser</span><span class="op">.</span><span class="nam">PARAM_KEY</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t211" href="#t211">211</a></span><span class="t">            <span class="nam">name</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="nam">param_node</span><span class="op">.</span><span class="nam">attrib</span><span class="op">[</span><span class="str">"name"</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t212" href="#t212">212</a></span><span class="t">            <span class="key">if</span> <span class="nam">name</span> <span class="key">in</span> <span class="nam">TestConfigParser</span><span class="op">.</span><span class="nam">EXPERTS_RULES_PARAMETERS_NAMES</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t213" href="#t213">213</a></span><span class="t">                <span class="nam">value</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_parse_experts_rules_parameters</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t214" href="#t214">214</a></span><span class="t">                    <span class="nam">param_node</span><span class="op">.</span><span class="nam">findall</span><span class="op">(</span><span class="nam">TestConfigParser</span><span class="op">.</span><span class="nam">ENTRY_KEY</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t215" href="#t215">215</a></span><span class="t">                <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t216" href="#t216">216</a></span><span class="t">            <span class="key">else</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t217" href="#t217">217</a></span><span class="t">                <span class="nam">value</span> <span class="op">=</span> <span class="nam">param_node</span><span class="op">.</span><span class="nam">text</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t218" href="#t218">218</a></span><span class="t">            <span class="nam">params</span><span class="op">[</span><span class="nam">name</span><span class="op">]</span> <span class="op">=</span> <span class="nam">value</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t219" href="#t219">219</a></span><span class="t">        <span class="key">return</span> <span class="nam">params</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t220" href="#t220">220</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t221" href="#t221">221</a></span><span class="t">    <span class="key">def</span> <span class="nam">_parse_test_parameters_sets</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">element</span><span class="op">)</span> <span class="op">-></span> <span class="nam">dict</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">dict</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">object</span><span class="op">]</span><span class="op">]</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t222" href="#t222">222</a></span><span class="t">        <span class="nam">parameters_sets</span> <span class="op">=</span> <span class="op">{</span><span class="op">}</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t223" href="#t223">223</a></span><span class="t">        <span class="nam">params_sets_node</span> <span class="op">=</span> <span class="nam">element</span><span class="op">.</span><span class="nam">findall</span><span class="op">(</span><span class="nam">TestConfigParser</span><span class="op">.</span><span class="nam">PARAMETERS_SET_KEY</span><span class="op">)</span><span class="op">[</span><span class="num">0</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t224" href="#t224">224</a></span><span class="t">        <span class="key">for</span> <span class="nam">param_set</span> <span class="key">in</span> <span class="nam">params_sets_node</span><span class="op">.</span><span class="nam">findall</span><span class="op">(</span><span class="nam">TestConfigParser</span><span class="op">.</span><span class="nam">PARAMETERS_KEY</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t225" href="#t225">225</a></span><span class="t">            <span class="nam">name</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="nam">param_set</span><span class="op">.</span><span class="nam">attrib</span><span class="op">[</span><span class="str">"name"</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t226" href="#t226">226</a></span><span class="t">            <span class="nam">parameters_sets</span><span class="op">[</span><span class="nam">name</span><span class="op">]</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">parse_test_parameters</span><span class="op">(</span><span class="nam">param_set</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t227" href="#t227">227</a></span><span class="t">        <span class="key">return</span> <span class="nam">parameters_sets</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t228" href="#t228">228</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t229" href="#t229">229</a></span><span class="t">    <span class="key">def</span> <span class="nam">_parse_test</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">element</span><span class="op">)</span> <span class="op">-></span> <span class="nam">TestConfig</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t230" href="#t230">230</a></span><span class="t">        <span class="nam">test_config</span> <span class="op">=</span> <span class="nam">TestConfig</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t231" href="#t231">231</a></span><span class="t">        <span class="nam">test_config</span><span class="op">.</span><span class="nam">parameter_configs</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_parse_test_parameters_sets</span><span class="op">(</span><span class="nam">element</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t232" href="#t232">232</a></span><span class="t">        <span class="nam">test_config</span><span class="op">.</span><span class="nam">datasets</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_parse_data_sets</span><span class="op">(</span><span class="nam">element</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t233" href="#t233">233</a></span><span class="t">        <span class="nam">test_config</span><span class="op">.</span><span class="nam">name</span> <span class="op">=</span> <span class="nam">element</span><span class="op">.</span><span class="nam">attrib</span><span class="op">[</span><span class="str">"name"</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t234" href="#t234">234</a></span><span class="t">        <span class="key">return</span> <span class="nam">test_config</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t235" href="#t235">235</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t236" href="#t236">236</a></span><span class="t">    <span class="key">def</span> <span class="nam">parse</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">file_path</span><span class="op">:</span> <span class="nam">str</span><span class="op">)</span> <span class="op">-></span> <span class="nam">dict</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">TestConfig</span><span class="op">]</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t237" href="#t237">237</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">tests_configs</span> <span class="op">=</span> <span class="op">{</span><span class="op">}</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t238" href="#t238">238</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">root</span> <span class="op">=</span> <span class="nam">ElementTree</span><span class="op">.</span><span class="nam">parse</span><span class="op">(</span><span class="nam">file_path</span><span class="op">)</span><span class="op">.</span><span class="nam">getroot</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t239" href="#t239">239</a></span><span class="t">        <span class="key">if</span> <span class="nam">self</span><span class="op">.</span><span class="nam">root</span><span class="op">.</span><span class="nam">tag</span> <span class="op">==</span> <span class="str">"test"</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t240" href="#t240">240</a></span><span class="t">            <span class="nam">test_elements</span> <span class="op">=</span> <span class="op">[</span><span class="nam">self</span><span class="op">.</span><span class="nam">root</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t241" href="#t241">241</a></span><span class="t">        <span class="key">else</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t242" href="#t242">242</a></span><span class="t">            <span class="nam">test_elements</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">root</span><span class="op">.</span><span class="nam">findall</span><span class="op">(</span><span class="nam">TestConfigParser</span><span class="op">.</span><span class="nam">TEST_KEY</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t243" href="#t243">243</a></span><span class="t">        <span class="key">for</span> <span class="nam">test_element</span> <span class="key">in</span> <span class="nam">test_elements</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t244" href="#t244">244</a></span><span class="t">            <span class="nam">test_config</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_parse_test</span><span class="op">(</span><span class="nam">test_element</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t245" href="#t245">245</a></span><span class="t">            <span class="nam">self</span><span class="op">.</span><span class="nam">tests_configs</span><span class="op">[</span><span class="nam">test_config</span><span class="op">.</span><span class="nam">name</span><span class="op">]</span> <span class="op">=</span> <span class="nam">test_config</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t246" href="#t246">246</a></span><span class="t">        <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">tests_configs</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t247" href="#t247">247</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t248" href="#t248">248</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t249" href="#t249">249</a></span><span class="t"><span class="key">class</span> <span class="nam">TestCaseFactory</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t250" href="#t250">250</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t251" href="#t251">251</a></span><span class="t">    <span class="key">def</span> <span class="nam">_make_test_case</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t252" href="#t252">252</a></span><span class="t">        <span class="nam">self</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t253" href="#t253">253</a></span><span class="t">        <span class="nam">test_case_name</span><span class="op">:</span> <span class="nam">str</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t254" href="#t254">254</a></span><span class="t">        <span class="nam">params</span><span class="op">:</span> <span class="nam">dict</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">object</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t255" href="#t255">255</a></span><span class="t">        <span class="nam">data_set_config</span><span class="op">:</span> <span class="nam">DataSetConfig</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t256" href="#t256">256</a></span><span class="t">        <span class="nam">problem_type</span><span class="op">:</span> <span class="nam">ProblemType</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t257" href="#t257">257</a></span><span class="t">    <span class="op">)</span> <span class="op">-></span> <span class="nam">TestCase</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t258" href="#t258">258</a></span><span class="t">        <span class="nam">test_case</span> <span class="op">=</span> <span class="nam">TestCase</span><span class="op">(</span><span class="nam">problem_type</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t259" href="#t259">259</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_fix_params_typing</span><span class="op">(</span><span class="nam">params</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t260" href="#t260">260</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_fix_deprecated_params</span><span class="op">(</span><span class="nam">params</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t261" href="#t261">261</a></span><span class="t">        <span class="nam">test_case</span><span class="op">.</span><span class="nam">induction_params</span> <span class="op">=</span> <span class="nam">params</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t262" href="#t262">262</a></span><span class="t">        <span class="nam">test_case</span><span class="op">.</span><span class="nam">data_set_file_path</span> <span class="op">=</span> <span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t263" href="#t263">263</a></span><span class="t">            <span class="str">f"{DATA_IN_DIRECTORY_PATH}/"</span> <span class="str">f"{data_set_config.train_file_name}"</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t264" href="#t264">264</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t265" href="#t265">265</a></span><span class="t">        <span class="nam">test_case</span><span class="op">.</span><span class="nam">label_attribute</span> <span class="op">=</span> <span class="nam">data_set_config</span><span class="op">.</span><span class="nam">label_attribute</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t266" href="#t266">266</a></span><span class="t">        <span class="nam">test_case</span><span class="op">.</span><span class="nam">name</span> <span class="op">=</span> <span class="nam">test_case_name</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t267" href="#t267">267</a></span><span class="t">        <span class="nam">test_case</span><span class="op">.</span><span class="nam">param_config</span> <span class="op">=</span> <span class="nam">params</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t268" href="#t268">268</a></span><span class="t">        <span class="key">return</span> <span class="nam">test_case</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t269" href="#t269">269</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t270" href="#t270">270</a></span><span class="t">    <span class="key">def</span> <span class="nam">_fix_deprecated_params</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">params</span><span class="op">:</span> <span class="nam">dict</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">object</span><span class="op">]</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t271" href="#t271">271</a></span><span class="t">        <span class="nam">deprecated_minsupp_new_name</span> <span class="op">=</span> <span class="str">"min_rule_covered"</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t272" href="#t272">272</a></span><span class="t">        <span class="key">if</span> <span class="nam">deprecated_minsupp_new_name</span> <span class="key">in</span> <span class="nam">params</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t273" href="#t273">273</a></span><span class="t">            <span class="nam">params</span><span class="op">[</span><span class="str">"minsupp_new"</span><span class="op">]</span> <span class="op">=</span> <span class="nam">params</span><span class="op">.</span><span class="nam">pop</span><span class="op">(</span><span class="nam">deprecated_minsupp_new_name</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t274" href="#t274">274</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t275" href="#t275">275</a></span><span class="t">    <span class="key">def</span> <span class="nam">_fix_params_typing</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">params</span><span class="op">:</span> <span class="nam">dict</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t276" href="#t276">276</a></span><span class="t">        <span class="key">for</span> <span class="nam">key</span><span class="op">,</span> <span class="nam">value</span> <span class="key">in</span> <span class="nam">params</span><span class="op">.</span><span class="nam">items</span><span class="op">(</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t277" href="#t277">277</a></span><span class="t">            <span class="key">if</span> <span class="nam">value</span> <span class="op">==</span> <span class="str">"false"</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t278" href="#t278">278</a></span><span class="t">                <span class="nam">params</span><span class="op">[</span><span class="nam">key</span><span class="op">]</span> <span class="op">=</span> <span class="key">False</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t279" href="#t279">279</a></span><span class="t">                <span class="key">continue</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t280" href="#t280">280</a></span><span class="t">            <span class="key">if</span> <span class="nam">value</span> <span class="op">==</span> <span class="str">"true"</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t281" href="#t281">281</a></span><span class="t">                <span class="nam">params</span><span class="op">[</span><span class="nam">key</span><span class="op">]</span> <span class="op">=</span> <span class="key">True</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t282" href="#t282">282</a></span><span class="t">                <span class="key">continue</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t283" href="#t283">283</a></span><span class="t">            <span class="key">if</span> <span class="key">not</span> <span class="str">"measure"</span> <span class="key">in</span> <span class="nam">key</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t284" href="#t284">284</a></span><span class="t">                <span class="nam">params</span><span class="op">[</span><span class="nam">key</span><span class="op">]</span> <span class="op">=</span> <span class="nam">int</span><span class="op">(</span><span class="nam">float</span><span class="op">(</span><span class="nam">value</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t285" href="#t285">285</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t286" href="#t286">286</a></span><span class="t">    <span class="key">def</span> <span class="nam">make</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t287" href="#t287">287</a></span><span class="t">        <span class="nam">self</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t288" href="#t288">288</a></span><span class="t">        <span class="nam">tests_configs</span><span class="op">:</span> <span class="nam">dict</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">TestConfig</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t289" href="#t289">289</a></span><span class="t">        <span class="nam">report_dir_path</span><span class="op">:</span> <span class="nam">str</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t290" href="#t290">290</a></span><span class="t">        <span class="nam">problem_type</span><span class="op">:</span> <span class="nam">ProblemType</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t291" href="#t291">291</a></span><span class="t">    <span class="op">)</span> <span class="op">-></span> <span class="nam">list</span><span class="op">[</span><span class="nam">TestCase</span><span class="op">]</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t292" href="#t292">292</a></span><span class="t">        <span class="nam">test_cases</span> <span class="op">=</span> <span class="op">[</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t293" href="#t293">293</a></span><span class="t">        <span class="key">for</span> <span class="nam">key</span> <span class="key">in</span> <span class="nam">tests_configs</span><span class="op">.</span><span class="nam">keys</span><span class="op">(</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t294" href="#t294">294</a></span><span class="t">            <span class="nam">test_config</span> <span class="op">=</span> <span class="nam">tests_configs</span><span class="op">[</span><span class="nam">key</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t295" href="#t295">295</a></span><span class="t">            <span class="key">for</span> <span class="nam">config_name</span> <span class="key">in</span> <span class="nam">test_config</span><span class="op">.</span><span class="nam">parameter_configs</span><span class="op">.</span><span class="nam">keys</span><span class="op">(</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t296" href="#t296">296</a></span><span class="t">                <span class="key">for</span> <span class="nam">data_set_config</span> <span class="key">in</span> <span class="nam">test_config</span><span class="op">.</span><span class="nam">datasets</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t297" href="#t297">297</a></span><span class="t">                    <span class="nam">params</span> <span class="op">=</span> <span class="nam">test_config</span><span class="op">.</span><span class="nam">parameter_configs</span><span class="op">[</span><span class="nam">config_name</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t298" href="#t298">298</a></span><span class="t">                    <span class="nam">test_case_name</span> <span class="op">=</span> <span class="str">f"{key}.{config_name}.{data_set_config.name}"</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t299" href="#t299">299</a></span><span class="t">                    <span class="nam">test_config</span><span class="op">.</span><span class="nam">parameter_configs</span><span class="op">[</span><span class="nam">config_name</span><span class="op">]</span><span class="op">.</span><span class="nam">pop</span><span class="op">(</span><span class="str">"use_expert"</span><span class="op">,</span> <span class="key">None</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t300" href="#t300">300</a></span><span class="t">                    <span class="nam">expert_rules</span> <span class="op">=</span> <span class="nam">test_config</span><span class="op">.</span><span class="nam">parameter_configs</span><span class="op">[</span><span class="nam">config_name</span><span class="op">]</span><span class="op">.</span><span class="nam">pop</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t301" href="#t301">301</a></span><span class="t">                        <span class="str">"expert_rules"</span><span class="op">,</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t302" href="#t302">302</a></span><span class="t">                    <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t303" href="#t303">303</a></span><span class="t">                    <span class="nam">preferred_conditions</span> <span class="op">=</span> <span class="nam">test_config</span><span class="op">.</span><span class="nam">parameter_configs</span><span class="op">[</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t304" href="#t304">304</a></span><span class="t">                        <span class="nam">config_name</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t305" href="#t305">305</a></span><span class="t">                    <span class="op">]</span><span class="op">.</span><span class="nam">pop</span><span class="op">(</span><span class="str">"expert_preferred_conditions"</span><span class="op">,</span> <span class="key">None</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t306" href="#t306">306</a></span><span class="t">                    <span class="nam">forbidden_conditions</span> <span class="op">=</span> <span class="nam">test_config</span><span class="op">.</span><span class="nam">parameter_configs</span><span class="op">[</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t307" href="#t307">307</a></span><span class="t">                        <span class="nam">config_name</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t308" href="#t308">308</a></span><span class="t">                    <span class="op">]</span><span class="op">.</span><span class="nam">pop</span><span class="op">(</span><span class="str">"expert_forbidden_conditions"</span><span class="op">,</span> <span class="key">None</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t309" href="#t309">309</a></span><span class="t">                    <span class="nam">test_case</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_make_test_case</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t310" href="#t310">310</a></span><span class="t">                        <span class="nam">test_case_name</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t311" href="#t311">311</a></span><span class="t">                        <span class="nam">test_config</span><span class="op">.</span><span class="nam">parameter_configs</span><span class="op">[</span><span class="nam">config_name</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t312" href="#t312">312</a></span><span class="t">                        <span class="nam">data_set_config</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t313" href="#t313">313</a></span><span class="t">                        <span class="nam">problem_type</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t314" href="#t314">314</a></span><span class="t">                    <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t315" href="#t315">315</a></span><span class="t">                    <span class="key">if</span> <span class="str">"use_report"</span> <span class="key">in</span> <span class="nam">params</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t316" href="#t316">316</a></span><span class="t">                        <span class="nam">report_file_name</span> <span class="op">=</span> <span class="nam">params</span><span class="op">[</span><span class="str">"use_report"</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t317" href="#t317">317</a></span><span class="t">                        <span class="nam">test_case</span><span class="op">.</span><span class="nam">using_existing_report_file</span> <span class="op">=</span> <span class="key">True</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t318" href="#t318">318</a></span><span class="t">                    <span class="key">else</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t319" href="#t319">319</a></span><span class="t">                        <span class="nam">report_file_name</span> <span class="op">=</span> <span class="nam">test_case_name</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t320" href="#t320">320</a></span><span class="t">                    <span class="nam">report_path</span> <span class="op">=</span> <span class="str">f"{report_dir_path}/{report_file_name}"</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t321" href="#t321">321</a></span><span class="t">                    <span class="nam">test_case</span><span class="op">.</span><span class="nam">report_file_path</span> <span class="op">=</span> <span class="nam">report_path</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t322" href="#t322">322</a></span><span class="t">                    <span class="nam">test_case</span><span class="op">.</span><span class="nam">survival_time</span> <span class="op">=</span> <span class="nam">data_set_config</span><span class="op">.</span><span class="nam">survival_time</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t323" href="#t323">323</a></span><span class="t">                    <span class="key">if</span> <span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t324" href="#t324">324</a></span><span class="t">                        <span class="nam">expert_rules</span> <span class="key">is</span> <span class="key">not</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t325" href="#t325">325</a></span><span class="t">                        <span class="key">or</span> <span class="nam">preferred_conditions</span> <span class="key">is</span> <span class="key">not</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t326" href="#t326">326</a></span><span class="t">                        <span class="key">or</span> <span class="nam">forbidden_conditions</span> <span class="key">is</span> <span class="key">not</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t327" href="#t327">327</a></span><span class="t">                    <span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t328" href="#t328">328</a></span><span class="t">                        <span class="nam">test_case</span><span class="op">.</span><span class="nam">knowledge</span> <span class="op">=</span> <span class="nam">Knowledge</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t329" href="#t329">329</a></span><span class="t">                        <span class="key">if</span> <span class="nam">expert_rules</span> <span class="key">is</span> <span class="key">not</span> <span class="key">None</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t330" href="#t330">330</a></span><span class="t">                            <span class="nam">test_case</span><span class="op">.</span><span class="nam">knowledge</span><span class="op">.</span><span class="nam">expert_rules</span> <span class="op">=</span> <span class="nam">expert_rules</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t331" href="#t331">331</a></span><span class="t">                        <span class="key">if</span> <span class="nam">forbidden_conditions</span> <span class="key">is</span> <span class="key">not</span> <span class="key">None</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t332" href="#t332">332</a></span><span class="t">                            <span class="nam">test_case</span><span class="op">.</span><span class="nam">knowledge</span><span class="op">.</span><span class="nam">expert_forbidden_conditions</span> <span class="op">=</span> <span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t333" href="#t333">333</a></span><span class="t">                                <span class="nam">forbidden_conditions</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t334" href="#t334">334</a></span><span class="t">                            <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t335" href="#t335">335</a></span><span class="t">                        <span class="key">if</span> <span class="nam">preferred_conditions</span> <span class="key">is</span> <span class="key">not</span> <span class="key">None</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t336" href="#t336">336</a></span><span class="t">                            <span class="nam">test_case</span><span class="op">.</span><span class="nam">knowledge</span><span class="op">.</span><span class="nam">expert_preferred_conditions</span> <span class="op">=</span> <span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t337" href="#t337">337</a></span><span class="t">                                <span class="nam">preferred_conditions</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t338" href="#t338">338</a></span><span class="t">                            <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t339" href="#t339">339</a></span><span class="t">                    <span class="nam">test_cases</span><span class="op">.</span><span class="nam">append</span><span class="op">(</span><span class="nam">test_case</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t340" href="#t340">340</a></span><span class="t">        <span class="key">return</span> <span class="nam">test_cases</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t341" href="#t341">341</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t342" href="#t342">342</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t343" href="#t343">343</a></span><span class="t">    <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">file_name</span><span class="op">:</span> <span class="nam">str</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t344" href="#t344">344</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">file_name</span> <span class="op">=</span> <span class="nam">file_name</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t345" href="#t345">345</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_file</span> <span class="op">=</span> <span class="nam">open</span><span class="op">(</span><span class="nam">file_name</span><span class="op">,</span> <span class="nam">encoding</span><span class="op">=</span><span class="str">'utf-8'</span><span class="op">,</span> <span class="nam">mode</span><span class="op">=</span><span class="str">'r'</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t343" href="#t343">343</a></span><span class="t"><span class="key">def</span> <span class="nam">get_rule_string</span><span class="op">(</span><span class="nam">rule</span><span class="op">)</span> <span class="op">-></span> <span class="nam">str</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t344" href="#t344">344</a></span><span class="t">    <span class="key">return</span> <span class="nam">re</span><span class="op">.</span><span class="nam">sub</span><span class="op">(</span><span class="str">r"(\\[[^\\]]*\\]$)|(\\([^\\)]*\\)$)"</span><span class="op">,</span> <span class="str">""</span><span class="op">,</span> <span class="nam">str</span><span class="op">(</span><span class="nam">rule</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t345" href="#t345">345</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t346" href="#t346">346</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t347" href="#t347">347</a></span><span class="t">    <span class="key">def</span> <span class="nam">_read_rules</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">test_report</span><span class="op">:</span> <span class="nam">TestReport</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t348" href="#t348">348</a></span><span class="t">        <span class="nam">rules</span> <span class="op">=</span> <span class="op">[</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t349" href="#t349">349</a></span><span class="t">        <span class="key">for</span> <span class="nam">line</span> <span class="key">in</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_file</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t350" href="#t350">350</a></span><span class="t">            <span class="key">if</span> <span class="nam">len</span><span class="op">(</span><span class="nam">line</span><span class="op">)</span> <span class="op">==</span> <span class="num">0</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t351" href="#t351">351</a></span><span class="t">                <span class="key">break</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t352" href="#t352">352</a></span><span class="t">            <span class="key">else</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t353" href="#t353">353</a></span><span class="t">                <span class="nam">rules</span><span class="op">.</span><span class="nam">append</span><span class="op">(</span><span class="nam">line</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t354" href="#t354">354</a></span><span class="t">        <span class="nam">test_report</span><span class="op">.</span><span class="nam">rules</span> <span class="op">=</span> <span class="nam">rules</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t355" href="#t355">355</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t356" href="#t356">356</a></span><span class="t">    <span class="key">def</span> <span class="nam">read</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">TestReport</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t357" href="#t357">357</a></span><span class="t">        <span class="nam">test_report</span> <span class="op">=</span> <span class="nam">TestReport</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">file_name</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t358" href="#t358">358</a></span><span class="t">        <span class="key">for</span> <span class="nam">line</span> <span class="key">in</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_file</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t359" href="#t359">359</a></span><span class="t">            <span class="nam">line</span> <span class="op">=</span> <span class="nam">line</span><span class="op">.</span><span class="nam">upper</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t360" href="#t360">360</a></span><span class="t">            <span class="nam">line</span> <span class="op">=</span> <span class="nam">re</span><span class="op">.</span><span class="nam">sub</span><span class="op">(</span><span class="str">r'\t'</span><span class="op">,</span> <span class="str">''</span><span class="op">,</span> <span class="nam">line</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t361" href="#t361">361</a></span><span class="t">            <span class="nam">line</span> <span class="op">=</span> <span class="nam">line</span><span class="op">.</span><span class="nam">replace</span><span class="op">(</span><span class="str">'\n'</span><span class="op">,</span> <span class="str">''</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t362" href="#t362">362</a></span><span class="t">            <span class="key">if</span> <span class="nam">line</span> <span class="op">==</span> <span class="nam">REPORTS_SECTIONS_HEADERS</span><span class="op">[</span><span class="str">'RULES'</span><span class="op">]</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t363" href="#t363">363</a></span><span class="t">                <span class="nam">self</span><span class="op">.</span><span class="nam">_read_rules</span><span class="op">(</span><span class="nam">test_report</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t364" href="#t364">364</a></span><span class="t">            <span class="key">elif</span> <span class="nam">line</span> <span class="op">==</span> <span class="str">''</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t365" href="#t365">365</a></span><span class="t">                <span class="key">continue</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t366" href="#t366">366</a></span><span class="t">            <span class="key">else</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t367" href="#t367">367</a></span><span class="t">                <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t368" href="#t368">368</a></span><span class="t">                    <span class="str">f'Invalid report file format for file: {self.file_name}'</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t369" href="#t369">369</a></span><span class="t">        <span class="key">return</span> <span class="nam">test_report</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t370" href="#t370">370</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t371" href="#t371">371</a></span><span class="t">    <span class="key">def</span> <span class="nam">close</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t372" href="#t372">372</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_file</span><span class="op">.</span><span class="nam">close</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t373" href="#t373">373</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t374" href="#t374">374</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t375" href="#t375">375</a></span><span class="t"><span class="key">class</span> <span class="nam">TestReportWriter</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t376" href="#t376">376</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t377" href="#t377">377</a></span><span class="t">    <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">file_name</span><span class="op">:</span> <span class="nam">str</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t378" href="#t378">378</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_file</span> <span class="op">=</span> <span class="nam">open</span><span class="op">(</span><span class="nam">file_name</span><span class="op">,</span> <span class="nam">encoding</span><span class="op">=</span><span class="str">'utf-8'</span><span class="op">,</span> <span class="nam">mode</span><span class="op">=</span><span class="str">"w"</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t379" href="#t379">379</a></span><span class="t">        <span class="key">if</span> <span class="key">not</span> <span class="nam">os</span><span class="op">.</span><span class="nam">path</span><span class="op">.</span><span class="nam">exists</span><span class="op">(</span><span class="nam">REPORTS_OUT_DIRECTORY_PATH</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t380" href="#t380">380</a></span><span class="t">            <span class="nam">os</span><span class="op">.</span><span class="nam">makedirs</span><span class="op">(</span><span class="nam">REPORTS_OUT_DIRECTORY_PATH</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t347" href="#t347">347</a></span><span class="t"><span class="key">class</span> <span class="nam">TestReportReader</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t348" href="#t348">348</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t349" href="#t349">349</a></span><span class="t">    <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">file_name</span><span class="op">:</span> <span class="nam">str</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t350" href="#t350">350</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">file_name</span> <span class="op">=</span> <span class="nam">file_name</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t351" href="#t351">351</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_file</span> <span class="op">=</span> <span class="nam">open</span><span class="op">(</span><span class="nam">file_name</span><span class="op">,</span> <span class="nam">encoding</span><span class="op">=</span><span class="str">"utf-8"</span><span class="op">,</span> <span class="nam">mode</span><span class="op">=</span><span class="str">"r"</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t352" href="#t352">352</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t353" href="#t353">353</a></span><span class="t">    <span class="key">def</span> <span class="nam">_read_rules</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">test_report</span><span class="op">:</span> <span class="nam">TestReport</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t354" href="#t354">354</a></span><span class="t">        <span class="nam">rules</span> <span class="op">=</span> <span class="op">[</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t355" href="#t355">355</a></span><span class="t">        <span class="key">for</span> <span class="nam">line</span> <span class="key">in</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_file</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t356" href="#t356">356</a></span><span class="t">            <span class="key">if</span> <span class="nam">len</span><span class="op">(</span><span class="nam">line</span><span class="op">)</span> <span class="op">==</span> <span class="num">0</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t357" href="#t357">357</a></span><span class="t">                <span class="key">break</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t358" href="#t358">358</a></span><span class="t">            <span class="key">else</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t359" href="#t359">359</a></span><span class="t">                <span class="nam">rules</span><span class="op">.</span><span class="nam">append</span><span class="op">(</span><span class="nam">line</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t360" href="#t360">360</a></span><span class="t">        <span class="nam">test_report</span><span class="op">.</span><span class="nam">rules</span> <span class="op">=</span> <span class="nam">rules</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t361" href="#t361">361</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t362" href="#t362">362</a></span><span class="t">    <span class="key">def</span> <span class="nam">read</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">TestReport</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t363" href="#t363">363</a></span><span class="t">        <span class="nam">test_report</span> <span class="op">=</span> <span class="nam">TestReport</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">file_name</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t364" href="#t364">364</a></span><span class="t">        <span class="key">for</span> <span class="nam">line</span> <span class="key">in</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_file</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t365" href="#t365">365</a></span><span class="t">            <span class="nam">line</span> <span class="op">=</span> <span class="nam">line</span><span class="op">.</span><span class="nam">upper</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t366" href="#t366">366</a></span><span class="t">            <span class="nam">line</span> <span class="op">=</span> <span class="nam">re</span><span class="op">.</span><span class="nam">sub</span><span class="op">(</span><span class="str">r"\t"</span><span class="op">,</span> <span class="str">""</span><span class="op">,</span> <span class="nam">line</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t367" href="#t367">367</a></span><span class="t">            <span class="nam">line</span> <span class="op">=</span> <span class="nam">line</span><span class="op">.</span><span class="nam">replace</span><span class="op">(</span><span class="str">"\n"</span><span class="op">,</span> <span class="str">""</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t368" href="#t368">368</a></span><span class="t">            <span class="key">if</span> <span class="nam">line</span> <span class="op">==</span> <span class="nam">REPORTS_SECTIONS_HEADERS</span><span class="op">[</span><span class="str">"RULES"</span><span class="op">]</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t369" href="#t369">369</a></span><span class="t">                <span class="nam">self</span><span class="op">.</span><span class="nam">_read_rules</span><span class="op">(</span><span class="nam">test_report</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t370" href="#t370">370</a></span><span class="t">            <span class="key">elif</span> <span class="nam">line</span> <span class="op">==</span> <span class="str">""</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t371" href="#t371">371</a></span><span class="t">                <span class="key">continue</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t372" href="#t372">372</a></span><span class="t">            <span class="key">else</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t373" href="#t373">373</a></span><span class="t">                <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t374" href="#t374">374</a></span><span class="t">                    <span class="str">f"Invalid report file format for file: {self.file_name}"</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t375" href="#t375">375</a></span><span class="t">                <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t376" href="#t376">376</a></span><span class="t">        <span class="key">return</span> <span class="nam">test_report</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t377" href="#t377">377</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t378" href="#t378">378</a></span><span class="t">    <span class="key">def</span> <span class="nam">close</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t379" href="#t379">379</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_file</span><span class="op">.</span><span class="nam">close</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t380" href="#t380">380</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t381" href="#t381">381</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t382" href="#t382">382</a></span><span class="t">    <span class="key">def</span> <span class="nam">write</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">rule_set</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t383" href="#t383">383</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_file</span><span class="op">.</span><span class="nam">write</span><span class="op">(</span><span class="str">'\n'</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t384" href="#t384">384</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_file</span><span class="op">.</span><span class="nam">write</span><span class="op">(</span><span class="str">f'{REPORTS_SECTIONS_HEADERS["RULES"]}\n'</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t385" href="#t385">385</a></span><span class="t">        <span class="key">for</span> <span class="nam">rule</span> <span class="key">in</span> <span class="nam">rule_set</span><span class="op">.</span><span class="nam">rules</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t386" href="#t386">386</a></span><span class="t">            <span class="nam">self</span><span class="op">.</span><span class="nam">_file</span><span class="op">.</span><span class="nam">write</span><span class="op">(</span><span class="str">f'\t{get_rule_string(rule)}'</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t387" href="#t387">387</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t388" href="#t388">388</a></span><span class="t">    <span class="key">def</span> <span class="nam">close</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t389" href="#t389">389</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_file</span><span class="op">.</span><span class="nam">close</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t390" href="#t390">390</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t391" href="#t391">391</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t392" href="#t392">392</a></span><span class="t"><span class="key">def</span> <span class="nam">get_test_cases</span><span class="op">(</span><span class="nam">class_name</span><span class="op">:</span> <span class="nam">str</span><span class="op">)</span> <span class="op">-></span> <span class="nam">list</span><span class="op">[</span><span class="nam">TestCase</span><span class="op">]</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t393" href="#t393">393</a></span><span class="t">    <span class="key">if</span> <span class="key">not</span> <span class="nam">os</span><span class="op">.</span><span class="nam">path</span><span class="op">.</span><span class="nam">exists</span><span class="op">(</span><span class="nam">DATA_IN_DIRECTORY_PATH</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t394" href="#t394">394</a></span><span class="t">        <span class="key">raise</span> <span class="nam">RuntimeError</span><span class="op">(</span><span class="str">'''\n</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t395" href="#t395">395</a></span><span class="t"><span class="str">Test resources directory dosen't exist. Check if 'tests/resources/' directory exist.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t396" href="#t396">396</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t397" href="#t397">397</a></span><span class="t"><span class="str">If you're running tests for the first time you need to download resources folder from RuleKit repository by running:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t398" href="#t398">398</a></span><span class="t"><span class="str">    python tests/resources.py download</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t399" href="#t399">399</a></span><span class="t"><span class="str">        '''</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t400" href="#t400">400</a></span><span class="t">    <span class="nam">problem_type</span><span class="op">:</span> <span class="nam">ProblemType</span> <span class="op">=</span> <span class="nam">_get_problem_type_from_test_case_class_name</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t401" href="#t401">401</a></span><span class="t">        <span class="nam">class_name</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t402" href="#t402">402</a></span><span class="t">    <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t403" href="#t403">403</a></span><span class="t">    <span class="nam">configs</span> <span class="op">=</span> <span class="nam">TestConfigParser</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">parse</span><span class="op">(</span><span class="str">f'{TEST_CONFIG_PATH}/{class_name}.xml'</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t404" href="#t404">404</a></span><span class="t">    <span class="key">return</span> <span class="nam">TestCaseFactory</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">make</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t405" href="#t405">405</a></span><span class="t">        <span class="nam">configs</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t406" href="#t406">406</a></span><span class="t">        <span class="str">f'{REPORTS_IN_DIRECTORY_PATH}/{class_name}/'</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t407" href="#t407">407</a></span><span class="t">        <span class="nam">problem_type</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t408" href="#t408">408</a></span><span class="t">    <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t409" href="#t409">409</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t410" href="#t410">410</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t411" href="#t411">411</a></span><span class="t"><span class="key">def</span> <span class="nam">_get_problem_type_from_test_case_class_name</span><span class="op">(</span><span class="nam">class_name</span><span class="op">:</span> <span class="nam">str</span><span class="op">)</span> <span class="op">-></span> <span class="nam">ProblemType</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t412" href="#t412">412</a></span><span class="t">    <span class="nam">class_name</span> <span class="op">=</span> <span class="nam">class_name</span><span class="op">.</span><span class="nam">lower</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t413" href="#t413">413</a></span><span class="t">    <span class="key">if</span> <span class="str">'regression'</span> <span class="key">in</span> <span class="nam">class_name</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t414" href="#t414">414</a></span><span class="t">        <span class="key">return</span> <span class="nam">ProblemType</span><span class="op">.</span><span class="nam">REGRESSION</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t415" href="#t415">415</a></span><span class="t">    <span class="key">elif</span> <span class="str">'survival'</span> <span class="key">in</span> <span class="nam">class_name</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t416" href="#t416">416</a></span><span class="t">        <span class="key">return</span> <span class="nam">ProblemType</span><span class="op">.</span><span class="nam">SURVIVAL</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t417" href="#t417">417</a></span><span class="t">    <span class="key">elif</span> <span class="str">'classification'</span> <span class="key">in</span> <span class="nam">class_name</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t418" href="#t418">418</a></span><span class="t">        <span class="key">return</span> <span class="nam">ProblemType</span><span class="op">.</span><span class="nam">CLASSIFICATION</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t419" href="#t419">419</a></span><span class="t">    <span class="key">raise</span> <span class="nam">Exception</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t420" href="#t420">420</a></span><span class="t">        <span class="str">f'Unknown problem type for test case class name: {class_name}'</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t421" href="#t421">421</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t422" href="#t422">422</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t423" href="#t423">423</a></span><span class="t"><span class="key">def</span> <span class="nam">assert_rules_are_equals</span><span class="op">(</span><span class="nam">expected</span><span class="op">:</span> <span class="nam">list</span><span class="op">[</span><span class="nam">str</span><span class="op">]</span><span class="op">,</span> <span class="nam">actual</span><span class="op">:</span> <span class="nam">list</span><span class="op">[</span><span class="nam">str</span><span class="op">]</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t424" href="#t424">424</a></span><span class="t">    <span class="key">def</span> <span class="nam">sanitize_rule_string</span><span class="op">(</span><span class="nam">rule_string</span><span class="op">:</span> <span class="nam">str</span><span class="op">)</span> <span class="op">-></span> <span class="nam">str</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t425" href="#t425">425</a></span><span class="t">        <span class="key">return</span> <span class="nam">re</span><span class="op">.</span><span class="nam">sub</span><span class="op">(</span><span class="str">r'(\t)|(\n)|(\[[^\]]*\]$)'</span><span class="op">,</span> <span class="str">''</span><span class="op">,</span> <span class="nam">rule_string</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t382" href="#t382">382</a></span><span class="t"><span class="key">class</span> <span class="nam">TestReportWriter</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t383" href="#t383">383</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t384" href="#t384">384</a></span><span class="t">    <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">file_name</span><span class="op">:</span> <span class="nam">str</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t385" href="#t385">385</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_file</span> <span class="op">=</span> <span class="nam">open</span><span class="op">(</span><span class="nam">file_name</span><span class="op">,</span> <span class="nam">encoding</span><span class="op">=</span><span class="str">"utf-8"</span><span class="op">,</span> <span class="nam">mode</span><span class="op">=</span><span class="str">"w"</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t386" href="#t386">386</a></span><span class="t">        <span class="key">if</span> <span class="key">not</span> <span class="nam">os</span><span class="op">.</span><span class="nam">path</span><span class="op">.</span><span class="nam">exists</span><span class="op">(</span><span class="nam">REPORTS_OUT_DIRECTORY_PATH</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t387" href="#t387">387</a></span><span class="t">            <span class="nam">os</span><span class="op">.</span><span class="nam">makedirs</span><span class="op">(</span><span class="nam">REPORTS_OUT_DIRECTORY_PATH</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t388" href="#t388">388</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t389" href="#t389">389</a></span><span class="t">    <span class="key">def</span> <span class="nam">write</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">rule_set</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t390" href="#t390">390</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_file</span><span class="op">.</span><span class="nam">write</span><span class="op">(</span><span class="str">"\n"</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t391" href="#t391">391</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_file</span><span class="op">.</span><span class="nam">write</span><span class="op">(</span><span class="str">f'{REPORTS_SECTIONS_HEADERS["RULES"]}\n'</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t392" href="#t392">392</a></span><span class="t">        <span class="key">for</span> <span class="nam">rule</span> <span class="key">in</span> <span class="nam">rule_set</span><span class="op">.</span><span class="nam">rules</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t393" href="#t393">393</a></span><span class="t">            <span class="nam">self</span><span class="op">.</span><span class="nam">_file</span><span class="op">.</span><span class="nam">write</span><span class="op">(</span><span class="str">f"\t{get_rule_string(rule)}"</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t394" href="#t394">394</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t395" href="#t395">395</a></span><span class="t">    <span class="key">def</span> <span class="nam">close</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t396" href="#t396">396</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_file</span><span class="op">.</span><span class="nam">close</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t397" href="#t397">397</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t398" href="#t398">398</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t399" href="#t399">399</a></span><span class="t"><span class="key">def</span> <span class="nam">get_test_cases</span><span class="op">(</span><span class="nam">class_name</span><span class="op">:</span> <span class="nam">str</span><span class="op">)</span> <span class="op">-></span> <span class="nam">list</span><span class="op">[</span><span class="nam">TestCase</span><span class="op">]</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t400" href="#t400">400</a></span><span class="t">    <span class="key">if</span> <span class="key">not</span> <span class="nam">os</span><span class="op">.</span><span class="nam">path</span><span class="op">.</span><span class="nam">exists</span><span class="op">(</span><span class="nam">DATA_IN_DIRECTORY_PATH</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t401" href="#t401">401</a></span><span class="t">        <span class="key">raise</span> <span class="nam">RuntimeError</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t402" href="#t402">402</a></span><span class="t">            <span class="str">"""\n</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t403" href="#t403">403</a></span><span class="t"><span class="str">Test resources directory dosen't exist. Check if 'tests/resources/' directory exist.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t404" href="#t404">404</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t405" href="#t405">405</a></span><span class="t"><span class="str">If you're running tests for the first time you need to download resources folder from RuleKit repository by running:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t406" href="#t406">406</a></span><span class="t"><span class="str">    python tests/resources.py download</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t407" href="#t407">407</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t408" href="#t408">408</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t409" href="#t409">409</a></span><span class="t">    <span class="nam">problem_type</span><span class="op">:</span> <span class="nam">ProblemType</span> <span class="op">=</span> <span class="nam">_get_problem_type_from_test_case_class_name</span><span class="op">(</span><span class="nam">class_name</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t410" href="#t410">410</a></span><span class="t">    <span class="nam">configs</span> <span class="op">=</span> <span class="nam">TestConfigParser</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">parse</span><span class="op">(</span><span class="str">f"{TEST_CONFIG_PATH}/{class_name}.xml"</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t411" href="#t411">411</a></span><span class="t">    <span class="key">return</span> <span class="nam">TestCaseFactory</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">make</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t412" href="#t412">412</a></span><span class="t">        <span class="nam">configs</span><span class="op">,</span> <span class="str">f"{REPORTS_IN_DIRECTORY_PATH}/{class_name}/"</span><span class="op">,</span> <span class="nam">problem_type</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t413" href="#t413">413</a></span><span class="t">    <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t414" href="#t414">414</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t415" href="#t415">415</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t416" href="#t416">416</a></span><span class="t"><span class="key">def</span> <span class="nam">_get_problem_type_from_test_case_class_name</span><span class="op">(</span><span class="nam">class_name</span><span class="op">:</span> <span class="nam">str</span><span class="op">)</span> <span class="op">-></span> <span class="nam">ProblemType</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t417" href="#t417">417</a></span><span class="t">    <span class="nam">class_name</span> <span class="op">=</span> <span class="nam">class_name</span><span class="op">.</span><span class="nam">lower</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t418" href="#t418">418</a></span><span class="t">    <span class="key">if</span> <span class="str">"regression"</span> <span class="key">in</span> <span class="nam">class_name</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t419" href="#t419">419</a></span><span class="t">        <span class="key">return</span> <span class="nam">ProblemType</span><span class="op">.</span><span class="nam">REGRESSION</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t420" href="#t420">420</a></span><span class="t">    <span class="key">elif</span> <span class="str">"survival"</span> <span class="key">in</span> <span class="nam">class_name</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t421" href="#t421">421</a></span><span class="t">        <span class="key">return</span> <span class="nam">ProblemType</span><span class="op">.</span><span class="nam">SURVIVAL</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t422" href="#t422">422</a></span><span class="t">    <span class="key">elif</span> <span class="str">"classification"</span> <span class="key">in</span> <span class="nam">class_name</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t423" href="#t423">423</a></span><span class="t">        <span class="key">return</span> <span class="nam">ProblemType</span><span class="op">.</span><span class="nam">CLASSIFICATION</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t424" href="#t424">424</a></span><span class="t">    <span class="key">raise</span> <span class="nam">Exception</span><span class="op">(</span><span class="str">f"Unknown problem type for test case class name: {class_name}"</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t425" href="#t425">425</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t426" href="#t426">426</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t427" href="#t427">427</a></span><span class="t">    <span class="nam">expected</span> <span class="op">=</span> <span class="nam">list</span><span class="op">(</span><span class="nam">map</span><span class="op">(</span><span class="nam">sanitize_rule_string</span><span class="op">,</span> <span class="nam">expected</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t428" href="#t428">428</a></span><span class="t">    <span class="nam">actual</span> <span class="op">=</span> <span class="nam">list</span><span class="op">(</span><span class="nam">map</span><span class="op">(</span><span class="nam">sanitize_rule_string</span><span class="op">,</span> <span class="nam">actual</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t429" href="#t429">429</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t430" href="#t430">430</a></span><span class="t">    <span class="key">if</span> <span class="nam">len</span><span class="op">(</span><span class="nam">expected</span><span class="op">)</span> <span class="op">!=</span> <span class="nam">len</span><span class="op">(</span><span class="nam">actual</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t431" href="#t431">431</a></span><span class="t">        <span class="key">raise</span> <span class="nam">AssertionError</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t432" href="#t432">432</a></span><span class="t">            <span class="str">f'Rulesets have different number of rules, actual: {len(actual)}, expected: {len(expected)}'</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t433" href="#t433">433</a></span><span class="t">    <span class="nam">dictionary</span> <span class="op">=</span> <span class="op">{</span><span class="op">}</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t434" href="#t434">434</a></span><span class="t">    <span class="key">for</span> <span class="nam">rule</span> <span class="key">in</span> <span class="nam">expected</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t435" href="#t435">435</a></span><span class="t">        <span class="nam">dictionary</span><span class="op">[</span><span class="nam">rule</span><span class="op">]</span> <span class="op">=</span> <span class="num">0</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t436" href="#t436">436</a></span><span class="t">    <span class="key">for</span> <span class="nam">rule</span> <span class="key">in</span> <span class="nam">actual</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t437" href="#t437">437</a></span><span class="t">        <span class="nam">key</span> <span class="op">=</span> <span class="nam">rule</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t438" href="#t438">438</a></span><span class="t">        <span class="key">if</span> <span class="nam">key</span> <span class="key">in</span> <span class="nam">dictionary</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t439" href="#t439">439</a></span><span class="t">            <span class="nam">dictionary</span><span class="op">[</span><span class="nam">key</span><span class="op">]</span> <span class="op">=</span> <span class="nam">dictionary</span><span class="op">[</span><span class="nam">key</span><span class="op">]</span> <span class="op">+</span> <span class="num">1</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t440" href="#t440">440</a></span><span class="t">        <span class="key">else</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t441" href="#t441">441</a></span><span class="t">            <span class="key">raise</span> <span class="nam">AssertionError</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t442" href="#t442">442</a></span><span class="t">                <span class="str">'Actual ruleset contains rules not present in expected ruleset'</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t443" href="#t443">443</a></span><span class="t">    <span class="key">for</span> <span class="nam">value</span> <span class="key">in</span> <span class="nam">dictionary</span><span class="op">.</span><span class="nam">values</span><span class="op">(</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t444" href="#t444">444</a></span><span class="t">        <span class="key">if</span> <span class="nam">value</span> <span class="op">==</span> <span class="num">0</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t445" href="#t445">445</a></span><span class="t">            <span class="key">raise</span> <span class="nam">AssertionError</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t446" href="#t446">446</a></span><span class="t">                <span class="str">'Ruleset are not equal, some rules are missing'</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t447" href="#t447">447</a></span><span class="t">        <span class="key">elif</span> <span class="nam">value</span> <span class="op">></span> <span class="num">1</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t448" href="#t448">448</a></span><span class="t">            <span class="key">raise</span> <span class="nam">AssertionError</span><span class="op">(</span><span class="str">'Somes rules were duplicated'</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t449" href="#t449">449</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t450" href="#t450">450</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t451" href="#t451">451</a></span><span class="t"><span class="key">def</span> <span class="nam">assert_accuracy_is_greater</span><span class="op">(</span><span class="nam">prediction</span><span class="op">,</span> <span class="nam">expected</span><span class="op">,</span> <span class="nam">threshold</span><span class="op">:</span> <span class="nam">float</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t452" href="#t452">452</a></span><span class="t">    <span class="nam">labels</span> <span class="op">=</span> <span class="nam">expected</span><span class="op">.</span><span class="nam">to_numpy</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">astype</span><span class="op">(</span><span class="nam">str</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t453" href="#t453">453</a></span><span class="t">    <span class="nam">acc</span> <span class="op">=</span> <span class="nam">metrics</span><span class="op">.</span><span class="nam">accuracy_score</span><span class="op">(</span><span class="nam">labels</span><span class="op">,</span> <span class="nam">prediction</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t454" href="#t454">454</a></span><span class="t">    <span class="key">if</span> <span class="nam">acc</span> <span class="op">&lt;=</span> <span class="nam">threshold</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t455" href="#t455">455</a></span><span class="t">        <span class="key">raise</span> <span class="nam">AssertionError</span><span class="op">(</span><span class="str">f'Accuracy should be greater than {threshold}'</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t456" href="#t456">456</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t457" href="#t457">457</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t458" href="#t458">458</a></span><span class="t"><span class="key">def</span> <span class="nam">assert_score_is_greater</span><span class="op">(</span><span class="nam">prediction</span><span class="op">,</span> <span class="nam">expected</span><span class="op">,</span> <span class="nam">threshold</span><span class="op">:</span> <span class="nam">float</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t459" href="#t459">459</a></span><span class="t">    <span class="key">if</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">prediction</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="op">,</span> <span class="nam">int</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t460" href="#t460">460</a></span><span class="t">        <span class="nam">labels</span> <span class="op">=</span> <span class="nam">expected</span><span class="op">.</span><span class="nam">to_numpy</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">astype</span><span class="op">(</span><span class="nam">int</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t461" href="#t461">461</a></span><span class="t">    <span class="key">if</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">prediction</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="op">,</span> <span class="nam">float</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t462" href="#t462">462</a></span><span class="t">        <span class="nam">labels</span> <span class="op">=</span> <span class="nam">expected</span><span class="op">.</span><span class="nam">to_numpy</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">astype</span><span class="op">(</span><span class="nam">float</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t463" href="#t463">463</a></span><span class="t">    <span class="nam">explained_variance_score</span> <span class="op">=</span> <span class="nam">metrics</span><span class="op">.</span><span class="nam">explained_variance_score</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t464" href="#t464">464</a></span><span class="t">        <span class="nam">labels</span><span class="op">,</span> <span class="nam">prediction</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t465" href="#t465">465</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t466" href="#t466">466</a></span><span class="t">    <span class="key">if</span> <span class="nam">explained_variance_score</span> <span class="op">&lt;=</span> <span class="nam">threshold</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t467" href="#t467">467</a></span><span class="t">        <span class="key">raise</span> <span class="nam">AssertionError</span><span class="op">(</span><span class="str">f'Score should be greater than {threshold}'</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t427" href="#t427">427</a></span><span class="t"><span class="key">def</span> <span class="nam">assert_rules_are_equals</span><span class="op">(</span><span class="nam">expected</span><span class="op">:</span> <span class="nam">list</span><span class="op">[</span><span class="nam">str</span><span class="op">]</span><span class="op">,</span> <span class="nam">actual</span><span class="op">:</span> <span class="nam">list</span><span class="op">[</span><span class="nam">str</span><span class="op">]</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t428" href="#t428">428</a></span><span class="t">    <span class="key">def</span> <span class="nam">sanitize_rule_string</span><span class="op">(</span><span class="nam">rule_string</span><span class="op">:</span> <span class="nam">str</span><span class="op">)</span> <span class="op">-></span> <span class="nam">str</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t429" href="#t429">429</a></span><span class="t">        <span class="key">return</span> <span class="nam">re</span><span class="op">.</span><span class="nam">sub</span><span class="op">(</span><span class="str">r"(\t)|(\n)|(\[[^\]]*\]$)"</span><span class="op">,</span> <span class="str">""</span><span class="op">,</span> <span class="nam">rule_string</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t430" href="#t430">430</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t431" href="#t431">431</a></span><span class="t">    <span class="nam">expected</span> <span class="op">=</span> <span class="nam">list</span><span class="op">(</span><span class="nam">map</span><span class="op">(</span><span class="nam">sanitize_rule_string</span><span class="op">,</span> <span class="nam">expected</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t432" href="#t432">432</a></span><span class="t">    <span class="nam">actual</span> <span class="op">=</span> <span class="nam">list</span><span class="op">(</span><span class="nam">map</span><span class="op">(</span><span class="nam">sanitize_rule_string</span><span class="op">,</span> <span class="nam">actual</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t433" href="#t433">433</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t434" href="#t434">434</a></span><span class="t">    <span class="key">if</span> <span class="nam">len</span><span class="op">(</span><span class="nam">expected</span><span class="op">)</span> <span class="op">!=</span> <span class="nam">len</span><span class="op">(</span><span class="nam">actual</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t435" href="#t435">435</a></span><span class="t">        <span class="key">raise</span> <span class="nam">AssertionError</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t436" href="#t436">436</a></span><span class="t">            <span class="str">f"Rulesets have different number of rules, actual: {len(actual)}, expected: {len(expected)}"</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t437" href="#t437">437</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t438" href="#t438">438</a></span><span class="t">    <span class="nam">dictionary</span> <span class="op">=</span> <span class="op">{</span><span class="op">}</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t439" href="#t439">439</a></span><span class="t">    <span class="key">for</span> <span class="nam">rule</span> <span class="key">in</span> <span class="nam">expected</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t440" href="#t440">440</a></span><span class="t">        <span class="nam">dictionary</span><span class="op">[</span><span class="nam">rule</span><span class="op">]</span> <span class="op">=</span> <span class="num">0</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t441" href="#t441">441</a></span><span class="t">    <span class="key">for</span> <span class="nam">rule</span> <span class="key">in</span> <span class="nam">actual</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t442" href="#t442">442</a></span><span class="t">        <span class="nam">key</span> <span class="op">=</span> <span class="nam">rule</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t443" href="#t443">443</a></span><span class="t">        <span class="key">if</span> <span class="nam">key</span> <span class="key">in</span> <span class="nam">dictionary</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t444" href="#t444">444</a></span><span class="t">            <span class="nam">dictionary</span><span class="op">[</span><span class="nam">key</span><span class="op">]</span> <span class="op">=</span> <span class="nam">dictionary</span><span class="op">[</span><span class="nam">key</span><span class="op">]</span> <span class="op">+</span> <span class="num">1</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t445" href="#t445">445</a></span><span class="t">        <span class="key">else</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t446" href="#t446">446</a></span><span class="t">            <span class="key">raise</span> <span class="nam">AssertionError</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t447" href="#t447">447</a></span><span class="t">                <span class="str">"Actual ruleset contains rules not present in expected ruleset"</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t448" href="#t448">448</a></span><span class="t">            <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t449" href="#t449">449</a></span><span class="t">    <span class="key">for</span> <span class="nam">value</span> <span class="key">in</span> <span class="nam">dictionary</span><span class="op">.</span><span class="nam">values</span><span class="op">(</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t450" href="#t450">450</a></span><span class="t">        <span class="key">if</span> <span class="nam">value</span> <span class="op">==</span> <span class="num">0</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t451" href="#t451">451</a></span><span class="t">            <span class="key">raise</span> <span class="nam">AssertionError</span><span class="op">(</span><span class="str">"Ruleset are not equal, some rules are missing"</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t452" href="#t452">452</a></span><span class="t">        <span class="key">elif</span> <span class="nam">value</span> <span class="op">></span> <span class="num">1</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t453" href="#t453">453</a></span><span class="t">            <span class="key">raise</span> <span class="nam">AssertionError</span><span class="op">(</span><span class="str">"Somes rules were duplicated"</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t454" href="#t454">454</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t455" href="#t455">455</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t456" href="#t456">456</a></span><span class="t"><span class="key">def</span> <span class="nam">assert_accuracy_is_greater</span><span class="op">(</span><span class="nam">prediction</span><span class="op">,</span> <span class="nam">expected</span><span class="op">,</span> <span class="nam">threshold</span><span class="op">:</span> <span class="nam">float</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t457" href="#t457">457</a></span><span class="t">    <span class="nam">labels</span> <span class="op">=</span> <span class="nam">expected</span><span class="op">.</span><span class="nam">to_numpy</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">astype</span><span class="op">(</span><span class="nam">str</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t458" href="#t458">458</a></span><span class="t">    <span class="nam">acc</span> <span class="op">=</span> <span class="nam">metrics</span><span class="op">.</span><span class="nam">accuracy_score</span><span class="op">(</span><span class="nam">labels</span><span class="op">,</span> <span class="nam">prediction</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t459" href="#t459">459</a></span><span class="t">    <span class="key">if</span> <span class="nam">acc</span> <span class="op">&lt;=</span> <span class="nam">threshold</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t460" href="#t460">460</a></span><span class="t">        <span class="key">raise</span> <span class="nam">AssertionError</span><span class="op">(</span><span class="str">f"Accuracy should be greater than {threshold} (was {acc})"</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t461" href="#t461">461</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t462" href="#t462">462</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t463" href="#t463">463</a></span><span class="t"><span class="key">def</span> <span class="nam">assert_score_is_greater</span><span class="op">(</span><span class="nam">prediction</span><span class="op">,</span> <span class="nam">expected</span><span class="op">,</span> <span class="nam">threshold</span><span class="op">:</span> <span class="nam">float</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t464" href="#t464">464</a></span><span class="t">    <span class="key">if</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">prediction</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="op">,</span> <span class="nam">int</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t465" href="#t465">465</a></span><span class="t">        <span class="nam">labels</span> <span class="op">=</span> <span class="nam">expected</span><span class="op">.</span><span class="nam">to_numpy</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">astype</span><span class="op">(</span><span class="nam">int</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t466" href="#t466">466</a></span><span class="t">    <span class="key">elif</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">prediction</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="op">,</span> <span class="nam">float</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t467" href="#t467">467</a></span><span class="t">        <span class="nam">labels</span> <span class="op">=</span> <span class="nam">expected</span><span class="op">.</span><span class="nam">to_numpy</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">astype</span><span class="op">(</span><span class="nam">float</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t468" href="#t468">468</a></span><span class="t">    <span class="key">else</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t469" href="#t469">469</a></span><span class="t">        <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t470" href="#t470">470</a></span><span class="t">            <span class="str">f"Invalid prediction type: {str(type(prediction[0]))}. "</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t471" href="#t471">471</a></span><span class="t">            <span class="op">+</span> <span class="str">"Supported types are: 1 dimensional numpy array or pandas Series object."</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t472" href="#t472">472</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t473" href="#t473">473</a></span><span class="t">    <span class="nam">explained_variance_score</span> <span class="op">=</span> <span class="nam">metrics</span><span class="op">.</span><span class="nam">explained_variance_score</span><span class="op">(</span><span class="nam">labels</span><span class="op">,</span> <span class="nam">prediction</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t474" href="#t474">474</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t475" href="#t475">475</a></span><span class="t">    <span class="key">if</span> <span class="nam">explained_variance_score</span> <span class="op">&lt;=</span> <span class="nam">threshold</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t476" href="#t476">476</a></span><span class="t">        <span class="key">raise</span> <span class="nam">AssertionError</span><span class="op">(</span><span class="str">f"Score should be greater than {threshold}"</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
 </main>
 <footer>
     <div class="content">
@@ -556,7 +565,7 @@ <h2>
             <a class="nav" href="index.html">&#xbb; next</a>
             &nbsp; &nbsp; &nbsp;
             <a class="nav" href="https://coverage.readthedocs.io/en/7.6.4">coverage.py v7.6.4</a>,
-            created at 2024-11-05 13:43 +0100
+            created at 2024-11-28 11:55 +0100
         </p>
     </div>
 </footer>
diff --git a/docs/reports/coverage/z_a87f2a4bb6695d91__helpers_py.html b/docs/reports/coverage/z_a87f2a4bb6695d91__helpers_py.html
index 4f95126..e71b0e8 100644
--- a/docs/reports/coverage/z_a87f2a4bb6695d91__helpers_py.html
+++ b/docs/reports/coverage/z_a87f2a4bb6695d91__helpers_py.html
@@ -2,7 +2,7 @@
 <html lang="en">
 <head>
     <meta http-equiv="Content-Type" content="text/html; charset=utf-8">
-    <title>Coverage for rulekit\_helpers.py: 88%</title>
+    <title>Coverage for rulekit\_helpers.py: 85%</title>
     <link rel="icon" sizes="32x32" href="favicon_32_cb_58284776.png">
     <link rel="stylesheet" href="style_cb_718ce007.css" type="text/css">
     <script src="coverage_html_cb_497bf287.js" defer></script>
@@ -12,7 +12,7 @@
     <div class="content">
         <h1>
             <span class="text">Coverage for </span><b>rulekit\_helpers.py</b>:
-            <span class="pc_cov">88%</span>
+            <span class="pc_cov">85%</span>
         </h1>
         <aside id="help_panel_wrapper">
             <input id="help_panel_state" type="checkbox">
@@ -54,9 +54,9 @@ <h1>
             </div>
         </aside>
         <h2>
-            <span class="text">232 statements &nbsp;</span>
-            <button type="button" class="run button_toggle_run" value="run" data-shortcut="r" title="Toggle lines run">203<span class="text"> run</span></button>
-            <button type="button" class="mis show_mis button_toggle_mis" value="mis" data-shortcut="m" title="Toggle lines missing">29<span class="text"> missing</span></button>
+            <span class="text">253 statements &nbsp;</span>
+            <button type="button" class="run button_toggle_run" value="run" data-shortcut="r" title="Toggle lines run">215<span class="text"> run</span></button>
+            <button type="button" class="mis show_mis button_toggle_mis" value="mis" data-shortcut="m" title="Toggle lines missing">38<span class="text"> missing</span></button>
             <button type="button" class="exc show_exc button_toggle_exc" value="exc" data-shortcut="x" title="Toggle lines excluded">0<span class="text"> excluded</span></button>
         </h2>
         <p class="text">
@@ -65,7 +65,7 @@ <h2>
             <a id="nextFileLink" class="nav" href="z_a87f2a4bb6695d91__logging_py.html">&#xbb; next</a>
             &nbsp; &nbsp; &nbsp;
             <a class="nav" href="https://coverage.readthedocs.io/en/7.6.4">coverage.py v7.6.4</a>,
-            created at 2024-11-08 14:43 +0100
+            created at 2024-11-28 12:20 +0100
         </p>
         <aside class="hidden">
             <button type="button" class="button_next_chunk" data-shortcut="j"></button>
@@ -82,490 +82,527 @@ <h2>
 <main id="source">
     <p class="pln"><span class="n"><a id="t1" href="#t1">1</a></span><span class="t"><span class="str">"""Contains helper functions and classes</span>&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t2" href="#t2">2</a></span><span class="t"><span class="str">"""</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t3" href="#t3">3</a></span><span class="t"><span class="key">import</span> <span class="nam">io</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t4" href="#t4">4</a></span><span class="t"><span class="key">import</span> <span class="nam">json</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t5" href="#t5">5</a></span><span class="t"><span class="key">from</span> <span class="nam">typing</span> <span class="key">import</span> <span class="nam">Any</span><span class="op">,</span> <span class="nam">Optional</span><span class="op">,</span> <span class="nam">Union</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t6" href="#t6">6</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t7" href="#t7">7</a></span><span class="t"><span class="key">import</span> <span class="nam">numpy</span> <span class="key">as</span> <span class="nam">np</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t8" href="#t8">8</a></span><span class="t"><span class="key">import</span> <span class="nam">pandas</span> <span class="key">as</span> <span class="nam">pd</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t9" href="#t9">9</a></span><span class="t"><span class="key">from</span> <span class="nam">jpype</span> <span class="key">import</span> <span class="nam">JArray</span><span class="op">,</span> <span class="nam">JClass</span><span class="op">,</span> <span class="nam">JObject</span><span class="op">,</span> <span class="nam">java</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t10" href="#t10">10</a></span><span class="t"><span class="key">from</span> <span class="nam">jpype</span><span class="op">.</span><span class="nam">pickle</span> <span class="key">import</span> <span class="nam">JPickler</span><span class="op">,</span> <span class="nam">JUnpickler</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t11" href="#t11">11</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t12" href="#t12">12</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">_logging</span> <span class="key">import</span> <span class="nam">_RuleKitJavaLoggerConfig</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t13" href="#t13">13</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">_problem_types</span> <span class="key">import</span> <span class="nam">ProblemType</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t14" href="#t14">14</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">exceptions</span> <span class="key">import</span> <span class="nam">RuleKitMisconfigurationException</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t15" href="#t15">15</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">main</span> <span class="key">import</span> <span class="nam">RuleKit</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t16" href="#t16">16</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">params</span> <span class="key">import</span> <span class="nam">Measures</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t17" href="#t17">17</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">rules</span> <span class="key">import</span> <span class="nam">BaseRule</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t18" href="#t18">18</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t3" href="#t3">3</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t4" href="#t4">4</a></span><span class="t"><span class="key">import</span> <span class="nam">io</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t5" href="#t5">5</a></span><span class="t"><span class="key">import</span> <span class="nam">json</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t6" href="#t6">6</a></span><span class="t"><span class="key">from</span> <span class="nam">typing</span> <span class="key">import</span> <span class="nam">Any</span><span class="op">,</span> <span class="nam">Callable</span><span class="op">,</span> <span class="nam">Optional</span><span class="op">,</span> <span class="nam">Union</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t7" href="#t7">7</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t8" href="#t8">8</a></span><span class="t"><span class="key">import</span> <span class="nam">numpy</span> <span class="key">as</span> <span class="nam">np</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t9" href="#t9">9</a></span><span class="t"><span class="key">import</span> <span class="nam">pandas</span> <span class="key">as</span> <span class="nam">pd</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t10" href="#t10">10</a></span><span class="t"><span class="key">from</span> <span class="nam">jpype</span> <span class="key">import</span> <span class="nam">JArray</span><span class="op">,</span> <span class="nam">JClass</span><span class="op">,</span> <span class="nam">JObject</span><span class="op">,</span> <span class="nam">java</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t11" href="#t11">11</a></span><span class="t"><span class="key">from</span> <span class="nam">jpype</span><span class="op">.</span><span class="nam">pickle</span> <span class="key">import</span> <span class="nam">JPickler</span><span class="op">,</span> <span class="nam">JUnpickler</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t12" href="#t12">12</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t13" href="#t13">13</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">_logging</span> <span class="key">import</span> <span class="nam">_RuleKitJavaLoggerConfig</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t14" href="#t14">14</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">_problem_types</span> <span class="key">import</span> <span class="nam">ProblemType</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t15" href="#t15">15</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">exceptions</span> <span class="key">import</span> <span class="nam">RuleKitMisconfigurationException</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t16" href="#t16">16</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">main</span> <span class="key">import</span> <span class="nam">RuleKit</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t17" href="#t17">17</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">params</span> <span class="key">import</span> <span class="nam">Measures</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t18" href="#t18">18</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">rules</span> <span class="key">import</span> <span class="nam">BaseRule</span>&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t19" href="#t19">19</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t20" href="#t20">20</a></span><span class="t"><span class="key">def</span> <span class="nam">get_rule_generator</span><span class="op">(</span><span class="nam">expert</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="key">False</span><span class="op">)</span> <span class="op">-></span> <span class="nam">Any</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t21" href="#t21">21</a></span><span class="t">    <span class="str">"""Factory for Java RuleGenerator class object</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t22" href="#t22">22</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t23" href="#t23">23</a></span><span class="t"><span class="str">    Args:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t24" href="#t24">24</a></span><span class="t"><span class="str">        expert (bool, optional): Whether expert induction is enables.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t25" href="#t25">25</a></span><span class="t"><span class="str">         Defaults to False.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t26" href="#t26">26</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t27" href="#t27">27</a></span><span class="t"><span class="str">    Returns:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t28" href="#t28">28</a></span><span class="t"><span class="str">        Any: RuleGenerator instance</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t29" href="#t29">29</a></span><span class="t"><span class="str">    """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t30" href="#t30">30</a></span><span class="t">    <span class="nam">RuleKit</span><span class="op">.</span><span class="nam">init</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t20" href="#t20">20</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t21" href="#t21">21</a></span><span class="t"><span class="key">def</span> <span class="nam">get_rule_generator</span><span class="op">(</span><span class="nam">expert</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="key">False</span><span class="op">)</span> <span class="op">-></span> <span class="nam">Any</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t22" href="#t22">22</a></span><span class="t">    <span class="str">"""Factory for Java RuleGenerator class object</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t23" href="#t23">23</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t24" href="#t24">24</a></span><span class="t"><span class="str">    Args:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t25" href="#t25">25</a></span><span class="t"><span class="str">        expert (bool, optional): Whether expert induction is enables.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t26" href="#t26">26</a></span><span class="t"><span class="str">         Defaults to False.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t27" href="#t27">27</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t28" href="#t28">28</a></span><span class="t"><span class="str">    Returns:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t29" href="#t29">29</a></span><span class="t"><span class="str">        Any: RuleGenerator instance</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t30" href="#t30">30</a></span><span class="t"><span class="str">    """</span>&nbsp;</span><span class="r"></span></p>
     <p class="run"><span class="n"><a id="t31" href="#t31">31</a></span><span class="t">    <span class="nam">RuleGenerator</span> <span class="op">=</span> <span class="nam">JClass</span><span class="op">(</span>  <span class="com"># pylint: disable=invalid-name</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t32" href="#t32">32</a></span><span class="t">        <span class="str">'adaa.analytics.rules.logic.rulegenerator.RuleGenerator'</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t32" href="#t32">32</a></span><span class="t">        <span class="str">"adaa.analytics.rules.logic.rulegenerator.RuleGenerator"</span>&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t33" href="#t33">33</a></span><span class="t">    <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
     <p class="run"><span class="n"><a id="t34" href="#t34">34</a></span><span class="t">    <span class="nam">rule_generator</span> <span class="op">=</span> <span class="nam">RuleGenerator</span><span class="op">(</span><span class="nam">expert</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
     <p class="run"><span class="n"><a id="t35" href="#t35">35</a></span><span class="t">    <span class="key">return</span> <span class="nam">rule_generator</span>&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t36" href="#t36">36</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t37" href="#t37">37</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
     <p class="run"><span class="n"><a id="t38" href="#t38">38</a></span><span class="t"><span class="key">class</span> <span class="nam">RuleGeneratorConfigurator</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t39" href="#t39">39</a></span><span class="t">    <span class="str">"""Class for configuring rule induction parameters</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t40" href="#t40">40</a></span><span class="t"><span class="str">    """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t41" href="#t41">41</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t42" href="#t42">42</a></span><span class="t">    <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">rule_generator</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t43" href="#t43">43</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">rule_generator</span> <span class="op">=</span> <span class="nam">rule_generator</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t44" href="#t44">44</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">LogRank</span> <span class="op">=</span> <span class="key">None</span>  <span class="com"># pylint: disable=invalid-name</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t45" href="#t45">45</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t46" href="#t46">46</a></span><span class="t">    <span class="key">def</span> <span class="nam">configure</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="op">**</span><span class="nam">params</span><span class="op">:</span> <span class="nam">dict</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">Any</span><span class="op">]</span><span class="op">)</span> <span class="op">-></span> <span class="nam">Any</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t47" href="#t47">47</a></span><span class="t">        <span class="str">"""Configures RuleGenerator instance with given induction parameters</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t48" href="#t48">48</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t49" href="#t49">49</a></span><span class="t"><span class="str">        Returns:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t50" href="#t50">50</a></span><span class="t"><span class="str">            Any: configured RuleGenerator instance</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t51" href="#t51">51</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t52" href="#t52">52</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_configure_rule_generator</span><span class="op">(</span><span class="op">**</span><span class="nam">params</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t53" href="#t53">53</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_validate_rule_generator_parameters</span><span class="op">(</span><span class="op">**</span><span class="nam">params</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t54" href="#t54">54</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_configure_java_logging</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t55" href="#t55">55</a></span><span class="t">        <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">rule_generator</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t56" href="#t56">56</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t57" href="#t57">57</a></span><span class="t">    <span class="key">def</span> <span class="nam">_configure_expert_parameter</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">param_name</span><span class="op">:</span> <span class="nam">str</span><span class="op">,</span> <span class="nam">param_value</span><span class="op">:</span> <span class="nam">Any</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t58" href="#t58">58</a></span><span class="t">        <span class="key">if</span> <span class="nam">param_value</span> <span class="key">is</span> <span class="key">None</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t59" href="#t59">59</a></span><span class="t">            <span class="key">return</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t60" href="#t60">60</a></span><span class="t">        <span class="nam">rules_list</span> <span class="op">=</span> <span class="nam">java</span><span class="op">.</span><span class="nam">util</span><span class="op">.</span><span class="nam">ArrayList</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t61" href="#t61">61</a></span><span class="t">        <span class="key">if</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">param_value</span><span class="op">,</span> <span class="nam">list</span><span class="op">)</span> <span class="key">and</span> <span class="nam">len</span><span class="op">(</span><span class="nam">param_value</span><span class="op">)</span> <span class="op">></span> <span class="num">0</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t62" href="#t62">62</a></span><span class="t">            <span class="key">if</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">param_value</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="op">,</span> <span class="nam">str</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t63" href="#t63">63</a></span><span class="t">                <span class="key">for</span> <span class="nam">index</span><span class="op">,</span> <span class="nam">rule</span> <span class="key">in</span> <span class="nam">enumerate</span><span class="op">(</span><span class="nam">param_value</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t64" href="#t64">64</a></span><span class="t">                    <span class="nam">rule_name</span> <span class="op">=</span> <span class="str">f'{param_name[:-1]}-{index}'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t65" href="#t65">65</a></span><span class="t">                    <span class="nam">rules_list</span><span class="op">.</span><span class="nam">add</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t66" href="#t66">66</a></span><span class="t">                        <span class="nam">JObject</span><span class="op">(</span><span class="op">[</span><span class="nam">rule_name</span><span class="op">,</span> <span class="nam">rule</span><span class="op">]</span><span class="op">,</span> <span class="nam">JArray</span><span class="op">(</span><span class="str">'java.lang.String'</span><span class="op">,</span> <span class="num">1</span><span class="op">)</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t67" href="#t67">67</a></span><span class="t">            <span class="key">elif</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">param_value</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="op">,</span> <span class="nam">BaseRule</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t68" href="#t68">68</a></span><span class="t">                <span class="key">for</span> <span class="nam">index</span><span class="op">,</span> <span class="nam">rule</span> <span class="key">in</span> <span class="nam">enumerate</span><span class="op">(</span><span class="nam">param_value</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t69" href="#t69">69</a></span><span class="t">                    <span class="nam">rule_name</span> <span class="op">=</span> <span class="str">f'{param_name[:-1]}-{index}'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t70" href="#t70">70</a></span><span class="t">                    <span class="nam">rules_list</span><span class="op">.</span><span class="nam">add</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t71" href="#t71">71</a></span><span class="t">                        <span class="nam">JObject</span><span class="op">(</span><span class="op">[</span><span class="nam">rule_name</span><span class="op">,</span> <span class="nam">str</span><span class="op">(</span><span class="nam">rule</span><span class="op">)</span><span class="op">]</span><span class="op">,</span> <span class="nam">JArray</span><span class="op">(</span><span class="str">'java.lang.String'</span><span class="op">,</span> <span class="num">1</span><span class="op">)</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t72" href="#t72">72</a></span><span class="t">            <span class="key">elif</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">param_value</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="op">,</span> <span class="nam">tuple</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t73" href="#t73">73</a></span><span class="t">                <span class="key">for</span> <span class="nam">index</span><span class="op">,</span> <span class="nam">rule</span> <span class="key">in</span> <span class="nam">enumerate</span><span class="op">(</span><span class="nam">param_value</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t74" href="#t74">74</a></span><span class="t">                    <span class="nam">rules_list</span><span class="op">.</span><span class="nam">add</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t75" href="#t75">75</a></span><span class="t">                        <span class="nam">JObject</span><span class="op">(</span><span class="op">[</span><span class="nam">rule</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="op">,</span> <span class="nam">rule</span><span class="op">[</span><span class="num">1</span><span class="op">]</span><span class="op">]</span><span class="op">,</span> <span class="nam">JArray</span><span class="op">(</span><span class="str">'java.lang.String'</span><span class="op">,</span> <span class="num">1</span><span class="op">)</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t76" href="#t76">76</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">rule_generator</span><span class="op">.</span><span class="nam">setListParameter</span><span class="op">(</span><span class="nam">param_name</span><span class="op">,</span> <span class="nam">rules_list</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t77" href="#t77">77</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t78" href="#t78">78</a></span><span class="t">    <span class="key">def</span> <span class="nam">_configure_simple_parameter</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">param_name</span><span class="op">:</span> <span class="nam">str</span><span class="op">,</span> <span class="nam">param_value</span><span class="op">:</span> <span class="nam">Any</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t79" href="#t79">79</a></span><span class="t">        <span class="key">if</span> <span class="nam">param_value</span> <span class="key">is</span> <span class="key">not</span> <span class="key">None</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t80" href="#t80">80</a></span><span class="t">            <span class="key">if</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">param_value</span><span class="op">,</span> <span class="nam">bool</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t81" href="#t81">81</a></span><span class="t">                <span class="nam">param_value</span> <span class="op">=</span> <span class="op">(</span><span class="nam">str</span><span class="op">(</span><span class="nam">param_value</span><span class="op">)</span><span class="op">)</span><span class="op">.</span><span class="nam">lower</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t82" href="#t82">82</a></span><span class="t">            <span class="key">elif</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">param_value</span><span class="op">,</span> <span class="nam">tuple</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t83" href="#t83">83</a></span><span class="t">                <span class="nam">param_value</span> <span class="op">=</span> <span class="str">' '</span><span class="op">.</span><span class="nam">join</span><span class="op">(</span><span class="nam">list</span><span class="op">(</span><span class="nam">map</span><span class="op">(</span><span class="nam">str</span><span class="op">,</span> <span class="nam">param_value</span><span class="op">)</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t84" href="#t84">84</a></span><span class="t">            <span class="key">elif</span> <span class="key">not</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">param_value</span><span class="op">,</span> <span class="nam">str</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t85" href="#t85">85</a></span><span class="t">                <span class="nam">param_value</span> <span class="op">=</span> <span class="nam">str</span><span class="op">(</span><span class="nam">param_value</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t86" href="#t86">86</a></span><span class="t">            <span class="nam">self</span><span class="op">.</span><span class="nam">rule_generator</span><span class="op">.</span><span class="nam">setParameter</span><span class="op">(</span><span class="nam">param_name</span><span class="op">,</span> <span class="nam">param_value</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t87" href="#t87">87</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t88" href="#t88">88</a></span><span class="t">    <span class="key">def</span> <span class="nam">_configure_measure_parameter</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">param_name</span><span class="op">:</span> <span class="nam">str</span><span class="op">,</span> <span class="nam">param_value</span><span class="op">:</span> <span class="nam">Union</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">Measures</span><span class="op">]</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t89" href="#t89">89</a></span><span class="t">        <span class="key">if</span> <span class="nam">param_value</span> <span class="key">is</span> <span class="key">not</span> <span class="key">None</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t90" href="#t90">90</a></span><span class="t">            <span class="key">if</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">param_value</span><span class="op">,</span> <span class="nam">Measures</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t91" href="#t91">91</a></span><span class="t">                <span class="nam">self</span><span class="op">.</span><span class="nam">rule_generator</span><span class="op">.</span><span class="nam">setParameter</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t92" href="#t92">92</a></span><span class="t">                    <span class="nam">param_name</span><span class="op">,</span> <span class="nam">param_value</span><span class="op">.</span><span class="nam">value</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t93" href="#t93">93</a></span><span class="t">            <span class="key">if</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">param_value</span><span class="op">,</span> <span class="nam">str</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t94" href="#t94">94</a></span><span class="t">                <span class="nam">self</span><span class="op">.</span><span class="nam">rule_generator</span><span class="op">.</span><span class="nam">setParameter</span><span class="op">(</span><span class="nam">param_name</span><span class="op">,</span> <span class="str">'UserDefined'</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t95" href="#t95">95</a></span><span class="t">                <span class="nam">self</span><span class="op">.</span><span class="nam">rule_generator</span><span class="op">.</span><span class="nam">setParameter</span><span class="op">(</span><span class="nam">param_name</span><span class="op">,</span> <span class="nam">param_value</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t39" href="#t39">39</a></span><span class="t">    <span class="str">"""Class for configuring rule induction parameters"""</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t40" href="#t40">40</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t41" href="#t41">41</a></span><span class="t">    <span class="nam">_MEASURES_PARAMETERS</span><span class="op">:</span> <span class="nam">list</span><span class="op">[</span><span class="nam">str</span><span class="op">]</span> <span class="op">=</span> <span class="op">[</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t42" href="#t42">42</a></span><span class="t">        <span class="str">"induction_measure"</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t43" href="#t43">43</a></span><span class="t">        <span class="str">"pruning_measure"</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t44" href="#t44">44</a></span><span class="t">        <span class="str">"voting_measure"</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t45" href="#t45">45</a></span><span class="t">    <span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t46" href="#t46">46</a></span><span class="t">    <span class="nam">_USER_DEFINED_MEASURE_VALUE</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="str">"UserDefined"</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t47" href="#t47">47</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t48" href="#t48">48</a></span><span class="t">    <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">rule_generator</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t49" href="#t49">49</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">rule_generator</span> <span class="op">=</span> <span class="nam">rule_generator</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t50" href="#t50">50</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">LogRank</span> <span class="op">=</span> <span class="key">None</span>  <span class="com"># pylint: disable=invalid-name</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t51" href="#t51">51</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t52" href="#t52">52</a></span><span class="t">    <span class="key">def</span> <span class="nam">configure</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="op">**</span><span class="nam">params</span><span class="op">:</span> <span class="nam">dict</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">Any</span><span class="op">]</span><span class="op">)</span> <span class="op">-></span> <span class="nam">Any</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t53" href="#t53">53</a></span><span class="t">        <span class="str">"""Configures RuleGenerator instance with given induction parameters</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t54" href="#t54">54</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t55" href="#t55">55</a></span><span class="t"><span class="str">        Returns:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t56" href="#t56">56</a></span><span class="t"><span class="str">            Any: configured RuleGenerator instance</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t57" href="#t57">57</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t58" href="#t58">58</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_configure_rule_generator</span><span class="op">(</span><span class="op">**</span><span class="nam">params</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t59" href="#t59">59</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_validate_rule_generator_parameters</span><span class="op">(</span><span class="op">**</span><span class="nam">params</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t60" href="#t60">60</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_configure_java_logging</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t61" href="#t61">61</a></span><span class="t">        <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">rule_generator</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t62" href="#t62">62</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t63" href="#t63">63</a></span><span class="t">    <span class="key">def</span> <span class="nam">_configure_expert_parameter</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">param_name</span><span class="op">:</span> <span class="nam">str</span><span class="op">,</span> <span class="nam">param_value</span><span class="op">:</span> <span class="nam">Any</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t64" href="#t64">64</a></span><span class="t">        <span class="key">if</span> <span class="nam">param_value</span> <span class="key">is</span> <span class="key">None</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t65" href="#t65">65</a></span><span class="t">            <span class="key">return</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t66" href="#t66">66</a></span><span class="t">        <span class="nam">rules_list</span> <span class="op">=</span> <span class="nam">java</span><span class="op">.</span><span class="nam">util</span><span class="op">.</span><span class="nam">ArrayList</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t67" href="#t67">67</a></span><span class="t">        <span class="key">if</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">param_value</span><span class="op">,</span> <span class="nam">list</span><span class="op">)</span> <span class="key">and</span> <span class="nam">len</span><span class="op">(</span><span class="nam">param_value</span><span class="op">)</span> <span class="op">></span> <span class="num">0</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t68" href="#t68">68</a></span><span class="t">            <span class="key">if</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">param_value</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="op">,</span> <span class="nam">str</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t69" href="#t69">69</a></span><span class="t">                <span class="key">for</span> <span class="nam">index</span><span class="op">,</span> <span class="nam">rule</span> <span class="key">in</span> <span class="nam">enumerate</span><span class="op">(</span><span class="nam">param_value</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t70" href="#t70">70</a></span><span class="t">                    <span class="nam">rule_name</span> <span class="op">=</span> <span class="str">f"{param_name[:-1]}-{index}"</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t71" href="#t71">71</a></span><span class="t">                    <span class="nam">rules_list</span><span class="op">.</span><span class="nam">add</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t72" href="#t72">72</a></span><span class="t">                        <span class="nam">JObject</span><span class="op">(</span><span class="op">[</span><span class="nam">rule_name</span><span class="op">,</span> <span class="nam">rule</span><span class="op">]</span><span class="op">,</span> <span class="nam">JArray</span><span class="op">(</span><span class="str">"java.lang.String"</span><span class="op">,</span> <span class="num">1</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t73" href="#t73">73</a></span><span class="t">                    <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t74" href="#t74">74</a></span><span class="t">            <span class="key">elif</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">param_value</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="op">,</span> <span class="nam">BaseRule</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t75" href="#t75">75</a></span><span class="t">                <span class="key">for</span> <span class="nam">index</span><span class="op">,</span> <span class="nam">rule</span> <span class="key">in</span> <span class="nam">enumerate</span><span class="op">(</span><span class="nam">param_value</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t76" href="#t76">76</a></span><span class="t">                    <span class="nam">rule_name</span> <span class="op">=</span> <span class="str">f"{param_name[:-1]}-{index}"</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t77" href="#t77">77</a></span><span class="t">                    <span class="nam">rules_list</span><span class="op">.</span><span class="nam">add</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t78" href="#t78">78</a></span><span class="t">                        <span class="nam">JObject</span><span class="op">(</span><span class="op">[</span><span class="nam">rule_name</span><span class="op">,</span> <span class="nam">str</span><span class="op">(</span><span class="nam">rule</span><span class="op">)</span><span class="op">]</span><span class="op">,</span> <span class="nam">JArray</span><span class="op">(</span><span class="str">"java.lang.String"</span><span class="op">,</span> <span class="num">1</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t79" href="#t79">79</a></span><span class="t">                    <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t80" href="#t80">80</a></span><span class="t">            <span class="key">elif</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">param_value</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="op">,</span> <span class="nam">tuple</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t81" href="#t81">81</a></span><span class="t">                <span class="key">for</span> <span class="nam">index</span><span class="op">,</span> <span class="nam">rule</span> <span class="key">in</span> <span class="nam">enumerate</span><span class="op">(</span><span class="nam">param_value</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t82" href="#t82">82</a></span><span class="t">                    <span class="nam">rules_list</span><span class="op">.</span><span class="nam">add</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t83" href="#t83">83</a></span><span class="t">                        <span class="nam">JObject</span><span class="op">(</span><span class="op">[</span><span class="nam">rule</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="op">,</span> <span class="nam">rule</span><span class="op">[</span><span class="num">1</span><span class="op">]</span><span class="op">]</span><span class="op">,</span> <span class="nam">JArray</span><span class="op">(</span><span class="str">"java.lang.String"</span><span class="op">,</span> <span class="num">1</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t84" href="#t84">84</a></span><span class="t">                    <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t85" href="#t85">85</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">rule_generator</span><span class="op">.</span><span class="nam">setListParameter</span><span class="op">(</span><span class="nam">param_name</span><span class="op">,</span> <span class="nam">rules_list</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t86" href="#t86">86</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t87" href="#t87">87</a></span><span class="t">    <span class="key">def</span> <span class="nam">_configure_simple_parameter</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">param_name</span><span class="op">:</span> <span class="nam">str</span><span class="op">,</span> <span class="nam">param_value</span><span class="op">:</span> <span class="nam">Any</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t88" href="#t88">88</a></span><span class="t">        <span class="key">if</span> <span class="nam">param_value</span> <span class="key">is</span> <span class="key">not</span> <span class="key">None</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t89" href="#t89">89</a></span><span class="t">            <span class="key">if</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">param_value</span><span class="op">,</span> <span class="nam">bool</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t90" href="#t90">90</a></span><span class="t">                <span class="nam">param_value</span> <span class="op">=</span> <span class="op">(</span><span class="nam">str</span><span class="op">(</span><span class="nam">param_value</span><span class="op">)</span><span class="op">)</span><span class="op">.</span><span class="nam">lower</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t91" href="#t91">91</a></span><span class="t">            <span class="key">elif</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">param_value</span><span class="op">,</span> <span class="nam">tuple</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t92" href="#t92">92</a></span><span class="t">                <span class="nam">param_value</span> <span class="op">=</span> <span class="str">" "</span><span class="op">.</span><span class="nam">join</span><span class="op">(</span><span class="nam">list</span><span class="op">(</span><span class="nam">map</span><span class="op">(</span><span class="nam">str</span><span class="op">,</span> <span class="nam">param_value</span><span class="op">)</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t93" href="#t93">93</a></span><span class="t">            <span class="key">elif</span> <span class="key">not</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">param_value</span><span class="op">,</span> <span class="nam">str</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t94" href="#t94">94</a></span><span class="t">                <span class="nam">param_value</span> <span class="op">=</span> <span class="nam">str</span><span class="op">(</span><span class="nam">param_value</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t95" href="#t95">95</a></span><span class="t">            <span class="nam">self</span><span class="op">.</span><span class="nam">rule_generator</span><span class="op">.</span><span class="nam">setParameter</span><span class="op">(</span><span class="nam">param_name</span><span class="op">,</span> <span class="nam">param_value</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t96" href="#t96">96</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t97" href="#t97">97</a></span><span class="t">    <span class="key">def</span> <span class="nam">_configure_rule_generator</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="op">**</span><span class="nam">kwargs</span><span class="op">:</span> <span class="nam">dict</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">Any</span><span class="op">]</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t98" href="#t98">98</a></span><span class="t">        <span class="key">if</span> <span class="nam">kwargs</span><span class="op">.</span><span class="nam">get</span><span class="op">(</span><span class="str">'induction_measure'</span><span class="op">)</span> <span class="op">==</span> <span class="nam">Measures</span><span class="op">.</span><span class="nam">LogRank</span> <span class="key">or</span> <span class="xx">\</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t99" href="#t99">99</a></span><span class="t">                <span class="nam">kwargs</span><span class="op">.</span><span class="nam">get</span><span class="op">(</span><span class="str">'pruning_measure'</span><span class="op">)</span> <span class="op">==</span> <span class="nam">Measures</span><span class="op">.</span><span class="nam">LogRank</span> <span class="key">or</span> <span class="xx">\</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t100" href="#t100">100</a></span><span class="t">                <span class="nam">kwargs</span><span class="op">.</span><span class="nam">get</span><span class="op">(</span><span class="str">'voting_measure'</span><span class="op">)</span> <span class="op">==</span> <span class="nam">Measures</span><span class="op">.</span><span class="nam">LogRank</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t101" href="#t101">101</a></span><span class="t">            <span class="nam">self</span><span class="op">.</span><span class="nam">LogRank</span> <span class="op">=</span> <span class="nam">JClass</span><span class="op">(</span><span class="str">'adaa.analytics.rules.logic.quality.LogRank'</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t102" href="#t102">102</a></span><span class="t">        <span class="key">for</span> <span class="nam">measure_param_name</span> <span class="key">in</span> <span class="op">[</span><span class="str">'induction_measure'</span><span class="op">,</span> <span class="str">'pruning_measure'</span><span class="op">,</span> <span class="str">'voting_measure'</span><span class="op">]</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t103" href="#t103">103</a></span><span class="t">            <span class="nam">measure_param_value</span><span class="op">:</span> <span class="nam">Measures</span> <span class="op">=</span> <span class="nam">kwargs</span><span class="op">.</span><span class="nam">pop</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t104" href="#t104">104</a></span><span class="t">                <span class="nam">measure_param_name</span><span class="op">,</span> <span class="key">None</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t105" href="#t105">105</a></span><span class="t">            <span class="nam">self</span><span class="op">.</span><span class="nam">_configure_measure_parameter</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t106" href="#t106">106</a></span><span class="t">                <span class="nam">measure_param_name</span><span class="op">,</span> <span class="nam">measure_param_value</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t107" href="#t107">107</a></span><span class="t">        <span class="key">for</span> <span class="nam">param_name</span><span class="op">,</span> <span class="nam">param_value</span> <span class="key">in</span> <span class="nam">kwargs</span><span class="op">.</span><span class="nam">items</span><span class="op">(</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t108" href="#t108">108</a></span><span class="t">            <span class="nam">self</span><span class="op">.</span><span class="nam">_configure_simple_parameter</span><span class="op">(</span><span class="nam">param_name</span><span class="op">,</span> <span class="nam">param_value</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t109" href="#t109">109</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t110" href="#t110">110</a></span><span class="t">    <span class="key">def</span> <span class="nam">_validate_rule_generator_parameters</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="op">**</span><span class="nam">python_parameters</span><span class="op">:</span> <span class="nam">dict</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">Any</span><span class="op">]</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t111" href="#t111">111</a></span><span class="t">        <span class="str">"""Validate whether operator parameters configuration is properly passed to the</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t112" href="#t112">112</a></span><span class="t"><span class="str">        java RuleGenerator class. Otherwise, it raises an error.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t113" href="#t113">113</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t114" href="#t114">114</a></span><span class="t"><span class="str">        Args:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t115" href="#t115">115</a></span><span class="t"><span class="str">            python_parameters (dict[str, Any]): parameters values configured for the</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t116" href="#t116">116</a></span><span class="t"><span class="str">                operator in Python</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t117" href="#t117">117</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t118" href="#t118">118</a></span><span class="t"><span class="str">        Raises:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t119" href="#t119">119</a></span><span class="t"><span class="str">            ValueError: If failed to retrieve RuleGenerator parameters JSON</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t120" href="#t120">120</a></span><span class="t"><span class="str">            RuleKitMisconfigurationException: If Java and Python parameters do not match</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t121" href="#t121">121</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t122" href="#t122">122</a></span><span class="t">        <span class="nam">python_parameters</span> <span class="op">=</span> <span class="nam">dict</span><span class="op">(</span><span class="nam">python_parameters</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t123" href="#t123">123</a></span><span class="t">        <span class="key">for</span> <span class="nam">param_name</span><span class="op">,</span> <span class="nam">param_value</span> <span class="key">in</span> <span class="nam">python_parameters</span><span class="op">.</span><span class="nam">items</span><span class="op">(</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t124" href="#t124">124</a></span><span class="t">            <span class="com"># convert measures to strings values for comparison</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t125" href="#t125">125</a></span><span class="t">            <span class="key">if</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">param_value</span><span class="op">,</span> <span class="nam">Measures</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t126" href="#t126">126</a></span><span class="t">                <span class="nam">python_parameters</span><span class="op">[</span><span class="nam">param_name</span><span class="op">]</span> <span class="op">=</span> <span class="nam">param_value</span><span class="op">.</span><span class="nam">value</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t127" href="#t127">127</a></span><span class="t">            <span class="com"># convert booleans to lowercase strings for comparison</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t128" href="#t128">128</a></span><span class="t">            <span class="key">elif</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">param_value</span><span class="op">,</span> <span class="nam">bool</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t129" href="#t129">129</a></span><span class="t">                <span class="nam">python_parameters</span><span class="op">[</span><span class="nam">param_name</span><span class="op">]</span> <span class="op">=</span> <span class="nam">str</span><span class="op">(</span><span class="nam">param_value</span><span class="op">)</span><span class="op">.</span><span class="nam">lower</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t130" href="#t130">130</a></span><span class="t">            <span class="com"># normalize tuples to strings for comparison</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t131" href="#t131">131</a></span><span class="t">            <span class="key">elif</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">param_value</span><span class="op">,</span> <span class="nam">tuple</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t132" href="#t132">132</a></span><span class="t">                <span class="nam">value</span> <span class="op">=</span> <span class="str">' '</span><span class="op">.</span><span class="nam">join</span><span class="op">(</span><span class="nam">list</span><span class="op">(</span><span class="nam">map</span><span class="op">(</span><span class="nam">str</span><span class="op">,</span> <span class="nam">param_value</span><span class="op">)</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t133" href="#t133">133</a></span><span class="t">                <span class="nam">python_parameters</span><span class="op">[</span><span class="nam">param_name</span><span class="op">]</span> <span class="op">=</span> <span class="nam">value</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t134" href="#t134">134</a></span><span class="t">            <span class="com"># convert numbers to strings for comparison</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t135" href="#t135">135</a></span><span class="t">            <span class="key">elif</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">param_value</span><span class="op">,</span> <span class="op">(</span><span class="nam">int</span><span class="op">,</span> <span class="nam">float</span><span class="op">)</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t136" href="#t136">136</a></span><span class="t">                <span class="nam">python_parameters</span><span class="op">[</span><span class="nam">param_name</span><span class="op">]</span> <span class="op">=</span> <span class="nam">str</span><span class="op">(</span><span class="nam">param_value</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t137" href="#t137">137</a></span><span class="t">        <span class="nam">java_params_json</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="nam">str</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t138" href="#t138">138</a></span><span class="t">            <span class="nam">self</span><span class="op">.</span><span class="nam">rule_generator</span><span class="op">.</span><span class="nam">getParamsAsJsonString</span><span class="op">(</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t139" href="#t139">139</a></span><span class="t">        <span class="key">try</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t140" href="#t140">140</a></span><span class="t">            <span class="nam">java_params</span><span class="op">:</span> <span class="nam">dict</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">Any</span><span class="op">]</span> <span class="op">=</span> <span class="nam">json</span><span class="op">.</span><span class="nam">loads</span><span class="op">(</span><span class="nam">java_params_json</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t141" href="#t141">141</a></span><span class="t">        <span class="key">except</span> <span class="nam">json</span><span class="op">.</span><span class="nam">JSONDecodeError</span> <span class="key">as</span> <span class="nam">error</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t142" href="#t142">142</a></span><span class="t">            <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t143" href="#t143">143</a></span><span class="t">                <span class="str">'Failed to decode RuleGenerator parameters JSON'</span><span class="op">)</span> <span class="key">from</span> <span class="nam">error</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t144" href="#t144">144</a></span><span class="t">        <span class="com"># select only values that are used by Python wrapper</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t145" href="#t145">145</a></span><span class="t">        <span class="nam">java_params</span> <span class="op">=</span> <span class="op">{</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t146" href="#t146">146</a></span><span class="t">            <span class="nam">param_name</span><span class="op">:</span> <span class="nam">str</span><span class="op">(</span><span class="nam">java_params</span><span class="op">[</span><span class="nam">param_name</span><span class="op">]</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t147" href="#t147">147</a></span><span class="t">            <span class="key">for</span> <span class="nam">param_name</span> <span class="key">in</span> <span class="nam">python_parameters</span><span class="op">.</span><span class="nam">keys</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t148" href="#t148">148</a></span><span class="t">        <span class="op">}</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t149" href="#t149">149</a></span><span class="t">        <span class="key">if</span> <span class="nam">java_params</span> <span class="op">!=</span> <span class="nam">python_parameters</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t150" href="#t150">150</a></span><span class="t">            <span class="key">raise</span> <span class="nam">RuleKitMisconfigurationException</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t151" href="#t151">151</a></span><span class="t">                <span class="nam">java_parameters</span><span class="op">=</span><span class="nam">java_params</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t152" href="#t152">152</a></span><span class="t">                <span class="nam">python_parameters</span><span class="op">=</span><span class="nam">python_parameters</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t153" href="#t153">153</a></span><span class="t">            <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t154" href="#t154">154</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t155" href="#t155">155</a></span><span class="t">    <span class="key">def</span> <span class="nam">_configure_java_logging</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t156" href="#t156">156</a></span><span class="t">        <span class="nam">logger_config</span><span class="op">:</span> <span class="nam">Optional</span><span class="op">[</span><span class="nam">_RuleKitJavaLoggerConfig</span><span class="op">]</span> <span class="op">=</span> <span class="nam">RuleKit</span><span class="op">.</span><span class="nam">get_java_logger_config</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t157" href="#t157">157</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t158" href="#t158">158</a></span><span class="t">        <span class="key">if</span> <span class="nam">logger_config</span> <span class="key">is</span> <span class="key">None</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t159" href="#t159">159</a></span><span class="t">            <span class="key">return</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t160" href="#t160">160</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">rule_generator</span><span class="op">.</span><span class="nam">configureLogger</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t161" href="#t161">161</a></span><span class="t">            <span class="nam">logger_config</span><span class="op">.</span><span class="nam">log_file_path</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t162" href="#t162">162</a></span><span class="t">            <span class="nam">logger_config</span><span class="op">.</span><span class="nam">verbosity_level</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t163" href="#t163">163</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t164" href="#t164">164</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t165" href="#t165">165</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t166" href="#t166">166</a></span><span class="t"><span class="key">class</span> <span class="nam">ExampleSetFactory</span><span class="op">(</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t167" href="#t167">167</a></span><span class="t">    <span class="str">""" Creates ExampleSet object from given data"""</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t168" href="#t168">168</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t169" href="#t169">169</a></span><span class="t">    <span class="nam">DEFAULT_LABEL_ATTRIBUTE_NAME</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="str">'label'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t170" href="#t170">170</a></span><span class="t">    <span class="nam">AUTOMATIC_ATTRIBUTES_NAMES_PREFIX</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="str">'att'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t171" href="#t171">171</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t172" href="#t172">172</a></span><span class="t">    <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">problem_type</span><span class="op">:</span> <span class="nam">ProblemType</span><span class="op">)</span> <span class="op">-></span> <span class="key">None</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t173" href="#t173">173</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_problem_type</span><span class="op">:</span> <span class="nam">ProblemType</span> <span class="op">=</span> <span class="nam">problem_type</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t174" href="#t174">174</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_attributes_names</span><span class="op">:</span> <span class="nam">list</span><span class="op">[</span><span class="nam">str</span><span class="op">]</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t175" href="#t175">175</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_label_name</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t176" href="#t176">176</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_survival_time_attribute</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t177" href="#t177">177</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_contrast_attribute</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t178" href="#t178">178</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_X</span><span class="op">:</span> <span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t179" href="#t179">179</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_y</span><span class="op">:</span> <span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t180" href="#t180">180</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t181" href="#t181">181</a></span><span class="t">    <span class="key">def</span> <span class="nam">make</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t182" href="#t182">182</a></span><span class="t">        <span class="nam">self</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t183" href="#t183">183</a></span><span class="t">        <span class="nam">X</span><span class="op">:</span> <span class="nam">Union</span><span class="op">[</span><span class="nam">pd</span><span class="op">.</span><span class="nam">DataFrame</span><span class="op">,</span> <span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t184" href="#t184">184</a></span><span class="t">        <span class="nam">y</span><span class="op">:</span> <span class="nam">Union</span><span class="op">[</span><span class="nam">pd</span><span class="op">.</span><span class="nam">Series</span><span class="op">,</span> <span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span><span class="op">]</span> <span class="op">=</span> <span class="key">None</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t185" href="#t185">185</a></span><span class="t">        <span class="nam">survival_time_attribute</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="key">None</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t186" href="#t186">186</a></span><span class="t">        <span class="nam">contrast_attribute</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="key">None</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t187" href="#t187">187</a></span><span class="t">    <span class="op">)</span> <span class="op">-></span> <span class="nam">JObject</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t188" href="#t188">188</a></span><span class="t">        <span class="str">"""Creates ExampleSet object from given data</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t189" href="#t189">189</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t190" href="#t190">190</a></span><span class="t"><span class="str">        Args:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t191" href="#t191">191</a></span><span class="t"><span class="str">            X (Union[pd.DataFrame, np.ndarray]): Data</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t192" href="#t192">192</a></span><span class="t"><span class="str">            y (Union[pd.Series, np.ndarray], optional): Labels. Defaults to None.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t193" href="#t193">193</a></span><span class="t"><span class="str">            survival_time_attribute (str, optional): Name of survival time attribute.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t194" href="#t194">194</a></span><span class="t"><span class="str">             Defaults to None.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t195" href="#t195">195</a></span><span class="t"><span class="str">            contrast_attribute (str, optional): Name of contrast attribute. Defaults to None.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t196" href="#t196">196</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t197" href="#t197">197</a></span><span class="t"><span class="str">        Returns:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t198" href="#t198">198</a></span><span class="t"><span class="str">            JObject: ExampleSet object</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t199" href="#t199">199</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t200" href="#t200">200</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_attributes_names</span> <span class="op">=</span> <span class="op">[</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t201" href="#t201">201</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_survival_time_attribute</span> <span class="op">=</span> <span class="nam">survival_time_attribute</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t202" href="#t202">202</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_contrast_attribute</span> <span class="op">=</span> <span class="nam">contrast_attribute</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t203" href="#t203">203</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_sanitize_X</span><span class="op">(</span><span class="nam">X</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t204" href="#t204">204</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_sanitize_y</span><span class="op">(</span><span class="nam">y</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t205" href="#t205">205</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_validate_X</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t206" href="#t206">206</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_validate_y</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t207" href="#t207">207</a></span><span class="t">        <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_create_example_set</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t97" href="#t97">97</a></span><span class="t">    <span class="key">def</span> <span class="nam">_configure_measure_parameter</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t98" href="#t98">98</a></span><span class="t">        <span class="nam">self</span><span class="op">,</span> <span class="nam">param_name</span><span class="op">:</span> <span class="nam">str</span><span class="op">,</span> <span class="nam">param_value</span><span class="op">:</span> <span class="nam">Union</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">Measures</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t99" href="#t99">99</a></span><span class="t">    <span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t100" href="#t100">100</a></span><span class="t">        <span class="key">if</span> <span class="nam">param_value</span> <span class="key">is</span> <span class="key">not</span> <span class="key">None</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t101" href="#t101">101</a></span><span class="t">            <span class="key">if</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">param_value</span><span class="op">,</span> <span class="nam">Measures</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t102" href="#t102">102</a></span><span class="t">                <span class="nam">self</span><span class="op">.</span><span class="nam">rule_generator</span><span class="op">.</span><span class="nam">setParameter</span><span class="op">(</span><span class="nam">param_name</span><span class="op">,</span> <span class="nam">param_value</span><span class="op">.</span><span class="nam">value</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t103" href="#t103">103</a></span><span class="t">            <span class="key">if</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">param_value</span><span class="op">,</span> <span class="nam">Callable</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t104" href="#t104">104</a></span><span class="t">                <span class="nam">self</span><span class="op">.</span><span class="nam">_configure_user_defined_measure_parameter</span><span class="op">(</span><span class="nam">param_name</span><span class="op">,</span> <span class="nam">param_value</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t105" href="#t105">105</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t106" href="#t106">106</a></span><span class="t">    <span class="key">def</span> <span class="nam">_configure_user_defined_measure_parameter</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t107" href="#t107">107</a></span><span class="t">        <span class="nam">self</span><span class="op">,</span> <span class="nam">param_name</span><span class="op">:</span> <span class="nam">str</span><span class="op">,</span> <span class="nam">param_value</span><span class="op">:</span> <span class="nam">Any</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t108" href="#t108">108</a></span><span class="t">    <span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t109" href="#t109">109</a></span><span class="t">        <span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">params</span> <span class="key">import</span> <span class="nam">_user_defined_measure_factory</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t110" href="#t110">110</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t111" href="#t111">111</a></span><span class="t">        <span class="nam">user_defined_measure</span> <span class="op">=</span> <span class="nam">_user_defined_measure_factory</span><span class="op">(</span><span class="nam">param_value</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t112" href="#t112">112</a></span><span class="t">        <span class="op">{</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t113" href="#t113">113</a></span><span class="t">            <span class="str">"induction_measure"</span><span class="op">:</span> <span class="nam">self</span><span class="op">.</span><span class="nam">rule_generator</span><span class="op">.</span><span class="nam">setUserMeasureInductionObject</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t114" href="#t114">114</a></span><span class="t">            <span class="str">"pruning_measure"</span><span class="op">:</span> <span class="nam">self</span><span class="op">.</span><span class="nam">rule_generator</span><span class="op">.</span><span class="nam">setUserMeasurePurningObject</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t115" href="#t115">115</a></span><span class="t">            <span class="str">"voting_measure"</span><span class="op">:</span> <span class="nam">self</span><span class="op">.</span><span class="nam">rule_generator</span><span class="op">.</span><span class="nam">setUserMeasureVotingObject</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t116" href="#t116">116</a></span><span class="t">        <span class="op">}</span><span class="op">[</span><span class="nam">param_name</span><span class="op">]</span><span class="op">(</span><span class="nam">user_defined_measure</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t117" href="#t117">117</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">rule_generator</span><span class="op">.</span><span class="nam">setParameter</span><span class="op">(</span><span class="nam">param_name</span><span class="op">,</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_USER_DEFINED_MEASURE_VALUE</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t118" href="#t118">118</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t119" href="#t119">119</a></span><span class="t">    <span class="key">def</span> <span class="nam">_configure_rule_generator</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="op">**</span><span class="nam">kwargs</span><span class="op">:</span> <span class="nam">dict</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">Any</span><span class="op">]</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t120" href="#t120">120</a></span><span class="t">        <span class="key">if</span> <span class="nam">any</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t121" href="#t121">121</a></span><span class="t">            <span class="op">[</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t122" href="#t122">122</a></span><span class="t">                <span class="nam">kwargs</span><span class="op">.</span><span class="nam">get</span><span class="op">(</span><span class="nam">param_name</span><span class="op">)</span> <span class="op">==</span> <span class="nam">Measures</span><span class="op">.</span><span class="nam">LogRank</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t123" href="#t123">123</a></span><span class="t">                <span class="key">for</span> <span class="nam">param_name</span> <span class="key">in</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_MEASURES_PARAMETERS</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t124" href="#t124">124</a></span><span class="t">            <span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t125" href="#t125">125</a></span><span class="t">        <span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t126" href="#t126">126</a></span><span class="t">            <span class="nam">self</span><span class="op">.</span><span class="nam">LogRank</span> <span class="op">=</span> <span class="nam">JClass</span><span class="op">(</span><span class="str">"adaa.analytics.rules.logic.quality.LogRank"</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t127" href="#t127">127</a></span><span class="t">        <span class="key">for</span> <span class="nam">measure_param_name</span> <span class="key">in</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_MEASURES_PARAMETERS</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t128" href="#t128">128</a></span><span class="t">            <span class="nam">measure_param_value</span><span class="op">:</span> <span class="nam">Measures</span> <span class="op">=</span> <span class="nam">kwargs</span><span class="op">.</span><span class="nam">pop</span><span class="op">(</span><span class="nam">measure_param_name</span><span class="op">,</span> <span class="key">None</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t129" href="#t129">129</a></span><span class="t">            <span class="nam">self</span><span class="op">.</span><span class="nam">_configure_measure_parameter</span><span class="op">(</span><span class="nam">measure_param_name</span><span class="op">,</span> <span class="nam">measure_param_value</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t130" href="#t130">130</a></span><span class="t">        <span class="key">for</span> <span class="nam">param_name</span><span class="op">,</span> <span class="nam">param_value</span> <span class="key">in</span> <span class="nam">kwargs</span><span class="op">.</span><span class="nam">items</span><span class="op">(</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t131" href="#t131">131</a></span><span class="t">            <span class="nam">self</span><span class="op">.</span><span class="nam">_configure_simple_parameter</span><span class="op">(</span><span class="nam">param_name</span><span class="op">,</span> <span class="nam">param_value</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t132" href="#t132">132</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t133" href="#t133">133</a></span><span class="t">    <span class="key">def</span> <span class="nam">_validate_rule_generator_parameters</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="op">**</span><span class="nam">python_parameters</span><span class="op">:</span> <span class="nam">dict</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">Any</span><span class="op">]</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t134" href="#t134">134</a></span><span class="t">        <span class="str">"""Validate whether operator parameters configuration is properly passed to the</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t135" href="#t135">135</a></span><span class="t"><span class="str">        java RuleGenerator class. Otherwise, it raises an error.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t136" href="#t136">136</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t137" href="#t137">137</a></span><span class="t"><span class="str">        Args:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t138" href="#t138">138</a></span><span class="t"><span class="str">            python_parameters (dict[str, Any]): parameters values configured for the</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t139" href="#t139">139</a></span><span class="t"><span class="str">                operator in Python</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t140" href="#t140">140</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t141" href="#t141">141</a></span><span class="t"><span class="str">        Raises:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t142" href="#t142">142</a></span><span class="t"><span class="str">            ValueError: If failed to retrieve RuleGenerator parameters JSON</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t143" href="#t143">143</a></span><span class="t"><span class="str">            RuleKitMisconfigurationException: If Java and Python parameters do not match</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t144" href="#t144">144</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t145" href="#t145">145</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t146" href="#t146">146</a></span><span class="t">        <span class="key">def</span> <span class="nam">are_params_equal</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t147" href="#t147">147</a></span><span class="t">            <span class="nam">java_params</span><span class="op">:</span> <span class="nam">dict</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">Any</span><span class="op">]</span><span class="op">,</span> <span class="nam">python_params</span><span class="op">:</span> <span class="nam">dict</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">Any</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t148" href="#t148">148</a></span><span class="t">        <span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t149" href="#t149">149</a></span><span class="t">            <span class="key">if</span> <span class="nam">java_params</span><span class="op">.</span><span class="nam">keys</span><span class="op">(</span><span class="op">)</span> <span class="op">!=</span> <span class="nam">python_params</span><span class="op">.</span><span class="nam">keys</span><span class="op">(</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t150" href="#t150">150</a></span><span class="t">                <span class="key">return</span> <span class="key">False</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t151" href="#t151">151</a></span><span class="t">            <span class="key">for</span> <span class="nam">key</span> <span class="key">in</span> <span class="nam">java_params</span><span class="op">.</span><span class="nam">keys</span><span class="op">(</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t152" href="#t152">152</a></span><span class="t">                <span class="nam">java_value</span> <span class="op">=</span> <span class="nam">java_params</span><span class="op">.</span><span class="nam">get</span><span class="op">(</span><span class="nam">key</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t153" href="#t153">153</a></span><span class="t">                <span class="nam">python_value</span> <span class="op">=</span> <span class="nam">python_params</span><span class="op">.</span><span class="nam">get</span><span class="op">(</span><span class="nam">key</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t154" href="#t154">154</a></span><span class="t">                <span class="nam">skip_check</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">python_value</span><span class="op">,</span> <span class="nam">Callable</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t155" href="#t155">155</a></span><span class="t">                <span class="key">if</span> <span class="nam">java_value</span> <span class="op">==</span> <span class="str">'None'</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t156" href="#t156">156</a></span><span class="t">                    <span class="nam">java_value</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t157" href="#t157">157</a></span><span class="t">                <span class="key">if</span> <span class="nam">java_value</span> <span class="key">is</span> <span class="key">None</span> <span class="key">and</span> <span class="nam">python_value</span> <span class="key">is</span> <span class="key">None</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t158" href="#t158">158</a></span><span class="t">                    <span class="key">continue</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t159" href="#t159">159</a></span><span class="t">                <span class="key">if</span> <span class="nam">java_value</span> <span class="op">!=</span> <span class="nam">python_value</span> <span class="key">and</span> <span class="key">not</span> <span class="nam">skip_check</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t160" href="#t160">160</a></span><span class="t">                    <span class="key">return</span> <span class="key">False</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t161" href="#t161">161</a></span><span class="t">            <span class="key">return</span> <span class="key">True</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t162" href="#t162">162</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t163" href="#t163">163</a></span><span class="t">        <span class="nam">python_parameters</span> <span class="op">=</span> <span class="nam">dict</span><span class="op">(</span><span class="nam">python_parameters</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t164" href="#t164">164</a></span><span class="t">        <span class="key">for</span> <span class="nam">param_name</span><span class="op">,</span> <span class="nam">param_value</span> <span class="key">in</span> <span class="nam">python_parameters</span><span class="op">.</span><span class="nam">items</span><span class="op">(</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t165" href="#t165">165</a></span><span class="t">            <span class="com"># convert measures to strings values for comparison</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t166" href="#t166">166</a></span><span class="t">            <span class="key">if</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">param_value</span><span class="op">,</span> <span class="nam">Measures</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t167" href="#t167">167</a></span><span class="t">                <span class="nam">python_parameters</span><span class="op">[</span><span class="nam">param_name</span><span class="op">]</span> <span class="op">=</span> <span class="nam">param_value</span><span class="op">.</span><span class="nam">value</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t168" href="#t168">168</a></span><span class="t">            <span class="com"># convert booleans to lowercase strings for comparison</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t169" href="#t169">169</a></span><span class="t">            <span class="key">elif</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">param_value</span><span class="op">,</span> <span class="nam">bool</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t170" href="#t170">170</a></span><span class="t">                <span class="nam">python_parameters</span><span class="op">[</span><span class="nam">param_name</span><span class="op">]</span> <span class="op">=</span> <span class="nam">str</span><span class="op">(</span><span class="nam">param_value</span><span class="op">)</span><span class="op">.</span><span class="nam">lower</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t171" href="#t171">171</a></span><span class="t">            <span class="com"># normalize tuples to strings for comparison</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t172" href="#t172">172</a></span><span class="t">            <span class="key">elif</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">param_value</span><span class="op">,</span> <span class="nam">tuple</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t173" href="#t173">173</a></span><span class="t">                <span class="nam">value</span> <span class="op">=</span> <span class="str">" "</span><span class="op">.</span><span class="nam">join</span><span class="op">(</span><span class="nam">list</span><span class="op">(</span><span class="nam">map</span><span class="op">(</span><span class="nam">str</span><span class="op">,</span> <span class="nam">param_value</span><span class="op">)</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t174" href="#t174">174</a></span><span class="t">                <span class="nam">python_parameters</span><span class="op">[</span><span class="nam">param_name</span><span class="op">]</span> <span class="op">=</span> <span class="nam">value</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t175" href="#t175">175</a></span><span class="t">            <span class="com"># convert numbers to strings for comparison</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t176" href="#t176">176</a></span><span class="t">            <span class="key">elif</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">param_value</span><span class="op">,</span> <span class="op">(</span><span class="nam">int</span><span class="op">,</span> <span class="nam">float</span><span class="op">)</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t177" href="#t177">177</a></span><span class="t">                <span class="nam">python_parameters</span><span class="op">[</span><span class="nam">param_name</span><span class="op">]</span> <span class="op">=</span> <span class="nam">str</span><span class="op">(</span><span class="nam">param_value</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t178" href="#t178">178</a></span><span class="t">        <span class="nam">java_params_json</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="nam">str</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">rule_generator</span><span class="op">.</span><span class="nam">getParamsAsJsonString</span><span class="op">(</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t179" href="#t179">179</a></span><span class="t">        <span class="key">try</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t180" href="#t180">180</a></span><span class="t">            <span class="nam">java_params</span><span class="op">:</span> <span class="nam">dict</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">Any</span><span class="op">]</span> <span class="op">=</span> <span class="nam">json</span><span class="op">.</span><span class="nam">loads</span><span class="op">(</span><span class="nam">java_params_json</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t181" href="#t181">181</a></span><span class="t">        <span class="key">except</span> <span class="nam">json</span><span class="op">.</span><span class="nam">JSONDecodeError</span> <span class="key">as</span> <span class="nam">error</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t182" href="#t182">182</a></span><span class="t">            <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t183" href="#t183">183</a></span><span class="t">                <span class="str">"Failed to decode RuleGenerator parameters JSON"</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t184" href="#t184">184</a></span><span class="t">            <span class="op">)</span> <span class="key">from</span> <span class="nam">error</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t185" href="#t185">185</a></span><span class="t">        <span class="com"># select only values that are used by Python wrapper</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t186" href="#t186">186</a></span><span class="t">        <span class="nam">java_params</span> <span class="op">=</span> <span class="op">{</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t187" href="#t187">187</a></span><span class="t">            <span class="nam">param_name</span><span class="op">:</span> <span class="nam">str</span><span class="op">(</span><span class="nam">java_params</span><span class="op">.</span><span class="nam">get</span><span class="op">(</span><span class="nam">param_name</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t188" href="#t188">188</a></span><span class="t">            <span class="key">for</span> <span class="nam">param_name</span> <span class="key">in</span> <span class="nam">python_parameters</span><span class="op">.</span><span class="nam">keys</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t189" href="#t189">189</a></span><span class="t">        <span class="op">}</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t190" href="#t190">190</a></span><span class="t">        <span class="key">if</span> <span class="key">not</span> <span class="nam">are_params_equal</span><span class="op">(</span><span class="nam">java_params</span><span class="op">,</span> <span class="nam">python_parameters</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t191" href="#t191">191</a></span><span class="t">            <span class="key">raise</span> <span class="nam">RuleKitMisconfigurationException</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t192" href="#t192">192</a></span><span class="t">                <span class="nam">java_parameters</span><span class="op">=</span><span class="nam">java_params</span><span class="op">,</span> <span class="nam">python_parameters</span><span class="op">=</span><span class="nam">python_parameters</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t193" href="#t193">193</a></span><span class="t">            <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t194" href="#t194">194</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t195" href="#t195">195</a></span><span class="t">    <span class="key">def</span> <span class="nam">_configure_java_logging</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t196" href="#t196">196</a></span><span class="t">        <span class="nam">logger_config</span><span class="op">:</span> <span class="nam">Optional</span><span class="op">[</span><span class="nam">_RuleKitJavaLoggerConfig</span><span class="op">]</span> <span class="op">=</span> <span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t197" href="#t197">197</a></span><span class="t">            <span class="nam">RuleKit</span><span class="op">.</span><span class="nam">get_java_logger_config</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t198" href="#t198">198</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t199" href="#t199">199</a></span><span class="t">        <span class="key">if</span> <span class="nam">logger_config</span> <span class="key">is</span> <span class="key">None</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t200" href="#t200">200</a></span><span class="t">            <span class="key">return</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t201" href="#t201">201</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">rule_generator</span><span class="op">.</span><span class="nam">configureLogger</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t202" href="#t202">202</a></span><span class="t">            <span class="nam">logger_config</span><span class="op">.</span><span class="nam">log_file_path</span><span class="op">,</span> <span class="nam">logger_config</span><span class="op">.</span><span class="nam">verbosity_level</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t203" href="#t203">203</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t204" href="#t204">204</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t205" href="#t205">205</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t206" href="#t206">206</a></span><span class="t"><span class="key">class</span> <span class="nam">ExampleSetFactory</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t207" href="#t207">207</a></span><span class="t">    <span class="str">"""Creates ExampleSet object from given data"""</span>&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t208" href="#t208">208</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t209" href="#t209">209</a></span><span class="t">    <span class="key">def</span> <span class="nam">_sanitize_y</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t210" href="#t210">210</a></span><span class="t">        <span class="nam">self</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t211" href="#t211">211</a></span><span class="t">        <span class="nam">y</span><span class="op">:</span> <span class="nam">Union</span><span class="op">[</span><span class="nam">pd</span><span class="op">.</span><span class="nam">Series</span><span class="op">,</span> <span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span><span class="op">,</span> <span class="nam">list</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t212" href="#t212">212</a></span><span class="t">    <span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t213" href="#t213">213</a></span><span class="t">        <span class="key">if</span> <span class="nam">y</span> <span class="key">is</span> <span class="key">None</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t214" href="#t214">214</a></span><span class="t">            <span class="key">return</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t215" href="#t215">215</a></span><span class="t">        <span class="key">elif</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">y</span><span class="op">,</span> <span class="nam">pd</span><span class="op">.</span><span class="nam">Series</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t216" href="#t216">216</a></span><span class="t">            <span class="nam">self</span><span class="op">.</span><span class="nam">_label_name</span> <span class="op">=</span> <span class="nam">y</span><span class="op">.</span><span class="nam">name</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t217" href="#t217">217</a></span><span class="t">            <span class="nam">self</span><span class="op">.</span><span class="nam">_attributes_names</span><span class="op">.</span><span class="nam">append</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">_label_name</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t218" href="#t218">218</a></span><span class="t">            <span class="nam">self</span><span class="op">.</span><span class="nam">_y</span> <span class="op">=</span> <span class="nam">y</span><span class="op">.</span><span class="nam">to_numpy</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t219" href="#t219">219</a></span><span class="t">        <span class="key">elif</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">y</span><span class="op">,</span> <span class="nam">list</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t220" href="#t220">220</a></span><span class="t">            <span class="nam">self</span><span class="op">.</span><span class="nam">_label_name</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">DEFAULT_LABEL_ATTRIBUTE_NAME</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t221" href="#t221">221</a></span><span class="t">            <span class="nam">self</span><span class="op">.</span><span class="nam">_attributes_names</span><span class="op">.</span><span class="nam">append</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">_label_name</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t222" href="#t222">222</a></span><span class="t">            <span class="nam">self</span><span class="op">.</span><span class="nam">_y</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">array</span><span class="op">(</span><span class="nam">y</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t223" href="#t223">223</a></span><span class="t">        <span class="key">elif</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">y</span><span class="op">,</span> <span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t224" href="#t224">224</a></span><span class="t">            <span class="nam">self</span><span class="op">.</span><span class="nam">_label_name</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">DEFAULT_LABEL_ATTRIBUTE_NAME</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t225" href="#t225">225</a></span><span class="t">            <span class="nam">self</span><span class="op">.</span><span class="nam">_attributes_names</span><span class="op">.</span><span class="nam">append</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">_label_name</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t226" href="#t226">226</a></span><span class="t">            <span class="nam">self</span><span class="op">.</span><span class="nam">_y</span> <span class="op">=</span> <span class="nam">y</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t227" href="#t227">227</a></span><span class="t">        <span class="key">else</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t228" href="#t228">228</a></span><span class="t">            <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t229" href="#t229">229</a></span><span class="t">                <span class="str">f'Invalid y type: {str(type(y))}. '</span> <span class="op">+</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t230" href="#t230">230</a></span><span class="t">                <span class="str">'Supported types are: 1 dimensional numpy array or pandas Series object.'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t231" href="#t231">231</a></span><span class="t">            <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t232" href="#t232">232</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t233" href="#t233">233</a></span><span class="t">    <span class="key">def</span> <span class="nam">_sanitize_X</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t234" href="#t234">234</a></span><span class="t">        <span class="nam">self</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t235" href="#t235">235</a></span><span class="t">        <span class="nam">X</span><span class="op">:</span> <span class="nam">Union</span><span class="op">[</span><span class="nam">pd</span><span class="op">.</span><span class="nam">DataFrame</span><span class="op">,</span> <span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t236" href="#t236">236</a></span><span class="t">    <span class="op">)</span> <span class="op">-></span> <span class="nam">tuple</span><span class="op">[</span><span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span><span class="op">,</span> <span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span><span class="op">]</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t237" href="#t237">237</a></span><span class="t">        <span class="key">if</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">X</span><span class="op">,</span> <span class="nam">pd</span><span class="op">.</span><span class="nam">DataFrame</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t238" href="#t238">238</a></span><span class="t">            <span class="nam">self</span><span class="op">.</span><span class="nam">_attributes_names</span> <span class="op">=</span> <span class="nam">X</span><span class="op">.</span><span class="nam">columns</span><span class="op">.</span><span class="nam">tolist</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t239" href="#t239">239</a></span><span class="t">            <span class="com"># replace nan values with None</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t240" href="#t240">240</a></span><span class="t">            <span class="nam">X</span> <span class="op">=</span> <span class="nam">X</span><span class="op">.</span><span class="nam">where</span><span class="op">(</span><span class="nam">pd</span><span class="op">.</span><span class="nam">notnull</span><span class="op">(</span><span class="nam">X</span><span class="op">)</span><span class="op">,</span> <span class="key">None</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t241" href="#t241">241</a></span><span class="t">            <span class="nam">self</span><span class="op">.</span><span class="nam">_X</span> <span class="op">=</span> <span class="nam">X</span><span class="op">.</span><span class="nam">to_numpy</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t242" href="#t242">242</a></span><span class="t">        <span class="key">elif</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">X</span><span class="op">,</span> <span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t243" href="#t243">243</a></span><span class="t">            <span class="nam">self</span><span class="op">.</span><span class="nam">_attributes_names</span> <span class="op">=</span> <span class="op">[</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t244" href="#t244">244</a></span><span class="t">                <span class="str">f'{self.AUTOMATIC_ATTRIBUTES_NAMES_PREFIX}{index + 1}'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t245" href="#t245">245</a></span><span class="t">                <span class="key">for</span> <span class="nam">index</span> <span class="key">in</span> <span class="nam">range</span><span class="op">(</span><span class="nam">X</span><span class="op">.</span><span class="nam">shape</span><span class="op">[</span><span class="num">1</span><span class="op">]</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t246" href="#t246">246</a></span><span class="t">            <span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t247" href="#t247">247</a></span><span class="t">            <span class="nam">self</span><span class="op">.</span><span class="nam">_X</span> <span class="op">=</span> <span class="nam">X</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t248" href="#t248">248</a></span><span class="t">        <span class="key">else</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t249" href="#t249">249</a></span><span class="t">            <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t250" href="#t250">250</a></span><span class="t">                <span class="str">f'Invalid X type: {str(type(X))}. '</span> <span class="op">+</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t251" href="#t251">251</a></span><span class="t">                <span class="str">'Supported types are: 2 dimensional numpy array or pandas DataFrame object.'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t252" href="#t252">252</a></span><span class="t">            <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t253" href="#t253">253</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t254" href="#t254">254</a></span><span class="t">    <span class="key">def</span> <span class="nam">_validate_X</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t255" href="#t255">255</a></span><span class="t">        <span class="key">if</span> <span class="nam">len</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">_X</span><span class="op">.</span><span class="nam">shape</span><span class="op">)</span> <span class="op">!=</span> <span class="num">2</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t256" href="#t256">256</a></span><span class="t">            <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t257" href="#t257">257</a></span><span class="t">                <span class="str">'X must be a 2 dimensional numpy array or pandas DataFrame object. '</span> <span class="op">+</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t258" href="#t258">258</a></span><span class="t">                <span class="str">f'Its current shape is: {str(self._X.shape)}'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t259" href="#t259">259</a></span><span class="t">            <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t260" href="#t260">260</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t261" href="#t261">261</a></span><span class="t">    <span class="key">def</span> <span class="nam">_validate_y</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t262" href="#t262">262</a></span><span class="t">        <span class="key">if</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_y</span> <span class="key">is</span> <span class="key">not</span> <span class="key">None</span> <span class="key">and</span> <span class="nam">len</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">_y</span><span class="op">.</span><span class="nam">shape</span><span class="op">)</span> <span class="op">!=</span> <span class="num">1</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t263" href="#t263">263</a></span><span class="t">            <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t264" href="#t264">264</a></span><span class="t">                <span class="str">'y must be a 1 dimensional numpy array or pandas DataFrame object. '</span> <span class="op">+</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t265" href="#t265">265</a></span><span class="t">                <span class="str">f'Its current shape is: {str(self._y.shape)}'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t266" href="#t266">266</a></span><span class="t">            <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t267" href="#t267">267</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t268" href="#t268">268</a></span><span class="t">    <span class="key">def</span> <span class="nam">_create_example_set</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">JObject</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t269" href="#t269">269</a></span><span class="t">        <span class="nam">data</span><span class="op">:</span> <span class="nam">JObject</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_prepare_data</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t270" href="#t270">270</a></span><span class="t">        <span class="nam">args</span><span class="op">:</span> <span class="nam">list</span> <span class="op">=</span> <span class="op">[</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t271" href="#t271">271</a></span><span class="t">            <span class="nam">data</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t272" href="#t272">272</a></span><span class="t">            <span class="nam">self</span><span class="op">.</span><span class="nam">_attributes_names</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t273" href="#t273">273</a></span><span class="t">            <span class="nam">self</span><span class="op">.</span><span class="nam">_label_name</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t274" href="#t274">274</a></span><span class="t">            <span class="nam">self</span><span class="op">.</span><span class="nam">_survival_time_attribute</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t275" href="#t275">275</a></span><span class="t">            <span class="nam">self</span><span class="op">.</span><span class="nam">_contrast_attribute</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t276" href="#t276">276</a></span><span class="t">        <span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t277" href="#t277">277</a></span><span class="t">        <span class="nam">DataTable</span> <span class="op">=</span> <span class="nam">JClass</span><span class="op">(</span>  <span class="com"># pylint: disable=invalid-name</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t278" href="#t278">278</a></span><span class="t">            <span class="str">'adaa.analytics.rules.data.DataTable'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t279" href="#t279">279</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t280" href="#t280">280</a></span><span class="t">        <span class="key">try</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t281" href="#t281">281</a></span><span class="t">            <span class="nam">table</span> <span class="op">=</span> <span class="nam">DataTable</span><span class="op">(</span><span class="op">*</span><span class="nam">args</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t282" href="#t282">282</a></span><span class="t">            <span class="key">if</span> <span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">_y</span> <span class="key">is</span> <span class="key">not</span> <span class="key">None</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t283" href="#t283">283</a></span><span class="t">                <span class="nam">ExampleSetFactory</span> <span class="op">=</span> <span class="nam">JClass</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t284" href="#t284">284</a></span><span class="t">                    <span class="str">'adaa.analytics.rules.logic.representation.exampleset.ExampleSetFactory'</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t285" href="#t285">285</a></span><span class="t">                <span class="nam">factory</span> <span class="op">=</span> <span class="nam">ExampleSetFactory</span><span class="op">(</span><span class="num">2</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t286" href="#t286">286</a></span><span class="t">                <span class="nam">example_set</span> <span class="op">=</span> <span class="nam">factory</span><span class="op">.</span><span class="nam">create</span><span class="op">(</span><span class="nam">table</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t287" href="#t287">287</a></span><span class="t">                <span class="key">return</span> <span class="nam">example_set</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t288" href="#t288">288</a></span><span class="t">            <span class="key">else</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t289" href="#t289">289</a></span><span class="t">                <span class="key">return</span> <span class="nam">table</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t290" href="#t290">290</a></span><span class="t">        <span class="key">except</span> <span class="nam">Exception</span> <span class="key">as</span> <span class="nam">error</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t291" href="#t291">291</a></span><span class="t">            <span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">exceptions</span> <span class="key">import</span> <span class="nam">RuleKitJavaException</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t292" href="#t292">292</a></span><span class="t">            <span class="nam">RuleKitJavaException</span><span class="op">(</span><span class="nam">error</span><span class="op">)</span><span class="op">.</span><span class="nam">print_java_stack_trace</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t293" href="#t293">293</a></span><span class="t">            <span class="key">raise</span> <span class="nam">error</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t294" href="#t294">294</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t295" href="#t295">295</a></span><span class="t">    <span class="key">def</span> <span class="nam">_wrap_training_example_set</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">example_set</span><span class="op">:</span> <span class="nam">JObject</span><span class="op">)</span> <span class="op">-></span> <span class="nam">JObject</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t296" href="#t296">296</a></span><span class="t">        <span class="com"># training dataset must be wrapped in additional classes for rule induction to work properly</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t297" href="#t297">297</a></span><span class="t">        <span class="nam">ExampleSetFactory</span> <span class="op">=</span> <span class="nam">JClass</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t298" href="#t298">298</a></span><span class="t">            <span class="str">'adaa.analytics.rules.logic.representation.exampleset.ExampleSetFactory'</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t299" href="#t299">299</a></span><span class="t">        <span class="nam">factory</span><span class="op">:</span> <span class="nam">JObject</span> <span class="op">=</span> <span class="nam">ExampleSetFactory</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">_problem_type</span><span class="op">.</span><span class="nam">value</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t300" href="#t300">300</a></span><span class="t">        <span class="key">return</span> <span class="nam">factory</span><span class="op">.</span><span class="nam">create</span><span class="op">(</span><span class="nam">example_set</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t301" href="#t301">301</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t302" href="#t302">302</a></span><span class="t">    <span class="key">def</span> <span class="nam">_prepare_data</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">JObject</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t303" href="#t303">303</a></span><span class="t">        <span class="key">if</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_y</span> <span class="key">is</span> <span class="key">None</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t304" href="#t304">304</a></span><span class="t">            <span class="nam">data</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_X</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t305" href="#t305">305</a></span><span class="t">        <span class="key">else</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t306" href="#t306">306</a></span><span class="t">            <span class="nam">data</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">hstack</span><span class="op">(</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">_X</span><span class="op">.</span><span class="nam">astype</span><span class="op">(</span><span class="nam">object</span><span class="op">)</span><span class="op">,</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_y</span><span class="op">.</span><span class="nam">reshape</span><span class="op">(</span><span class="op">-</span><span class="num">1</span><span class="op">,</span> <span class="num">1</span><span class="op">)</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t307" href="#t307">307</a></span><span class="t">        <span class="nam">java_data</span> <span class="op">=</span> <span class="nam">JObject</span><span class="op">(</span><span class="nam">data</span><span class="op">,</span> <span class="nam">JArray</span><span class="op">(</span><span class="str">'java.lang.Object'</span><span class="op">,</span> <span class="num">2</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t308" href="#t308">308</a></span><span class="t">        <span class="key">return</span> <span class="nam">java_data</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t309" href="#t309">309</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t310" href="#t310">310</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t311" href="#t311">311</a></span><span class="t"><span class="key">class</span> <span class="nam">PredictionResultMapper</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t312" href="#t312">312</a></span><span class="t">    <span class="str">"""Maps prediction results to numpy array</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t313" href="#t313">313</a></span><span class="t"><span class="str">    """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t314" href="#t314">314</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t315" href="#t315">315</a></span><span class="t">    <span class="nam">PREDICTION_COLUMN_ROLE</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="str">'prediction'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t316" href="#t316">316</a></span><span class="t">    <span class="nam">CONFIDENCE_COLUMN_ROLE</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="str">'confidence'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t317" href="#t317">317</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t318" href="#t318">318</a></span><span class="t">    <span class="op">@</span><span class="nam">staticmethod</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t319" href="#t319">319</a></span><span class="t">    <span class="key">def</span> <span class="nam">map_confidence</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t320" href="#t320">320</a></span><span class="t">        <span class="nam">predicted_example_set</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t321" href="#t321">321</a></span><span class="t">        <span class="nam">label_unique_values</span><span class="op">:</span> <span class="nam">list</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t322" href="#t322">322</a></span><span class="t">    <span class="op">)</span> <span class="op">-></span> <span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t323" href="#t323">323</a></span><span class="t">        <span class="str">"""Maps models confidence values to numpy array</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t324" href="#t324">324</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t325" href="#t325">325</a></span><span class="t"><span class="str">        Args:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t326" href="#t326">326</a></span><span class="t"><span class="str">            predicted_example_set (_type_): predicted ExampleSet instance</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t327" href="#t327">327</a></span><span class="t"><span class="str">            label_unique_values (list): unique labels values</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t328" href="#t328">328</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t329" href="#t329">329</a></span><span class="t"><span class="str">        Returns:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t330" href="#t330">330</a></span><span class="t"><span class="str">            np.ndarray: numpy array with mapped confidence values</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t331" href="#t331">331</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t332" href="#t332">332</a></span><span class="t">        <span class="nam">confidence_matrix</span><span class="op">:</span> <span class="nam">list</span><span class="op">[</span><span class="nam">list</span><span class="op">[</span><span class="nam">float</span><span class="op">]</span><span class="op">]</span> <span class="op">=</span> <span class="op">[</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t333" href="#t333">333</a></span><span class="t">        <span class="key">for</span> <span class="nam">label_value</span> <span class="key">in</span> <span class="nam">label_unique_values</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t334" href="#t334">334</a></span><span class="t">            <span class="nam">confidence_col</span><span class="op">:</span> <span class="nam">JObject</span> <span class="op">=</span> <span class="nam">PredictionResultMapper</span><span class="op">.</span><span class="nam">_get_column_by_role</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t335" href="#t335">335</a></span><span class="t">                <span class="nam">predicted_example_set</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t336" href="#t336">336</a></span><span class="t">                <span class="str">f'{PredictionResultMapper.CONFIDENCE_COLUMN_ROLE}_{label_value}'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t337" href="#t337">337</a></span><span class="t">            <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t338" href="#t338">338</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t339" href="#t339">339</a></span><span class="t">            <span class="nam">confidence_values</span> <span class="op">=</span> <span class="op">[</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t340" href="#t340">340</a></span><span class="t">                <span class="nam">float</span><span class="op">(</span><span class="nam">predicted_example_set</span><span class="op">.</span><span class="nam">getExample</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t341" href="#t341">341</a></span><span class="t">                    <span class="nam">i</span><span class="op">)</span><span class="op">.</span><span class="nam">getValue</span><span class="op">(</span><span class="nam">confidence_col</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t342" href="#t342">342</a></span><span class="t">                <span class="key">for</span> <span class="nam">i</span> <span class="key">in</span> <span class="nam">range</span><span class="op">(</span><span class="nam">predicted_example_set</span><span class="op">.</span><span class="nam">size</span><span class="op">(</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t343" href="#t343">343</a></span><span class="t">            <span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t344" href="#t344">344</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t345" href="#t345">345</a></span><span class="t">            <span class="nam">confidence_matrix</span><span class="op">.</span><span class="nam">append</span><span class="op">(</span><span class="nam">confidence_values</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t346" href="#t346">346</a></span><span class="t">        <span class="key">return</span> <span class="nam">np</span><span class="op">.</span><span class="nam">array</span><span class="op">(</span><span class="nam">confidence_matrix</span><span class="op">,</span> <span class="nam">dtype</span><span class="op">=</span><span class="nam">float</span><span class="op">)</span><span class="op">.</span><span class="nam">T</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t347" href="#t347">347</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t348" href="#t348">348</a></span><span class="t">    <span class="op">@</span><span class="nam">staticmethod</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t349" href="#t349">349</a></span><span class="t">    <span class="key">def</span> <span class="nam">map</span><span class="op">(</span><span class="nam">predicted_example_set</span><span class="op">:</span> <span class="nam">JObject</span><span class="op">)</span> <span class="op">-></span> <span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t350" href="#t350">350</a></span><span class="t">        <span class="str">"""Maps models predictions to numpy array</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t351" href="#t351">351</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t352" href="#t352">352</a></span><span class="t"><span class="str">        Args:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t353" href="#t353">353</a></span><span class="t"><span class="str">            predicted_example_set (_type_): ExampleSet with predictions</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t354" href="#t354">354</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t355" href="#t355">355</a></span><span class="t"><span class="str">        Returns:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t356" href="#t356">356</a></span><span class="t"><span class="str">            np.ndarray: numpy array containing predictions</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t357" href="#t357">357</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t358" href="#t358">358</a></span><span class="t">        <span class="nam">prediction_col</span><span class="op">:</span> <span class="nam">JObject</span> <span class="op">=</span> <span class="nam">PredictionResultMapper</span><span class="op">.</span><span class="nam">_get_column_by_role</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t359" href="#t359">359</a></span><span class="t">            <span class="nam">predicted_example_set</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t360" href="#t360">360</a></span><span class="t">            <span class="nam">PredictionResultMapper</span><span class="op">.</span><span class="nam">PREDICTION_COLUMN_ROLE</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t361" href="#t361">361</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t362" href="#t362">362</a></span><span class="t">        <span class="key">if</span> <span class="nam">prediction_col</span><span class="op">.</span><span class="nam">isNominal</span><span class="op">(</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t363" href="#t363">363</a></span><span class="t">            <span class="key">return</span> <span class="nam">PredictionResultMapper</span><span class="op">.</span><span class="nam">map_to_nominal</span><span class="op">(</span><span class="nam">predicted_example_set</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t364" href="#t364">364</a></span><span class="t">        <span class="key">return</span> <span class="nam">PredictionResultMapper</span><span class="op">.</span><span class="nam">map_to_numerical</span><span class="op">(</span><span class="nam">predicted_example_set</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t365" href="#t365">365</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t366" href="#t366">366</a></span><span class="t">    <span class="op">@</span><span class="nam">staticmethod</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t367" href="#t367">367</a></span><span class="t">    <span class="key">def</span> <span class="nam">map_to_nominal</span><span class="op">(</span><span class="nam">predicted_example_set</span><span class="op">:</span> <span class="nam">JObject</span><span class="op">)</span> <span class="op">-></span> <span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t368" href="#t368">368</a></span><span class="t">        <span class="str">"""Maps models predictions to nominal numpy array of strings</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t369" href="#t369">369</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t370" href="#t370">370</a></span><span class="t"><span class="str">        Args:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t371" href="#t371">371</a></span><span class="t"><span class="str">            predicted_example_set (_type_): ExampleSet with predictions</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t372" href="#t372">372</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t373" href="#t373">373</a></span><span class="t"><span class="str">        Returns:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t374" href="#t374">374</a></span><span class="t"><span class="str">            np.ndarray: numpy array containing predictions</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t375" href="#t375">375</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t376" href="#t376">376</a></span><span class="t">        <span class="nam">prediction_col</span><span class="op">:</span> <span class="nam">JObject</span> <span class="op">=</span> <span class="nam">PredictionResultMapper</span><span class="op">.</span><span class="nam">_get_column_by_role</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t377" href="#t377">377</a></span><span class="t">            <span class="nam">predicted_example_set</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t378" href="#t378">378</a></span><span class="t">            <span class="nam">PredictionResultMapper</span><span class="op">.</span><span class="nam">PREDICTION_COLUMN_ROLE</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t379" href="#t379">379</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t380" href="#t380">380</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t381" href="#t381">381</a></span><span class="t">        <span class="key">return</span> <span class="nam">np</span><span class="op">.</span><span class="nam">array</span><span class="op">(</span><span class="op">[</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t382" href="#t382">382</a></span><span class="t">            <span class="nam">str</span><span class="op">(</span><span class="nam">predicted_example_set</span><span class="op">.</span><span class="nam">getExample</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t383" href="#t383">383</a></span><span class="t">                <span class="nam">i</span><span class="op">)</span><span class="op">.</span><span class="nam">getNominalValue</span><span class="op">(</span><span class="nam">prediction_col</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t384" href="#t384">384</a></span><span class="t">            <span class="key">for</span> <span class="nam">i</span> <span class="key">in</span> <span class="nam">range</span><span class="op">(</span><span class="nam">predicted_example_set</span><span class="op">.</span><span class="nam">size</span><span class="op">(</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t385" href="#t385">385</a></span><span class="t">        <span class="op">]</span><span class="op">,</span> <span class="nam">dtype</span><span class="op">=</span><span class="nam">str</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t209" href="#t209">209</a></span><span class="t">    <span class="nam">DEFAULT_LABEL_ATTRIBUTE_NAME</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="str">"label"</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t210" href="#t210">210</a></span><span class="t">    <span class="nam">AUTOMATIC_ATTRIBUTES_NAMES_PREFIX</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="str">"att"</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t211" href="#t211">211</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t212" href="#t212">212</a></span><span class="t">    <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">problem_type</span><span class="op">:</span> <span class="nam">ProblemType</span><span class="op">)</span> <span class="op">-></span> <span class="key">None</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t213" href="#t213">213</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_problem_type</span><span class="op">:</span> <span class="nam">ProblemType</span> <span class="op">=</span> <span class="nam">problem_type</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t214" href="#t214">214</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_attributes_names</span><span class="op">:</span> <span class="nam">list</span><span class="op">[</span><span class="nam">str</span><span class="op">]</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t215" href="#t215">215</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_label_name</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t216" href="#t216">216</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_survival_time_attribute</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t217" href="#t217">217</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_contrast_attribute</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t218" href="#t218">218</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_X</span><span class="op">:</span> <span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t219" href="#t219">219</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_y</span><span class="op">:</span> <span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t220" href="#t220">220</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t221" href="#t221">221</a></span><span class="t">    <span class="key">def</span> <span class="nam">make</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t222" href="#t222">222</a></span><span class="t">        <span class="nam">self</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t223" href="#t223">223</a></span><span class="t">        <span class="nam">X</span><span class="op">:</span> <span class="nam">Union</span><span class="op">[</span><span class="nam">pd</span><span class="op">.</span><span class="nam">DataFrame</span><span class="op">,</span> <span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t224" href="#t224">224</a></span><span class="t">        <span class="nam">y</span><span class="op">:</span> <span class="nam">Union</span><span class="op">[</span><span class="nam">pd</span><span class="op">.</span><span class="nam">Series</span><span class="op">,</span> <span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span><span class="op">]</span> <span class="op">=</span> <span class="key">None</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t225" href="#t225">225</a></span><span class="t">        <span class="nam">survival_time_attribute</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="key">None</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t226" href="#t226">226</a></span><span class="t">        <span class="nam">contrast_attribute</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="key">None</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t227" href="#t227">227</a></span><span class="t">    <span class="op">)</span> <span class="op">-></span> <span class="nam">JObject</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t228" href="#t228">228</a></span><span class="t">        <span class="str">"""Creates ExampleSet object from given data</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t229" href="#t229">229</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t230" href="#t230">230</a></span><span class="t"><span class="str">        Args:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t231" href="#t231">231</a></span><span class="t"><span class="str">            X (Union[pd.DataFrame, np.ndarray]): Data</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t232" href="#t232">232</a></span><span class="t"><span class="str">            y (Union[pd.Series, np.ndarray], optional): Labels. Defaults to None.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t233" href="#t233">233</a></span><span class="t"><span class="str">            survival_time_attribute (str, optional): Name of survival time attribute.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t234" href="#t234">234</a></span><span class="t"><span class="str">             Defaults to None.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t235" href="#t235">235</a></span><span class="t"><span class="str">            contrast_attribute (str, optional): Name of contrast attribute. Defaults to None.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t236" href="#t236">236</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t237" href="#t237">237</a></span><span class="t"><span class="str">        Returns:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t238" href="#t238">238</a></span><span class="t"><span class="str">            JObject: ExampleSet object</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t239" href="#t239">239</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t240" href="#t240">240</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_attributes_names</span> <span class="op">=</span> <span class="op">[</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t241" href="#t241">241</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_survival_time_attribute</span> <span class="op">=</span> <span class="nam">survival_time_attribute</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t242" href="#t242">242</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_contrast_attribute</span> <span class="op">=</span> <span class="nam">contrast_attribute</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t243" href="#t243">243</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_sanitize_X</span><span class="op">(</span><span class="nam">X</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t244" href="#t244">244</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_sanitize_y</span><span class="op">(</span><span class="nam">y</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t245" href="#t245">245</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_validate_X</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t246" href="#t246">246</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_validate_y</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t247" href="#t247">247</a></span><span class="t">        <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_create_example_set</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t248" href="#t248">248</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t249" href="#t249">249</a></span><span class="t">    <span class="key">def</span> <span class="nam">_sanitize_y</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">y</span><span class="op">:</span> <span class="nam">Union</span><span class="op">[</span><span class="nam">pd</span><span class="op">.</span><span class="nam">Series</span><span class="op">,</span> <span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span><span class="op">,</span> <span class="nam">list</span><span class="op">]</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t250" href="#t250">250</a></span><span class="t">        <span class="key">if</span> <span class="nam">y</span> <span class="key">is</span> <span class="key">None</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t251" href="#t251">251</a></span><span class="t">            <span class="key">return</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t252" href="#t252">252</a></span><span class="t">        <span class="key">elif</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">y</span><span class="op">,</span> <span class="nam">pd</span><span class="op">.</span><span class="nam">Series</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t253" href="#t253">253</a></span><span class="t">            <span class="nam">self</span><span class="op">.</span><span class="nam">_label_name</span> <span class="op">=</span> <span class="nam">y</span><span class="op">.</span><span class="nam">name</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t254" href="#t254">254</a></span><span class="t">            <span class="nam">self</span><span class="op">.</span><span class="nam">_attributes_names</span><span class="op">.</span><span class="nam">append</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">_label_name</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t255" href="#t255">255</a></span><span class="t">            <span class="nam">self</span><span class="op">.</span><span class="nam">_y</span> <span class="op">=</span> <span class="nam">y</span><span class="op">.</span><span class="nam">to_numpy</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t256" href="#t256">256</a></span><span class="t">        <span class="key">elif</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">y</span><span class="op">,</span> <span class="nam">list</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t257" href="#t257">257</a></span><span class="t">            <span class="nam">self</span><span class="op">.</span><span class="nam">_label_name</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">DEFAULT_LABEL_ATTRIBUTE_NAME</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t258" href="#t258">258</a></span><span class="t">            <span class="nam">self</span><span class="op">.</span><span class="nam">_attributes_names</span><span class="op">.</span><span class="nam">append</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">_label_name</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t259" href="#t259">259</a></span><span class="t">            <span class="nam">self</span><span class="op">.</span><span class="nam">_y</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">array</span><span class="op">(</span><span class="nam">y</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t260" href="#t260">260</a></span><span class="t">        <span class="key">elif</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">y</span><span class="op">,</span> <span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t261" href="#t261">261</a></span><span class="t">            <span class="nam">self</span><span class="op">.</span><span class="nam">_label_name</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">DEFAULT_LABEL_ATTRIBUTE_NAME</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t262" href="#t262">262</a></span><span class="t">            <span class="nam">self</span><span class="op">.</span><span class="nam">_attributes_names</span><span class="op">.</span><span class="nam">append</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">_label_name</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t263" href="#t263">263</a></span><span class="t">            <span class="nam">self</span><span class="op">.</span><span class="nam">_y</span> <span class="op">=</span> <span class="nam">y</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t264" href="#t264">264</a></span><span class="t">        <span class="key">else</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t265" href="#t265">265</a></span><span class="t">            <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t266" href="#t266">266</a></span><span class="t">                <span class="str">f"Invalid y type: {str(type(y))}. "</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t267" href="#t267">267</a></span><span class="t">                <span class="op">+</span> <span class="str">"Supported types are: 1 dimensional numpy array or pandas Series object."</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t268" href="#t268">268</a></span><span class="t">            <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t269" href="#t269">269</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t270" href="#t270">270</a></span><span class="t">    <span class="key">def</span> <span class="nam">_sanitize_X</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t271" href="#t271">271</a></span><span class="t">        <span class="nam">self</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t272" href="#t272">272</a></span><span class="t">        <span class="nam">X</span><span class="op">:</span> <span class="nam">Union</span><span class="op">[</span><span class="nam">pd</span><span class="op">.</span><span class="nam">DataFrame</span><span class="op">,</span> <span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t273" href="#t273">273</a></span><span class="t">    <span class="op">)</span> <span class="op">-></span> <span class="nam">tuple</span><span class="op">[</span><span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span><span class="op">,</span> <span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span><span class="op">]</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t274" href="#t274">274</a></span><span class="t">        <span class="key">if</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">X</span><span class="op">,</span> <span class="nam">pd</span><span class="op">.</span><span class="nam">DataFrame</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t275" href="#t275">275</a></span><span class="t">            <span class="nam">self</span><span class="op">.</span><span class="nam">_attributes_names</span> <span class="op">=</span> <span class="nam">X</span><span class="op">.</span><span class="nam">columns</span><span class="op">.</span><span class="nam">tolist</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t276" href="#t276">276</a></span><span class="t">            <span class="com"># replace nan values with None</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t277" href="#t277">277</a></span><span class="t">            <span class="nam">X</span> <span class="op">=</span> <span class="nam">X</span><span class="op">.</span><span class="nam">where</span><span class="op">(</span><span class="nam">pd</span><span class="op">.</span><span class="nam">notnull</span><span class="op">(</span><span class="nam">X</span><span class="op">)</span><span class="op">,</span> <span class="key">None</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t278" href="#t278">278</a></span><span class="t">            <span class="nam">self</span><span class="op">.</span><span class="nam">_X</span> <span class="op">=</span> <span class="nam">X</span><span class="op">.</span><span class="nam">to_numpy</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t279" href="#t279">279</a></span><span class="t">        <span class="key">elif</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">X</span><span class="op">,</span> <span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t280" href="#t280">280</a></span><span class="t">            <span class="nam">self</span><span class="op">.</span><span class="nam">_attributes_names</span> <span class="op">=</span> <span class="op">[</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t281" href="#t281">281</a></span><span class="t">                <span class="str">f"{self.AUTOMATIC_ATTRIBUTES_NAMES_PREFIX}{index + 1}"</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t282" href="#t282">282</a></span><span class="t">                <span class="key">for</span> <span class="nam">index</span> <span class="key">in</span> <span class="nam">range</span><span class="op">(</span><span class="nam">X</span><span class="op">.</span><span class="nam">shape</span><span class="op">[</span><span class="num">1</span><span class="op">]</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t283" href="#t283">283</a></span><span class="t">            <span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t284" href="#t284">284</a></span><span class="t">            <span class="nam">self</span><span class="op">.</span><span class="nam">_X</span> <span class="op">=</span> <span class="nam">X</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t285" href="#t285">285</a></span><span class="t">        <span class="key">else</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t286" href="#t286">286</a></span><span class="t">            <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t287" href="#t287">287</a></span><span class="t">                <span class="str">f"Invalid X type: {str(type(X))}. "</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t288" href="#t288">288</a></span><span class="t">                <span class="op">+</span> <span class="str">"Supported types are: 2 dimensional numpy array or pandas DataFrame object."</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t289" href="#t289">289</a></span><span class="t">            <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t290" href="#t290">290</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t291" href="#t291">291</a></span><span class="t">    <span class="key">def</span> <span class="nam">_validate_X</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t292" href="#t292">292</a></span><span class="t">        <span class="key">if</span> <span class="nam">len</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">_X</span><span class="op">.</span><span class="nam">shape</span><span class="op">)</span> <span class="op">!=</span> <span class="num">2</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t293" href="#t293">293</a></span><span class="t">            <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t294" href="#t294">294</a></span><span class="t">                <span class="str">"X must be a 2 dimensional numpy array or pandas DataFrame object. "</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t295" href="#t295">295</a></span><span class="t">                <span class="op">+</span> <span class="str">f"Its current shape is: {str(self._X.shape)}"</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t296" href="#t296">296</a></span><span class="t">            <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t297" href="#t297">297</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t298" href="#t298">298</a></span><span class="t">    <span class="key">def</span> <span class="nam">_validate_y</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t299" href="#t299">299</a></span><span class="t">        <span class="key">if</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_y</span> <span class="key">is</span> <span class="key">not</span> <span class="key">None</span> <span class="key">and</span> <span class="nam">len</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">_y</span><span class="op">.</span><span class="nam">shape</span><span class="op">)</span> <span class="op">!=</span> <span class="num">1</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t300" href="#t300">300</a></span><span class="t">            <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t301" href="#t301">301</a></span><span class="t">                <span class="str">"y must be a 1 dimensional numpy array or pandas DataFrame object. "</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t302" href="#t302">302</a></span><span class="t">                <span class="op">+</span> <span class="str">f"Its current shape is: {str(self._y.shape)}"</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t303" href="#t303">303</a></span><span class="t">            <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t304" href="#t304">304</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t305" href="#t305">305</a></span><span class="t">    <span class="key">def</span> <span class="nam">_create_example_set</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">JObject</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t306" href="#t306">306</a></span><span class="t">        <span class="nam">data</span><span class="op">:</span> <span class="nam">JObject</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_prepare_data</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t307" href="#t307">307</a></span><span class="t">        <span class="nam">args</span><span class="op">:</span> <span class="nam">list</span> <span class="op">=</span> <span class="op">[</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t308" href="#t308">308</a></span><span class="t">            <span class="nam">data</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t309" href="#t309">309</a></span><span class="t">            <span class="nam">self</span><span class="op">.</span><span class="nam">_attributes_names</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t310" href="#t310">310</a></span><span class="t">            <span class="nam">self</span><span class="op">.</span><span class="nam">_label_name</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t311" href="#t311">311</a></span><span class="t">            <span class="nam">self</span><span class="op">.</span><span class="nam">_survival_time_attribute</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t312" href="#t312">312</a></span><span class="t">            <span class="nam">self</span><span class="op">.</span><span class="nam">_contrast_attribute</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t313" href="#t313">313</a></span><span class="t">        <span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t314" href="#t314">314</a></span><span class="t">        <span class="nam">DataTable</span> <span class="op">=</span> <span class="nam">JClass</span><span class="op">(</span>  <span class="com"># pylint: disable=invalid-name</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t315" href="#t315">315</a></span><span class="t">            <span class="str">"adaa.analytics.rules.data.DataTable"</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t316" href="#t316">316</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t317" href="#t317">317</a></span><span class="t">        <span class="key">try</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t318" href="#t318">318</a></span><span class="t">            <span class="nam">table</span> <span class="op">=</span> <span class="nam">DataTable</span><span class="op">(</span><span class="op">*</span><span class="nam">args</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t319" href="#t319">319</a></span><span class="t">            <span class="key">if</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_y</span> <span class="key">is</span> <span class="key">not</span> <span class="key">None</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t320" href="#t320">320</a></span><span class="t">                <span class="nam">ExampleSetFactory</span> <span class="op">=</span> <span class="nam">JClass</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t321" href="#t321">321</a></span><span class="t">                    <span class="str">"adaa.analytics.rules.logic.representation.exampleset.ExampleSetFactory"</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t322" href="#t322">322</a></span><span class="t">                <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t323" href="#t323">323</a></span><span class="t">                <span class="nam">factory</span> <span class="op">=</span> <span class="nam">ExampleSetFactory</span><span class="op">(</span><span class="num">2</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t324" href="#t324">324</a></span><span class="t">                <span class="nam">example_set</span> <span class="op">=</span> <span class="nam">factory</span><span class="op">.</span><span class="nam">create</span><span class="op">(</span><span class="nam">table</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t325" href="#t325">325</a></span><span class="t">                <span class="key">return</span> <span class="nam">example_set</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t326" href="#t326">326</a></span><span class="t">            <span class="key">else</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t327" href="#t327">327</a></span><span class="t">                <span class="key">return</span> <span class="nam">table</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t328" href="#t328">328</a></span><span class="t">        <span class="key">except</span> <span class="nam">Exception</span> <span class="key">as</span> <span class="nam">error</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t329" href="#t329">329</a></span><span class="t">            <span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">exceptions</span> <span class="key">import</span> <span class="nam">RuleKitJavaException</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t330" href="#t330">330</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t331" href="#t331">331</a></span><span class="t">            <span class="nam">RuleKitJavaException</span><span class="op">(</span><span class="nam">error</span><span class="op">)</span><span class="op">.</span><span class="nam">print_java_stack_trace</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t332" href="#t332">332</a></span><span class="t">            <span class="key">raise</span> <span class="nam">error</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t333" href="#t333">333</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t334" href="#t334">334</a></span><span class="t">    <span class="key">def</span> <span class="nam">_wrap_training_example_set</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">example_set</span><span class="op">:</span> <span class="nam">JObject</span><span class="op">)</span> <span class="op">-></span> <span class="nam">JObject</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t335" href="#t335">335</a></span><span class="t">        <span class="com"># training dataset must be wrapped in additional classes for rule induction to work properly</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t336" href="#t336">336</a></span><span class="t">        <span class="nam">ExampleSetFactory</span> <span class="op">=</span> <span class="nam">JClass</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t337" href="#t337">337</a></span><span class="t">            <span class="str">"adaa.analytics.rules.logic.representation.exampleset.ExampleSetFactory"</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t338" href="#t338">338</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t339" href="#t339">339</a></span><span class="t">        <span class="nam">factory</span><span class="op">:</span> <span class="nam">JObject</span> <span class="op">=</span> <span class="nam">ExampleSetFactory</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">_problem_type</span><span class="op">.</span><span class="nam">value</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t340" href="#t340">340</a></span><span class="t">        <span class="key">return</span> <span class="nam">factory</span><span class="op">.</span><span class="nam">create</span><span class="op">(</span><span class="nam">example_set</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t341" href="#t341">341</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t342" href="#t342">342</a></span><span class="t">    <span class="key">def</span> <span class="nam">_prepare_data</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">JObject</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t343" href="#t343">343</a></span><span class="t">        <span class="key">if</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_y</span> <span class="key">is</span> <span class="key">None</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t344" href="#t344">344</a></span><span class="t">            <span class="nam">data</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_X</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t345" href="#t345">345</a></span><span class="t">        <span class="key">else</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t346" href="#t346">346</a></span><span class="t">            <span class="nam">data</span> <span class="op">=</span> <span class="nam">np</span><span class="op">.</span><span class="nam">hstack</span><span class="op">(</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">_X</span><span class="op">.</span><span class="nam">astype</span><span class="op">(</span><span class="nam">object</span><span class="op">)</span><span class="op">,</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_y</span><span class="op">.</span><span class="nam">reshape</span><span class="op">(</span><span class="op">-</span><span class="num">1</span><span class="op">,</span> <span class="num">1</span><span class="op">)</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t347" href="#t347">347</a></span><span class="t">        <span class="nam">java_data</span> <span class="op">=</span> <span class="nam">JObject</span><span class="op">(</span><span class="nam">data</span><span class="op">,</span> <span class="nam">JArray</span><span class="op">(</span><span class="str">"java.lang.Object"</span><span class="op">,</span> <span class="num">2</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t348" href="#t348">348</a></span><span class="t">        <span class="key">return</span> <span class="nam">java_data</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t349" href="#t349">349</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t350" href="#t350">350</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t351" href="#t351">351</a></span><span class="t"><span class="key">class</span> <span class="nam">PredictionResultMapper</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t352" href="#t352">352</a></span><span class="t">    <span class="str">"""Maps prediction results to numpy array"""</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t353" href="#t353">353</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t354" href="#t354">354</a></span><span class="t">    <span class="nam">PREDICTION_COLUMN_ROLE</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="str">"prediction"</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t355" href="#t355">355</a></span><span class="t">    <span class="nam">CONFIDENCE_COLUMN_ROLE</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="str">"confidence"</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t356" href="#t356">356</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t357" href="#t357">357</a></span><span class="t">    <span class="op">@</span><span class="nam">staticmethod</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t358" href="#t358">358</a></span><span class="t">    <span class="key">def</span> <span class="nam">map_confidence</span><span class="op">(</span><span class="nam">predicted_example_set</span><span class="op">,</span> <span class="nam">label_unique_values</span><span class="op">:</span> <span class="nam">list</span><span class="op">)</span> <span class="op">-></span> <span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t359" href="#t359">359</a></span><span class="t">        <span class="str">"""Maps models confidence values to numpy array</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t360" href="#t360">360</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t361" href="#t361">361</a></span><span class="t"><span class="str">        Args:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t362" href="#t362">362</a></span><span class="t"><span class="str">            predicted_example_set (_type_): predicted ExampleSet instance</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t363" href="#t363">363</a></span><span class="t"><span class="str">            label_unique_values (list): unique labels values</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t364" href="#t364">364</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t365" href="#t365">365</a></span><span class="t"><span class="str">        Returns:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t366" href="#t366">366</a></span><span class="t"><span class="str">            np.ndarray: numpy array with mapped confidence values</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t367" href="#t367">367</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t368" href="#t368">368</a></span><span class="t">        <span class="nam">confidence_matrix</span><span class="op">:</span> <span class="nam">list</span><span class="op">[</span><span class="nam">list</span><span class="op">[</span><span class="nam">float</span><span class="op">]</span><span class="op">]</span> <span class="op">=</span> <span class="op">[</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t369" href="#t369">369</a></span><span class="t">        <span class="key">for</span> <span class="nam">label_value</span> <span class="key">in</span> <span class="nam">label_unique_values</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t370" href="#t370">370</a></span><span class="t">            <span class="nam">confidence_col</span><span class="op">:</span> <span class="nam">JObject</span> <span class="op">=</span> <span class="nam">PredictionResultMapper</span><span class="op">.</span><span class="nam">_get_column_by_role</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t371" href="#t371">371</a></span><span class="t">                <span class="nam">predicted_example_set</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t372" href="#t372">372</a></span><span class="t">                <span class="str">f"{PredictionResultMapper.CONFIDENCE_COLUMN_ROLE}_{label_value}"</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t373" href="#t373">373</a></span><span class="t">            <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t374" href="#t374">374</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t375" href="#t375">375</a></span><span class="t">            <span class="nam">confidence_values</span> <span class="op">=</span> <span class="op">[</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t376" href="#t376">376</a></span><span class="t">                <span class="nam">float</span><span class="op">(</span><span class="nam">predicted_example_set</span><span class="op">.</span><span class="nam">getExample</span><span class="op">(</span><span class="nam">i</span><span class="op">)</span><span class="op">.</span><span class="nam">getValue</span><span class="op">(</span><span class="nam">confidence_col</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t377" href="#t377">377</a></span><span class="t">                <span class="key">for</span> <span class="nam">i</span> <span class="key">in</span> <span class="nam">range</span><span class="op">(</span><span class="nam">predicted_example_set</span><span class="op">.</span><span class="nam">size</span><span class="op">(</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t378" href="#t378">378</a></span><span class="t">            <span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t379" href="#t379">379</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t380" href="#t380">380</a></span><span class="t">            <span class="nam">confidence_matrix</span><span class="op">.</span><span class="nam">append</span><span class="op">(</span><span class="nam">confidence_values</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t381" href="#t381">381</a></span><span class="t">        <span class="key">return</span> <span class="nam">np</span><span class="op">.</span><span class="nam">array</span><span class="op">(</span><span class="nam">confidence_matrix</span><span class="op">,</span> <span class="nam">dtype</span><span class="op">=</span><span class="nam">float</span><span class="op">)</span><span class="op">.</span><span class="nam">T</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t382" href="#t382">382</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t383" href="#t383">383</a></span><span class="t">    <span class="op">@</span><span class="nam">staticmethod</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t384" href="#t384">384</a></span><span class="t">    <span class="key">def</span> <span class="nam">map</span><span class="op">(</span><span class="nam">predicted_example_set</span><span class="op">:</span> <span class="nam">JObject</span><span class="op">)</span> <span class="op">-></span> <span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t385" href="#t385">385</a></span><span class="t">        <span class="str">"""Maps models predictions to numpy array</span>&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t386" href="#t386">386</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t387" href="#t387">387</a></span><span class="t">    <span class="op">@</span><span class="nam">staticmethod</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t388" href="#t388">388</a></span><span class="t">    <span class="key">def</span> <span class="nam">map_to_numerical</span><span class="op">(</span><span class="nam">predicted_example_set</span><span class="op">:</span> <span class="nam">JObject</span><span class="op">,</span> <span class="nam">remap</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="key">True</span><span class="op">)</span> <span class="op">-></span> <span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t389" href="#t389">389</a></span><span class="t">        <span class="str">"""Maps models predictions to numerical numpy array</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t390" href="#t390">390</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t391" href="#t391">391</a></span><span class="t"><span class="str">        Args:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t392" href="#t392">392</a></span><span class="t"><span class="str">            predicted_example_set (_type_): ExampleSet with predictions</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t393" href="#t393">393</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t394" href="#t394">394</a></span><span class="t"><span class="str">        Returns:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t395" href="#t395">395</a></span><span class="t"><span class="str">            np.ndarray: numpy array containing predictions</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t396" href="#t396">396</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t397" href="#t397">397</a></span><span class="t">        <span class="nam">prediction_col</span><span class="op">:</span> <span class="nam">JObject</span> <span class="op">=</span> <span class="nam">PredictionResultMapper</span><span class="op">.</span><span class="nam">_get_column_by_role</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t398" href="#t398">398</a></span><span class="t">            <span class="nam">predicted_example_set</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t399" href="#t399">399</a></span><span class="t">            <span class="nam">PredictionResultMapper</span><span class="op">.</span><span class="nam">PREDICTION_COLUMN_ROLE</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t400" href="#t400">400</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t401" href="#t401">401</a></span><span class="t">        <span class="nam">label_mapping</span> <span class="op">=</span> <span class="nam">predicted_example_set</span><span class="op">.</span><span class="nam">getAttributes</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">getLabel</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">getMapping</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t402" href="#t402">402</a></span><span class="t">        <span class="key">if</span> <span class="nam">remap</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t403" href="#t403">403</a></span><span class="t">            <span class="nam">predictions</span><span class="op">:</span> <span class="nam">list</span> <span class="op">=</span> <span class="op">[</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t404" href="#t404">404</a></span><span class="t">                <span class="nam">label_mapping</span><span class="op">.</span><span class="nam">mapIndex</span><span class="op">(</span><span class="nam">int</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t405" href="#t405">405</a></span><span class="t">                    <span class="nam">predicted_example_set</span><span class="op">.</span><span class="nam">getExample</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t406" href="#t406">406</a></span><span class="t">                        <span class="nam">i</span><span class="op">)</span><span class="op">.</span><span class="nam">getValue</span><span class="op">(</span><span class="nam">prediction_col</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t407" href="#t407">407</a></span><span class="t">                <span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t408" href="#t408">408</a></span><span class="t">                <span class="key">for</span> <span class="nam">i</span> <span class="key">in</span> <span class="nam">range</span><span class="op">(</span><span class="nam">predicted_example_set</span><span class="op">.</span><span class="nam">size</span><span class="op">(</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t409" href="#t409">409</a></span><span class="t">            <span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t410" href="#t410">410</a></span><span class="t">            <span class="nam">predictions</span> <span class="op">=</span> <span class="nam">list</span><span class="op">(</span><span class="nam">map</span><span class="op">(</span><span class="key">lambda</span> <span class="nam">x</span><span class="op">:</span> <span class="nam">float</span><span class="op">(</span><span class="nam">str</span><span class="op">(</span><span class="nam">x</span><span class="op">)</span><span class="op">)</span><span class="op">,</span> <span class="nam">predictions</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t411" href="#t411">411</a></span><span class="t">            <span class="key">return</span> <span class="nam">np</span><span class="op">.</span><span class="nam">array</span><span class="op">(</span><span class="nam">predictions</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t412" href="#t412">412</a></span><span class="t">        <span class="key">return</span> <span class="nam">np</span><span class="op">.</span><span class="nam">array</span><span class="op">(</span><span class="op">[</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t413" href="#t413">413</a></span><span class="t">            <span class="nam">float</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t414" href="#t414">414</a></span><span class="t">                <span class="nam">predicted_example_set</span><span class="op">.</span><span class="nam">getExample</span><span class="op">(</span><span class="nam">i</span><span class="op">)</span><span class="op">.</span><span class="nam">getValue</span><span class="op">(</span><span class="nam">prediction_col</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t415" href="#t415">415</a></span><span class="t">            <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t416" href="#t416">416</a></span><span class="t">            <span class="key">for</span> <span class="nam">i</span> <span class="key">in</span> <span class="nam">range</span><span class="op">(</span><span class="nam">predicted_example_set</span><span class="op">.</span><span class="nam">size</span><span class="op">(</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t417" href="#t417">417</a></span><span class="t">        <span class="op">]</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t418" href="#t418">418</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t419" href="#t419">419</a></span><span class="t">    <span class="op">@</span><span class="nam">staticmethod</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t420" href="#t420">420</a></span><span class="t">    <span class="key">def</span> <span class="nam">map_survival</span><span class="op">(</span><span class="nam">predicted_example_set</span><span class="op">)</span> <span class="op">-></span> <span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t421" href="#t421">421</a></span><span class="t">        <span class="str">"""Maps survival models predictions to numpy array. Used as alternative to `map` method</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t422" href="#t422">422</a></span><span class="t"><span class="str">        used in survival analysis</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t423" href="#t423">423</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t424" href="#t424">424</a></span><span class="t"><span class="str">        Args:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t425" href="#t425">425</a></span><span class="t"><span class="str">            predicted_example_set (_type_): ExampleSet with predictions</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t426" href="#t426">426</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t427" href="#t427">427</a></span><span class="t"><span class="str">        Returns:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t428" href="#t428">428</a></span><span class="t"><span class="str">            np.ndarray: numpy array containing predictions</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t429" href="#t429">429</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t430" href="#t430">430</a></span><span class="t">        <span class="nam">estimators</span> <span class="op">=</span> <span class="op">[</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t431" href="#t431">431</a></span><span class="t">        <span class="nam">attribute</span> <span class="op">=</span> <span class="nam">predicted_example_set</span><span class="op">.</span><span class="nam">getAttributes</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">get</span><span class="op">(</span><span class="str">"estimator"</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t432" href="#t432">432</a></span><span class="t">        <span class="nam">example_set_iterator</span> <span class="op">=</span> <span class="nam">predicted_example_set</span><span class="op">.</span><span class="nam">iterator</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t433" href="#t433">433</a></span><span class="t">        <span class="key">while</span> <span class="nam">example_set_iterator</span><span class="op">.</span><span class="nam">hasNext</span><span class="op">(</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t434" href="#t434">434</a></span><span class="t">            <span class="nam">example</span> <span class="op">=</span> <span class="nam">example_set_iterator</span><span class="op">.</span><span class="nam">next</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t435" href="#t435">435</a></span><span class="t">            <span class="nam">example_estimator</span> <span class="op">=</span> <span class="nam">str</span><span class="op">(</span><span class="nam">example</span><span class="op">.</span><span class="nam">getValueAsString</span><span class="op">(</span><span class="nam">attribute</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t436" href="#t436">436</a></span><span class="t">            <span class="nam">example_estimator</span> <span class="op">=</span> <span class="nam">example_estimator</span><span class="op">.</span><span class="nam">split</span><span class="op">(</span><span class="str">" "</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t437" href="#t437">437</a></span><span class="t">            <span class="nam">_</span><span class="op">,</span> <span class="nam">example_estimator</span><span class="op">[</span><span class="num">0</span><span class="op">]</span> <span class="op">=</span> <span class="nam">example_estimator</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="op">.</span><span class="nam">split</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t438" href="#t438">438</a></span><span class="t">                <span class="str">":"</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t439" href="#t439">439</a></span><span class="t">            <span class="nam">times</span> <span class="op">=</span> <span class="op">[</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t440" href="#t440">440</a></span><span class="t">                <span class="nam">float</span><span class="op">(</span><span class="nam">example_estimator</span><span class="op">[</span><span class="nam">i</span><span class="op">]</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t441" href="#t441">441</a></span><span class="t">                <span class="key">for</span> <span class="nam">i</span> <span class="key">in</span> <span class="nam">range</span><span class="op">(</span><span class="nam">len</span><span class="op">(</span><span class="nam">example_estimator</span><span class="op">)</span> <span class="op">-</span> <span class="num">1</span><span class="op">)</span> <span class="key">if</span> <span class="nam">i</span> <span class="op">%</span> <span class="num">2</span> <span class="op">==</span> <span class="num">0</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t442" href="#t442">442</a></span><span class="t">            <span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t443" href="#t443">443</a></span><span class="t">            <span class="nam">probabilities</span> <span class="op">=</span> <span class="op">[</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t444" href="#t444">444</a></span><span class="t">                <span class="nam">float</span><span class="op">(</span><span class="nam">example_estimator</span><span class="op">[</span><span class="nam">i</span><span class="op">]</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t445" href="#t445">445</a></span><span class="t">                <span class="key">for</span> <span class="nam">i</span> <span class="key">in</span> <span class="nam">range</span><span class="op">(</span><span class="nam">len</span><span class="op">(</span><span class="nam">example_estimator</span><span class="op">)</span><span class="op">)</span> <span class="key">if</span> <span class="nam">i</span> <span class="op">%</span> <span class="num">2</span> <span class="op">!=</span> <span class="num">0</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t446" href="#t446">446</a></span><span class="t">            <span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t447" href="#t447">447</a></span><span class="t">            <span class="nam">estimator</span> <span class="op">=</span> <span class="op">{</span><span class="str">'times'</span><span class="op">:</span> <span class="nam">times</span><span class="op">,</span> <span class="str">'probabilities'</span><span class="op">:</span> <span class="nam">probabilities</span><span class="op">}</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t448" href="#t448">448</a></span><span class="t">            <span class="nam">estimators</span><span class="op">.</span><span class="nam">append</span><span class="op">(</span><span class="nam">estimator</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t449" href="#t449">449</a></span><span class="t">        <span class="key">return</span> <span class="nam">np</span><span class="op">.</span><span class="nam">array</span><span class="op">(</span><span class="nam">estimators</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t450" href="#t450">450</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t451" href="#t451">451</a></span><span class="t">    <span class="op">@</span><span class="nam">staticmethod</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t452" href="#t452">452</a></span><span class="t">    <span class="key">def</span> <span class="nam">_get_column_by_role</span><span class="op">(</span><span class="nam">predicted_example_set</span><span class="op">:</span> <span class="nam">JObject</span><span class="op">,</span> <span class="nam">role</span><span class="op">:</span> <span class="nam">str</span><span class="op">)</span> <span class="op">-></span> <span class="nam">JObject</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t453" href="#t453">453</a></span><span class="t">        <span class="key">return</span> <span class="nam">predicted_example_set</span><span class="op">.</span><span class="nam">getAttributes</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">getColumnByRole</span><span class="op">(</span><span class="nam">role</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t454" href="#t454">454</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t455" href="#t455">455</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t456" href="#t456">456</a></span><span class="t"><span class="key">class</span> <span class="nam">ModelSerializer</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t457" href="#t457">457</a></span><span class="t">    <span class="str">"""Class for serializing models</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t458" href="#t458">458</a></span><span class="t"><span class="str">    """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t459" href="#t459">459</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t460" href="#t460">460</a></span><span class="t">    <span class="op">@</span><span class="nam">staticmethod</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t461" href="#t461">461</a></span><span class="t">    <span class="key">def</span> <span class="nam">serialize</span><span class="op">(</span><span class="nam">real_model</span><span class="op">:</span> <span class="nam">object</span><span class="op">)</span> <span class="op">-></span> <span class="nam">bytes</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t462" href="#t462">462</a></span><span class="t">        <span class="str">"""Serialize Java ruleset object.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t463" href="#t463">463</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t464" href="#t464">464</a></span><span class="t"><span class="str">        Args:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t465" href="#t465">465</a></span><span class="t"><span class="str">            real_model (object): Java ruleset object</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t466" href="#t466">466</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t467" href="#t467">467</a></span><span class="t">        <span class="nam">in_memory_file</span> <span class="op">=</span> <span class="nam">io</span><span class="op">.</span><span class="nam">BytesIO</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t468" href="#t468">468</a></span><span class="t">        <span class="nam">JPickler</span><span class="op">(</span><span class="nam">in_memory_file</span><span class="op">)</span><span class="op">.</span><span class="nam">dump</span><span class="op">(</span><span class="nam">real_model</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t469" href="#t469">469</a></span><span class="t">        <span class="nam">serialized_bytes</span> <span class="op">=</span> <span class="nam">in_memory_file</span><span class="op">.</span><span class="nam">getvalue</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t470" href="#t470">470</a></span><span class="t">        <span class="nam">in_memory_file</span><span class="op">.</span><span class="nam">close</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t471" href="#t471">471</a></span><span class="t">        <span class="key">return</span> <span class="nam">serialized_bytes</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t472" href="#t472">472</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t473" href="#t473">473</a></span><span class="t">    <span class="op">@</span><span class="nam">staticmethod</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t474" href="#t474">474</a></span><span class="t">    <span class="key">def</span> <span class="nam">deserialize</span><span class="op">(</span><span class="nam">serialized_bytes</span><span class="op">:</span> <span class="nam">bytes</span><span class="op">)</span> <span class="op">-></span> <span class="nam">object</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t475" href="#t475">475</a></span><span class="t">        <span class="str">"""Deserialize Java ruleset object from bytes.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t476" href="#t476">476</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t477" href="#t477">477</a></span><span class="t"><span class="str">        Args:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t478" href="#t478">478</a></span><span class="t"><span class="str">            serialized_bytes (bytes): serialized bytes</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t479" href="#t479">479</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t480" href="#t480">480</a></span><span class="t"><span class="str">        Returns:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t481" href="#t481">481</a></span><span class="t"><span class="str">            object: deserialized Java ruleset object</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t482" href="#t482">482</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t483" href="#t483">483</a></span><span class="t">        <span class="nam">in_memory_file</span> <span class="op">=</span> <span class="nam">io</span><span class="op">.</span><span class="nam">BytesIO</span><span class="op">(</span><span class="nam">serialized_bytes</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t484" href="#t484">484</a></span><span class="t">        <span class="nam">model</span> <span class="op">=</span> <span class="nam">JUnpickler</span><span class="op">(</span><span class="nam">in_memory_file</span><span class="op">)</span><span class="op">.</span><span class="nam">load</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t485" href="#t485">485</a></span><span class="t">        <span class="nam">in_memory_file</span><span class="op">.</span><span class="nam">close</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t486" href="#t486">486</a></span><span class="t">        <span class="key">return</span> <span class="nam">model</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t387" href="#t387">387</a></span><span class="t"><span class="str">        Args:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t388" href="#t388">388</a></span><span class="t"><span class="str">            predicted_example_set (_type_): ExampleSet with predictions</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t389" href="#t389">389</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t390" href="#t390">390</a></span><span class="t"><span class="str">        Returns:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t391" href="#t391">391</a></span><span class="t"><span class="str">            np.ndarray: numpy array containing predictions</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t392" href="#t392">392</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t393" href="#t393">393</a></span><span class="t">        <span class="nam">prediction_col</span><span class="op">:</span> <span class="nam">JObject</span> <span class="op">=</span> <span class="nam">PredictionResultMapper</span><span class="op">.</span><span class="nam">_get_column_by_role</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t394" href="#t394">394</a></span><span class="t">            <span class="nam">predicted_example_set</span><span class="op">,</span> <span class="nam">PredictionResultMapper</span><span class="op">.</span><span class="nam">PREDICTION_COLUMN_ROLE</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t395" href="#t395">395</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t396" href="#t396">396</a></span><span class="t">        <span class="key">if</span> <span class="nam">prediction_col</span><span class="op">.</span><span class="nam">isNominal</span><span class="op">(</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t397" href="#t397">397</a></span><span class="t">            <span class="key">return</span> <span class="nam">PredictionResultMapper</span><span class="op">.</span><span class="nam">map_to_nominal</span><span class="op">(</span><span class="nam">predicted_example_set</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t398" href="#t398">398</a></span><span class="t">        <span class="key">return</span> <span class="nam">PredictionResultMapper</span><span class="op">.</span><span class="nam">map_to_numerical</span><span class="op">(</span><span class="nam">predicted_example_set</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t399" href="#t399">399</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t400" href="#t400">400</a></span><span class="t">    <span class="op">@</span><span class="nam">staticmethod</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t401" href="#t401">401</a></span><span class="t">    <span class="key">def</span> <span class="nam">map_to_nominal</span><span class="op">(</span><span class="nam">predicted_example_set</span><span class="op">:</span> <span class="nam">JObject</span><span class="op">)</span> <span class="op">-></span> <span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t402" href="#t402">402</a></span><span class="t">        <span class="str">"""Maps models predictions to nominal numpy array of strings</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t403" href="#t403">403</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t404" href="#t404">404</a></span><span class="t"><span class="str">        Args:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t405" href="#t405">405</a></span><span class="t"><span class="str">            predicted_example_set (_type_): ExampleSet with predictions</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t406" href="#t406">406</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t407" href="#t407">407</a></span><span class="t"><span class="str">        Returns:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t408" href="#t408">408</a></span><span class="t"><span class="str">            np.ndarray: numpy array containing predictions</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t409" href="#t409">409</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t410" href="#t410">410</a></span><span class="t">        <span class="nam">prediction_col</span><span class="op">:</span> <span class="nam">JObject</span> <span class="op">=</span> <span class="nam">PredictionResultMapper</span><span class="op">.</span><span class="nam">_get_column_by_role</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t411" href="#t411">411</a></span><span class="t">            <span class="nam">predicted_example_set</span><span class="op">,</span> <span class="nam">PredictionResultMapper</span><span class="op">.</span><span class="nam">PREDICTION_COLUMN_ROLE</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t412" href="#t412">412</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t413" href="#t413">413</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t414" href="#t414">414</a></span><span class="t">        <span class="key">return</span> <span class="nam">np</span><span class="op">.</span><span class="nam">array</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t415" href="#t415">415</a></span><span class="t">            <span class="op">[</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t416" href="#t416">416</a></span><span class="t">                <span class="nam">str</span><span class="op">(</span><span class="nam">predicted_example_set</span><span class="op">.</span><span class="nam">getExample</span><span class="op">(</span><span class="nam">i</span><span class="op">)</span><span class="op">.</span><span class="nam">getNominalValue</span><span class="op">(</span><span class="nam">prediction_col</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t417" href="#t417">417</a></span><span class="t">                <span class="key">for</span> <span class="nam">i</span> <span class="key">in</span> <span class="nam">range</span><span class="op">(</span><span class="nam">predicted_example_set</span><span class="op">.</span><span class="nam">size</span><span class="op">(</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t418" href="#t418">418</a></span><span class="t">            <span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t419" href="#t419">419</a></span><span class="t">            <span class="nam">dtype</span><span class="op">=</span><span class="nam">str</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t420" href="#t420">420</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t421" href="#t421">421</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t422" href="#t422">422</a></span><span class="t">    <span class="op">@</span><span class="nam">staticmethod</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t423" href="#t423">423</a></span><span class="t">    <span class="key">def</span> <span class="nam">map_to_numerical</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t424" href="#t424">424</a></span><span class="t">        <span class="nam">predicted_example_set</span><span class="op">:</span> <span class="nam">JObject</span><span class="op">,</span> <span class="nam">remap</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="key">True</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t425" href="#t425">425</a></span><span class="t">    <span class="op">)</span> <span class="op">-></span> <span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t426" href="#t426">426</a></span><span class="t">        <span class="str">"""Maps models predictions to numerical numpy array</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t427" href="#t427">427</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t428" href="#t428">428</a></span><span class="t"><span class="str">        Args:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t429" href="#t429">429</a></span><span class="t"><span class="str">            predicted_example_set (_type_): ExampleSet with predictions</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t430" href="#t430">430</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t431" href="#t431">431</a></span><span class="t"><span class="str">        Returns:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t432" href="#t432">432</a></span><span class="t"><span class="str">            np.ndarray: numpy array containing predictions</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t433" href="#t433">433</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t434" href="#t434">434</a></span><span class="t">        <span class="nam">prediction_col</span><span class="op">:</span> <span class="nam">JObject</span> <span class="op">=</span> <span class="nam">PredictionResultMapper</span><span class="op">.</span><span class="nam">_get_column_by_role</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t435" href="#t435">435</a></span><span class="t">            <span class="nam">predicted_example_set</span><span class="op">,</span> <span class="nam">PredictionResultMapper</span><span class="op">.</span><span class="nam">PREDICTION_COLUMN_ROLE</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t436" href="#t436">436</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t437" href="#t437">437</a></span><span class="t">        <span class="nam">label_mapping</span> <span class="op">=</span> <span class="nam">predicted_example_set</span><span class="op">.</span><span class="nam">getAttributes</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">getLabel</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">getMapping</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t438" href="#t438">438</a></span><span class="t">        <span class="key">if</span> <span class="nam">remap</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t439" href="#t439">439</a></span><span class="t">            <span class="nam">predictions</span><span class="op">:</span> <span class="nam">list</span> <span class="op">=</span> <span class="op">[</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t440" href="#t440">440</a></span><span class="t">                <span class="nam">label_mapping</span><span class="op">.</span><span class="nam">mapIndex</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t441" href="#t441">441</a></span><span class="t">                    <span class="nam">int</span><span class="op">(</span><span class="nam">predicted_example_set</span><span class="op">.</span><span class="nam">getExample</span><span class="op">(</span><span class="nam">i</span><span class="op">)</span><span class="op">.</span><span class="nam">getValue</span><span class="op">(</span><span class="nam">prediction_col</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t442" href="#t442">442</a></span><span class="t">                <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t443" href="#t443">443</a></span><span class="t">                <span class="key">for</span> <span class="nam">i</span> <span class="key">in</span> <span class="nam">range</span><span class="op">(</span><span class="nam">predicted_example_set</span><span class="op">.</span><span class="nam">size</span><span class="op">(</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t444" href="#t444">444</a></span><span class="t">            <span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t445" href="#t445">445</a></span><span class="t">            <span class="nam">predictions</span> <span class="op">=</span> <span class="nam">list</span><span class="op">(</span><span class="nam">map</span><span class="op">(</span><span class="key">lambda</span> <span class="nam">x</span><span class="op">:</span> <span class="nam">float</span><span class="op">(</span><span class="nam">str</span><span class="op">(</span><span class="nam">x</span><span class="op">)</span><span class="op">)</span><span class="op">,</span> <span class="nam">predictions</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t446" href="#t446">446</a></span><span class="t">            <span class="key">return</span> <span class="nam">np</span><span class="op">.</span><span class="nam">array</span><span class="op">(</span><span class="nam">predictions</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t447" href="#t447">447</a></span><span class="t">        <span class="key">return</span> <span class="nam">np</span><span class="op">.</span><span class="nam">array</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t448" href="#t448">448</a></span><span class="t">            <span class="op">[</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t449" href="#t449">449</a></span><span class="t">                <span class="nam">float</span><span class="op">(</span><span class="nam">predicted_example_set</span><span class="op">.</span><span class="nam">getExample</span><span class="op">(</span><span class="nam">i</span><span class="op">)</span><span class="op">.</span><span class="nam">getValue</span><span class="op">(</span><span class="nam">prediction_col</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t450" href="#t450">450</a></span><span class="t">                <span class="key">for</span> <span class="nam">i</span> <span class="key">in</span> <span class="nam">range</span><span class="op">(</span><span class="nam">predicted_example_set</span><span class="op">.</span><span class="nam">size</span><span class="op">(</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t451" href="#t451">451</a></span><span class="t">            <span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t452" href="#t452">452</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t453" href="#t453">453</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t454" href="#t454">454</a></span><span class="t">    <span class="op">@</span><span class="nam">staticmethod</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t455" href="#t455">455</a></span><span class="t">    <span class="key">def</span> <span class="nam">map_survival</span><span class="op">(</span><span class="nam">predicted_example_set</span><span class="op">)</span> <span class="op">-></span> <span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t456" href="#t456">456</a></span><span class="t">        <span class="str">"""Maps survival models predictions to numpy array. Used as alternative to `map` method</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t457" href="#t457">457</a></span><span class="t"><span class="str">        used in survival analysis</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t458" href="#t458">458</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t459" href="#t459">459</a></span><span class="t"><span class="str">        Args:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t460" href="#t460">460</a></span><span class="t"><span class="str">            predicted_example_set (_type_): ExampleSet with predictions</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t461" href="#t461">461</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t462" href="#t462">462</a></span><span class="t"><span class="str">        Returns:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t463" href="#t463">463</a></span><span class="t"><span class="str">            np.ndarray: numpy array containing predictions</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t464" href="#t464">464</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t465" href="#t465">465</a></span><span class="t">        <span class="nam">estimators</span> <span class="op">=</span> <span class="op">[</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t466" href="#t466">466</a></span><span class="t">        <span class="nam">attribute</span> <span class="op">=</span> <span class="nam">predicted_example_set</span><span class="op">.</span><span class="nam">getAttributes</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">get</span><span class="op">(</span><span class="str">"estimator"</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t467" href="#t467">467</a></span><span class="t">        <span class="nam">example_set_iterator</span> <span class="op">=</span> <span class="nam">predicted_example_set</span><span class="op">.</span><span class="nam">iterator</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t468" href="#t468">468</a></span><span class="t">        <span class="key">while</span> <span class="nam">example_set_iterator</span><span class="op">.</span><span class="nam">hasNext</span><span class="op">(</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t469" href="#t469">469</a></span><span class="t">            <span class="nam">example</span> <span class="op">=</span> <span class="nam">example_set_iterator</span><span class="op">.</span><span class="nam">next</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t470" href="#t470">470</a></span><span class="t">            <span class="nam">example_estimator</span> <span class="op">=</span> <span class="nam">str</span><span class="op">(</span><span class="nam">example</span><span class="op">.</span><span class="nam">getValueAsString</span><span class="op">(</span><span class="nam">attribute</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t471" href="#t471">471</a></span><span class="t">            <span class="nam">example_estimator</span> <span class="op">=</span> <span class="nam">example_estimator</span><span class="op">.</span><span class="nam">split</span><span class="op">(</span><span class="str">" "</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t472" href="#t472">472</a></span><span class="t">            <span class="nam">_</span><span class="op">,</span> <span class="nam">example_estimator</span><span class="op">[</span><span class="num">0</span><span class="op">]</span> <span class="op">=</span> <span class="nam">example_estimator</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="op">.</span><span class="nam">split</span><span class="op">(</span><span class="str">":"</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t473" href="#t473">473</a></span><span class="t">            <span class="nam">times</span> <span class="op">=</span> <span class="op">[</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t474" href="#t474">474</a></span><span class="t">                <span class="nam">float</span><span class="op">(</span><span class="nam">example_estimator</span><span class="op">[</span><span class="nam">i</span><span class="op">]</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t475" href="#t475">475</a></span><span class="t">                <span class="key">for</span> <span class="nam">i</span> <span class="key">in</span> <span class="nam">range</span><span class="op">(</span><span class="nam">len</span><span class="op">(</span><span class="nam">example_estimator</span><span class="op">)</span> <span class="op">-</span> <span class="num">1</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t476" href="#t476">476</a></span><span class="t">                <span class="key">if</span> <span class="nam">i</span> <span class="op">%</span> <span class="num">2</span> <span class="op">==</span> <span class="num">0</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t477" href="#t477">477</a></span><span class="t">            <span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t478" href="#t478">478</a></span><span class="t">            <span class="nam">probabilities</span> <span class="op">=</span> <span class="op">[</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t479" href="#t479">479</a></span><span class="t">                <span class="nam">float</span><span class="op">(</span><span class="nam">example_estimator</span><span class="op">[</span><span class="nam">i</span><span class="op">]</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t480" href="#t480">480</a></span><span class="t">                <span class="key">for</span> <span class="nam">i</span> <span class="key">in</span> <span class="nam">range</span><span class="op">(</span><span class="nam">len</span><span class="op">(</span><span class="nam">example_estimator</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t481" href="#t481">481</a></span><span class="t">                <span class="key">if</span> <span class="nam">i</span> <span class="op">%</span> <span class="num">2</span> <span class="op">!=</span> <span class="num">0</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t482" href="#t482">482</a></span><span class="t">            <span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t483" href="#t483">483</a></span><span class="t">            <span class="nam">estimator</span> <span class="op">=</span> <span class="op">{</span><span class="str">"times"</span><span class="op">:</span> <span class="nam">times</span><span class="op">,</span> <span class="str">"probabilities"</span><span class="op">:</span> <span class="nam">probabilities</span><span class="op">}</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t484" href="#t484">484</a></span><span class="t">            <span class="nam">estimators</span><span class="op">.</span><span class="nam">append</span><span class="op">(</span><span class="nam">estimator</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t485" href="#t485">485</a></span><span class="t">        <span class="key">return</span> <span class="nam">np</span><span class="op">.</span><span class="nam">array</span><span class="op">(</span><span class="nam">estimators</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t486" href="#t486">486</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t487" href="#t487">487</a></span><span class="t">    <span class="op">@</span><span class="nam">staticmethod</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t488" href="#t488">488</a></span><span class="t">    <span class="key">def</span> <span class="nam">_get_column_by_role</span><span class="op">(</span><span class="nam">predicted_example_set</span><span class="op">:</span> <span class="nam">JObject</span><span class="op">,</span> <span class="nam">role</span><span class="op">:</span> <span class="nam">str</span><span class="op">)</span> <span class="op">-></span> <span class="nam">JObject</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t489" href="#t489">489</a></span><span class="t">        <span class="key">return</span> <span class="nam">predicted_example_set</span><span class="op">.</span><span class="nam">getAttributes</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">getColumnByRole</span><span class="op">(</span><span class="nam">role</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t490" href="#t490">490</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t491" href="#t491">491</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t492" href="#t492">492</a></span><span class="t"><span class="key">class</span> <span class="nam">ModelSerializer</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t493" href="#t493">493</a></span><span class="t">    <span class="str">"""Class for serializing models"""</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t494" href="#t494">494</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t495" href="#t495">495</a></span><span class="t">    <span class="op">@</span><span class="nam">staticmethod</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t496" href="#t496">496</a></span><span class="t">    <span class="key">def</span> <span class="nam">serialize</span><span class="op">(</span><span class="nam">real_model</span><span class="op">:</span> <span class="nam">object</span><span class="op">)</span> <span class="op">-></span> <span class="nam">bytes</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t497" href="#t497">497</a></span><span class="t">        <span class="str">"""Serialize Java ruleset object.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t498" href="#t498">498</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t499" href="#t499">499</a></span><span class="t"><span class="str">        Args:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t500" href="#t500">500</a></span><span class="t"><span class="str">            real_model (object): Java ruleset object</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t501" href="#t501">501</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t502" href="#t502">502</a></span><span class="t">        <span class="nam">in_memory_file</span> <span class="op">=</span> <span class="nam">io</span><span class="op">.</span><span class="nam">BytesIO</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t503" href="#t503">503</a></span><span class="t">        <span class="nam">JPickler</span><span class="op">(</span><span class="nam">in_memory_file</span><span class="op">)</span><span class="op">.</span><span class="nam">dump</span><span class="op">(</span><span class="nam">real_model</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t504" href="#t504">504</a></span><span class="t">        <span class="nam">serialized_bytes</span> <span class="op">=</span> <span class="nam">in_memory_file</span><span class="op">.</span><span class="nam">getvalue</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t505" href="#t505">505</a></span><span class="t">        <span class="nam">in_memory_file</span><span class="op">.</span><span class="nam">close</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t506" href="#t506">506</a></span><span class="t">        <span class="key">return</span> <span class="nam">serialized_bytes</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t507" href="#t507">507</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t508" href="#t508">508</a></span><span class="t">    <span class="op">@</span><span class="nam">staticmethod</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t509" href="#t509">509</a></span><span class="t">    <span class="key">def</span> <span class="nam">deserialize</span><span class="op">(</span><span class="nam">serialized_bytes</span><span class="op">:</span> <span class="nam">bytes</span><span class="op">)</span> <span class="op">-></span> <span class="nam">object</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t510" href="#t510">510</a></span><span class="t">        <span class="str">"""Deserialize Java ruleset object from bytes.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t511" href="#t511">511</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t512" href="#t512">512</a></span><span class="t"><span class="str">        Args:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t513" href="#t513">513</a></span><span class="t"><span class="str">            serialized_bytes (bytes): serialized bytes</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t514" href="#t514">514</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t515" href="#t515">515</a></span><span class="t"><span class="str">        Returns:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t516" href="#t516">516</a></span><span class="t"><span class="str">            object: deserialized Java ruleset object</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t517" href="#t517">517</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t518" href="#t518">518</a></span><span class="t">        <span class="key">if</span> <span class="key">not</span> <span class="nam">RuleKit</span><span class="op">.</span><span class="nam">initialized</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t519" href="#t519">519</a></span><span class="t">            <span class="nam">RuleKit</span><span class="op">.</span><span class="nam">init</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t520" href="#t520">520</a></span><span class="t">        <span class="nam">in_memory_file</span> <span class="op">=</span> <span class="nam">io</span><span class="op">.</span><span class="nam">BytesIO</span><span class="op">(</span><span class="nam">serialized_bytes</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t521" href="#t521">521</a></span><span class="t">        <span class="nam">model</span> <span class="op">=</span> <span class="nam">JUnpickler</span><span class="op">(</span><span class="nam">in_memory_file</span><span class="op">)</span><span class="op">.</span><span class="nam">load</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t522" href="#t522">522</a></span><span class="t">        <span class="nam">in_memory_file</span><span class="op">.</span><span class="nam">close</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t523" href="#t523">523</a></span><span class="t">        <span class="key">return</span> <span class="nam">model</span>&nbsp;</span><span class="r"></span></p>
 </main>
 <footer>
     <div class="content">
@@ -575,7 +612,7 @@ <h2>
             <a class="nav" href="z_a87f2a4bb6695d91__logging_py.html">&#xbb; next</a>
             &nbsp; &nbsp; &nbsp;
             <a class="nav" href="https://coverage.readthedocs.io/en/7.6.4">coverage.py v7.6.4</a>,
-            created at 2024-11-08 14:43 +0100
+            created at 2024-11-28 12:20 +0100
         </p>
     </div>
 </footer>
diff --git a/docs/reports/coverage/z_a87f2a4bb6695d91__operator_py.html b/docs/reports/coverage/z_a87f2a4bb6695d91__operator_py.html
index 382d5c2..0af905c 100644
--- a/docs/reports/coverage/z_a87f2a4bb6695d91__operator_py.html
+++ b/docs/reports/coverage/z_a87f2a4bb6695d91__operator_py.html
@@ -2,7 +2,7 @@
 <html lang="en">
 <head>
     <meta http-equiv="Content-Type" content="text/html; charset=utf-8">
-    <title>Coverage for rulekit\_operator.py: 90%</title>
+    <title>Coverage for rulekit\_operator.py: 91%</title>
     <link rel="icon" sizes="32x32" href="favicon_32_cb_58284776.png">
     <link rel="stylesheet" href="style_cb_718ce007.css" type="text/css">
     <script src="coverage_html_cb_497bf287.js" defer></script>
@@ -12,7 +12,7 @@
     <div class="content">
         <h1>
             <span class="text">Coverage for </span><b>rulekit\_operator.py</b>:
-            <span class="pc_cov">90%</span>
+            <span class="pc_cov">91%</span>
         </h1>
         <aside id="help_panel_wrapper">
             <input id="help_panel_state" type="checkbox">
@@ -54,8 +54,8 @@ <h1>
             </div>
         </aside>
         <h2>
-            <span class="text">112 statements &nbsp;</span>
-            <button type="button" class="run button_toggle_run" value="run" data-shortcut="r" title="Toggle lines run">101<span class="text"> run</span></button>
+            <span class="text">121 statements &nbsp;</span>
+            <button type="button" class="run button_toggle_run" value="run" data-shortcut="r" title="Toggle lines run">110<span class="text"> run</span></button>
             <button type="button" class="mis show_mis button_toggle_mis" value="mis" data-shortcut="m" title="Toggle lines missing">11<span class="text"> missing</span></button>
             <button type="button" class="exc show_exc button_toggle_exc" value="exc" data-shortcut="x" title="Toggle lines excluded">0<span class="text"> excluded</span></button>
         </h2>
@@ -65,7 +65,7 @@ <h2>
             <a id="nextFileLink" class="nav" href="z_a87f2a4bb6695d91__problem_types_py.html">&#xbb; next</a>
             &nbsp; &nbsp; &nbsp;
             <a class="nav" href="https://coverage.readthedocs.io/en/7.6.4">coverage.py v7.6.4</a>,
-            created at 2024-11-08 14:43 +0100
+            created at 2024-11-28 11:55 +0100
         </p>
         <aside class="hidden">
             <button type="button" class="button_next_chunk" data-shortcut="j"></button>
@@ -84,271 +84,277 @@ <h2>
     <p class="pln"><span class="n"><a id="t2" href="#t2">2</a></span><span class="t"><span class="str">"""</span>&nbsp;</span><span class="r"></span></p>
     <p class="run"><span class="n"><a id="t3" href="#t3">3</a></span><span class="t"><span class="key">from</span> <span class="nam">__future__</span> <span class="key">import</span> <span class="nam">annotations</span>&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t4" href="#t4">4</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t5" href="#t5">5</a></span><span class="t"><span class="key">from</span> <span class="nam">abc</span> <span class="key">import</span> <span class="nam">ABC</span><span class="op">,</span> <span class="nam">abstractmethod</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t6" href="#t6">6</a></span><span class="t"><span class="key">from</span> <span class="nam">typing</span> <span class="key">import</span> <span class="nam">Any</span><span class="op">,</span> <span class="nam">Optional</span><span class="op">,</span> <span class="nam">Union</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t7" href="#t7">7</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t8" href="#t8">8</a></span><span class="t"><span class="key">import</span> <span class="nam">numpy</span> <span class="key">as</span> <span class="nam">np</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t9" href="#t9">9</a></span><span class="t"><span class="key">import</span> <span class="nam">pandas</span> <span class="key">as</span> <span class="nam">pd</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t10" href="#t10">10</a></span><span class="t"><span class="key">from</span> <span class="nam">pydantic</span> <span class="key">import</span> <span class="nam">BaseModel</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t11" href="#t11">11</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t12" href="#t12">12</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">_helpers</span> <span class="key">import</span> <span class="op">(</span><span class="nam">ExampleSetFactory</span><span class="op">,</span> <span class="nam">ModelSerializer</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t13" href="#t13">13</a></span><span class="t">                              <span class="nam">PredictionResultMapper</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t14" href="#t14">14</a></span><span class="t">                              <span class="nam">RuleGeneratorConfigurator</span><span class="op">,</span> <span class="nam">get_rule_generator</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t15" href="#t15">15</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">_problem_types</span> <span class="key">import</span> <span class="nam">ProblemType</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t16" href="#t16">16</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">events</span> <span class="key">import</span> <span class="op">(</span><span class="nam">RuleInductionProgressListener</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t17" href="#t17">17</a></span><span class="t">                            <span class="nam">command_listener_factory</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t18" href="#t18">18</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">main</span> <span class="key">import</span> <span class="nam">RuleKit</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t19" href="#t19">19</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">rules</span> <span class="key">import</span> <span class="nam">BaseRule</span><span class="op">,</span> <span class="nam">RuleSet</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t20" href="#t20">20</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t21" href="#t21">21</a></span><span class="t"><span class="nam">Data</span> <span class="op">=</span> <span class="nam">Union</span><span class="op">[</span><span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span><span class="op">,</span> <span class="nam">pd</span><span class="op">.</span><span class="nam">DataFrame</span><span class="op">,</span> <span class="nam">list</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t22" href="#t22">22</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t23" href="#t23">23</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t24" href="#t24">24</a></span><span class="t"><span class="key">class</span> <span class="nam">BaseOperator</span><span class="op">(</span><span class="nam">ABC</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t25" href="#t25">25</a></span><span class="t">    <span class="str">"""Base class for rule induction operator</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t26" href="#t26">26</a></span><span class="t"><span class="str">    """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t27" href="#t27">27</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t28" href="#t28">28</a></span><span class="t">    <span class="nam">__params_class__</span><span class="op">:</span> <span class="nam">type</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t5" href="#t5">5</a></span><span class="t"><span class="key">from</span> <span class="nam">abc</span> <span class="key">import</span> <span class="nam">ABC</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t6" href="#t6">6</a></span><span class="t"><span class="key">from</span> <span class="nam">abc</span> <span class="key">import</span> <span class="nam">abstractmethod</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t7" href="#t7">7</a></span><span class="t"><span class="key">from</span> <span class="nam">typing</span> <span class="key">import</span> <span class="nam">Any</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t8" href="#t8">8</a></span><span class="t"><span class="key">from</span> <span class="nam">typing</span> <span class="key">import</span> <span class="nam">Optional</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t9" href="#t9">9</a></span><span class="t"><span class="key">from</span> <span class="nam">typing</span> <span class="key">import</span> <span class="nam">Union</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t10" href="#t10">10</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t11" href="#t11">11</a></span><span class="t"><span class="key">import</span> <span class="nam">numpy</span> <span class="key">as</span> <span class="nam">np</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t12" href="#t12">12</a></span><span class="t"><span class="key">import</span> <span class="nam">pandas</span> <span class="key">as</span> <span class="nam">pd</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t13" href="#t13">13</a></span><span class="t"><span class="key">from</span> <span class="nam">pydantic</span> <span class="key">import</span> <span class="nam">BaseModel</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t14" href="#t14">14</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t15" href="#t15">15</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">_helpers</span> <span class="key">import</span> <span class="nam">ExampleSetFactory</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t16" href="#t16">16</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">_helpers</span> <span class="key">import</span> <span class="nam">get_rule_generator</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t17" href="#t17">17</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">_helpers</span> <span class="key">import</span> <span class="nam">ModelSerializer</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t18" href="#t18">18</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">_helpers</span> <span class="key">import</span> <span class="nam">PredictionResultMapper</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t19" href="#t19">19</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">_helpers</span> <span class="key">import</span> <span class="nam">RuleGeneratorConfigurator</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t20" href="#t20">20</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">_problem_types</span> <span class="key">import</span> <span class="nam">ProblemType</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t21" href="#t21">21</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">events</span> <span class="key">import</span> <span class="nam">_command_listener_factory</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t22" href="#t22">22</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">events</span> <span class="key">import</span> <span class="nam">RuleInductionProgressListener</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t23" href="#t23">23</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">main</span> <span class="key">import</span> <span class="nam">RuleKit</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t24" href="#t24">24</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">rules</span> <span class="key">import</span> <span class="nam">BaseRule</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t25" href="#t25">25</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">rules</span> <span class="key">import</span> <span class="nam">RuleSet</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t26" href="#t26">26</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t27" href="#t27">27</a></span><span class="t"><span class="nam">Data</span> <span class="op">=</span> <span class="nam">Union</span><span class="op">[</span><span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span><span class="op">,</span> <span class="nam">pd</span><span class="op">.</span><span class="nam">DataFrame</span><span class="op">,</span> <span class="nam">list</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t28" href="#t28">28</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t29" href="#t29">29</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t30" href="#t30">30</a></span><span class="t">    <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="op">**</span><span class="nam">kwargs</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t31" href="#t31">31</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_initialize_rulekit</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t32" href="#t32">32</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_params</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t33" href="#t33">33</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_rule_generator</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t34" href="#t34">34</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">set_params</span><span class="op">(</span><span class="op">**</span><span class="nam">kwargs</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t35" href="#t35">35</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">model</span><span class="op">:</span> <span class="nam">RuleSet</span><span class="op">[</span><span class="nam">BaseRule</span><span class="op">]</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t36" href="#t36">36</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t37" href="#t37">37</a></span><span class="t">    <span class="key">def</span> <span class="nam">_initialize_rulekit</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t38" href="#t38">38</a></span><span class="t">        <span class="key">if</span> <span class="key">not</span> <span class="nam">RuleKit</span><span class="op">.</span><span class="nam">initialized</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t39" href="#t39">39</a></span><span class="t">            <span class="nam">RuleKit</span><span class="op">.</span><span class="nam">init</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t40" href="#t40">40</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t41" href="#t41">41</a></span><span class="t">    <span class="key">def</span> <span class="nam">_map_result</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">predicted_example_set</span><span class="op">)</span> <span class="op">-></span> <span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t42" href="#t42">42</a></span><span class="t">        <span class="key">return</span> <span class="nam">PredictionResultMapper</span><span class="op">.</span><span class="nam">map</span><span class="op">(</span><span class="nam">predicted_example_set</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t43" href="#t43">43</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t44" href="#t44">44</a></span><span class="t">    <span class="key">def</span> <span class="nam">_validate_contrast_attribute</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t45" href="#t45">45</a></span><span class="t">        <span class="nam">self</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t46" href="#t46">46</a></span><span class="t">        <span class="nam">example_set</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t47" href="#t47">47</a></span><span class="t">        <span class="nam">contrast_attribute</span><span class="op">:</span> <span class="nam">Optional</span><span class="op">[</span><span class="nam">str</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t48" href="#t48">48</a></span><span class="t">    <span class="op">)</span> <span class="op">-></span> <span class="key">None</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t49" href="#t49">49</a></span><span class="t">        <span class="key">if</span> <span class="nam">contrast_attribute</span> <span class="key">is</span> <span class="key">None</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t50" href="#t50">50</a></span><span class="t">            <span class="key">return</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t51" href="#t51">51</a></span><span class="t">        <span class="nam">contrast_attribute_instance</span> <span class="op">=</span> <span class="nam">example_set</span><span class="op">.</span><span class="nam">getAttributes</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">get</span><span class="op">(</span><span class="nam">contrast_attribute</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t52" href="#t52">52</a></span><span class="t">        <span class="key">if</span> <span class="nam">contrast_attribute_instance</span><span class="op">.</span><span class="nam">isNumerical</span><span class="op">(</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t53" href="#t53">53</a></span><span class="t">            <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t54" href="#t54">54</a></span><span class="t">                <span class="str">'Contrast set attributes must be a nominal attribute while '</span> <span class="op">+</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t55" href="#t55">55</a></span><span class="t">                <span class="str">f'"{contrast_attribute}" is a numerical one.'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t56" href="#t56">56</a></span><span class="t">            <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t57" href="#t57">57</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t58" href="#t58">58</a></span><span class="t">    <span class="key">def</span> <span class="nam">fit</span><span class="op">(</span>  <span class="com"># pylint: disable=missing-function-docstring</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t59" href="#t59">59</a></span><span class="t">        <span class="nam">self</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t60" href="#t60">60</a></span><span class="t">        <span class="nam">values</span><span class="op">:</span> <span class="nam">Data</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t61" href="#t61">61</a></span><span class="t">        <span class="nam">labels</span><span class="op">:</span> <span class="nam">Data</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t62" href="#t62">62</a></span><span class="t">        <span class="nam">survival_time_attribute</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="key">None</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t63" href="#t63">63</a></span><span class="t">        <span class="nam">contrast_attribute</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="key">None</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t64" href="#t64">64</a></span><span class="t">    <span class="op">)</span> <span class="op">-></span> <span class="nam">BaseOperator</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t65" href="#t65">65</a></span><span class="t">        <span class="nam">example_set</span> <span class="op">=</span> <span class="nam">ExampleSetFactory</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">_get_problem_type</span><span class="op">(</span><span class="op">)</span><span class="op">)</span><span class="op">.</span><span class="nam">make</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t66" href="#t66">66</a></span><span class="t">            <span class="nam">values</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t67" href="#t67">67</a></span><span class="t">            <span class="nam">labels</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t68" href="#t68">68</a></span><span class="t">            <span class="nam">survival_time_attribute</span><span class="op">=</span><span class="nam">survival_time_attribute</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t69" href="#t69">69</a></span><span class="t">            <span class="nam">contrast_attribute</span><span class="op">=</span><span class="nam">contrast_attribute</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t70" href="#t70">70</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t71" href="#t71">71</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_validate_contrast_attribute</span><span class="op">(</span><span class="nam">example_set</span><span class="op">,</span> <span class="nam">contrast_attribute</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t72" href="#t72">72</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t73" href="#t73">73</a></span><span class="t">        <span class="nam">java_model</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_rule_generator</span><span class="op">.</span><span class="nam">learn</span><span class="op">(</span><span class="nam">example_set</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t74" href="#t74">74</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">model</span> <span class="op">=</span> <span class="nam">RuleSet</span><span class="op">[</span><span class="nam">BaseRule</span><span class="op">]</span><span class="op">(</span><span class="nam">java_model</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t75" href="#t75">75</a></span><span class="t">        <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">model</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t76" href="#t76">76</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t77" href="#t77">77</a></span><span class="t">    <span class="key">def</span> <span class="nam">predict</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">values</span><span class="op">:</span> <span class="nam">Data</span><span class="op">)</span> <span class="op">-></span> <span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span><span class="op">:</span>  <span class="com"># pylint: disable=missing-function-docstring</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t78" href="#t78">78</a></span><span class="t">        <span class="key">if</span> <span class="nam">self</span><span class="op">.</span><span class="nam">model</span> <span class="key">is</span> <span class="key">None</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t79" href="#t79">79</a></span><span class="t">            <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t80" href="#t80">80</a></span><span class="t">                <span class="str">'"fit" method must be called before calling this method'</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t81" href="#t81">81</a></span><span class="t">        <span class="nam">example_set</span> <span class="op">=</span> <span class="nam">ExampleSetFactory</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">_get_problem_type</span><span class="op">(</span><span class="op">)</span><span class="op">)</span><span class="op">.</span><span class="nam">make</span><span class="op">(</span><span class="nam">values</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t82" href="#t82">82</a></span><span class="t">        <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">model</span><span class="op">.</span><span class="nam">_java_object</span><span class="op">.</span><span class="nam">apply</span><span class="op">(</span><span class="nam">example_set</span><span class="op">)</span>  <span class="com"># pylint: disable=protected-access</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t83" href="#t83">83</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t84" href="#t84">84</a></span><span class="t">    <span class="key">def</span> <span class="nam">get_params</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">deep</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="key">True</span><span class="op">)</span> <span class="op">-></span> <span class="nam">dict</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">Any</span><span class="op">]</span><span class="op">:</span>  <span class="com"># pylint: disable=unused-argument</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t85" href="#t85">85</a></span><span class="t">        <span class="str">"""</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t86" href="#t86">86</a></span><span class="t"><span class="str">        Parameters</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t87" href="#t87">87</a></span><span class="t"><span class="str">        ----------</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t88" href="#t88">88</a></span><span class="t"><span class="str">        deep : :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t89" href="#t89">89</a></span><span class="t"><span class="str">            Parameter for scikit-learn compatibility. Not used.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t90" href="#t90">90</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t91" href="#t91">91</a></span><span class="t"><span class="str">        Returns</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t92" href="#t92">92</a></span><span class="t"><span class="str">        -------</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t93" href="#t93">93</a></span><span class="t"><span class="str">        hyperparameters : np.ndarray</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t94" href="#t94">94</a></span><span class="t"><span class="str">            Dictionary containing model hyperparameters.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t95" href="#t95">95</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t96" href="#t96">96</a></span><span class="t">        <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_params</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t97" href="#t97">97</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t98" href="#t98">98</a></span><span class="t">    <span class="key">def</span> <span class="nam">set_params</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="op">**</span><span class="nam">kwargs</span><span class="op">)</span> <span class="op">-></span> <span class="nam">object</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t99" href="#t99">99</a></span><span class="t">        <span class="str">"""Set models hyperparameters. Parameters are the same as in constructor."""</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t100" href="#t100">100</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_rule_generator</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_get_rule_generator</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t101" href="#t101">101</a></span><span class="t">        <span class="nam">params</span><span class="op">:</span> <span class="nam">BaseModel</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">__params_class__</span><span class="op">(</span>  <span class="com"># pylint: disable=not-callable</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t102" href="#t102">102</a></span><span class="t">            <span class="op">**</span><span class="nam">kwargs</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t103" href="#t103">103</a></span><span class="t">        <span class="nam">params_dict</span><span class="op">:</span> <span class="nam">dict</span> <span class="op">=</span> <span class="nam">params</span><span class="op">.</span><span class="nam">model_dump</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t104" href="#t104">104</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_params</span> <span class="op">=</span> <span class="op">{</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t105" href="#t105">105</a></span><span class="t">            <span class="nam">key</span><span class="op">:</span> <span class="nam">value</span> <span class="key">for</span> <span class="nam">key</span><span class="op">,</span> <span class="nam">value</span> <span class="key">in</span> <span class="nam">params_dict</span><span class="op">.</span><span class="nam">items</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t106" href="#t106">106</a></span><span class="t">            <span class="key">if</span> <span class="nam">value</span> <span class="key">is</span> <span class="key">not</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t107" href="#t107">107</a></span><span class="t">        <span class="op">}</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t108" href="#t108">108</a></span><span class="t">        <span class="nam">configurator</span> <span class="op">=</span> <span class="nam">RuleGeneratorConfigurator</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">_rule_generator</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t109" href="#t109">109</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_rule_generator</span> <span class="op">=</span> <span class="nam">configurator</span><span class="op">.</span><span class="nam">configure</span><span class="op">(</span><span class="op">**</span><span class="nam">params_dict</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t110" href="#t110">110</a></span><span class="t">        <span class="key">return</span> <span class="nam">self</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t111" href="#t111">111</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t112" href="#t112">112</a></span><span class="t">    <span class="key">def</span> <span class="nam">get_metadata_routing</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="key">None</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t113" href="#t113">113</a></span><span class="t">        <span class="str">"""</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t114" href="#t114">114</a></span><span class="t"><span class="str">        .. warning:: Scikit-learn metadata routing is not supported yet.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t115" href="#t115">115</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t116" href="#t116">116</a></span><span class="t"><span class="str">        Raises:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t117" href="#t117">117</a></span><span class="t"><span class="str">            NotImplementedError: _description_</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t118" href="#t118">118</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t119" href="#t119">119</a></span><span class="t">        <span class="key">raise</span> <span class="nam">NotImplementedError</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t120" href="#t120">120</a></span><span class="t">            <span class="str">'Scikit-learn metadata routing is not supported yet.'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t121" href="#t121">121</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t122" href="#t122">122</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t123" href="#t123">123</a></span><span class="t">    <span class="key">def</span> <span class="nam">get_coverage_matrix</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">values</span><span class="op">:</span> <span class="nam">Data</span><span class="op">)</span> <span class="op">-></span> <span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t124" href="#t124">124</a></span><span class="t">        <span class="str">"""Calculates coverage matrix for ruleset.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t125" href="#t125">125</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t126" href="#t126">126</a></span><span class="t"><span class="str">        Parameters</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t127" href="#t127">127</a></span><span class="t"><span class="str">        ----------</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t128" href="#t128">128</a></span><span class="t"><span class="str">        values : :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t129" href="#t129">129</a></span><span class="t"><span class="str">            dataset</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t130" href="#t130">130</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t131" href="#t131">131</a></span><span class="t"><span class="str">        Returns</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t132" href="#t132">132</a></span><span class="t"><span class="str">        -------</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t133" href="#t133">133</a></span><span class="t"><span class="str">        coverage_matrix : np.ndarray</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t134" href="#t134">134</a></span><span class="t"><span class="str">            Each row of the matrix represent single example from dataset and every column represent</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t135" href="#t135">135</a></span><span class="t"><span class="str">            on rule from rule set. Value 1 in the matrix cell means that rule covered certain</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t136" href="#t136">136</a></span><span class="t"><span class="str">             example, value 0 means that it doesn't.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t137" href="#t137">137</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t138" href="#t138">138</a></span><span class="t">        <span class="key">if</span> <span class="nam">self</span><span class="op">.</span><span class="nam">model</span> <span class="key">is</span> <span class="key">None</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t139" href="#t139">139</a></span><span class="t">            <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t140" href="#t140">140</a></span><span class="t">                <span class="str">'"fit" method must be called before calling this method'</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t141" href="#t141">141</a></span><span class="t">        <span class="nam">example_set</span> <span class="op">=</span> <span class="nam">ExampleSetFactory</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">_get_problem_type</span><span class="op">(</span><span class="op">)</span><span class="op">)</span><span class="op">.</span><span class="nam">make</span><span class="op">(</span><span class="nam">values</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t142" href="#t142">142</a></span><span class="t">        <span class="nam">covering_info</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">model</span><span class="op">.</span><span class="nam">covering</span><span class="op">(</span><span class="nam">example_set</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t143" href="#t143">143</a></span><span class="t">        <span class="key">if</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">values</span><span class="op">,</span> <span class="op">(</span><span class="nam">pd</span><span class="op">.</span><span class="nam">Series</span><span class="op">,</span> <span class="nam">pd</span><span class="op">.</span><span class="nam">DataFrame</span><span class="op">)</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t144" href="#t144">144</a></span><span class="t">            <span class="nam">values</span> <span class="op">=</span> <span class="nam">values</span><span class="op">.</span><span class="nam">to_numpy</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t145" href="#t145">145</a></span><span class="t">        <span class="nam">result</span> <span class="op">=</span> <span class="op">[</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t146" href="#t146">146</a></span><span class="t">        <span class="key">for</span> <span class="nam">i</span> <span class="key">in</span> <span class="nam">range</span><span class="op">(</span><span class="nam">len</span><span class="op">(</span><span class="nam">values</span><span class="op">)</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t147" href="#t147">147</a></span><span class="t">            <span class="nam">row_result</span><span class="op">:</span> <span class="nam">list</span><span class="op">[</span><span class="nam">int</span><span class="op">]</span> <span class="op">=</span> <span class="op">[</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t148" href="#t148">148</a></span><span class="t">                <span class="num">0</span> <span class="key">if</span> <span class="nam">item</span> <span class="key">is</span> <span class="key">None</span> <span class="key">or</span> <span class="key">not</span> <span class="nam">i</span> <span class="key">in</span> <span class="nam">item</span> <span class="key">else</span> <span class="num">1</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t149" href="#t149">149</a></span><span class="t">                <span class="key">for</span> <span class="nam">item</span> <span class="key">in</span> <span class="nam">covering_info</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t150" href="#t150">150</a></span><span class="t">            <span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t151" href="#t151">151</a></span><span class="t">            <span class="nam">result</span><span class="op">.</span><span class="nam">append</span><span class="op">(</span><span class="nam">np</span><span class="op">.</span><span class="nam">array</span><span class="op">(</span><span class="nam">row_result</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t152" href="#t152">152</a></span><span class="t">        <span class="key">return</span> <span class="nam">np</span><span class="op">.</span><span class="nam">array</span><span class="op">(</span><span class="nam">result</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t153" href="#t153">153</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t154" href="#t154">154</a></span><span class="t">    <span class="key">def</span> <span class="nam">add_event_listener</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">listener</span><span class="op">:</span> <span class="nam">RuleInductionProgressListener</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t155" href="#t155">155</a></span><span class="t">        <span class="str">"""Add event listener object to the operator which allows to monitor</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t156" href="#t156">156</a></span><span class="t"><span class="str">         rule induction progress.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t157" href="#t157">157</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t158" href="#t158">158</a></span><span class="t"><span class="str">        Example:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t159" href="#t159">159</a></span><span class="t"><span class="str">            >>> from rulekit.events import RuleInductionProgressListener</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t160" href="#t160">160</a></span><span class="t"><span class="str">            >>> from rulekit.classification import RuleClassifier</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t161" href="#t161">161</a></span><span class="t"><span class="str">            >>></span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t162" href="#t162">162</a></span><span class="t"><span class="str">            >>> class MyEventListener(RuleInductionProgressListener):</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t163" href="#t163">163</a></span><span class="t"><span class="str">            >>>     def on_new_rule(self, rule):</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t164" href="#t164">164</a></span><span class="t"><span class="str">            >>>         print('Do something with new rule', rule)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t165" href="#t165">165</a></span><span class="t"><span class="str">            >>></span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t166" href="#t166">166</a></span><span class="t"><span class="str">            >>> operator = RuleClassifier()</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t167" href="#t167">167</a></span><span class="t"><span class="str">            >>> operator.add_event_listener(MyEventListener())</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t168" href="#t168">168</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t169" href="#t169">169</a></span><span class="t"><span class="str">        Args:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t170" href="#t170">170</a></span><span class="t"><span class="str">            listener (RuleInductionProgressListener): listener object</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t171" href="#t171">171</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t172" href="#t172">172</a></span><span class="t">        <span class="nam">command_listener</span> <span class="op">=</span> <span class="nam">command_listener_factory</span><span class="op">(</span><span class="nam">listener</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t173" href="#t173">173</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_rule_generator</span><span class="op">.</span><span class="nam">addOperatorListener</span><span class="op">(</span><span class="nam">command_listener</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t30" href="#t30">30</a></span><span class="t"><span class="key">class</span> <span class="nam">BaseOperator</span><span class="op">(</span><span class="nam">ABC</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t31" href="#t31">31</a></span><span class="t">    <span class="str">"""Base class for rule induction operator</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t32" href="#t32">32</a></span><span class="t"><span class="str">    """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t33" href="#t33">33</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t34" href="#t34">34</a></span><span class="t">    <span class="nam">__params_class__</span><span class="op">:</span> <span class="nam">type</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t35" href="#t35">35</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t36" href="#t36">36</a></span><span class="t">    <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="op">**</span><span class="nam">kwargs</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t37" href="#t37">37</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_initialize_rulekit</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t38" href="#t38">38</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_params</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t39" href="#t39">39</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_rule_generator</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t40" href="#t40">40</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">set_params</span><span class="op">(</span><span class="op">**</span><span class="nam">kwargs</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t41" href="#t41">41</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">model</span><span class="op">:</span> <span class="nam">RuleSet</span><span class="op">[</span><span class="nam">BaseRule</span><span class="op">]</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t42" href="#t42">42</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t43" href="#t43">43</a></span><span class="t">    <span class="key">def</span> <span class="nam">_initialize_rulekit</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t44" href="#t44">44</a></span><span class="t">        <span class="key">if</span> <span class="key">not</span> <span class="nam">RuleKit</span><span class="op">.</span><span class="nam">initialized</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t45" href="#t45">45</a></span><span class="t">            <span class="nam">RuleKit</span><span class="op">.</span><span class="nam">init</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t46" href="#t46">46</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t47" href="#t47">47</a></span><span class="t">    <span class="key">def</span> <span class="nam">_map_result</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">predicted_example_set</span><span class="op">)</span> <span class="op">-></span> <span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t48" href="#t48">48</a></span><span class="t">        <span class="key">return</span> <span class="nam">PredictionResultMapper</span><span class="op">.</span><span class="nam">map</span><span class="op">(</span><span class="nam">predicted_example_set</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t49" href="#t49">49</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t50" href="#t50">50</a></span><span class="t">    <span class="key">def</span> <span class="nam">_validate_contrast_attribute</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t51" href="#t51">51</a></span><span class="t">        <span class="nam">self</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t52" href="#t52">52</a></span><span class="t">        <span class="nam">example_set</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t53" href="#t53">53</a></span><span class="t">        <span class="nam">contrast_attribute</span><span class="op">:</span> <span class="nam">Optional</span><span class="op">[</span><span class="nam">str</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t54" href="#t54">54</a></span><span class="t">    <span class="op">)</span> <span class="op">-></span> <span class="key">None</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t55" href="#t55">55</a></span><span class="t">        <span class="key">if</span> <span class="nam">contrast_attribute</span> <span class="key">is</span> <span class="key">None</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t56" href="#t56">56</a></span><span class="t">            <span class="key">return</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t57" href="#t57">57</a></span><span class="t">        <span class="nam">contrast_attribute_instance</span> <span class="op">=</span> <span class="nam">example_set</span><span class="op">.</span><span class="nam">getAttributes</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">get</span><span class="op">(</span><span class="nam">contrast_attribute</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t58" href="#t58">58</a></span><span class="t">        <span class="key">if</span> <span class="nam">contrast_attribute_instance</span><span class="op">.</span><span class="nam">isNumerical</span><span class="op">(</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t59" href="#t59">59</a></span><span class="t">            <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t60" href="#t60">60</a></span><span class="t">                <span class="str">'Contrast set attributes must be a nominal attribute while '</span> <span class="op">+</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t61" href="#t61">61</a></span><span class="t">                <span class="str">f'"{contrast_attribute}" is a numerical one.'</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t62" href="#t62">62</a></span><span class="t">            <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t63" href="#t63">63</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t64" href="#t64">64</a></span><span class="t">    <span class="key">def</span> <span class="nam">fit</span><span class="op">(</span>  <span class="com"># pylint: disable=missing-function-docstring</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t65" href="#t65">65</a></span><span class="t">        <span class="nam">self</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t66" href="#t66">66</a></span><span class="t">        <span class="nam">values</span><span class="op">:</span> <span class="nam">Data</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t67" href="#t67">67</a></span><span class="t">        <span class="nam">labels</span><span class="op">:</span> <span class="nam">Data</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t68" href="#t68">68</a></span><span class="t">        <span class="nam">survival_time_attribute</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="key">None</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t69" href="#t69">69</a></span><span class="t">        <span class="nam">contrast_attribute</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="key">None</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t70" href="#t70">70</a></span><span class="t">    <span class="op">)</span> <span class="op">-></span> <span class="nam">BaseOperator</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t71" href="#t71">71</a></span><span class="t">        <span class="nam">example_set</span> <span class="op">=</span> <span class="nam">ExampleSetFactory</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">_get_problem_type</span><span class="op">(</span><span class="op">)</span><span class="op">)</span><span class="op">.</span><span class="nam">make</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t72" href="#t72">72</a></span><span class="t">            <span class="nam">values</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t73" href="#t73">73</a></span><span class="t">            <span class="nam">labels</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t74" href="#t74">74</a></span><span class="t">            <span class="nam">survival_time_attribute</span><span class="op">=</span><span class="nam">survival_time_attribute</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t75" href="#t75">75</a></span><span class="t">            <span class="nam">contrast_attribute</span><span class="op">=</span><span class="nam">contrast_attribute</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t76" href="#t76">76</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t77" href="#t77">77</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_validate_contrast_attribute</span><span class="op">(</span><span class="nam">example_set</span><span class="op">,</span> <span class="nam">contrast_attribute</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t78" href="#t78">78</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t79" href="#t79">79</a></span><span class="t">        <span class="nam">java_model</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_rule_generator</span><span class="op">.</span><span class="nam">learn</span><span class="op">(</span><span class="nam">example_set</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t80" href="#t80">80</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">model</span> <span class="op">=</span> <span class="nam">RuleSet</span><span class="op">[</span><span class="nam">BaseRule</span><span class="op">]</span><span class="op">(</span><span class="nam">java_model</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t81" href="#t81">81</a></span><span class="t">        <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">model</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t82" href="#t82">82</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t83" href="#t83">83</a></span><span class="t">    <span class="key">def</span> <span class="nam">predict</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">values</span><span class="op">:</span> <span class="nam">Data</span><span class="op">)</span> <span class="op">-></span> <span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span><span class="op">:</span>  <span class="com"># pylint: disable=missing-function-docstring</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t84" href="#t84">84</a></span><span class="t">        <span class="key">if</span> <span class="nam">self</span><span class="op">.</span><span class="nam">model</span> <span class="key">is</span> <span class="key">None</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t85" href="#t85">85</a></span><span class="t">            <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t86" href="#t86">86</a></span><span class="t">                <span class="str">'"fit" method must be called before calling this method'</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t87" href="#t87">87</a></span><span class="t">        <span class="nam">example_set</span> <span class="op">=</span> <span class="nam">ExampleSetFactory</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">_get_problem_type</span><span class="op">(</span><span class="op">)</span><span class="op">)</span><span class="op">.</span><span class="nam">make</span><span class="op">(</span><span class="nam">values</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t88" href="#t88">88</a></span><span class="t">        <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">model</span><span class="op">.</span><span class="nam">_java_object</span><span class="op">.</span><span class="nam">apply</span><span class="op">(</span><span class="nam">example_set</span><span class="op">)</span>  <span class="com"># pylint: disable=protected-access</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t89" href="#t89">89</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t90" href="#t90">90</a></span><span class="t">    <span class="key">def</span> <span class="nam">get_params</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">deep</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="key">True</span><span class="op">)</span> <span class="op">-></span> <span class="nam">dict</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">Any</span><span class="op">]</span><span class="op">:</span>  <span class="com"># pylint: disable=unused-argument</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t91" href="#t91">91</a></span><span class="t">        <span class="str">"""</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t92" href="#t92">92</a></span><span class="t"><span class="str">        Parameters</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t93" href="#t93">93</a></span><span class="t"><span class="str">        ----------</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t94" href="#t94">94</a></span><span class="t"><span class="str">        deep : :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t95" href="#t95">95</a></span><span class="t"><span class="str">            Parameter for scikit-learn compatibility. Not used.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t96" href="#t96">96</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t97" href="#t97">97</a></span><span class="t"><span class="str">        Returns</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t98" href="#t98">98</a></span><span class="t"><span class="str">        -------</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t99" href="#t99">99</a></span><span class="t"><span class="str">        hyperparameters : np.ndarray</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t100" href="#t100">100</a></span><span class="t"><span class="str">            Dictionary containing model hyperparameters.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t101" href="#t101">101</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t102" href="#t102">102</a></span><span class="t">        <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_params</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t103" href="#t103">103</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t104" href="#t104">104</a></span><span class="t">    <span class="key">def</span> <span class="nam">set_params</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="op">**</span><span class="nam">kwargs</span><span class="op">)</span> <span class="op">-></span> <span class="nam">object</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t105" href="#t105">105</a></span><span class="t">        <span class="str">"""Set models hyperparameters. Parameters are the same as in constructor."""</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t106" href="#t106">106</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_rule_generator</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_get_rule_generator</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t107" href="#t107">107</a></span><span class="t">        <span class="nam">params</span><span class="op">:</span> <span class="nam">BaseModel</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">__params_class__</span><span class="op">(</span>  <span class="com"># pylint: disable=not-callable</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t108" href="#t108">108</a></span><span class="t">            <span class="op">**</span><span class="nam">kwargs</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t109" href="#t109">109</a></span><span class="t">        <span class="nam">params_dict</span><span class="op">:</span> <span class="nam">dict</span> <span class="op">=</span> <span class="nam">params</span><span class="op">.</span><span class="nam">model_dump</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t110" href="#t110">110</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_params</span> <span class="op">=</span> <span class="op">{</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t111" href="#t111">111</a></span><span class="t">            <span class="nam">key</span><span class="op">:</span> <span class="nam">value</span> <span class="key">for</span> <span class="nam">key</span><span class="op">,</span> <span class="nam">value</span> <span class="key">in</span> <span class="nam">params_dict</span><span class="op">.</span><span class="nam">items</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t112" href="#t112">112</a></span><span class="t">            <span class="key">if</span> <span class="nam">value</span> <span class="key">is</span> <span class="key">not</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t113" href="#t113">113</a></span><span class="t">        <span class="op">}</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t114" href="#t114">114</a></span><span class="t">        <span class="nam">configurator</span> <span class="op">=</span> <span class="nam">RuleGeneratorConfigurator</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">_rule_generator</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t115" href="#t115">115</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_rule_generator</span> <span class="op">=</span> <span class="nam">configurator</span><span class="op">.</span><span class="nam">configure</span><span class="op">(</span><span class="op">**</span><span class="nam">params_dict</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t116" href="#t116">116</a></span><span class="t">        <span class="key">return</span> <span class="nam">self</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t117" href="#t117">117</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t118" href="#t118">118</a></span><span class="t">    <span class="key">def</span> <span class="nam">get_metadata_routing</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="key">None</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t119" href="#t119">119</a></span><span class="t">        <span class="str">"""</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t120" href="#t120">120</a></span><span class="t"><span class="str">        .. warning:: Scikit-learn metadata routing is not supported yet.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t121" href="#t121">121</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t122" href="#t122">122</a></span><span class="t"><span class="str">        Raises:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t123" href="#t123">123</a></span><span class="t"><span class="str">            NotImplementedError: _description_</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t124" href="#t124">124</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t125" href="#t125">125</a></span><span class="t">        <span class="key">raise</span> <span class="nam">NotImplementedError</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t126" href="#t126">126</a></span><span class="t">            <span class="str">'Scikit-learn metadata routing is not supported yet.'</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t127" href="#t127">127</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t128" href="#t128">128</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t129" href="#t129">129</a></span><span class="t">    <span class="key">def</span> <span class="nam">get_coverage_matrix</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">values</span><span class="op">:</span> <span class="nam">Data</span><span class="op">)</span> <span class="op">-></span> <span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t130" href="#t130">130</a></span><span class="t">        <span class="str">"""Calculates coverage matrix for ruleset.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t131" href="#t131">131</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t132" href="#t132">132</a></span><span class="t"><span class="str">        Parameters</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t133" href="#t133">133</a></span><span class="t"><span class="str">        ----------</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t134" href="#t134">134</a></span><span class="t"><span class="str">        values : :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t135" href="#t135">135</a></span><span class="t"><span class="str">            dataset</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t136" href="#t136">136</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t137" href="#t137">137</a></span><span class="t"><span class="str">        Returns</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t138" href="#t138">138</a></span><span class="t"><span class="str">        -------</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t139" href="#t139">139</a></span><span class="t"><span class="str">        coverage_matrix : np.ndarray</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t140" href="#t140">140</a></span><span class="t"><span class="str">            Each row of the matrix represent single example from dataset and every column represent</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t141" href="#t141">141</a></span><span class="t"><span class="str">            on rule from rule set. Value 1 in the matrix cell means that rule covered certain</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t142" href="#t142">142</a></span><span class="t"><span class="str">             example, value 0 means that it doesn't.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t143" href="#t143">143</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t144" href="#t144">144</a></span><span class="t">        <span class="key">if</span> <span class="nam">self</span><span class="op">.</span><span class="nam">model</span> <span class="key">is</span> <span class="key">None</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t145" href="#t145">145</a></span><span class="t">            <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t146" href="#t146">146</a></span><span class="t">                <span class="str">'"fit" method must be called before calling this method'</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t147" href="#t147">147</a></span><span class="t">        <span class="nam">example_set</span> <span class="op">=</span> <span class="nam">ExampleSetFactory</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">_get_problem_type</span><span class="op">(</span><span class="op">)</span><span class="op">)</span><span class="op">.</span><span class="nam">make</span><span class="op">(</span><span class="nam">values</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t148" href="#t148">148</a></span><span class="t">        <span class="nam">covering_info</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">model</span><span class="op">.</span><span class="nam">covering</span><span class="op">(</span><span class="nam">example_set</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t149" href="#t149">149</a></span><span class="t">        <span class="key">if</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">values</span><span class="op">,</span> <span class="op">(</span><span class="nam">pd</span><span class="op">.</span><span class="nam">Series</span><span class="op">,</span> <span class="nam">pd</span><span class="op">.</span><span class="nam">DataFrame</span><span class="op">)</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t150" href="#t150">150</a></span><span class="t">            <span class="nam">values</span> <span class="op">=</span> <span class="nam">values</span><span class="op">.</span><span class="nam">to_numpy</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t151" href="#t151">151</a></span><span class="t">        <span class="nam">result</span> <span class="op">=</span> <span class="op">[</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t152" href="#t152">152</a></span><span class="t">        <span class="key">for</span> <span class="nam">i</span> <span class="key">in</span> <span class="nam">range</span><span class="op">(</span><span class="nam">len</span><span class="op">(</span><span class="nam">values</span><span class="op">)</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t153" href="#t153">153</a></span><span class="t">            <span class="nam">row_result</span><span class="op">:</span> <span class="nam">list</span><span class="op">[</span><span class="nam">int</span><span class="op">]</span> <span class="op">=</span> <span class="op">[</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t154" href="#t154">154</a></span><span class="t">                <span class="num">0</span> <span class="key">if</span> <span class="nam">item</span> <span class="key">is</span> <span class="key">None</span> <span class="key">or</span> <span class="key">not</span> <span class="nam">i</span> <span class="key">in</span> <span class="nam">item</span> <span class="key">else</span> <span class="num">1</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t155" href="#t155">155</a></span><span class="t">                <span class="key">for</span> <span class="nam">item</span> <span class="key">in</span> <span class="nam">covering_info</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t156" href="#t156">156</a></span><span class="t">            <span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t157" href="#t157">157</a></span><span class="t">            <span class="nam">result</span><span class="op">.</span><span class="nam">append</span><span class="op">(</span><span class="nam">np</span><span class="op">.</span><span class="nam">array</span><span class="op">(</span><span class="nam">row_result</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t158" href="#t158">158</a></span><span class="t">        <span class="key">return</span> <span class="nam">np</span><span class="op">.</span><span class="nam">array</span><span class="op">(</span><span class="nam">result</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t159" href="#t159">159</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t160" href="#t160">160</a></span><span class="t">    <span class="key">def</span> <span class="nam">add_event_listener</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">listener</span><span class="op">:</span> <span class="nam">RuleInductionProgressListener</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t161" href="#t161">161</a></span><span class="t">        <span class="str">"""Add event listener object to the operator which allows to monitor</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t162" href="#t162">162</a></span><span class="t"><span class="str">         rule induction progress.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t163" href="#t163">163</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t164" href="#t164">164</a></span><span class="t"><span class="str">        Example:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t165" href="#t165">165</a></span><span class="t"><span class="str">            >>> from rulekit.events import RuleInductionProgressListener</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t166" href="#t166">166</a></span><span class="t"><span class="str">            >>> from rulekit.classification import RuleClassifier</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t167" href="#t167">167</a></span><span class="t"><span class="str">            >>></span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t168" href="#t168">168</a></span><span class="t"><span class="str">            >>> class MyEventListener(RuleInductionProgressListener):</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t169" href="#t169">169</a></span><span class="t"><span class="str">            >>>     def on_new_rule(self, rule):</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t170" href="#t170">170</a></span><span class="t"><span class="str">            >>>         print('Do something with new rule', rule)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t171" href="#t171">171</a></span><span class="t"><span class="str">            >>></span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t172" href="#t172">172</a></span><span class="t"><span class="str">            >>> operator = RuleClassifier()</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t173" href="#t173">173</a></span><span class="t"><span class="str">            >>> operator.add_event_listener(MyEventListener())</span>&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t174" href="#t174">174</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t175" href="#t175">175</a></span><span class="t">    <span class="key">def</span> <span class="nam">__getstate__</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">dict</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t176" href="#t176">176</a></span><span class="t">        <span class="nam">state</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">__dict__</span><span class="op">.</span><span class="nam">copy</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t177" href="#t177">177</a></span><span class="t">        <span class="nam">state</span><span class="op">.</span><span class="nam">pop</span><span class="op">(</span><span class="str">'_rule_generator'</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t178" href="#t178">178</a></span><span class="t">        <span class="key">return</span> <span class="op">{</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t179" href="#t179">179</a></span><span class="t">            <span class="str">'_params'</span><span class="op">:</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_params</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t180" href="#t180">180</a></span><span class="t">            <span class="str">'model'</span><span class="op">:</span> <span class="nam">ModelSerializer</span><span class="op">.</span><span class="nam">serialize</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">model</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t181" href="#t181">181</a></span><span class="t">        <span class="op">}</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t182" href="#t182">182</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t183" href="#t183">183</a></span><span class="t">    <span class="key">def</span> <span class="nam">__setstate__</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">state</span><span class="op">:</span> <span class="nam">dict</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t184" href="#t184">184</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">model</span> <span class="op">=</span> <span class="nam">ModelSerializer</span><span class="op">.</span><span class="nam">deserialize</span><span class="op">(</span><span class="nam">state</span><span class="op">[</span><span class="str">'model'</span><span class="op">]</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t185" href="#t185">185</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_rule_generator</span> <span class="op">=</span> <span class="nam">get_rule_generator</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t186" href="#t186">186</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">set_params</span><span class="op">(</span><span class="op">**</span><span class="nam">state</span><span class="op">[</span><span class="str">'_params'</span><span class="op">]</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t187" href="#t187">187</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t188" href="#t188">188</a></span><span class="t">    <span class="key">def</span> <span class="nam">_get_rule_generator</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">RuleGeneratorConfigurator</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t189" href="#t189">189</a></span><span class="t">        <span class="key">return</span> <span class="nam">get_rule_generator</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t190" href="#t190">190</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t191" href="#t191">191</a></span><span class="t">    <span class="op">@</span><span class="nam">abstractmethod</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t192" href="#t192">192</a></span><span class="t">    <span class="key">def</span> <span class="nam">_get_problem_type</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">ProblemType</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t193" href="#t193">193</a></span><span class="t">        <span class="key">pass</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t194" href="#t194">194</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t195" href="#t195">195</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t196" href="#t196">196</a></span><span class="t"><span class="key">class</span> <span class="nam">ExpertKnowledgeOperator</span><span class="op">(</span><span class="nam">BaseOperator</span><span class="op">,</span> <span class="nam">ABC</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t197" href="#t197">197</a></span><span class="t">    <span class="str">"""Base class for expert rule induction operator</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t198" href="#t198">198</a></span><span class="t"><span class="str">    """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t199" href="#t199">199</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t200" href="#t200">200</a></span><span class="t">    <span class="key">def</span> <span class="nam">fit</span><span class="op">(</span>  <span class="com"># pylint: disable=missing-function-docstring,too-many-arguments</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t201" href="#t201">201</a></span><span class="t">        <span class="nam">self</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t202" href="#t202">202</a></span><span class="t">        <span class="nam">values</span><span class="op">:</span> <span class="nam">Data</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t203" href="#t203">203</a></span><span class="t">        <span class="nam">labels</span><span class="op">:</span> <span class="nam">Data</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t204" href="#t204">204</a></span><span class="t">        <span class="nam">survival_time_attribute</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="key">None</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t205" href="#t205">205</a></span><span class="t">        <span class="nam">contrast_attribute</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="key">None</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t206" href="#t206">206</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t207" href="#t207">207</a></span><span class="t">        <span class="nam">expert_rules</span><span class="op">:</span> <span class="nam">list</span><span class="op">[</span><span class="nam">Union</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">BaseRule</span><span class="op">]</span><span class="op">]</span> <span class="op">=</span> <span class="key">None</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t208" href="#t208">208</a></span><span class="t">        <span class="nam">expert_preferred_conditions</span><span class="op">:</span> <span class="nam">list</span><span class="op">[</span><span class="nam">Union</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">BaseRule</span><span class="op">]</span><span class="op">]</span> <span class="op">=</span> <span class="key">None</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t209" href="#t209">209</a></span><span class="t">        <span class="nam">expert_forbidden_conditions</span><span class="op">:</span> <span class="nam">list</span><span class="op">[</span><span class="nam">Union</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">BaseRule</span><span class="op">]</span><span class="op">]</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t210" href="#t210">210</a></span><span class="t">    <span class="op">)</span> <span class="op">-></span> <span class="nam">ExpertKnowledgeOperator</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t211" href="#t211">211</a></span><span class="t">        <span class="nam">example_set</span> <span class="op">=</span> <span class="nam">ExampleSetFactory</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">_get_problem_type</span><span class="op">(</span><span class="op">)</span><span class="op">)</span><span class="op">.</span><span class="nam">make</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t212" href="#t212">212</a></span><span class="t">            <span class="nam">values</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t213" href="#t213">213</a></span><span class="t">            <span class="nam">labels</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t214" href="#t214">214</a></span><span class="t">            <span class="nam">survival_time_attribute</span><span class="op">=</span><span class="nam">survival_time_attribute</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t215" href="#t215">215</a></span><span class="t">            <span class="nam">contrast_attribute</span><span class="op">=</span><span class="nam">contrast_attribute</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t216" href="#t216">216</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t217" href="#t217">217</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_validate_contrast_attribute</span><span class="op">(</span><span class="nam">example_set</span><span class="op">,</span> <span class="nam">contrast_attribute</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t218" href="#t218">218</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_configure_expert_parameters</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t219" href="#t219">219</a></span><span class="t">            <span class="nam">expert_rules</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t220" href="#t220">220</a></span><span class="t">            <span class="nam">expert_preferred_conditions</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t221" href="#t221">221</a></span><span class="t">            <span class="nam">expert_forbidden_conditions</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t175" href="#t175">175</a></span><span class="t"><span class="str">        Args:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t176" href="#t176">176</a></span><span class="t"><span class="str">            listener (RuleInductionProgressListener): listener object</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t177" href="#t177">177</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t178" href="#t178">178</a></span><span class="t">        <span class="nam">command_listener</span> <span class="op">=</span> <span class="nam">_command_listener_factory</span><span class="op">(</span><span class="nam">listener</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t179" href="#t179">179</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_rule_generator</span><span class="op">.</span><span class="nam">addOperatorListener</span><span class="op">(</span><span class="nam">command_listener</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t180" href="#t180">180</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t181" href="#t181">181</a></span><span class="t">    <span class="key">def</span> <span class="nam">__getstate__</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">dict</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t182" href="#t182">182</a></span><span class="t">        <span class="nam">state</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">__dict__</span><span class="op">.</span><span class="nam">copy</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t183" href="#t183">183</a></span><span class="t">        <span class="nam">state</span><span class="op">.</span><span class="nam">pop</span><span class="op">(</span><span class="str">'_rule_generator'</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t184" href="#t184">184</a></span><span class="t">        <span class="key">return</span> <span class="op">{</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t185" href="#t185">185</a></span><span class="t">            <span class="str">'_params'</span><span class="op">:</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_params</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t186" href="#t186">186</a></span><span class="t">            <span class="str">'model'</span><span class="op">:</span> <span class="nam">ModelSerializer</span><span class="op">.</span><span class="nam">serialize</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">model</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t187" href="#t187">187</a></span><span class="t">        <span class="op">}</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t188" href="#t188">188</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t189" href="#t189">189</a></span><span class="t">    <span class="key">def</span> <span class="nam">__setstate__</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">state</span><span class="op">:</span> <span class="nam">dict</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t190" href="#t190">190</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">model</span> <span class="op">=</span> <span class="nam">ModelSerializer</span><span class="op">.</span><span class="nam">deserialize</span><span class="op">(</span><span class="nam">state</span><span class="op">[</span><span class="str">'model'</span><span class="op">]</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t191" href="#t191">191</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_rule_generator</span> <span class="op">=</span> <span class="nam">get_rule_generator</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t192" href="#t192">192</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">set_params</span><span class="op">(</span><span class="op">**</span><span class="nam">state</span><span class="op">[</span><span class="str">'_params'</span><span class="op">]</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t193" href="#t193">193</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t194" href="#t194">194</a></span><span class="t">    <span class="key">def</span> <span class="nam">_get_rule_generator</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">RuleGeneratorConfigurator</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t195" href="#t195">195</a></span><span class="t">        <span class="key">return</span> <span class="nam">get_rule_generator</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t196" href="#t196">196</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t197" href="#t197">197</a></span><span class="t">    <span class="op">@</span><span class="nam">abstractmethod</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t198" href="#t198">198</a></span><span class="t">    <span class="key">def</span> <span class="nam">_get_problem_type</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">ProblemType</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t199" href="#t199">199</a></span><span class="t">        <span class="key">pass</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t200" href="#t200">200</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t201" href="#t201">201</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t202" href="#t202">202</a></span><span class="t"><span class="key">class</span> <span class="nam">ExpertKnowledgeOperator</span><span class="op">(</span><span class="nam">BaseOperator</span><span class="op">,</span> <span class="nam">ABC</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t203" href="#t203">203</a></span><span class="t">    <span class="str">"""Base class for expert rule induction operator</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t204" href="#t204">204</a></span><span class="t"><span class="str">    """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t205" href="#t205">205</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t206" href="#t206">206</a></span><span class="t">    <span class="key">def</span> <span class="nam">fit</span><span class="op">(</span>  <span class="com"># pylint: disable=missing-function-docstring,too-many-arguments</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t207" href="#t207">207</a></span><span class="t">        <span class="nam">self</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t208" href="#t208">208</a></span><span class="t">        <span class="nam">values</span><span class="op">:</span> <span class="nam">Data</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t209" href="#t209">209</a></span><span class="t">        <span class="nam">labels</span><span class="op">:</span> <span class="nam">Data</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t210" href="#t210">210</a></span><span class="t">        <span class="nam">survival_time_attribute</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="key">None</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t211" href="#t211">211</a></span><span class="t">        <span class="nam">contrast_attribute</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="key">None</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t212" href="#t212">212</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t213" href="#t213">213</a></span><span class="t">        <span class="nam">expert_rules</span><span class="op">:</span> <span class="nam">list</span><span class="op">[</span><span class="nam">Union</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">BaseRule</span><span class="op">]</span><span class="op">]</span> <span class="op">=</span> <span class="key">None</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t214" href="#t214">214</a></span><span class="t">        <span class="nam">expert_preferred_conditions</span><span class="op">:</span> <span class="nam">list</span><span class="op">[</span><span class="nam">Union</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">BaseRule</span><span class="op">]</span><span class="op">]</span> <span class="op">=</span> <span class="key">None</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t215" href="#t215">215</a></span><span class="t">        <span class="nam">expert_forbidden_conditions</span><span class="op">:</span> <span class="nam">list</span><span class="op">[</span><span class="nam">Union</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">BaseRule</span><span class="op">]</span><span class="op">]</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t216" href="#t216">216</a></span><span class="t">    <span class="op">)</span> <span class="op">-></span> <span class="nam">ExpertKnowledgeOperator</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t217" href="#t217">217</a></span><span class="t">        <span class="nam">example_set</span> <span class="op">=</span> <span class="nam">ExampleSetFactory</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">_get_problem_type</span><span class="op">(</span><span class="op">)</span><span class="op">)</span><span class="op">.</span><span class="nam">make</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t218" href="#t218">218</a></span><span class="t">            <span class="nam">values</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t219" href="#t219">219</a></span><span class="t">            <span class="nam">labels</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t220" href="#t220">220</a></span><span class="t">            <span class="nam">survival_time_attribute</span><span class="op">=</span><span class="nam">survival_time_attribute</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t221" href="#t221">221</a></span><span class="t">            <span class="nam">contrast_attribute</span><span class="op">=</span><span class="nam">contrast_attribute</span>&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t222" href="#t222">222</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t223" href="#t223">223</a></span><span class="t">        <span class="nam">java_model</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_rule_generator</span><span class="op">.</span><span class="nam">learn</span><span class="op">(</span><span class="nam">example_set</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t224" href="#t224">224</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">model</span> <span class="op">=</span> <span class="nam">RuleSet</span><span class="op">(</span><span class="nam">java_model</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t225" href="#t225">225</a></span><span class="t">        <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">model</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t226" href="#t226">226</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t227" href="#t227">227</a></span><span class="t">    <span class="key">def</span> <span class="nam">_get_rule_generator</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">RuleGeneratorConfigurator</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t228" href="#t228">228</a></span><span class="t">        <span class="key">return</span> <span class="nam">get_rule_generator</span><span class="op">(</span><span class="nam">expert</span><span class="op">=</span><span class="key">True</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t229" href="#t229">229</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t230" href="#t230">230</a></span><span class="t">    <span class="key">def</span> <span class="nam">_configure_expert_parameters</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t231" href="#t231">231</a></span><span class="t">        <span class="nam">self</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t232" href="#t232">232</a></span><span class="t">        <span class="nam">expert_rules</span><span class="op">:</span> <span class="nam">Optional</span><span class="op">[</span><span class="nam">list</span><span class="op">[</span><span class="nam">Union</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">BaseRule</span><span class="op">]</span><span class="op">]</span><span class="op">]</span> <span class="op">=</span> <span class="key">None</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t233" href="#t233">233</a></span><span class="t">        <span class="nam">expert_preferred_conditions</span><span class="op">:</span> <span class="nam">Optional</span><span class="op">[</span><span class="nam">list</span><span class="op">[</span><span class="nam">Union</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">BaseRule</span><span class="op">]</span><span class="op">]</span><span class="op">]</span> <span class="op">=</span> <span class="key">None</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t234" href="#t234">234</a></span><span class="t">        <span class="nam">expert_forbidden_conditions</span><span class="op">:</span> <span class="nam">Optional</span><span class="op">[</span><span class="nam">list</span><span class="op">[</span><span class="nam">Union</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">BaseRule</span><span class="op">]</span><span class="op">]</span><span class="op">]</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t235" href="#t235">235</a></span><span class="t">    <span class="op">)</span> <span class="op">-></span> <span class="key">None</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t236" href="#t236">236</a></span><span class="t">        <span class="key">if</span> <span class="nam">expert_rules</span> <span class="key">is</span> <span class="key">None</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t237" href="#t237">237</a></span><span class="t">            <span class="nam">expert_rules</span> <span class="op">=</span> <span class="op">[</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t238" href="#t238">238</a></span><span class="t">        <span class="key">if</span> <span class="nam">expert_preferred_conditions</span> <span class="key">is</span> <span class="key">None</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t239" href="#t239">239</a></span><span class="t">            <span class="nam">expert_preferred_conditions</span> <span class="op">=</span> <span class="op">[</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t240" href="#t240">240</a></span><span class="t">        <span class="key">if</span> <span class="nam">expert_forbidden_conditions</span> <span class="key">is</span> <span class="key">None</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t241" href="#t241">241</a></span><span class="t">            <span class="nam">expert_forbidden_conditions</span> <span class="op">=</span> <span class="op">[</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t242" href="#t242">242</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t243" href="#t243">243</a></span><span class="t">        <span class="nam">configurator</span> <span class="op">=</span> <span class="nam">RuleGeneratorConfigurator</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">_rule_generator</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t244" href="#t244">244</a></span><span class="t">        <span class="nam">configurator</span><span class="op">.</span><span class="nam">_configure_simple_parameter</span><span class="op">(</span>  <span class="com"># pylint: disable=protected-access</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t245" href="#t245">245</a></span><span class="t">            <span class="str">'use_expert'</span><span class="op">,</span> <span class="key">True</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t246" href="#t246">246</a></span><span class="t">        <span class="nam">configurator</span><span class="op">.</span><span class="nam">_configure_expert_parameter</span><span class="op">(</span>  <span class="com"># pylint: disable=protected-access</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t247" href="#t247">247</a></span><span class="t">            <span class="str">'expert_preferred_conditions'</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t248" href="#t248">248</a></span><span class="t">            <span class="nam">self</span><span class="op">.</span><span class="nam">_sanitize_expert_parameter</span><span class="op">(</span><span class="nam">expert_preferred_conditions</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t249" href="#t249">249</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t250" href="#t250">250</a></span><span class="t">        <span class="nam">configurator</span><span class="op">.</span><span class="nam">_configure_expert_parameter</span><span class="op">(</span>  <span class="com"># pylint: disable=protected-access</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t251" href="#t251">251</a></span><span class="t">            <span class="str">'expert_forbidden_conditions'</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t252" href="#t252">252</a></span><span class="t">            <span class="nam">self</span><span class="op">.</span><span class="nam">_sanitize_expert_parameter</span><span class="op">(</span><span class="nam">expert_forbidden_conditions</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t253" href="#t253">253</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t254" href="#t254">254</a></span><span class="t">        <span class="nam">configurator</span><span class="op">.</span><span class="nam">_configure_expert_parameter</span><span class="op">(</span>  <span class="com"># pylint: disable=protected-access</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t255" href="#t255">255</a></span><span class="t">            <span class="str">'expert_rules'</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t256" href="#t256">256</a></span><span class="t">            <span class="nam">self</span><span class="op">.</span><span class="nam">_sanitize_expert_parameter</span><span class="op">(</span><span class="nam">expert_rules</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t257" href="#t257">257</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t258" href="#t258">258</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t259" href="#t259">259</a></span><span class="t">    <span class="key">def</span> <span class="nam">_sanitize_expert_parameter</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t260" href="#t260">260</a></span><span class="t">        <span class="nam">self</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t261" href="#t261">261</a></span><span class="t">        <span class="nam">expert_parameter</span><span class="op">:</span> <span class="nam">Optional</span><span class="op">[</span><span class="nam">list</span><span class="op">[</span><span class="nam">tuple</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">str</span><span class="op">]</span><span class="op">]</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t262" href="#t262">262</a></span><span class="t">    <span class="op">)</span> <span class="op">-></span> <span class="nam">list</span><span class="op">[</span><span class="nam">tuple</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">str</span><span class="op">]</span><span class="op">]</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t263" href="#t263">263</a></span><span class="t">        <span class="key">if</span> <span class="nam">expert_parameter</span> <span class="key">is</span> <span class="key">None</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t264" href="#t264">264</a></span><span class="t">            <span class="key">return</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t265" href="#t265">265</a></span><span class="t">        <span class="nam">sanitized_parameter</span><span class="op">:</span> <span class="nam">list</span><span class="op">[</span><span class="nam">tuple</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">str</span><span class="op">]</span><span class="op">]</span> <span class="op">=</span> <span class="op">[</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t266" href="#t266">266</a></span><span class="t">        <span class="key">for</span> <span class="nam">item</span> <span class="key">in</span> <span class="nam">expert_parameter</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t267" href="#t267">267</a></span><span class="t">            <span class="nam">item_id</span><span class="op">,</span> <span class="nam">item_value</span> <span class="op">=</span> <span class="nam">item</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t268" href="#t268">268</a></span><span class="t">            <span class="nam">sanitized_parameter</span><span class="op">.</span><span class="nam">append</span><span class="op">(</span><span class="op">(</span><span class="nam">item_id</span><span class="op">,</span> <span class="nam">item_value</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t269" href="#t269">269</a></span><span class="t">        <span class="key">return</span> <span class="nam">sanitized_parameter</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t223" href="#t223">223</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_validate_contrast_attribute</span><span class="op">(</span><span class="nam">example_set</span><span class="op">,</span> <span class="nam">contrast_attribute</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t224" href="#t224">224</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_configure_expert_parameters</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t225" href="#t225">225</a></span><span class="t">            <span class="nam">expert_rules</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t226" href="#t226">226</a></span><span class="t">            <span class="nam">expert_preferred_conditions</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t227" href="#t227">227</a></span><span class="t">            <span class="nam">expert_forbidden_conditions</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t228" href="#t228">228</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t229" href="#t229">229</a></span><span class="t">        <span class="nam">java_model</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_rule_generator</span><span class="op">.</span><span class="nam">learn</span><span class="op">(</span><span class="nam">example_set</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t230" href="#t230">230</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">model</span> <span class="op">=</span> <span class="nam">RuleSet</span><span class="op">(</span><span class="nam">java_model</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t231" href="#t231">231</a></span><span class="t">        <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">model</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t232" href="#t232">232</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t233" href="#t233">233</a></span><span class="t">    <span class="key">def</span> <span class="nam">_get_rule_generator</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">RuleGeneratorConfigurator</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t234" href="#t234">234</a></span><span class="t">        <span class="key">return</span> <span class="nam">get_rule_generator</span><span class="op">(</span><span class="nam">expert</span><span class="op">=</span><span class="key">True</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t235" href="#t235">235</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t236" href="#t236">236</a></span><span class="t">    <span class="key">def</span> <span class="nam">_configure_expert_parameters</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t237" href="#t237">237</a></span><span class="t">        <span class="nam">self</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t238" href="#t238">238</a></span><span class="t">        <span class="nam">expert_rules</span><span class="op">:</span> <span class="nam">Optional</span><span class="op">[</span><span class="nam">list</span><span class="op">[</span><span class="nam">Union</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">BaseRule</span><span class="op">]</span><span class="op">]</span><span class="op">]</span> <span class="op">=</span> <span class="key">None</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t239" href="#t239">239</a></span><span class="t">        <span class="nam">expert_preferred_conditions</span><span class="op">:</span> <span class="nam">Optional</span><span class="op">[</span><span class="nam">list</span><span class="op">[</span><span class="nam">Union</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">BaseRule</span><span class="op">]</span><span class="op">]</span><span class="op">]</span> <span class="op">=</span> <span class="key">None</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t240" href="#t240">240</a></span><span class="t">        <span class="nam">expert_forbidden_conditions</span><span class="op">:</span> <span class="nam">Optional</span><span class="op">[</span><span class="nam">list</span><span class="op">[</span><span class="nam">Union</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">BaseRule</span><span class="op">]</span><span class="op">]</span><span class="op">]</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t241" href="#t241">241</a></span><span class="t">    <span class="op">)</span> <span class="op">-></span> <span class="key">None</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t242" href="#t242">242</a></span><span class="t">        <span class="key">if</span> <span class="nam">expert_rules</span> <span class="key">is</span> <span class="key">None</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t243" href="#t243">243</a></span><span class="t">            <span class="nam">expert_rules</span> <span class="op">=</span> <span class="op">[</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t244" href="#t244">244</a></span><span class="t">        <span class="key">if</span> <span class="nam">expert_preferred_conditions</span> <span class="key">is</span> <span class="key">None</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t245" href="#t245">245</a></span><span class="t">            <span class="nam">expert_preferred_conditions</span> <span class="op">=</span> <span class="op">[</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t246" href="#t246">246</a></span><span class="t">        <span class="key">if</span> <span class="nam">expert_forbidden_conditions</span> <span class="key">is</span> <span class="key">None</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t247" href="#t247">247</a></span><span class="t">            <span class="nam">expert_forbidden_conditions</span> <span class="op">=</span> <span class="op">[</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t248" href="#t248">248</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t249" href="#t249">249</a></span><span class="t">        <span class="nam">configurator</span> <span class="op">=</span> <span class="nam">RuleGeneratorConfigurator</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">_rule_generator</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t250" href="#t250">250</a></span><span class="t">        <span class="nam">configurator</span><span class="op">.</span><span class="nam">_configure_simple_parameter</span><span class="op">(</span>  <span class="com"># pylint: disable=protected-access</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t251" href="#t251">251</a></span><span class="t">            <span class="str">'use_expert'</span><span class="op">,</span> <span class="key">True</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t252" href="#t252">252</a></span><span class="t">        <span class="nam">configurator</span><span class="op">.</span><span class="nam">_configure_expert_parameter</span><span class="op">(</span>  <span class="com"># pylint: disable=protected-access</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t253" href="#t253">253</a></span><span class="t">            <span class="str">'expert_preferred_conditions'</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t254" href="#t254">254</a></span><span class="t">            <span class="nam">self</span><span class="op">.</span><span class="nam">_sanitize_expert_parameter</span><span class="op">(</span><span class="nam">expert_preferred_conditions</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t255" href="#t255">255</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t256" href="#t256">256</a></span><span class="t">        <span class="nam">configurator</span><span class="op">.</span><span class="nam">_configure_expert_parameter</span><span class="op">(</span>  <span class="com"># pylint: disable=protected-access</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t257" href="#t257">257</a></span><span class="t">            <span class="str">'expert_forbidden_conditions'</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t258" href="#t258">258</a></span><span class="t">            <span class="nam">self</span><span class="op">.</span><span class="nam">_sanitize_expert_parameter</span><span class="op">(</span><span class="nam">expert_forbidden_conditions</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t259" href="#t259">259</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t260" href="#t260">260</a></span><span class="t">        <span class="nam">configurator</span><span class="op">.</span><span class="nam">_configure_expert_parameter</span><span class="op">(</span>  <span class="com"># pylint: disable=protected-access</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t261" href="#t261">261</a></span><span class="t">            <span class="str">'expert_rules'</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t262" href="#t262">262</a></span><span class="t">            <span class="nam">self</span><span class="op">.</span><span class="nam">_sanitize_expert_parameter</span><span class="op">(</span><span class="nam">expert_rules</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t263" href="#t263">263</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t264" href="#t264">264</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t265" href="#t265">265</a></span><span class="t">    <span class="key">def</span> <span class="nam">_sanitize_expert_parameter</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t266" href="#t266">266</a></span><span class="t">        <span class="nam">self</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t267" href="#t267">267</a></span><span class="t">        <span class="nam">expert_parameter</span><span class="op">:</span> <span class="nam">Optional</span><span class="op">[</span><span class="nam">list</span><span class="op">[</span><span class="nam">tuple</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">str</span><span class="op">]</span><span class="op">]</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t268" href="#t268">268</a></span><span class="t">    <span class="op">)</span> <span class="op">-></span> <span class="nam">list</span><span class="op">[</span><span class="nam">tuple</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">str</span><span class="op">]</span><span class="op">]</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t269" href="#t269">269</a></span><span class="t">        <span class="key">if</span> <span class="nam">expert_parameter</span> <span class="key">is</span> <span class="key">None</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t270" href="#t270">270</a></span><span class="t">            <span class="key">return</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t271" href="#t271">271</a></span><span class="t">        <span class="nam">sanitized_parameter</span><span class="op">:</span> <span class="nam">list</span><span class="op">[</span><span class="nam">tuple</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">str</span><span class="op">]</span><span class="op">]</span> <span class="op">=</span> <span class="op">[</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t272" href="#t272">272</a></span><span class="t">        <span class="key">for</span> <span class="nam">item</span> <span class="key">in</span> <span class="nam">expert_parameter</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t273" href="#t273">273</a></span><span class="t">            <span class="nam">item_id</span><span class="op">,</span> <span class="nam">item_value</span> <span class="op">=</span> <span class="nam">item</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t274" href="#t274">274</a></span><span class="t">            <span class="nam">sanitized_parameter</span><span class="op">.</span><span class="nam">append</span><span class="op">(</span><span class="op">(</span><span class="nam">item_id</span><span class="op">,</span> <span class="nam">item_value</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t275" href="#t275">275</a></span><span class="t">        <span class="key">return</span> <span class="nam">sanitized_parameter</span>&nbsp;</span><span class="r"></span></p>
 </main>
 <footer>
     <div class="content">
@@ -358,7 +364,7 @@ <h2>
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             &nbsp; &nbsp; &nbsp;
             <a class="nav" href="https://coverage.readthedocs.io/en/7.6.4">coverage.py v7.6.4</a>,
-            created at 2024-11-08 14:43 +0100
+            created at 2024-11-28 11:55 +0100
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diff --git a/docs/reports/coverage/z_a87f2a4bb6695d91_arff_py.html b/docs/reports/coverage/z_a87f2a4bb6695d91_arff_py.html
index 3ec61b0..4545f08 100644
--- a/docs/reports/coverage/z_a87f2a4bb6695d91_arff_py.html
+++ b/docs/reports/coverage/z_a87f2a4bb6695d91_arff_py.html
@@ -65,7 +65,7 @@ <h2>
             <a id="nextFileLink" class="nav" href="z_a87f2a4bb6695d91_classification_py.html">&#xbb; next</a>
             &nbsp; &nbsp; &nbsp;
             <a class="nav" href="https://coverage.readthedocs.io/en/7.6.4">coverage.py v7.6.4</a>,
-            created at 2024-11-08 14:43 +0100
+            created at 2024-11-28 11:55 +0100
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         <aside class="hidden">
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@@ -104,46 +104,57 @@ <h2>
     <p class="mis show_mis"><span class="n"><a id="t22" href="#t22">22</a></span><span class="t">    <span class="key">return</span> <span class="nam">io</span><span class="op">.</span><span class="nam">StringIO</span><span class="op">(</span><span class="nam">raw_text</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t23" href="#t23">23</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t24" href="#t24">24</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t25" href="#t25">25</a></span><span class="t"><span class="key">def</span> <span class="nam">read_arff</span><span class="op">(</span><span class="nam">file_path_or_file</span><span class="op">:</span> <span class="nam">Union</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">io</span><span class="op">.</span><span class="nam">IOBase</span><span class="op">]</span><span class="op">,</span> <span class="nam">encoding</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="str">"utf-8"</span><span class="op">)</span> <span class="op">-></span> <span class="nam">pd</span><span class="op">.</span><span class="nam">DataFrame</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t26" href="#t26">26</a></span><span class="t">    <span class="str">"""Reads an .arff file and returns a pandas DataFrame.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t27" href="#t27">27</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t28" href="#t28">28</a></span><span class="t"><span class="str">    This function offers a more convenient interface to read .arff files</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t29" href="#t29">29</a></span><span class="t"><span class="str">    than scipy.io arff.loadarff function. It also fix multiple problems with it,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t30" href="#t30">30</a></span><span class="t"><span class="str">    such as handling missing "?" values and encoding nominal columns.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t31" href="#t31">31</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t32" href="#t32">32</a></span><span class="t"><span class="str">    Args:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t33" href="#t33">33</a></span><span class="t"><span class="str">        file_path_or_file (str): Either path to the .arff file or a readable  file-like object. The path</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t34" href="#t34">34</a></span><span class="t"><span class="str">        can also be a http or https URL.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t35" href="#t35">35</a></span><span class="t"><span class="str">        encoding (str, optional): Optional file encoding. Defaults to "utf-8".</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t36" href="#t36">36</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t37" href="#t37">37</a></span><span class="t"><span class="str">    Returns:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t38" href="#t38">38</a></span><span class="t"><span class="str">        pd.DataFrame: pandas DataFrame with the data</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t39" href="#t39">39</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t40" href="#t40">40</a></span><span class="t"><span class="str">    Example:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t41" href="#t41">41</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t42" href="#t42">42</a></span><span class="t"><span class="str">        >>> # read from file path</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t43" href="#t43">43</a></span><span class="t"><span class="str">        >>> df: pd.DataFrame = read_arff('./cholesterol.arff')</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t44" href="#t44">44</a></span><span class="t"><span class="str">        >>></span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t45" href="#t45">45</a></span><span class="t"><span class="str">        >>> # read from file-like object</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t46" href="#t46">46</a></span><span class="t"><span class="str">        >>> with open('./cholesterol.arff', 'r') as f:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t47" href="#t47">47</a></span><span class="t"><span class="str">        >>>     df: pd.DataFrame = read_arff(f)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t25" href="#t25">25</a></span><span class="t"><span class="key">def</span> <span class="nam">read_arff</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t26" href="#t26">26</a></span><span class="t">    <span class="nam">file_path_or_file</span><span class="op">:</span> <span class="nam">Union</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">io</span><span class="op">.</span><span class="nam">IOBase</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t27" href="#t27">27</a></span><span class="t">    <span class="nam">encoding</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="str">"utf-8"</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t28" href="#t28">28</a></span><span class="t"><span class="op">)</span> <span class="op">-></span> <span class="nam">pd</span><span class="op">.</span><span class="nam">DataFrame</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t29" href="#t29">29</a></span><span class="t">    <span class="str">"""Reads an .arff file and returns a pandas DataFrame.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t30" href="#t30">30</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t31" href="#t31">31</a></span><span class="t"><span class="str">    This function offers a more convenient interface to read .arff files</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t32" href="#t32">32</a></span><span class="t"><span class="str">    than scipy.io arff.loadarff function. It also fix multiple</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t33" href="#t33">33</a></span><span class="t"><span class="str">    problems with it, such as handling missing "?" values and encoding</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t34" href="#t34">34</a></span><span class="t"><span class="str">    nominal columns.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t35" href="#t35">35</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t36" href="#t36">36</a></span><span class="t"><span class="str">    Args:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t37" href="#t37">37</a></span><span class="t"><span class="str">        file_path_or_file (str): Either path to the .arff file or a readable</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t38" href="#t38">38</a></span><span class="t"><span class="str">        file-like object. The path can also be a http or https URL.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t39" href="#t39">39</a></span><span class="t"><span class="str">        encoding (str, optional): Optional file encoding. Defaults to "utf-8".</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t40" href="#t40">40</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t41" href="#t41">41</a></span><span class="t"><span class="str">    Returns:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t42" href="#t42">42</a></span><span class="t"><span class="str">        pd.DataFrame: pandas DataFrame with the data</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t43" href="#t43">43</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t44" href="#t44">44</a></span><span class="t"><span class="str">    Example:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t45" href="#t45">45</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t46" href="#t46">46</a></span><span class="t"><span class="str">        >>> # read from file path</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t47" href="#t47">47</a></span><span class="t"><span class="str">        >>> df: pd.DataFrame = read_arff('./cholesterol.arff')</span>&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t48" href="#t48">48</a></span><span class="t"><span class="str">        >>></span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t49" href="#t49">49</a></span><span class="t"><span class="str">        >>> # read from URL</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t50" href="#t50">50</a></span><span class="t"><span class="str">        >>> df: pd.DataFrame = read_arff('https://raw.githubusercontent.com/adaa-polsl/RuleKit-python/master/tests/additional_resources/cholesterol.arff')</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t51" href="#t51">51</a></span><span class="t"><span class="str">    """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t52" href="#t52">52</a></span><span class="t">    <span class="key">if</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">file_path_or_file</span><span class="op">,</span> <span class="nam">str</span><span class="op">)</span> <span class="key">and</span> <span class="nam">_is_path_and_url</span><span class="op">(</span><span class="nam">file_path_or_file</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t53" href="#t53">53</a></span><span class="t">        <span class="nam">file_path_or_file</span> <span class="op">=</span> <span class="nam">_make_file_object_from_url</span><span class="op">(</span><span class="nam">file_path_or_file</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t54" href="#t54">54</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t55" href="#t55">55</a></span><span class="t">    <span class="nam">df</span> <span class="op">=</span> <span class="nam">pd</span><span class="op">.</span><span class="nam">DataFrame</span><span class="op">(</span><span class="nam">arff</span><span class="op">.</span><span class="nam">loadarff</span><span class="op">(</span><span class="nam">file_path_or_file</span><span class="op">)</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t56" href="#t56">56</a></span><span class="t">    <span class="com"># code to change encoding of the file</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t57" href="#t57">57</a></span><span class="t">    <span class="nam">decoded_df</span><span class="op">:</span> <span class="nam">pd</span><span class="op">.</span><span class="nam">DataFrame</span> <span class="op">=</span> <span class="nam">df</span><span class="op">.</span><span class="nam">select_dtypes</span><span class="op">(</span><span class="op">[</span><span class="nam">np</span><span class="op">.</span><span class="nam">object_</span><span class="op">]</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t58" href="#t58">58</a></span><span class="t">    <span class="key">if</span> <span class="key">not</span> <span class="nam">decoded_df</span><span class="op">.</span><span class="nam">empty</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t59" href="#t59">59</a></span><span class="t">        <span class="nam">decoded_df</span> <span class="op">=</span> <span class="nam">decoded_df</span><span class="op">.</span><span class="nam">stack</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">str</span><span class="op">.</span><span class="nam">decode</span><span class="op">(</span><span class="nam">encoding</span><span class="op">)</span><span class="op">.</span><span class="nam">unstack</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t60" href="#t60">60</a></span><span class="t">        <span class="key">for</span> <span class="nam">col</span> <span class="key">in</span> <span class="nam">decoded_df</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t61" href="#t61">61</a></span><span class="t">            <span class="nam">df</span><span class="op">[</span><span class="nam">col</span><span class="op">]</span> <span class="op">=</span> <span class="nam">decoded_df</span><span class="op">[</span><span class="nam">col</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t62" href="#t62">62</a></span><span class="t">    <span class="nam">df</span> <span class="op">=</span> <span class="nam">df</span><span class="op">.</span><span class="nam">where</span><span class="op">(</span><span class="nam">pd</span><span class="op">.</span><span class="nam">notnull</span><span class="op">(</span><span class="nam">df</span><span class="op">)</span><span class="op">,</span> <span class="key">None</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t63" href="#t63">63</a></span><span class="t">    <span class="nam">df</span> <span class="op">=</span> <span class="nam">df</span><span class="op">.</span><span class="nam">replace</span><span class="op">(</span><span class="op">{</span><span class="str">'?'</span><span class="op">:</span> <span class="key">None</span><span class="op">}</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t64" href="#t64">64</a></span><span class="t">    <span class="key">return</span> <span class="nam">df</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t49" href="#t49">49</a></span><span class="t"><span class="str">        >>> # read from file-like object</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t50" href="#t50">50</a></span><span class="t"><span class="str">        >>> with open('./cholesterol.arff', 'r') as f:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t51" href="#t51">51</a></span><span class="t"><span class="str">        >>>     df: pd.DataFrame = read_arff(f)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t52" href="#t52">52</a></span><span class="t"><span class="str">        >>></span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t53" href="#t53">53</a></span><span class="t"><span class="str">        >>> # read from URL</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t54" href="#t54">54</a></span><span class="t"><span class="str">        >>> df: pd.DataFrame = read_arff(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t55" href="#t55">55</a></span><span class="t"><span class="str">        >>>    'https://raw.githubusercontent.com' +</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t56" href="#t56">56</a></span><span class="t"><span class="str">        >>>    '/adaa-polsl/RuleKit-python/master/tests' +</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t57" href="#t57">57</a></span><span class="t"><span class="str">        >>>    '/additional_resources/cholesterol.arff'</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t58" href="#t58">58</a></span><span class="t"><span class="str">        >>> )</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t59" href="#t59">59</a></span><span class="t"><span class="str">    """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t60" href="#t60">60</a></span><span class="t">    <span class="key">if</span> <span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t61" href="#t61">61</a></span><span class="t">        <span class="nam">isinstance</span><span class="op">(</span><span class="nam">file_path_or_file</span><span class="op">,</span> <span class="nam">str</span><span class="op">)</span> <span class="key">and</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t62" href="#t62">62</a></span><span class="t">        <span class="nam">_is_path_and_url</span><span class="op">(</span><span class="nam">file_path_or_file</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t63" href="#t63">63</a></span><span class="t">    <span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t64" href="#t64">64</a></span><span class="t">        <span class="nam">file_path_or_file</span> <span class="op">=</span> <span class="nam">_make_file_object_from_url</span><span class="op">(</span><span class="nam">file_path_or_file</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t65" href="#t65">65</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t66" href="#t66">66</a></span><span class="t">    <span class="nam">df</span> <span class="op">=</span> <span class="nam">pd</span><span class="op">.</span><span class="nam">DataFrame</span><span class="op">(</span><span class="nam">arff</span><span class="op">.</span><span class="nam">loadarff</span><span class="op">(</span><span class="nam">file_path_or_file</span><span class="op">)</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t67" href="#t67">67</a></span><span class="t">    <span class="com"># code to change encoding of the file</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t68" href="#t68">68</a></span><span class="t">    <span class="nam">decoded_df</span><span class="op">:</span> <span class="nam">pd</span><span class="op">.</span><span class="nam">DataFrame</span> <span class="op">=</span> <span class="nam">df</span><span class="op">.</span><span class="nam">select_dtypes</span><span class="op">(</span><span class="op">[</span><span class="nam">np</span><span class="op">.</span><span class="nam">object_</span><span class="op">]</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t69" href="#t69">69</a></span><span class="t">    <span class="key">if</span> <span class="key">not</span> <span class="nam">decoded_df</span><span class="op">.</span><span class="nam">empty</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t70" href="#t70">70</a></span><span class="t">        <span class="nam">decoded_df</span> <span class="op">=</span> <span class="nam">decoded_df</span><span class="op">.</span><span class="nam">stack</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">str</span><span class="op">.</span><span class="nam">decode</span><span class="op">(</span><span class="nam">encoding</span><span class="op">)</span><span class="op">.</span><span class="nam">unstack</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t71" href="#t71">71</a></span><span class="t">        <span class="key">for</span> <span class="nam">col</span> <span class="key">in</span> <span class="nam">decoded_df</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t72" href="#t72">72</a></span><span class="t">            <span class="nam">df</span><span class="op">[</span><span class="nam">col</span><span class="op">]</span> <span class="op">=</span> <span class="nam">decoded_df</span><span class="op">[</span><span class="nam">col</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t73" href="#t73">73</a></span><span class="t">    <span class="nam">df</span> <span class="op">=</span> <span class="nam">df</span><span class="op">.</span><span class="nam">where</span><span class="op">(</span><span class="nam">pd</span><span class="op">.</span><span class="nam">notnull</span><span class="op">(</span><span class="nam">df</span><span class="op">)</span><span class="op">,</span> <span class="key">None</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t74" href="#t74">74</a></span><span class="t">    <span class="nam">df</span> <span class="op">=</span> <span class="nam">df</span><span class="op">.</span><span class="nam">replace</span><span class="op">(</span><span class="op">{</span><span class="str">'?'</span><span class="op">:</span> <span class="key">None</span><span class="op">}</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t75" href="#t75">75</a></span><span class="t">    <span class="key">return</span> <span class="nam">df</span>&nbsp;</span><span class="r"></span></p>
 </main>
 <footer>
     <div class="content">
@@ -153,7 +164,7 @@ <h2>
             <a class="nav" href="z_a87f2a4bb6695d91_classification_py.html">&#xbb; next</a>
             &nbsp; &nbsp; &nbsp;
             <a class="nav" href="https://coverage.readthedocs.io/en/7.6.4">coverage.py v7.6.4</a>,
-            created at 2024-11-08 14:43 +0100
+            created at 2024-11-28 11:55 +0100
         </p>
     </div>
 </footer>
diff --git a/docs/reports/coverage/z_a87f2a4bb6695d91_classification_py.html b/docs/reports/coverage/z_a87f2a4bb6695d91_classification_py.html
index ab77c98..e1bb0d8 100644
--- a/docs/reports/coverage/z_a87f2a4bb6695d91_classification_py.html
+++ b/docs/reports/coverage/z_a87f2a4bb6695d91_classification_py.html
@@ -2,7 +2,7 @@
 <html lang="en">
 <head>
     <meta http-equiv="Content-Type" content="text/html; charset=utf-8">
-    <title>Coverage for rulekit\classification.py: 78%</title>
+    <title>Coverage for rulekit\classification.py: 81%</title>
     <link rel="icon" sizes="32x32" href="favicon_32_cb_58284776.png">
     <link rel="stylesheet" href="style_cb_718ce007.css" type="text/css">
     <script src="coverage_html_cb_497bf287.js" defer></script>
@@ -12,7 +12,7 @@
     <div class="content">
         <h1>
             <span class="text">Coverage for </span><b>rulekit\classification.py</b>:
-            <span class="pc_cov">78%</span>
+            <span class="pc_cov">81%</span>
         </h1>
         <aside id="help_panel_wrapper">
             <input id="help_panel_state" type="checkbox">
@@ -54,9 +54,9 @@ <h1>
             </div>
         </aside>
         <h2>
-            <span class="text">173 statements &nbsp;</span>
-            <button type="button" class="run button_toggle_run" value="run" data-shortcut="r" title="Toggle lines run">135<span class="text"> run</span></button>
-            <button type="button" class="mis show_mis button_toggle_mis" value="mis" data-shortcut="m" title="Toggle lines missing">38<span class="text"> missing</span></button>
+            <span class="text">185 statements &nbsp;</span>
+            <button type="button" class="run button_toggle_run" value="run" data-shortcut="r" title="Toggle lines run">149<span class="text"> run</span></button>
+            <button type="button" class="mis show_mis button_toggle_mis" value="mis" data-shortcut="m" title="Toggle lines missing">36<span class="text"> missing</span></button>
             <button type="button" class="exc show_exc button_toggle_exc" value="exc" data-shortcut="x" title="Toggle lines excluded">0<span class="text"> excluded</span></button>
         </h2>
         <p class="text">
@@ -65,7 +65,7 @@ <h2>
             <a id="nextFileLink" class="nav" href="z_a87f2a4bb6695d91_events_py.html">&#xbb; next</a>
             &nbsp; &nbsp; &nbsp;
             <a class="nav" href="https://coverage.readthedocs.io/en/7.6.4">coverage.py v7.6.4</a>,
-            created at 2024-11-08 14:43 +0100
+            created at 2024-11-28 12:33 +0100
         </p>
         <aside class="hidden">
             <button type="button" class="button_next_chunk" data-shortcut="j"></button>
@@ -86,785 +86,810 @@ <h2>
     <p class="pln"><span class="n"><a id="t4" href="#t4">4</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
     <p class="run"><span class="n"><a id="t5" href="#t5">5</a></span><span class="t"><span class="key">from</span> <span class="nam">enum</span> <span class="key">import</span> <span class="nam">Enum</span>&nbsp;</span><span class="r"></span></p>
     <p class="run"><span class="n"><a id="t6" href="#t6">6</a></span><span class="t"><span class="key">from</span> <span class="nam">numbers</span> <span class="key">import</span> <span class="nam">Number</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t7" href="#t7">7</a></span><span class="t"><span class="key">from</span> <span class="nam">typing</span> <span class="key">import</span> <span class="nam">Tuple</span><span class="op">,</span> <span class="nam">TypedDict</span><span class="op">,</span> <span class="nam">Union</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t8" href="#t8">8</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t9" href="#t9">9</a></span><span class="t"><span class="key">import</span> <span class="nam">numpy</span> <span class="key">as</span> <span class="nam">np</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t10" href="#t10">10</a></span><span class="t"><span class="key">import</span> <span class="nam">pandas</span> <span class="key">as</span> <span class="nam">pd</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t11" href="#t11">11</a></span><span class="t"><span class="key">from</span> <span class="nam">jpype</span> <span class="key">import</span> <span class="nam">JClass</span><span class="op">,</span> <span class="nam">JObject</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t12" href="#t12">12</a></span><span class="t"><span class="key">from</span> <span class="nam">sklearn</span> <span class="key">import</span> <span class="nam">metrics</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t13" href="#t13">13</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t14" href="#t14">14</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">_helpers</span> <span class="key">import</span> <span class="nam">PredictionResultMapper</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t15" href="#t15">15</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">_operator</span> <span class="key">import</span> <span class="nam">BaseOperator</span><span class="op">,</span> <span class="nam">Data</span><span class="op">,</span> <span class="nam">ExpertKnowledgeOperator</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t16" href="#t16">16</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">_problem_types</span> <span class="key">import</span> <span class="nam">ProblemType</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t17" href="#t17">17</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">params</span> <span class="key">import</span> <span class="op">(</span><span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">,</span> <span class="nam">ContrastSetModelParams</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t18" href="#t18">18</a></span><span class="t">                            <span class="nam">Measures</span><span class="op">,</span> <span class="nam">ModelsParams</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t19" href="#t19">19</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">rules</span> <span class="key">import</span> <span class="nam">ClassificationRule</span><span class="op">,</span> <span class="nam">RuleSet</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t20" href="#t20">20</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t21" href="#t21">21</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t22" href="#t22">22</a></span><span class="t"><span class="key">class</span> <span class="nam">ClassificationPredictionMetrics</span><span class="op">(</span><span class="nam">TypedDict</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t23" href="#t23">23</a></span><span class="t">    <span class="str">"""Stores additional metrics for classification prediction.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t24" href="#t24">24</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t25" href="#t25">25</a></span><span class="t"><span class="str">    Fields:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t26" href="#t26">26</a></span><span class="t"><span class="str">        * rules_per_example (float): Average number of rules per example.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t27" href="#t27">27</a></span><span class="t"><span class="str">        * voting_conflicts (_type_): Number of voting conflicts.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t28" href="#t28">28</a></span><span class="t"><span class="str">    """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t29" href="#t29">29</a></span><span class="t">    <span class="nam">rules_per_example</span><span class="op">:</span> <span class="nam">float</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t30" href="#t30">30</a></span><span class="t">    <span class="nam">voting_conflicts</span><span class="op">:</span> <span class="nam">float</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t31" href="#t31">31</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t32" href="#t32">32</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t33" href="#t33">33</a></span><span class="t"><span class="key">class</span> <span class="nam">_ClassificationParams</span><span class="op">(</span><span class="nam">ModelsParams</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t34" href="#t34">34</a></span><span class="t">    <span class="nam">control_apriori_precision</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'control_apriori_precision'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t35" href="#t35">35</a></span><span class="t">    <span class="nam">approximate_induction</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'approximate_induction'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t36" href="#t36">36</a></span><span class="t">    <span class="nam">approximate_bins_count</span><span class="op">:</span> <span class="nam">int</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'approximate_bins_count'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t37" href="#t37">37</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t38" href="#t38">38</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t39" href="#t39">39</a></span><span class="t"><span class="key">class</span> <span class="nam">BaseClassifier</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t40" href="#t40">40</a></span><span class="t">    <span class="str">""":meta private:"""</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t7" href="#t7">7</a></span><span class="t"><span class="key">from</span> <span class="nam">typing</span> <span class="key">import</span> <span class="nam">Tuple</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t8" href="#t8">8</a></span><span class="t"><span class="key">from</span> <span class="nam">typing</span> <span class="key">import</span> <span class="nam">TypedDict</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t9" href="#t9">9</a></span><span class="t"><span class="key">from</span> <span class="nam">typing</span> <span class="key">import</span> <span class="nam">Union</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t10" href="#t10">10</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t11" href="#t11">11</a></span><span class="t"><span class="key">import</span> <span class="nam">numpy</span> <span class="key">as</span> <span class="nam">np</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t12" href="#t12">12</a></span><span class="t"><span class="key">import</span> <span class="nam">pandas</span> <span class="key">as</span> <span class="nam">pd</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t13" href="#t13">13</a></span><span class="t"><span class="key">from</span> <span class="nam">jpype</span> <span class="key">import</span> <span class="nam">JClass</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t14" href="#t14">14</a></span><span class="t"><span class="key">from</span> <span class="nam">jpype</span> <span class="key">import</span> <span class="nam">JObject</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t15" href="#t15">15</a></span><span class="t"><span class="key">from</span> <span class="nam">sklearn</span> <span class="key">import</span> <span class="nam">metrics</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t16" href="#t16">16</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t17" href="#t17">17</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">_helpers</span> <span class="key">import</span> <span class="nam">PredictionResultMapper</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t18" href="#t18">18</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">_operator</span> <span class="key">import</span> <span class="nam">BaseOperator</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t19" href="#t19">19</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">_operator</span> <span class="key">import</span> <span class="nam">Data</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t20" href="#t20">20</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">_operator</span> <span class="key">import</span> <span class="nam">ExpertKnowledgeOperator</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t21" href="#t21">21</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">_problem_types</span> <span class="key">import</span> <span class="nam">ProblemType</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t22" href="#t22">22</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">params</span> <span class="key">import</span> <span class="nam">ContrastSetModelParams</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t23" href="#t23">23</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">params</span> <span class="key">import</span> <span class="nam">DEFAULT_PARAMS_VALUE</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t24" href="#t24">24</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">params</span> <span class="key">import</span> <span class="nam">ExpertModelParams</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t25" href="#t25">25</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">params</span> <span class="key">import</span> <span class="nam">Measures</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t26" href="#t26">26</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">params</span> <span class="key">import</span> <span class="nam">ModelsParams</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t27" href="#t27">27</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">rules</span> <span class="key">import</span> <span class="nam">ClassificationRule</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t28" href="#t28">28</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">rules</span> <span class="key">import</span> <span class="nam">RuleSet</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t29" href="#t29">29</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t30" href="#t30">30</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t31" href="#t31">31</a></span><span class="t"><span class="key">class</span> <span class="nam">ClassificationPredictionMetrics</span><span class="op">(</span><span class="nam">TypedDict</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t32" href="#t32">32</a></span><span class="t">    <span class="str">"""Stores additional metrics for classification prediction.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t33" href="#t33">33</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t34" href="#t34">34</a></span><span class="t"><span class="str">    Fields:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t35" href="#t35">35</a></span><span class="t"><span class="str">        * rules_per_example (float): Average number of rules per example.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t36" href="#t36">36</a></span><span class="t"><span class="str">        * voting_conflicts (_type_): Number of voting conflicts.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t37" href="#t37">37</a></span><span class="t"><span class="str">    """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t38" href="#t38">38</a></span><span class="t">    <span class="nam">rules_per_example</span><span class="op">:</span> <span class="nam">float</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t39" href="#t39">39</a></span><span class="t">    <span class="nam">voting_conflicts</span><span class="op">:</span> <span class="nam">float</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t40" href="#t40">40</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t41" href="#t41">41</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t42" href="#t42">42</a></span><span class="t">    <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t43" href="#t43">43</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_ClassificationRulesPerformance</span><span class="op">:</span> <span class="nam">JClass</span> <span class="op">=</span> <span class="key">None</span>  <span class="com"># pylint: disable=invalid-name</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t44" href="#t44">44</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_NegativeVotingConflictsPerformance</span><span class="op">:</span> <span class="nam">JClass</span> <span class="op">=</span> <span class="key">None</span>  <span class="com"># pylint: disable=invalid-name</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t45" href="#t45">45</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_init_classification_rule_performance_classes</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t42" href="#t42">42</a></span><span class="t"><span class="key">class</span> <span class="nam">_ClassificationParams</span><span class="op">(</span><span class="nam">ModelsParams</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t43" href="#t43">43</a></span><span class="t">    <span class="nam">control_apriori_precision</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'control_apriori_precision'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t44" href="#t44">44</a></span><span class="t">    <span class="nam">approximate_induction</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'approximate_induction'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t45" href="#t45">45</a></span><span class="t">    <span class="nam">approximate_bins_count</span><span class="op">:</span> <span class="nam">int</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'approximate_bins_count'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t46" href="#t46">46</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t47" href="#t47">47</a></span><span class="t">    <span class="key">class</span> <span class="nam">MetricTypes</span><span class="op">(</span><span class="nam">Enum</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t48" href="#t48">48</a></span><span class="t">        <span class="str">""":meta private:"""</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t49" href="#t49">49</a></span><span class="t">        <span class="nam">RulesPerExample</span> <span class="op">=</span> <span class="num">1</span>  <span class="com"># pylint: disable=invalid-name</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t50" href="#t50">50</a></span><span class="t">        <span class="nam">VotingConflicts</span> <span class="op">=</span> <span class="num">2</span>  <span class="com"># pylint: disable=invalid-name</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t51" href="#t51">51</a></span><span class="t">        <span class="nam">NegativeVotingConflicts</span> <span class="op">=</span> <span class="num">3</span>  <span class="com"># pylint: disable=invalid-name</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t52" href="#t52">52</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t53" href="#t53">53</a></span><span class="t">    <span class="key">def</span> <span class="nam">_init_classification_rule_performance_classes</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t54" href="#t54">54</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_ClassificationRulesPerformance</span> <span class="op">=</span> <span class="nam">JClass</span><span class="op">(</span>  <span class="com"># pylint: disable=invalid-name</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t55" href="#t55">55</a></span><span class="t">            <span class="str">'adaa.analytics.rules.logic.performance.ClassificationRulesPerformance'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t56" href="#t56">56</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t57" href="#t57">57</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t58" href="#t58">58</a></span><span class="t">    <span class="key">def</span> <span class="nam">_calculate_metric</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">example_set</span><span class="op">:</span> <span class="nam">JObject</span><span class="op">,</span> <span class="nam">metric_type</span><span class="op">:</span> <span class="nam">MetricTypes</span><span class="op">)</span> <span class="op">-></span> <span class="nam">float</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t59" href="#t59">59</a></span><span class="t">        <span class="nam">metric</span><span class="op">:</span> <span class="nam">JObject</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_ClassificationRulesPerformance</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t60" href="#t60">60</a></span><span class="t">            <span class="nam">metric_type</span><span class="op">.</span><span class="nam">value</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t61" href="#t61">61</a></span><span class="t">        <span class="nam">metric_value</span> <span class="op">=</span> <span class="nam">float</span><span class="op">(</span><span class="nam">metric</span><span class="op">.</span><span class="nam">countExample</span><span class="op">(</span><span class="nam">example_set</span><span class="op">)</span><span class="op">.</span><span class="nam">getValue</span><span class="op">(</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t62" href="#t62">62</a></span><span class="t">        <span class="key">return</span> <span class="nam">metric_value</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t63" href="#t63">63</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t64" href="#t64">64</a></span><span class="t">    <span class="key">def</span> <span class="nam">_calculate_prediction_metrics</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">example_set</span><span class="op">)</span> <span class="op">-></span> <span class="nam">ClassificationPredictionMetrics</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t65" href="#t65">65</a></span><span class="t">        <span class="key">return</span> <span class="nam">ClassificationPredictionMetrics</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t66" href="#t66">66</a></span><span class="t">            <span class="nam">rules_per_example</span><span class="op">=</span><span class="nam">self</span><span class="op">.</span><span class="nam">_calculate_metric</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t67" href="#t67">67</a></span><span class="t">                <span class="nam">example_set</span><span class="op">,</span> <span class="nam">BaseClassifier</span><span class="op">.</span><span class="nam">MetricTypes</span><span class="op">.</span><span class="nam">RulesPerExample</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t68" href="#t68">68</a></span><span class="t">            <span class="op">)</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t69" href="#t69">69</a></span><span class="t">            <span class="nam">voting_conflicts</span><span class="op">=</span><span class="nam">self</span><span class="op">.</span><span class="nam">_calculate_metric</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t70" href="#t70">70</a></span><span class="t">                <span class="nam">example_set</span><span class="op">,</span> <span class="nam">BaseClassifier</span><span class="op">.</span><span class="nam">MetricTypes</span><span class="op">.</span><span class="nam">VotingConflicts</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t71" href="#t71">71</a></span><span class="t">            <span class="op">)</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t72" href="#t72">72</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t73" href="#t73">73</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t74" href="#t74">74</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t75" href="#t75">75</a></span><span class="t"><span class="key">class</span> <span class="nam">RuleClassifier</span><span class="op">(</span><span class="nam">BaseOperator</span><span class="op">,</span> <span class="nam">BaseClassifier</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t76" href="#t76">76</a></span><span class="t">    <span class="str">"""Classification model."""</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t77" href="#t77">77</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t78" href="#t78">78</a></span><span class="t">    <span class="nam">__params_class__</span> <span class="op">=</span> <span class="nam">_ClassificationParams</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t79" href="#t79">79</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t80" href="#t80">80</a></span><span class="t">    <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span>  <span class="com"># pylint: disable=too-many-arguments,too-many-locals</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t81" href="#t81">81</a></span><span class="t">        <span class="nam">self</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t82" href="#t82">82</a></span><span class="t">        <span class="nam">minsupp_new</span><span class="op">:</span> <span class="nam">float</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'minsupp_new'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t83" href="#t83">83</a></span><span class="t">        <span class="nam">induction_measure</span><span class="op">:</span> <span class="nam">Measures</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'induction_measure'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t84" href="#t84">84</a></span><span class="t">        <span class="nam">pruning_measure</span><span class="op">:</span> <span class="nam">Union</span><span class="op">[</span><span class="nam">Measures</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t85" href="#t85">85</a></span><span class="t">                               <span class="nam">str</span><span class="op">]</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'pruning_measure'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t86" href="#t86">86</a></span><span class="t">        <span class="nam">voting_measure</span><span class="op">:</span> <span class="nam">Measures</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'voting_measure'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t87" href="#t87">87</a></span><span class="t">        <span class="nam">max_growing</span><span class="op">:</span> <span class="nam">float</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'max_growing'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t88" href="#t88">88</a></span><span class="t">        <span class="nam">enable_pruning</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'enable_pruning'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t89" href="#t89">89</a></span><span class="t">        <span class="nam">ignore_missing</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'ignore_missing'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t90" href="#t90">90</a></span><span class="t">        <span class="nam">max_uncovered_fraction</span><span class="op">:</span> <span class="nam">float</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'max_uncovered_fraction'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t91" href="#t91">91</a></span><span class="t">        <span class="nam">select_best_candidate</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'select_best_candidate'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t92" href="#t92">92</a></span><span class="t">        <span class="nam">complementary_conditions</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'complementary_conditions'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t93" href="#t93">93</a></span><span class="t">        <span class="nam">control_apriori_precision</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'control_apriori_precision'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t94" href="#t94">94</a></span><span class="t">        <span class="nam">max_rule_count</span><span class="op">:</span> <span class="nam">int</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'max_rule_count'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t95" href="#t95">95</a></span><span class="t">        <span class="nam">approximate_induction</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'approximate_induction'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t96" href="#t96">96</a></span><span class="t">        <span class="nam">approximate_bins_count</span><span class="op">:</span> <span class="nam">int</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'approximate_bins_count'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t97" href="#t97">97</a></span><span class="t">    <span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t98" href="#t98">98</a></span><span class="t">        <span class="str">"""</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t99" href="#t99">99</a></span><span class="t"><span class="str">        Parameters</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t100" href="#t100">100</a></span><span class="t"><span class="str">        ----------</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t101" href="#t101">101</a></span><span class="t"><span class="str">        minsupp_new : float = 5.0</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t102" href="#t102">102</a></span><span class="t"><span class="str">            a minimum number (or fraction, if value &lt; 1.0) of previously uncovered examples</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t103" href="#t103">103</a></span><span class="t"><span class="str">             to be covered by a new rule (positive examples for classification problems);</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t104" href="#t104">104</a></span><span class="t"><span class="str">             default: 5,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t105" href="#t105">105</a></span><span class="t"><span class="str">        induction_measure : :class:`rulekit.params.Measures` = :class:`rulekit.params.\</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t106" href="#t106">106</a></span><span class="t"><span class="str">            Measures.Correlation`</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t107" href="#t107">107</a></span><span class="t"><span class="str">            measure used during induction; default measure is correlation</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t108" href="#t108">108</a></span><span class="t"><span class="str">        pruning_measure : Union[:class:`rulekit.params.Measures`, str] = \</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t109" href="#t109">109</a></span><span class="t"><span class="str">            :class:`rulekit.params.Measures.Correlation`</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t110" href="#t110">110</a></span><span class="t"><span class="str">            measure used during pruning. Could be user defined (string), for example</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t111" href="#t111">111</a></span><span class="t"><span class="str">             :code:`2 * p / n`; default measure is correlation</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t112" href="#t112">112</a></span><span class="t"><span class="str">        voting_measure : :class:`rulekit.params.Measures` = \</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t113" href="#t113">113</a></span><span class="t"><span class="str">            :class:`rulekit.params.Measures.Correlation`</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t114" href="#t114">114</a></span><span class="t"><span class="str">            measure used during voting; default measure is correlation</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t115" href="#t115">115</a></span><span class="t"><span class="str">        max_growing : int = 0.0</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t116" href="#t116">116</a></span><span class="t"><span class="str">            non-negative integer representing maximum number of conditions which can be added</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t117" href="#t117">117</a></span><span class="t"><span class="str">            to the rule in the growing phase (use this parameter for large datasets if execution</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t118" href="#t118">118</a></span><span class="t"><span class="str">            time is prohibitive); 0 indicates no limit; default: 0,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t119" href="#t119">119</a></span><span class="t"><span class="str">        enable_pruning : bool = True</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t120" href="#t120">120</a></span><span class="t"><span class="str">            enable or disable pruning, default is True.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t121" href="#t121">121</a></span><span class="t"><span class="str">        ignore_missing : bool = False</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t122" href="#t122">122</a></span><span class="t"><span class="str">            boolean telling whether missing values should be ignored (by default, a missing value</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t123" href="#t123">123</a></span><span class="t"><span class="str">            of given attribute is always cconsidered as not fulfilling the condition build upon</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t124" href="#t124">124</a></span><span class="t"><span class="str">             that attribute); default: False.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t125" href="#t125">125</a></span><span class="t"><span class="str">        max_uncovered_fraction : float = 0.0</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t126" href="#t126">126</a></span><span class="t"><span class="str">            Floating-point number from [0,1] interval representing maximum fraction of examples</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t127" href="#t127">127</a></span><span class="t"><span class="str">            that may remain uncovered by the rule set, default: 0.0.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t128" href="#t128">128</a></span><span class="t"><span class="str">        select_best_candidate : bool = False</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t129" href="#t129">129</a></span><span class="t"><span class="str">            Flag determining if best candidate should be selected from growing phase; default:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t130" href="#t130">130</a></span><span class="t"><span class="str">            False.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t131" href="#t131">131</a></span><span class="t"><span class="str">        complementary_conditions : bool = False</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t132" href="#t132">132</a></span><span class="t"><span class="str">            If enabled, complementary conditions in the form a = !{value} for nominal attributes</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t133" href="#t133">133</a></span><span class="t"><span class="str">            are supported.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t134" href="#t134">134</a></span><span class="t"><span class="str">        control_apriori_precision : bool = True</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t135" href="#t135">135</a></span><span class="t"><span class="str">            When inducing classification rules, verify if candidate precision is higher than</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t136" href="#t136">136</a></span><span class="t"><span class="str">             apriori precision of the investigated class.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t137" href="#t137">137</a></span><span class="t"><span class="str">        max_rule_count : int = 0</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t138" href="#t138">138</a></span><span class="t"><span class="str">            Maximum number of rules to be generated (for classification data sets it applies</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t139" href="#t139">139</a></span><span class="t"><span class="str">             to a single class); 0 indicates no limit.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t140" href="#t140">140</a></span><span class="t"><span class="str">        approximate_induction: bool = False</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t141" href="#t141">141</a></span><span class="t"><span class="str">            Use an approximate induction heuristic which does not check all possible splits;</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t142" href="#t142">142</a></span><span class="t"><span class="str">            note: this is an experimental feature and currently works only for classification</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t143" href="#t143">143</a></span><span class="t"><span class="str">            data sets, results may change in future;</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t144" href="#t144">144</a></span><span class="t"><span class="str">        approximate_bins_count: int = 100</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t145" href="#t145">145</a></span><span class="t"><span class="str">            maximum number of bins for an attribute evaluated in the approximate induction.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t146" href="#t146">146</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t147" href="#t147">147</a></span><span class="t">        <span class="nam">BaseOperator</span><span class="op">.</span><span class="nam">__init__</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t148" href="#t148">148</a></span><span class="t">            <span class="nam">self</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t149" href="#t149">149</a></span><span class="t">            <span class="nam">minsupp_new</span><span class="op">=</span><span class="nam">minsupp_new</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t150" href="#t150">150</a></span><span class="t">            <span class="nam">induction_measure</span><span class="op">=</span><span class="nam">induction_measure</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t151" href="#t151">151</a></span><span class="t">            <span class="nam">pruning_measure</span><span class="op">=</span><span class="nam">pruning_measure</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t152" href="#t152">152</a></span><span class="t">            <span class="nam">voting_measure</span><span class="op">=</span><span class="nam">voting_measure</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t153" href="#t153">153</a></span><span class="t">            <span class="nam">max_growing</span><span class="op">=</span><span class="nam">max_growing</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t154" href="#t154">154</a></span><span class="t">            <span class="nam">enable_pruning</span><span class="op">=</span><span class="nam">enable_pruning</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t155" href="#t155">155</a></span><span class="t">            <span class="nam">ignore_missing</span><span class="op">=</span><span class="nam">ignore_missing</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t156" href="#t156">156</a></span><span class="t">            <span class="nam">max_uncovered_fraction</span><span class="op">=</span><span class="nam">max_uncovered_fraction</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t157" href="#t157">157</a></span><span class="t">            <span class="nam">select_best_candidate</span><span class="op">=</span><span class="nam">select_best_candidate</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t158" href="#t158">158</a></span><span class="t">            <span class="nam">complementary_conditions</span><span class="op">=</span><span class="nam">complementary_conditions</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t159" href="#t159">159</a></span><span class="t">            <span class="nam">control_apriori_precision</span><span class="op">=</span><span class="nam">control_apriori_precision</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t160" href="#t160">160</a></span><span class="t">            <span class="nam">max_rule_count</span><span class="op">=</span><span class="nam">max_rule_count</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t161" href="#t161">161</a></span><span class="t">            <span class="nam">approximate_induction</span><span class="op">=</span><span class="nam">approximate_induction</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t162" href="#t162">162</a></span><span class="t">            <span class="nam">approximate_bins_count</span><span class="op">=</span><span class="nam">approximate_bins_count</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t163" href="#t163">163</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t164" href="#t164">164</a></span><span class="t">        <span class="nam">BaseClassifier</span><span class="op">.</span><span class="nam">__init__</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t165" href="#t165">165</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_remap_to_numeric</span> <span class="op">=</span> <span class="key">False</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t166" href="#t166">166</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">label_unique_values</span> <span class="op">=</span> <span class="op">[</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t167" href="#t167">167</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">model</span><span class="op">:</span> <span class="nam">RuleSet</span><span class="op">[</span><span class="nam">ClassificationRule</span><span class="op">]</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t168" href="#t168">168</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t169" href="#t169">169</a></span><span class="t">    <span class="key">def</span> <span class="nam">_map_result</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">predicted_example_set</span><span class="op">)</span> <span class="op">-></span> <span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t170" href="#t170">170</a></span><span class="t">        <span class="nam">prediction</span><span class="op">:</span> <span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t171" href="#t171">171</a></span><span class="t">        <span class="key">if</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_remap_to_numeric</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t172" href="#t172">172</a></span><span class="t">            <span class="nam">prediction</span> <span class="op">=</span> <span class="nam">PredictionResultMapper</span><span class="op">.</span><span class="nam">map_to_numerical</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t173" href="#t173">173</a></span><span class="t">                <span class="nam">predicted_example_set</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t174" href="#t174">174</a></span><span class="t">        <span class="key">else</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t175" href="#t175">175</a></span><span class="t">            <span class="nam">prediction</span> <span class="op">=</span> <span class="nam">PredictionResultMapper</span><span class="op">.</span><span class="nam">map_to_nominal</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t176" href="#t176">176</a></span><span class="t">                <span class="nam">predicted_example_set</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t177" href="#t177">177</a></span><span class="t">        <span class="key">return</span> <span class="nam">prediction</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t178" href="#t178">178</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t179" href="#t179">179</a></span><span class="t">    <span class="key">def</span> <span class="nam">_map_confidence</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">predicted_example_set</span><span class="op">)</span> <span class="op">-></span> <span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t180" href="#t180">180</a></span><span class="t">        <span class="key">return</span> <span class="nam">PredictionResultMapper</span><span class="op">.</span><span class="nam">map_confidence</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t181" href="#t181">181</a></span><span class="t">            <span class="nam">predicted_example_set</span><span class="op">,</span> <span class="nam">self</span><span class="op">.</span><span class="nam">label_unique_values</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t182" href="#t182">182</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t183" href="#t183">183</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t184" href="#t184">184</a></span><span class="t">    <span class="key">def</span> <span class="nam">_get_unique_label_values</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">labels</span><span class="op">:</span> <span class="nam">Data</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t185" href="#t185">185</a></span><span class="t">        <span class="nam">tmp</span> <span class="op">=</span> <span class="op">{</span><span class="op">}</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t186" href="#t186">186</a></span><span class="t">        <span class="key">for</span> <span class="nam">label_value</span> <span class="key">in</span> <span class="nam">labels</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t187" href="#t187">187</a></span><span class="t">            <span class="nam">tmp</span><span class="op">[</span><span class="nam">label_value</span><span class="op">]</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t188" href="#t188">188</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">label_unique_values</span> <span class="op">=</span> <span class="nam">list</span><span class="op">(</span><span class="nam">tmp</span><span class="op">.</span><span class="nam">keys</span><span class="op">(</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t189" href="#t189">189</a></span><span class="t">        <span class="key">if</span> <span class="nam">len</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">label_unique_values</span><span class="op">)</span> <span class="op">></span> <span class="num">0</span> <span class="key">and</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">label_unique_values</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="op">,</span> <span class="nam">bytes</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t190" href="#t190">190</a></span><span class="t">            <span class="nam">self</span><span class="op">.</span><span class="nam">label_unique_values</span> <span class="op">=</span> <span class="op">[</span><span class="nam">item</span><span class="op">.</span><span class="nam">decode</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t191" href="#t191">191</a></span><span class="t">                <span class="str">'utf-8'</span><span class="op">)</span> <span class="key">for</span> <span class="nam">item</span> <span class="key">in</span> <span class="nam">self</span><span class="op">.</span><span class="nam">label_unique_values</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t192" href="#t192">192</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t193" href="#t193">193</a></span><span class="t">    <span class="key">def</span> <span class="nam">_prepare_labels</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">labels</span><span class="op">:</span> <span class="nam">Data</span><span class="op">)</span> <span class="op">-></span> <span class="nam">Data</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t194" href="#t194">194</a></span><span class="t">        <span class="key">if</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">labels</span><span class="op">,</span> <span class="op">(</span><span class="nam">pd</span><span class="op">.</span><span class="nam">DataFrame</span><span class="op">,</span> <span class="nam">pd</span><span class="op">.</span><span class="nam">Series</span><span class="op">)</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t195" href="#t195">195</a></span><span class="t">            <span class="key">if</span> <span class="nam">labels</span><span class="op">.</span><span class="nam">dtypes</span><span class="op">.</span><span class="nam">name</span> <span class="op">==</span> <span class="str">'bool'</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t196" href="#t196">196</a></span><span class="t">                <span class="key">return</span> <span class="nam">labels</span><span class="op">.</span><span class="nam">astype</span><span class="op">(</span><span class="nam">str</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t197" href="#t197">197</a></span><span class="t">            <span class="key">if</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">labels</span><span class="op">.</span><span class="nam">iloc</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="op">,</span> <span class="nam">Number</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t198" href="#t198">198</a></span><span class="t">                <span class="nam">self</span><span class="op">.</span><span class="nam">_remap_to_numeric</span> <span class="op">=</span> <span class="key">True</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t199" href="#t199">199</a></span><span class="t">                <span class="key">return</span> <span class="nam">labels</span><span class="op">.</span><span class="nam">astype</span><span class="op">(</span><span class="nam">str</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t200" href="#t200">200</a></span><span class="t">        <span class="key">else</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t201" href="#t201">201</a></span><span class="t">            <span class="key">if</span> <span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t202" href="#t202">202</a></span><span class="t">                <span class="nam">isinstance</span><span class="op">(</span><span class="nam">labels</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="op">,</span> <span class="nam">bool</span><span class="op">)</span> <span class="key">or</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t203" href="#t203">203</a></span><span class="t">                <span class="op">(</span><span class="nam">isinstance</span><span class="op">(</span><span class="nam">labels</span><span class="op">,</span> <span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span><span class="op">)</span> <span class="key">and</span> <span class="nam">labels</span><span class="op">.</span><span class="nam">dtype</span><span class="op">.</span><span class="nam">name</span> <span class="op">==</span> <span class="str">'bool'</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t204" href="#t204">204</a></span><span class="t">            <span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t205" href="#t205">205</a></span><span class="t">                <span class="key">return</span> <span class="nam">np</span><span class="op">.</span><span class="nam">array</span><span class="op">(</span><span class="nam">list</span><span class="op">(</span><span class="nam">map</span><span class="op">(</span><span class="nam">str</span><span class="op">,</span> <span class="nam">labels</span><span class="op">)</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t206" href="#t206">206</a></span><span class="t">            <span class="key">if</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">labels</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="op">,</span> <span class="nam">Number</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t207" href="#t207">207</a></span><span class="t">                <span class="nam">self</span><span class="op">.</span><span class="nam">_remap_to_numeric</span> <span class="op">=</span> <span class="key">True</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t208" href="#t208">208</a></span><span class="t">                <span class="key">return</span> <span class="nam">np</span><span class="op">.</span><span class="nam">array</span><span class="op">(</span><span class="nam">list</span><span class="op">(</span><span class="nam">map</span><span class="op">(</span><span class="nam">str</span><span class="op">,</span> <span class="nam">labels</span><span class="op">)</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t209" href="#t209">209</a></span><span class="t">        <span class="key">return</span> <span class="nam">labels</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t210" href="#t210">210</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t211" href="#t211">211</a></span><span class="t">    <span class="key">def</span> <span class="nam">fit</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">values</span><span class="op">:</span> <span class="nam">Data</span><span class="op">,</span> <span class="nam">labels</span><span class="op">:</span> <span class="nam">Data</span><span class="op">)</span> <span class="op">-></span> <span class="nam">RuleClassifier</span><span class="op">:</span>  <span class="com"># pylint: disable=arguments-differ</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t212" href="#t212">212</a></span><span class="t">        <span class="str">"""Train model on given dataset.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t213" href="#t213">213</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t214" href="#t214">214</a></span><span class="t"><span class="str">        Parameters</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t215" href="#t215">215</a></span><span class="t"><span class="str">        ----------</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t216" href="#t216">216</a></span><span class="t"><span class="str">        values : :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t217" href="#t217">217</a></span><span class="t"><span class="str">            attributes</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t218" href="#t218">218</a></span><span class="t"><span class="str">        labels : :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t219" href="#t219">219</a></span><span class="t"><span class="str">            labels</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t220" href="#t220">220</a></span><span class="t"><span class="str">        Returns</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t221" href="#t221">221</a></span><span class="t"><span class="str">        -------</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t222" href="#t222">222</a></span><span class="t"><span class="str">        self : RuleClassifier</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t223" href="#t223">223</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t224" href="#t224">224</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_get_unique_label_values</span><span class="op">(</span><span class="nam">labels</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t225" href="#t225">225</a></span><span class="t">        <span class="nam">labels</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_prepare_labels</span><span class="op">(</span><span class="nam">labels</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t226" href="#t226">226</a></span><span class="t">        <span class="nam">BaseOperator</span><span class="op">.</span><span class="nam">fit</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">values</span><span class="op">,</span> <span class="nam">labels</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t227" href="#t227">227</a></span><span class="t">        <span class="key">return</span> <span class="nam">self</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t228" href="#t228">228</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t229" href="#t229">229</a></span><span class="t">    <span class="key">def</span> <span class="nam">predict</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t230" href="#t230">230</a></span><span class="t">        <span class="nam">self</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t231" href="#t231">231</a></span><span class="t">        <span class="nam">values</span><span class="op">:</span> <span class="nam">Data</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t232" href="#t232">232</a></span><span class="t">        <span class="nam">return_metrics</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="key">False</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t233" href="#t233">233</a></span><span class="t">    <span class="op">)</span> <span class="op">-></span> <span class="nam">Union</span><span class="op">[</span><span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span><span class="op">,</span> <span class="nam">tuple</span><span class="op">[</span><span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span><span class="op">,</span> <span class="nam">ClassificationPredictionMetrics</span><span class="op">]</span><span class="op">]</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t234" href="#t234">234</a></span><span class="t">        <span class="str">"""Perform prediction and returns predicted labels.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t235" href="#t235">235</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t236" href="#t236">236</a></span><span class="t"><span class="str">        Parameters</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t237" href="#t237">237</a></span><span class="t"><span class="str">        ----------</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t238" href="#t238">238</a></span><span class="t"><span class="str">        values : :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t239" href="#t239">239</a></span><span class="t"><span class="str">            attributes</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t240" href="#t240">240</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t241" href="#t241">241</a></span><span class="t"><span class="str">        return_metrics: bool = False</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t242" href="#t242">242</a></span><span class="t"><span class="str">            Optional flag. If set to *True* method will calculate some additional model metrics.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t243" href="#t243">243</a></span><span class="t"><span class="str">             Method will then return tuple instead of just predicted labels.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t244" href="#t244">244</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t245" href="#t245">245</a></span><span class="t"><span class="str">        Returns</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t246" href="#t246">246</a></span><span class="t"><span class="str">        -------</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t247" href="#t247">247</a></span><span class="t"><span class="str">        result : Union[np.ndarray, tuple[np.ndarray, :class:`rulekit.classification.ClassificationPredictionMetrics`]]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t248" href="#t248">248</a></span><span class="t"><span class="str">            If *return_metrics* flag wasn't set it will return just prediction, otherwise a tuple</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t249" href="#t249">249</a></span><span class="t"><span class="str">             will be returned with first element being prediction and second one being metrics.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t250" href="#t250">250</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t251" href="#t251">251</a></span><span class="t">        <span class="nam">result_example_set</span> <span class="op">=</span> <span class="nam">BaseOperator</span><span class="op">.</span><span class="nam">predict</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">values</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t252" href="#t252">252</a></span><span class="t">        <span class="nam">y_pred</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_map_result</span><span class="op">(</span><span class="nam">result_example_set</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t253" href="#t253">253</a></span><span class="t">        <span class="key">if</span> <span class="nam">return_metrics</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t254" href="#t254">254</a></span><span class="t">            <span class="nam">metrics_values</span><span class="op">:</span> <span class="nam">dict</span> <span class="op">=</span> <span class="nam">BaseClassifier</span><span class="op">.</span><span class="nam">_calculate_prediction_metrics</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t255" href="#t255">255</a></span><span class="t">                <span class="nam">self</span><span class="op">,</span> <span class="nam">result_example_set</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t256" href="#t256">256</a></span><span class="t">            <span class="key">return</span> <span class="op">(</span><span class="nam">y_pred</span><span class="op">,</span> <span class="nam">metrics_values</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t257" href="#t257">257</a></span><span class="t">        <span class="key">return</span> <span class="nam">y_pred</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t258" href="#t258">258</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t259" href="#t259">259</a></span><span class="t">    <span class="key">def</span> <span class="nam">predict_proba</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t260" href="#t260">260</a></span><span class="t">        <span class="nam">self</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t261" href="#t261">261</a></span><span class="t">        <span class="nam">values</span><span class="op">:</span> <span class="nam">Data</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t262" href="#t262">262</a></span><span class="t">        <span class="nam">return_metrics</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="key">False</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t263" href="#t263">263</a></span><span class="t">    <span class="op">)</span> <span class="op">-></span> <span class="nam">Union</span><span class="op">[</span><span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span><span class="op">,</span> <span class="nam">tuple</span><span class="op">[</span><span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span><span class="op">,</span> <span class="nam">ClassificationPredictionMetrics</span><span class="op">]</span><span class="op">]</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t264" href="#t264">264</a></span><span class="t">        <span class="str">"""Perform prediction and returns class probabilities for each example.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t265" href="#t265">265</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t266" href="#t266">266</a></span><span class="t"><span class="str">        Parameters</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t267" href="#t267">267</a></span><span class="t"><span class="str">        ----------</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t268" href="#t268">268</a></span><span class="t"><span class="str">        values : :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t269" href="#t269">269</a></span><span class="t"><span class="str">            attributes</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t270" href="#t270">270</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t271" href="#t271">271</a></span><span class="t"><span class="str">        return_metrics: bool = False</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t272" href="#t272">272</a></span><span class="t"><span class="str">            Optional flag. If set to *True* method will calculate some additional model metrics.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t273" href="#t273">273</a></span><span class="t"><span class="str">             Method will then return tuple instead of just probabilities.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t47" href="#t47">47</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t48" href="#t48">48</a></span><span class="t"><span class="key">class</span> <span class="nam">_ClassificationExpertParams</span><span class="op">(</span><span class="nam">_ClassificationParams</span><span class="op">,</span> <span class="nam">ExpertModelParams</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t49" href="#t49">49</a></span><span class="t">    <span class="key">pass</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t50" href="#t50">50</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t51" href="#t51">51</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t52" href="#t52">52</a></span><span class="t"><span class="key">class</span> <span class="nam">BaseClassifier</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t53" href="#t53">53</a></span><span class="t">    <span class="str">""":meta private:"""</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t54" href="#t54">54</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t55" href="#t55">55</a></span><span class="t">    <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t56" href="#t56">56</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_ClassificationRulesPerformance</span><span class="op">:</span> <span class="nam">JClass</span> <span class="op">=</span> <span class="key">None</span>  <span class="com"># pylint: disable=invalid-name</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t57" href="#t57">57</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_NegativeVotingConflictsPerformance</span><span class="op">:</span> <span class="nam">JClass</span> <span class="op">=</span> <span class="key">None</span>  <span class="com"># pylint: disable=invalid-name</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t58" href="#t58">58</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_init_classification_rule_performance_classes</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t59" href="#t59">59</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t60" href="#t60">60</a></span><span class="t">    <span class="key">class</span> <span class="nam">MetricTypes</span><span class="op">(</span><span class="nam">Enum</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t61" href="#t61">61</a></span><span class="t">        <span class="str">""":meta private:"""</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t62" href="#t62">62</a></span><span class="t">        <span class="nam">RulesPerExample</span> <span class="op">=</span> <span class="num">1</span>  <span class="com"># pylint: disable=invalid-name</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t63" href="#t63">63</a></span><span class="t">        <span class="nam">VotingConflicts</span> <span class="op">=</span> <span class="num">2</span>  <span class="com"># pylint: disable=invalid-name</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t64" href="#t64">64</a></span><span class="t">        <span class="nam">NegativeVotingConflicts</span> <span class="op">=</span> <span class="num">3</span>  <span class="com"># pylint: disable=invalid-name</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t65" href="#t65">65</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t66" href="#t66">66</a></span><span class="t">    <span class="key">def</span> <span class="nam">_init_classification_rule_performance_classes</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t67" href="#t67">67</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_ClassificationRulesPerformance</span> <span class="op">=</span> <span class="nam">JClass</span><span class="op">(</span>  <span class="com"># pylint: disable=invalid-name</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t68" href="#t68">68</a></span><span class="t">            <span class="str">'adaa.analytics.rules.logic.performance.ClassificationRulesPerformance'</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t69" href="#t69">69</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t70" href="#t70">70</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t71" href="#t71">71</a></span><span class="t">    <span class="key">def</span> <span class="nam">_calculate_metric</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">example_set</span><span class="op">:</span> <span class="nam">JObject</span><span class="op">,</span> <span class="nam">metric_type</span><span class="op">:</span> <span class="nam">MetricTypes</span><span class="op">)</span> <span class="op">-></span> <span class="nam">float</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t72" href="#t72">72</a></span><span class="t">        <span class="nam">metric</span><span class="op">:</span> <span class="nam">JObject</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_ClassificationRulesPerformance</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t73" href="#t73">73</a></span><span class="t">            <span class="nam">metric_type</span><span class="op">.</span><span class="nam">value</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t74" href="#t74">74</a></span><span class="t">        <span class="nam">metric_value</span> <span class="op">=</span> <span class="nam">float</span><span class="op">(</span><span class="nam">metric</span><span class="op">.</span><span class="nam">countExample</span><span class="op">(</span><span class="nam">example_set</span><span class="op">)</span><span class="op">.</span><span class="nam">getValue</span><span class="op">(</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t75" href="#t75">75</a></span><span class="t">        <span class="key">return</span> <span class="nam">metric_value</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t76" href="#t76">76</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t77" href="#t77">77</a></span><span class="t">    <span class="key">def</span> <span class="nam">_calculate_prediction_metrics</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">example_set</span><span class="op">)</span> <span class="op">-></span> <span class="nam">ClassificationPredictionMetrics</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t78" href="#t78">78</a></span><span class="t">        <span class="key">return</span> <span class="nam">ClassificationPredictionMetrics</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t79" href="#t79">79</a></span><span class="t">            <span class="nam">rules_per_example</span><span class="op">=</span><span class="nam">self</span><span class="op">.</span><span class="nam">_calculate_metric</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t80" href="#t80">80</a></span><span class="t">                <span class="nam">example_set</span><span class="op">,</span> <span class="nam">BaseClassifier</span><span class="op">.</span><span class="nam">MetricTypes</span><span class="op">.</span><span class="nam">RulesPerExample</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t81" href="#t81">81</a></span><span class="t">            <span class="op">)</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t82" href="#t82">82</a></span><span class="t">            <span class="nam">voting_conflicts</span><span class="op">=</span><span class="nam">self</span><span class="op">.</span><span class="nam">_calculate_metric</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t83" href="#t83">83</a></span><span class="t">                <span class="nam">example_set</span><span class="op">,</span> <span class="nam">BaseClassifier</span><span class="op">.</span><span class="nam">MetricTypes</span><span class="op">.</span><span class="nam">VotingConflicts</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t84" href="#t84">84</a></span><span class="t">            <span class="op">)</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t85" href="#t85">85</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t86" href="#t86">86</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t87" href="#t87">87</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t88" href="#t88">88</a></span><span class="t"><span class="key">class</span> <span class="nam">RuleClassifier</span><span class="op">(</span><span class="nam">BaseOperator</span><span class="op">,</span> <span class="nam">BaseClassifier</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t89" href="#t89">89</a></span><span class="t">    <span class="str">"""Classification model."""</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t90" href="#t90">90</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t91" href="#t91">91</a></span><span class="t">    <span class="nam">__params_class__</span> <span class="op">=</span> <span class="nam">_ClassificationParams</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t92" href="#t92">92</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t93" href="#t93">93</a></span><span class="t">    <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span>  <span class="com"># pylint: disable=too-many-arguments,too-many-locals</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t94" href="#t94">94</a></span><span class="t">        <span class="nam">self</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t95" href="#t95">95</a></span><span class="t">        <span class="nam">minsupp_new</span><span class="op">:</span> <span class="nam">float</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'minsupp_new'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t96" href="#t96">96</a></span><span class="t">        <span class="nam">induction_measure</span><span class="op">:</span> <span class="nam">Measures</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'induction_measure'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t97" href="#t97">97</a></span><span class="t">        <span class="nam">pruning_measure</span><span class="op">:</span> <span class="nam">Union</span><span class="op">[</span><span class="nam">Measures</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t98" href="#t98">98</a></span><span class="t">                               <span class="nam">str</span><span class="op">]</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'pruning_measure'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t99" href="#t99">99</a></span><span class="t">        <span class="nam">voting_measure</span><span class="op">:</span> <span class="nam">Measures</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'voting_measure'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t100" href="#t100">100</a></span><span class="t">        <span class="nam">max_growing</span><span class="op">:</span> <span class="nam">float</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'max_growing'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t101" href="#t101">101</a></span><span class="t">        <span class="nam">enable_pruning</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'enable_pruning'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t102" href="#t102">102</a></span><span class="t">        <span class="nam">ignore_missing</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'ignore_missing'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t103" href="#t103">103</a></span><span class="t">        <span class="nam">max_uncovered_fraction</span><span class="op">:</span> <span class="nam">float</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'max_uncovered_fraction'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t104" href="#t104">104</a></span><span class="t">        <span class="nam">select_best_candidate</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'select_best_candidate'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t105" href="#t105">105</a></span><span class="t">        <span class="nam">complementary_conditions</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'complementary_conditions'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t106" href="#t106">106</a></span><span class="t">        <span class="nam">control_apriori_precision</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'control_apriori_precision'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t107" href="#t107">107</a></span><span class="t">        <span class="nam">max_rule_count</span><span class="op">:</span> <span class="nam">int</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'max_rule_count'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t108" href="#t108">108</a></span><span class="t">        <span class="nam">approximate_induction</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'approximate_induction'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t109" href="#t109">109</a></span><span class="t">        <span class="nam">approximate_bins_count</span><span class="op">:</span> <span class="nam">int</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'approximate_bins_count'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t110" href="#t110">110</a></span><span class="t">    <span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t111" href="#t111">111</a></span><span class="t">        <span class="str">"""</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t112" href="#t112">112</a></span><span class="t"><span class="str">        Parameters</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t113" href="#t113">113</a></span><span class="t"><span class="str">        ----------</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t114" href="#t114">114</a></span><span class="t"><span class="str">        minsupp_new : float = 5.0</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t115" href="#t115">115</a></span><span class="t"><span class="str">            a minimum number (or fraction, if value &lt; 1.0) of previously uncovered examples</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t116" href="#t116">116</a></span><span class="t"><span class="str">             to be covered by a new rule (positive examples for classification problems);</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t117" href="#t117">117</a></span><span class="t"><span class="str">             default: 5,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t118" href="#t118">118</a></span><span class="t"><span class="str">        induction_measure : :class:`rulekit.params.Measures` = :class:`rulekit.params.\</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t119" href="#t119">119</a></span><span class="t"><span class="str">            Measures.Correlation`</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t120" href="#t120">120</a></span><span class="t"><span class="str">            measure used during induction; default measure is correlation</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t121" href="#t121">121</a></span><span class="t"><span class="str">        pruning_measure : Union[:class:`rulekit.params.Measures`, str] = \</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t122" href="#t122">122</a></span><span class="t"><span class="str">            :class:`rulekit.params.Measures.Correlation`</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t123" href="#t123">123</a></span><span class="t"><span class="str">            measure used during pruning. Could be user defined (string), for example</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t124" href="#t124">124</a></span><span class="t"><span class="str">             :code:`2 * p / n`; default measure is correlation</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t125" href="#t125">125</a></span><span class="t"><span class="str">        voting_measure : :class:`rulekit.params.Measures` = \</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t126" href="#t126">126</a></span><span class="t"><span class="str">            :class:`rulekit.params.Measures.Correlation`</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t127" href="#t127">127</a></span><span class="t"><span class="str">            measure used during voting; default measure is correlation</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t128" href="#t128">128</a></span><span class="t"><span class="str">        max_growing : int = 0.0</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t129" href="#t129">129</a></span><span class="t"><span class="str">            non-negative integer representing maximum number of conditions which can be added</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t130" href="#t130">130</a></span><span class="t"><span class="str">            to the rule in the growing phase (use this parameter for large datasets if execution</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t131" href="#t131">131</a></span><span class="t"><span class="str">            time is prohibitive); 0 indicates no limit; default: 0,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t132" href="#t132">132</a></span><span class="t"><span class="str">        enable_pruning : bool = True</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t133" href="#t133">133</a></span><span class="t"><span class="str">            enable or disable pruning, default is True.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t134" href="#t134">134</a></span><span class="t"><span class="str">        ignore_missing : bool = False</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t135" href="#t135">135</a></span><span class="t"><span class="str">            boolean telling whether missing values should be ignored (by default, a missing value</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t136" href="#t136">136</a></span><span class="t"><span class="str">            of given attribute is always cconsidered as not fulfilling the condition build upon</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t137" href="#t137">137</a></span><span class="t"><span class="str">             that attribute); default: False.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t138" href="#t138">138</a></span><span class="t"><span class="str">        max_uncovered_fraction : float = 0.0</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t139" href="#t139">139</a></span><span class="t"><span class="str">            Floating-point number from [0,1] interval representing maximum fraction of examples</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t140" href="#t140">140</a></span><span class="t"><span class="str">            that may remain uncovered by the rule set, default: 0.0.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t141" href="#t141">141</a></span><span class="t"><span class="str">        select_best_candidate : bool = False</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t142" href="#t142">142</a></span><span class="t"><span class="str">            Flag determining if best candidate should be selected from growing phase; default:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t143" href="#t143">143</a></span><span class="t"><span class="str">            False.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t144" href="#t144">144</a></span><span class="t"><span class="str">        complementary_conditions : bool = False</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t145" href="#t145">145</a></span><span class="t"><span class="str">            If enabled, complementary conditions in the form a = !{value} for nominal attributes</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t146" href="#t146">146</a></span><span class="t"><span class="str">            are supported.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t147" href="#t147">147</a></span><span class="t"><span class="str">        control_apriori_precision : bool = True</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t148" href="#t148">148</a></span><span class="t"><span class="str">            When inducing classification rules, verify if candidate precision is higher than</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t149" href="#t149">149</a></span><span class="t"><span class="str">             apriori precision of the investigated class.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t150" href="#t150">150</a></span><span class="t"><span class="str">        max_rule_count : int = 0</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t151" href="#t151">151</a></span><span class="t"><span class="str">            Maximum number of rules to be generated (for classification data sets it applies</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t152" href="#t152">152</a></span><span class="t"><span class="str">             to a single class); 0 indicates no limit.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t153" href="#t153">153</a></span><span class="t"><span class="str">        approximate_induction: bool = False</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t154" href="#t154">154</a></span><span class="t"><span class="str">            Use an approximate induction heuristic which does not check all possible splits;</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t155" href="#t155">155</a></span><span class="t"><span class="str">            note: this is an experimental feature and currently works only for classification</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t156" href="#t156">156</a></span><span class="t"><span class="str">            data sets, results may change in future;</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t157" href="#t157">157</a></span><span class="t"><span class="str">        approximate_bins_count: int = 100</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t158" href="#t158">158</a></span><span class="t"><span class="str">            maximum number of bins for an attribute evaluated in the approximate induction.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t159" href="#t159">159</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t160" href="#t160">160</a></span><span class="t">        <span class="nam">BaseOperator</span><span class="op">.</span><span class="nam">__init__</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t161" href="#t161">161</a></span><span class="t">            <span class="nam">self</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t162" href="#t162">162</a></span><span class="t">            <span class="nam">minsupp_new</span><span class="op">=</span><span class="nam">minsupp_new</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t163" href="#t163">163</a></span><span class="t">            <span class="nam">induction_measure</span><span class="op">=</span><span class="nam">induction_measure</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t164" href="#t164">164</a></span><span class="t">            <span class="nam">pruning_measure</span><span class="op">=</span><span class="nam">pruning_measure</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t165" href="#t165">165</a></span><span class="t">            <span class="nam">voting_measure</span><span class="op">=</span><span class="nam">voting_measure</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t166" href="#t166">166</a></span><span class="t">            <span class="nam">max_growing</span><span class="op">=</span><span class="nam">max_growing</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t167" href="#t167">167</a></span><span class="t">            <span class="nam">enable_pruning</span><span class="op">=</span><span class="nam">enable_pruning</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t168" href="#t168">168</a></span><span class="t">            <span class="nam">ignore_missing</span><span class="op">=</span><span class="nam">ignore_missing</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t169" href="#t169">169</a></span><span class="t">            <span class="nam">max_uncovered_fraction</span><span class="op">=</span><span class="nam">max_uncovered_fraction</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t170" href="#t170">170</a></span><span class="t">            <span class="nam">select_best_candidate</span><span class="op">=</span><span class="nam">select_best_candidate</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t171" href="#t171">171</a></span><span class="t">            <span class="nam">complementary_conditions</span><span class="op">=</span><span class="nam">complementary_conditions</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t172" href="#t172">172</a></span><span class="t">            <span class="nam">control_apriori_precision</span><span class="op">=</span><span class="nam">control_apriori_precision</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t173" href="#t173">173</a></span><span class="t">            <span class="nam">max_rule_count</span><span class="op">=</span><span class="nam">max_rule_count</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t174" href="#t174">174</a></span><span class="t">            <span class="nam">approximate_induction</span><span class="op">=</span><span class="nam">approximate_induction</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t175" href="#t175">175</a></span><span class="t">            <span class="nam">approximate_bins_count</span><span class="op">=</span><span class="nam">approximate_bins_count</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t176" href="#t176">176</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t177" href="#t177">177</a></span><span class="t">        <span class="nam">BaseClassifier</span><span class="op">.</span><span class="nam">__init__</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t178" href="#t178">178</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_remap_to_numeric</span> <span class="op">=</span> <span class="key">False</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t179" href="#t179">179</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">label_unique_values</span> <span class="op">=</span> <span class="op">[</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t180" href="#t180">180</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">model</span><span class="op">:</span> <span class="nam">RuleSet</span><span class="op">[</span><span class="nam">ClassificationRule</span><span class="op">]</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t181" href="#t181">181</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t182" href="#t182">182</a></span><span class="t">    <span class="key">def</span> <span class="nam">_map_result</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">predicted_example_set</span><span class="op">)</span> <span class="op">-></span> <span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t183" href="#t183">183</a></span><span class="t">        <span class="nam">prediction</span><span class="op">:</span> <span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t184" href="#t184">184</a></span><span class="t">        <span class="key">if</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_remap_to_numeric</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t185" href="#t185">185</a></span><span class="t">            <span class="nam">prediction</span> <span class="op">=</span> <span class="nam">PredictionResultMapper</span><span class="op">.</span><span class="nam">map_to_numerical</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t186" href="#t186">186</a></span><span class="t">                <span class="nam">predicted_example_set</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t187" href="#t187">187</a></span><span class="t">        <span class="key">else</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t188" href="#t188">188</a></span><span class="t">            <span class="nam">prediction</span> <span class="op">=</span> <span class="nam">PredictionResultMapper</span><span class="op">.</span><span class="nam">map_to_nominal</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t189" href="#t189">189</a></span><span class="t">                <span class="nam">predicted_example_set</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t190" href="#t190">190</a></span><span class="t">        <span class="key">return</span> <span class="nam">prediction</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t191" href="#t191">191</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t192" href="#t192">192</a></span><span class="t">    <span class="key">def</span> <span class="nam">_map_confidence</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">predicted_example_set</span><span class="op">)</span> <span class="op">-></span> <span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t193" href="#t193">193</a></span><span class="t">        <span class="key">return</span> <span class="nam">PredictionResultMapper</span><span class="op">.</span><span class="nam">map_confidence</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t194" href="#t194">194</a></span><span class="t">            <span class="nam">predicted_example_set</span><span class="op">,</span> <span class="nam">self</span><span class="op">.</span><span class="nam">label_unique_values</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t195" href="#t195">195</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t196" href="#t196">196</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t197" href="#t197">197</a></span><span class="t">    <span class="key">def</span> <span class="nam">_get_unique_label_values</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">labels</span><span class="op">:</span> <span class="nam">Data</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t198" href="#t198">198</a></span><span class="t">        <span class="nam">tmp</span> <span class="op">=</span> <span class="op">{</span><span class="op">}</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t199" href="#t199">199</a></span><span class="t">        <span class="key">for</span> <span class="nam">label_value</span> <span class="key">in</span> <span class="nam">labels</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t200" href="#t200">200</a></span><span class="t">            <span class="nam">tmp</span><span class="op">[</span><span class="nam">label_value</span><span class="op">]</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t201" href="#t201">201</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">label_unique_values</span> <span class="op">=</span> <span class="nam">list</span><span class="op">(</span><span class="nam">tmp</span><span class="op">.</span><span class="nam">keys</span><span class="op">(</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t202" href="#t202">202</a></span><span class="t">        <span class="key">if</span> <span class="nam">len</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">label_unique_values</span><span class="op">)</span> <span class="op">></span> <span class="num">0</span> <span class="key">and</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">label_unique_values</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="op">,</span> <span class="nam">bytes</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t203" href="#t203">203</a></span><span class="t">            <span class="nam">self</span><span class="op">.</span><span class="nam">label_unique_values</span> <span class="op">=</span> <span class="op">[</span><span class="nam">item</span><span class="op">.</span><span class="nam">decode</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t204" href="#t204">204</a></span><span class="t">                <span class="str">'utf-8'</span><span class="op">)</span> <span class="key">for</span> <span class="nam">item</span> <span class="key">in</span> <span class="nam">self</span><span class="op">.</span><span class="nam">label_unique_values</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t205" href="#t205">205</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t206" href="#t206">206</a></span><span class="t">    <span class="key">def</span> <span class="nam">_prepare_labels</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">labels</span><span class="op">:</span> <span class="nam">Data</span><span class="op">)</span> <span class="op">-></span> <span class="nam">Data</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t207" href="#t207">207</a></span><span class="t">        <span class="key">if</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">labels</span><span class="op">,</span> <span class="op">(</span><span class="nam">pd</span><span class="op">.</span><span class="nam">DataFrame</span><span class="op">,</span> <span class="nam">pd</span><span class="op">.</span><span class="nam">Series</span><span class="op">)</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t208" href="#t208">208</a></span><span class="t">            <span class="key">if</span> <span class="nam">labels</span><span class="op">.</span><span class="nam">dtypes</span><span class="op">.</span><span class="nam">name</span> <span class="op">==</span> <span class="str">'bool'</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t209" href="#t209">209</a></span><span class="t">                <span class="key">return</span> <span class="nam">labels</span><span class="op">.</span><span class="nam">astype</span><span class="op">(</span><span class="nam">str</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t210" href="#t210">210</a></span><span class="t">            <span class="key">if</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">labels</span><span class="op">.</span><span class="nam">iloc</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="op">,</span> <span class="nam">Number</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t211" href="#t211">211</a></span><span class="t">                <span class="nam">self</span><span class="op">.</span><span class="nam">_remap_to_numeric</span> <span class="op">=</span> <span class="key">True</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t212" href="#t212">212</a></span><span class="t">                <span class="key">return</span> <span class="nam">labels</span><span class="op">.</span><span class="nam">astype</span><span class="op">(</span><span class="nam">str</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t213" href="#t213">213</a></span><span class="t">        <span class="key">else</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t214" href="#t214">214</a></span><span class="t">            <span class="key">if</span> <span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t215" href="#t215">215</a></span><span class="t">                <span class="nam">isinstance</span><span class="op">(</span><span class="nam">labels</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="op">,</span> <span class="nam">bool</span><span class="op">)</span> <span class="key">or</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t216" href="#t216">216</a></span><span class="t">                <span class="op">(</span><span class="nam">isinstance</span><span class="op">(</span><span class="nam">labels</span><span class="op">,</span> <span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span><span class="op">)</span> <span class="key">and</span> <span class="nam">labels</span><span class="op">.</span><span class="nam">dtype</span><span class="op">.</span><span class="nam">name</span> <span class="op">==</span> <span class="str">'bool'</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t217" href="#t217">217</a></span><span class="t">            <span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t218" href="#t218">218</a></span><span class="t">                <span class="key">return</span> <span class="nam">np</span><span class="op">.</span><span class="nam">array</span><span class="op">(</span><span class="nam">list</span><span class="op">(</span><span class="nam">map</span><span class="op">(</span><span class="nam">str</span><span class="op">,</span> <span class="nam">labels</span><span class="op">)</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t219" href="#t219">219</a></span><span class="t">            <span class="key">if</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">labels</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="op">,</span> <span class="nam">Number</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t220" href="#t220">220</a></span><span class="t">                <span class="nam">self</span><span class="op">.</span><span class="nam">_remap_to_numeric</span> <span class="op">=</span> <span class="key">True</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t221" href="#t221">221</a></span><span class="t">                <span class="key">return</span> <span class="nam">np</span><span class="op">.</span><span class="nam">array</span><span class="op">(</span><span class="nam">list</span><span class="op">(</span><span class="nam">map</span><span class="op">(</span><span class="nam">str</span><span class="op">,</span> <span class="nam">labels</span><span class="op">)</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t222" href="#t222">222</a></span><span class="t">        <span class="key">return</span> <span class="nam">labels</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t223" href="#t223">223</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t224" href="#t224">224</a></span><span class="t">    <span class="key">def</span> <span class="nam">fit</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">values</span><span class="op">:</span> <span class="nam">Data</span><span class="op">,</span> <span class="nam">labels</span><span class="op">:</span> <span class="nam">Data</span><span class="op">)</span> <span class="op">-></span> <span class="nam">RuleClassifier</span><span class="op">:</span>  <span class="com"># pylint: disable=arguments-differ</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t225" href="#t225">225</a></span><span class="t">        <span class="str">"""Train model on given dataset.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t226" href="#t226">226</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t227" href="#t227">227</a></span><span class="t"><span class="str">        Parameters</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t228" href="#t228">228</a></span><span class="t"><span class="str">        ----------</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t229" href="#t229">229</a></span><span class="t"><span class="str">        values : :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t230" href="#t230">230</a></span><span class="t"><span class="str">            attributes</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t231" href="#t231">231</a></span><span class="t"><span class="str">        labels : :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t232" href="#t232">232</a></span><span class="t"><span class="str">            labels</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t233" href="#t233">233</a></span><span class="t"><span class="str">        Returns</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t234" href="#t234">234</a></span><span class="t"><span class="str">        -------</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t235" href="#t235">235</a></span><span class="t"><span class="str">        self : RuleClassifier</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t236" href="#t236">236</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t237" href="#t237">237</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_get_unique_label_values</span><span class="op">(</span><span class="nam">labels</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t238" href="#t238">238</a></span><span class="t">        <span class="nam">labels</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_prepare_labels</span><span class="op">(</span><span class="nam">labels</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t239" href="#t239">239</a></span><span class="t">        <span class="nam">BaseOperator</span><span class="op">.</span><span class="nam">fit</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">values</span><span class="op">,</span> <span class="nam">labels</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t240" href="#t240">240</a></span><span class="t">        <span class="key">return</span> <span class="nam">self</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t241" href="#t241">241</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t242" href="#t242">242</a></span><span class="t">    <span class="key">def</span> <span class="nam">predict</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t243" href="#t243">243</a></span><span class="t">        <span class="nam">self</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t244" href="#t244">244</a></span><span class="t">        <span class="nam">values</span><span class="op">:</span> <span class="nam">Data</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t245" href="#t245">245</a></span><span class="t">        <span class="nam">return_metrics</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="key">False</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t246" href="#t246">246</a></span><span class="t">    <span class="op">)</span> <span class="op">-></span> <span class="nam">Union</span><span class="op">[</span><span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span><span class="op">,</span> <span class="nam">tuple</span><span class="op">[</span><span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span><span class="op">,</span> <span class="nam">ClassificationPredictionMetrics</span><span class="op">]</span><span class="op">]</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t247" href="#t247">247</a></span><span class="t">        <span class="str">"""Perform prediction and returns predicted labels.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t248" href="#t248">248</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t249" href="#t249">249</a></span><span class="t"><span class="str">        Parameters</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t250" href="#t250">250</a></span><span class="t"><span class="str">        ----------</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t251" href="#t251">251</a></span><span class="t"><span class="str">        values : :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t252" href="#t252">252</a></span><span class="t"><span class="str">            attributes</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t253" href="#t253">253</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t254" href="#t254">254</a></span><span class="t"><span class="str">        return_metrics: bool = False</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t255" href="#t255">255</a></span><span class="t"><span class="str">            Optional flag. If set to *True* method will calculate some additional model metrics.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t256" href="#t256">256</a></span><span class="t"><span class="str">             Method will then return tuple instead of just predicted labels.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t257" href="#t257">257</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t258" href="#t258">258</a></span><span class="t"><span class="str">        Returns</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t259" href="#t259">259</a></span><span class="t"><span class="str">        -------</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t260" href="#t260">260</a></span><span class="t"><span class="str">        result : Union[</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t261" href="#t261">261</a></span><span class="t"><span class="str">            np.ndarray,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t262" href="#t262">262</a></span><span class="t"><span class="str">            tuple[np.ndarray, :class:`rulekit.classification.ClassificationPredictionMetrics`]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t263" href="#t263">263</a></span><span class="t"><span class="str">        ]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t264" href="#t264">264</a></span><span class="t"><span class="str">        If *return_metrics* flag wasn't set it will return just prediction, otherwise a tuple</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t265" href="#t265">265</a></span><span class="t"><span class="str">        will be returned with first element being prediction and second one being metrics.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t266" href="#t266">266</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t267" href="#t267">267</a></span><span class="t">        <span class="nam">result_example_set</span> <span class="op">=</span> <span class="nam">BaseOperator</span><span class="op">.</span><span class="nam">predict</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">values</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t268" href="#t268">268</a></span><span class="t">        <span class="nam">y_pred</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_map_result</span><span class="op">(</span><span class="nam">result_example_set</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t269" href="#t269">269</a></span><span class="t">        <span class="key">if</span> <span class="nam">return_metrics</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t270" href="#t270">270</a></span><span class="t">            <span class="nam">metrics_values</span><span class="op">:</span> <span class="nam">dict</span> <span class="op">=</span> <span class="nam">BaseClassifier</span><span class="op">.</span><span class="nam">_calculate_prediction_metrics</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t271" href="#t271">271</a></span><span class="t">                <span class="nam">self</span><span class="op">,</span> <span class="nam">result_example_set</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t272" href="#t272">272</a></span><span class="t">            <span class="key">return</span> <span class="op">(</span><span class="nam">y_pred</span><span class="op">,</span> <span class="nam">metrics_values</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t273" href="#t273">273</a></span><span class="t">        <span class="key">return</span> <span class="nam">y_pred</span>&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t274" href="#t274">274</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t275" href="#t275">275</a></span><span class="t"><span class="str">        Returns</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t276" href="#t276">276</a></span><span class="t"><span class="str">        -------</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t277" href="#t277">277</a></span><span class="t"><span class="str">        result : Union[np.ndarray, tuple[np.ndarray, :class:`rulekit.classification.ClassificationPredictionMetrics`]]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t278" href="#t278">278</a></span><span class="t"><span class="str">            If *return_metrics* flag wasn't set it will return just probabilities matrix, otherwise</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t279" href="#t279">279</a></span><span class="t"><span class="str">            a tuple will be returned with first element being prediction and second one being metrics.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t280" href="#t280">280</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t281" href="#t281">281</a></span><span class="t">        <span class="nam">result_example_set</span> <span class="op">=</span> <span class="nam">BaseOperator</span><span class="op">.</span><span class="nam">predict</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">values</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t282" href="#t282">282</a></span><span class="t">        <span class="nam">mapped_result_example_set</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_map_confidence</span><span class="op">(</span><span class="nam">result_example_set</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t283" href="#t283">283</a></span><span class="t">        <span class="key">if</span> <span class="nam">return_metrics</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t284" href="#t284">284</a></span><span class="t">            <span class="nam">metrics_values</span><span class="op">:</span> <span class="nam">dict</span> <span class="op">=</span> <span class="nam">BaseClassifier</span><span class="op">.</span><span class="nam">_calculate_prediction_metrics</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t285" href="#t285">285</a></span><span class="t">                <span class="nam">self</span><span class="op">,</span> <span class="nam">result_example_set</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t286" href="#t286">286</a></span><span class="t">            <span class="key">return</span> <span class="op">(</span><span class="nam">mapped_result_example_set</span><span class="op">,</span> <span class="nam">metrics_values</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t287" href="#t287">287</a></span><span class="t">        <span class="key">return</span> <span class="nam">mapped_result_example_set</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t288" href="#t288">288</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t289" href="#t289">289</a></span><span class="t">    <span class="key">def</span> <span class="nam">score</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">values</span><span class="op">:</span> <span class="nam">Data</span><span class="op">,</span> <span class="nam">labels</span><span class="op">:</span> <span class="nam">Data</span><span class="op">)</span> <span class="op">-></span> <span class="nam">float</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t290" href="#t290">290</a></span><span class="t">        <span class="str">"""Return the accuracy on the given test data and labels.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t291" href="#t291">291</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t292" href="#t292">292</a></span><span class="t"><span class="str">        Parameters</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t293" href="#t293">293</a></span><span class="t"><span class="str">        ----------</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t294" href="#t294">294</a></span><span class="t"><span class="str">        values : :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t295" href="#t295">295</a></span><span class="t"><span class="str">            attributes</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t296" href="#t296">296</a></span><span class="t"><span class="str">        labels : :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t297" href="#t297">297</a></span><span class="t"><span class="str">            true labels</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t298" href="#t298">298</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t299" href="#t299">299</a></span><span class="t"><span class="str">        Returns</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t300" href="#t300">300</a></span><span class="t"><span class="str">        -------</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t301" href="#t301">301</a></span><span class="t"><span class="str">        score : float</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t302" href="#t302">302</a></span><span class="t"><span class="str">            Accuracy of self.predict(values) wrt. labels.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t303" href="#t303">303</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t304" href="#t304">304</a></span><span class="t">        <span class="nam">predicted_labels</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">predict</span><span class="op">(</span><span class="nam">values</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t305" href="#t305">305</a></span><span class="t">        <span class="key">return</span> <span class="nam">metrics</span><span class="op">.</span><span class="nam">accuracy_score</span><span class="op">(</span><span class="nam">labels</span><span class="op">,</span> <span class="nam">predicted_labels</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t306" href="#t306">306</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t307" href="#t307">307</a></span><span class="t">    <span class="key">def</span> <span class="nam">__getstate__</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">dict</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t308" href="#t308">308</a></span><span class="t">        <span class="key">return</span> <span class="op">{</span><span class="op">**</span><span class="nam">BaseOperator</span><span class="op">.</span><span class="nam">__getstate__</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">,</span> <span class="op">**</span><span class="op">{</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t309" href="#t309">309</a></span><span class="t">            <span class="str">'label_unique_values'</span><span class="op">:</span> <span class="nam">self</span><span class="op">.</span><span class="nam">label_unique_values</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t310" href="#t310">310</a></span><span class="t">            <span class="str">'_remap_to_numeric'</span><span class="op">:</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_remap_to_numeric</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t311" href="#t311">311</a></span><span class="t">        <span class="op">}</span><span class="op">}</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t312" href="#t312">312</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t313" href="#t313">313</a></span><span class="t">    <span class="key">def</span> <span class="nam">__setstate__</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">state</span><span class="op">:</span> <span class="nam">dict</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t314" href="#t314">314</a></span><span class="t">        <span class="nam">BaseOperator</span><span class="op">.</span><span class="nam">__setstate__</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">state</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t315" href="#t315">315</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_init_classification_rule_performance_classes</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t316" href="#t316">316</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">label_unique_values</span> <span class="op">=</span> <span class="nam">state</span><span class="op">[</span><span class="str">'label_unique_values'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t317" href="#t317">317</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_remap_to_numeric</span> <span class="op">=</span> <span class="nam">state</span><span class="op">[</span><span class="str">'_remap_to_numeric'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t275" href="#t275">275</a></span><span class="t">    <span class="key">def</span> <span class="nam">predict_proba</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t276" href="#t276">276</a></span><span class="t">        <span class="nam">self</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t277" href="#t277">277</a></span><span class="t">        <span class="nam">values</span><span class="op">:</span> <span class="nam">Data</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t278" href="#t278">278</a></span><span class="t">        <span class="nam">return_metrics</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="key">False</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t279" href="#t279">279</a></span><span class="t">    <span class="op">)</span> <span class="op">-></span> <span class="nam">Union</span><span class="op">[</span><span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span><span class="op">,</span> <span class="nam">tuple</span><span class="op">[</span><span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span><span class="op">,</span> <span class="nam">ClassificationPredictionMetrics</span><span class="op">]</span><span class="op">]</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t280" href="#t280">280</a></span><span class="t">        <span class="str">"""Perform prediction and returns class probabilities for each example.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t281" href="#t281">281</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t282" href="#t282">282</a></span><span class="t"><span class="str">        Parameters</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t283" href="#t283">283</a></span><span class="t"><span class="str">        ----------</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t284" href="#t284">284</a></span><span class="t"><span class="str">        values : :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t285" href="#t285">285</a></span><span class="t"><span class="str">            attributes</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t286" href="#t286">286</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t287" href="#t287">287</a></span><span class="t"><span class="str">        return_metrics: bool = False</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t288" href="#t288">288</a></span><span class="t"><span class="str">            Optional flag. If set to *True* method will calculate some additional model metrics.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t289" href="#t289">289</a></span><span class="t"><span class="str">             Method will then return tuple instead of just probabilities.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t290" href="#t290">290</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t291" href="#t291">291</a></span><span class="t"><span class="str">        Returns</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t292" href="#t292">292</a></span><span class="t"><span class="str">        -------</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t293" href="#t293">293</a></span><span class="t"><span class="str">        result :</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t294" href="#t294">294</a></span><span class="t"><span class="str">        Union[</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t295" href="#t295">295</a></span><span class="t"><span class="str">            np.ndarray,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t296" href="#t296">296</a></span><span class="t"><span class="str">            tuple[np.ndarray, :class:`rulekit.classification.ClassificationPredictionMetrics`]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t297" href="#t297">297</a></span><span class="t"><span class="str">        ]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t298" href="#t298">298</a></span><span class="t"><span class="str">        If *return_metrics* flag wasn't set it will return just probabilities matrix, otherwise</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t299" href="#t299">299</a></span><span class="t"><span class="str">        a tuple will be returned with first element being prediction and second one being metrics.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t300" href="#t300">300</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t301" href="#t301">301</a></span><span class="t">        <span class="nam">result_example_set</span> <span class="op">=</span> <span class="nam">BaseOperator</span><span class="op">.</span><span class="nam">predict</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">values</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t302" href="#t302">302</a></span><span class="t">        <span class="nam">mapped_result_example_set</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_map_confidence</span><span class="op">(</span><span class="nam">result_example_set</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t303" href="#t303">303</a></span><span class="t">        <span class="key">if</span> <span class="nam">return_metrics</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t304" href="#t304">304</a></span><span class="t">            <span class="nam">metrics_values</span><span class="op">:</span> <span class="nam">dict</span> <span class="op">=</span> <span class="nam">BaseClassifier</span><span class="op">.</span><span class="nam">_calculate_prediction_metrics</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t305" href="#t305">305</a></span><span class="t">                <span class="nam">self</span><span class="op">,</span> <span class="nam">result_example_set</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t306" href="#t306">306</a></span><span class="t">            <span class="key">return</span> <span class="op">(</span><span class="nam">mapped_result_example_set</span><span class="op">,</span> <span class="nam">metrics_values</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t307" href="#t307">307</a></span><span class="t">        <span class="key">return</span> <span class="nam">mapped_result_example_set</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t308" href="#t308">308</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t309" href="#t309">309</a></span><span class="t">    <span class="key">def</span> <span class="nam">score</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">values</span><span class="op">:</span> <span class="nam">Data</span><span class="op">,</span> <span class="nam">labels</span><span class="op">:</span> <span class="nam">Data</span><span class="op">)</span> <span class="op">-></span> <span class="nam">float</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t310" href="#t310">310</a></span><span class="t">        <span class="str">"""Return the accuracy on the given test data and labels.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t311" href="#t311">311</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t312" href="#t312">312</a></span><span class="t"><span class="str">        Parameters</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t313" href="#t313">313</a></span><span class="t"><span class="str">        ----------</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t314" href="#t314">314</a></span><span class="t"><span class="str">        values : :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t315" href="#t315">315</a></span><span class="t"><span class="str">            attributes</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t316" href="#t316">316</a></span><span class="t"><span class="str">        labels : :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t317" href="#t317">317</a></span><span class="t"><span class="str">            true labels</span>&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t318" href="#t318">318</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t319" href="#t319">319</a></span><span class="t">    <span class="key">def</span> <span class="nam">_get_problem_type</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">ProblemType</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t320" href="#t320">320</a></span><span class="t">        <span class="key">return</span> <span class="nam">ProblemType</span><span class="op">.</span><span class="nam">CLASSIFICATION</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t321" href="#t321">321</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t322" href="#t322">322</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t323" href="#t323">323</a></span><span class="t"><span class="key">class</span> <span class="nam">ExpertRuleClassifier</span><span class="op">(</span><span class="nam">ExpertKnowledgeOperator</span><span class="op">,</span> <span class="nam">RuleClassifier</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t324" href="#t324">324</a></span><span class="t">    <span class="str">"""Classification model using expert knowledge."""</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t325" href="#t325">325</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t326" href="#t326">326</a></span><span class="t">    <span class="nam">__params_class__</span> <span class="op">=</span> <span class="nam">_ClassificationParams</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t327" href="#t327">327</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t328" href="#t328">328</a></span><span class="t">    <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span>  <span class="com"># pylint: disable=too-many-arguments,too-many-locals</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t329" href="#t329">329</a></span><span class="t">        <span class="nam">self</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t330" href="#t330">330</a></span><span class="t">        <span class="nam">minsupp_new</span><span class="op">:</span> <span class="nam">float</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'minsupp_new'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t331" href="#t331">331</a></span><span class="t">        <span class="nam">induction_measure</span><span class="op">:</span> <span class="nam">Measures</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'induction_measure'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t332" href="#t332">332</a></span><span class="t">        <span class="nam">pruning_measure</span><span class="op">:</span> <span class="nam">Union</span><span class="op">[</span><span class="nam">Measures</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t333" href="#t333">333</a></span><span class="t">                               <span class="nam">str</span><span class="op">]</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'pruning_measure'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t334" href="#t334">334</a></span><span class="t">        <span class="nam">voting_measure</span><span class="op">:</span> <span class="nam">Measures</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'voting_measure'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t335" href="#t335">335</a></span><span class="t">        <span class="nam">max_growing</span><span class="op">:</span> <span class="nam">float</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'max_growing'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t336" href="#t336">336</a></span><span class="t">        <span class="nam">enable_pruning</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'enable_pruning'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t337" href="#t337">337</a></span><span class="t">        <span class="nam">ignore_missing</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'ignore_missing'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t338" href="#t338">338</a></span><span class="t">        <span class="nam">max_uncovered_fraction</span><span class="op">:</span> <span class="nam">float</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'max_uncovered_fraction'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t339" href="#t339">339</a></span><span class="t">        <span class="nam">select_best_candidate</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'select_best_candidate'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t340" href="#t340">340</a></span><span class="t">        <span class="nam">complementary_conditions</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'complementary_conditions'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t341" href="#t341">341</a></span><span class="t">        <span class="nam">control_apriori_precision</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'control_apriori_precision'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t342" href="#t342">342</a></span><span class="t">        <span class="nam">max_rule_count</span><span class="op">:</span> <span class="nam">int</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'max_rule_count'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t343" href="#t343">343</a></span><span class="t">        <span class="nam">approximate_induction</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'approximate_induction'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t344" href="#t344">344</a></span><span class="t">        <span class="nam">approximate_bins_count</span><span class="op">:</span> <span class="nam">int</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'approximate_bins_count'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t319" href="#t319">319</a></span><span class="t"><span class="str">        Returns</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t320" href="#t320">320</a></span><span class="t"><span class="str">        -------</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t321" href="#t321">321</a></span><span class="t"><span class="str">        score : float</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t322" href="#t322">322</a></span><span class="t"><span class="str">            Accuracy of self.predict(values) wrt. labels.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t323" href="#t323">323</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t324" href="#t324">324</a></span><span class="t">        <span class="nam">predicted_labels</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">predict</span><span class="op">(</span><span class="nam">values</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t325" href="#t325">325</a></span><span class="t">        <span class="key">return</span> <span class="nam">metrics</span><span class="op">.</span><span class="nam">accuracy_score</span><span class="op">(</span><span class="nam">labels</span><span class="op">,</span> <span class="nam">predicted_labels</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t326" href="#t326">326</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t327" href="#t327">327</a></span><span class="t">    <span class="key">def</span> <span class="nam">__getstate__</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">dict</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t328" href="#t328">328</a></span><span class="t">        <span class="key">return</span> <span class="op">{</span><span class="op">**</span><span class="nam">BaseOperator</span><span class="op">.</span><span class="nam">__getstate__</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">,</span> <span class="op">**</span><span class="op">{</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t329" href="#t329">329</a></span><span class="t">            <span class="str">'label_unique_values'</span><span class="op">:</span> <span class="nam">self</span><span class="op">.</span><span class="nam">label_unique_values</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t330" href="#t330">330</a></span><span class="t">            <span class="str">'_remap_to_numeric'</span><span class="op">:</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_remap_to_numeric</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t331" href="#t331">331</a></span><span class="t">        <span class="op">}</span><span class="op">}</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t332" href="#t332">332</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t333" href="#t333">333</a></span><span class="t">    <span class="key">def</span> <span class="nam">__setstate__</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">state</span><span class="op">:</span> <span class="nam">dict</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t334" href="#t334">334</a></span><span class="t">        <span class="nam">BaseOperator</span><span class="op">.</span><span class="nam">__setstate__</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">state</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t335" href="#t335">335</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_init_classification_rule_performance_classes</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t336" href="#t336">336</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">label_unique_values</span> <span class="op">=</span> <span class="nam">state</span><span class="op">[</span><span class="str">'label_unique_values'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t337" href="#t337">337</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_remap_to_numeric</span> <span class="op">=</span> <span class="nam">state</span><span class="op">[</span><span class="str">'_remap_to_numeric'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t338" href="#t338">338</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t339" href="#t339">339</a></span><span class="t">    <span class="key">def</span> <span class="nam">_get_problem_type</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">ProblemType</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t340" href="#t340">340</a></span><span class="t">        <span class="key">return</span> <span class="nam">ProblemType</span><span class="op">.</span><span class="nam">CLASSIFICATION</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t341" href="#t341">341</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t342" href="#t342">342</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t343" href="#t343">343</a></span><span class="t"><span class="key">class</span> <span class="nam">ExpertRuleClassifier</span><span class="op">(</span><span class="nam">ExpertKnowledgeOperator</span><span class="op">,</span> <span class="nam">RuleClassifier</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t344" href="#t344">344</a></span><span class="t">    <span class="str">"""Classification model using expert knowledge."""</span>&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t345" href="#t345">345</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t346" href="#t346">346</a></span><span class="t">        <span class="nam">extend_using_preferred</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'extend_using_preferred'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t347" href="#t347">347</a></span><span class="t">        <span class="nam">extend_using_automatic</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'extend_using_automatic'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t348" href="#t348">348</a></span><span class="t">        <span class="nam">induce_using_preferred</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'induce_using_preferred'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t349" href="#t349">349</a></span><span class="t">        <span class="nam">induce_using_automatic</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'induce_using_automatic'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t350" href="#t350">350</a></span><span class="t">        <span class="nam">consider_other_classes</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'consider_other_classes'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t351" href="#t351">351</a></span><span class="t">        <span class="nam">preferred_conditions_per_rule</span><span class="op">:</span> <span class="nam">int</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t352" href="#t352">352</a></span><span class="t">            <span class="str">'preferred_conditions_per_rule'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t353" href="#t353">353</a></span><span class="t">        <span class="nam">preferred_attributes_per_rule</span><span class="op">:</span> <span class="nam">int</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t354" href="#t354">354</a></span><span class="t">            <span class="str">'preferred_attributes_per_rule'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t355" href="#t355">355</a></span><span class="t">    <span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t356" href="#t356">356</a></span><span class="t">        <span class="str">"""</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t357" href="#t357">357</a></span><span class="t"><span class="str">        Parameters</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t358" href="#t358">358</a></span><span class="t"><span class="str">        ----------</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t359" href="#t359">359</a></span><span class="t"><span class="str">        minsupp_new : float = 5.0</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t360" href="#t360">360</a></span><span class="t"><span class="str">            a minimum number (or fraction, if value &lt; 1.0) of previously uncovered examples</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t361" href="#t361">361</a></span><span class="t"><span class="str">             to be covered by a new rule (positive examples for classification problems); default: 5,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t362" href="#t362">362</a></span><span class="t"><span class="str">        induction_measure : :class:`rulekit.params.Measures` = \</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t363" href="#t363">363</a></span><span class="t"><span class="str">            :class:`rulekit.params.Measures.Correlation`</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t364" href="#t364">364</a></span><span class="t"><span class="str">            measure used during induction; default measure is correlation</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t365" href="#t365">365</a></span><span class="t"><span class="str">        pruning_measure : Union[:class:`rulekit.params.Measures`, str] = \</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t366" href="#t366">366</a></span><span class="t"><span class="str">            :class:`rulekit.params.Measures.Correlation`</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t367" href="#t367">367</a></span><span class="t"><span class="str">            measure used during pruning. Could be user defined (string), for example</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t368" href="#t368">368</a></span><span class="t"><span class="str">             :code:`2 * p / n`; default measure is correlation</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t369" href="#t369">369</a></span><span class="t"><span class="str">        voting_measure : :class:`rulekit.params.Measures` = \</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t370" href="#t370">370</a></span><span class="t"><span class="str">            :class:`rulekit.params.Measures.Correlation`</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t371" href="#t371">371</a></span><span class="t"><span class="str">            measure used during voting; default measure is correlation</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t372" href="#t372">372</a></span><span class="t"><span class="str">        max_growing : int = 0.0</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t373" href="#t373">373</a></span><span class="t"><span class="str">            non-negative integer representing maximum number of conditions which can be added to</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t374" href="#t374">374</a></span><span class="t"><span class="str">            the rule in the growing phase (use this parameter for large datasets if execution time</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t375" href="#t375">375</a></span><span class="t"><span class="str">            is prohibitive); 0 indicates no limit; default: 0,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t376" href="#t376">376</a></span><span class="t"><span class="str">        enable_pruning : bool = True</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t377" href="#t377">377</a></span><span class="t"><span class="str">            enable or disable pruning, default is True.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t378" href="#t378">378</a></span><span class="t"><span class="str">        ignore_missing : bool = False</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t379" href="#t379">379</a></span><span class="t"><span class="str">            boolean telling whether missing values should be ignored (by default, a missing value</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t380" href="#t380">380</a></span><span class="t"><span class="str">            of given attribute is always considered as not fulfilling the condition build upon</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t381" href="#t381">381</a></span><span class="t"><span class="str">             that attribute); default: False.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t382" href="#t382">382</a></span><span class="t"><span class="str">        max_uncovered_fraction : float = 0.0</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t383" href="#t383">383</a></span><span class="t"><span class="str">            Floating-point number from [0,1] interval representing maximum fraction of examples</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t384" href="#t384">384</a></span><span class="t"><span class="str">            that may remain uncovered by the rule set, default: 0.0.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t385" href="#t385">385</a></span><span class="t"><span class="str">        select_best_candidate : bool = False</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t386" href="#t386">386</a></span><span class="t"><span class="str">            Flag determining if best candidate should be selected from growing phase; default:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t387" href="#t387">387</a></span><span class="t"><span class="str">             False.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t388" href="#t388">388</a></span><span class="t"><span class="str">        complementary_conditions : bool = False</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t389" href="#t389">389</a></span><span class="t"><span class="str">            If enabled, complementary conditions in the form a = !{value} for nominal attributes</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t390" href="#t390">390</a></span><span class="t"><span class="str">            are supported.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t391" href="#t391">391</a></span><span class="t"><span class="str">        control_apriori_precision : bool = True</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t392" href="#t392">392</a></span><span class="t"><span class="str">            When inducing classification rules, verify if candidate precision is higher than</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t393" href="#t393">393</a></span><span class="t"><span class="str">             apriori precision of the investigated class.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t394" href="#t394">394</a></span><span class="t"><span class="str">        max_rule_count : int = 0</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t395" href="#t395">395</a></span><span class="t"><span class="str">            Maximum number of rules to be generated (for classification data sets it applies</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t396" href="#t396">396</a></span><span class="t"><span class="str">             to a single class); 0 indicates no limit.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t397" href="#t397">397</a></span><span class="t"><span class="str">        approximate_induction: bool = False</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t398" href="#t398">398</a></span><span class="t"><span class="str">            Use an approximate induction heuristic which does not check all possible splits;</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t399" href="#t399">399</a></span><span class="t"><span class="str">            note: this is an experimental feature and currently works only for classification</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t400" href="#t400">400</a></span><span class="t"><span class="str">            data sets, results may change in future;</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t401" href="#t401">401</a></span><span class="t"><span class="str">        approximate_bins_count: int = 100</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t402" href="#t402">402</a></span><span class="t"><span class="str">            maximum number of bins for an attribute evaluated in the approximate induction.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t403" href="#t403">403</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t404" href="#t404">404</a></span><span class="t"><span class="str">        extend_using_preferred : bool = False</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t405" href="#t405">405</a></span><span class="t"><span class="str">            boolean indicating whether initial rules should be extended with a use of preferred</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t406" href="#t406">406</a></span><span class="t"><span class="str">            conditions and attributes; default is False</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t407" href="#t407">407</a></span><span class="t"><span class="str">        extend_using_automatic : bool = False</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t408" href="#t408">408</a></span><span class="t"><span class="str">            boolean indicating whether initial rules should be extended with a use of automatic</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t409" href="#t409">409</a></span><span class="t"><span class="str">             conditions and attributes; default is False</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t410" href="#t410">410</a></span><span class="t"><span class="str">        induce_using_preferred : bool = False</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t411" href="#t411">411</a></span><span class="t"><span class="str">            boolean indicating whether new rules should be induced with a use of preferred</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t412" href="#t412">412</a></span><span class="t"><span class="str">             conditions and attributes; default is False</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t413" href="#t413">413</a></span><span class="t"><span class="str">        induce_using_automatic : bool = False</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t414" href="#t414">414</a></span><span class="t"><span class="str">            boolean indicating whether new rules should be induced with a use of automatic</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t415" href="#t415">415</a></span><span class="t"><span class="str">             conditions and attributes; default is False</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t416" href="#t416">416</a></span><span class="t"><span class="str">        consider_other_classes : bool = False</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t417" href="#t417">417</a></span><span class="t"><span class="str">            boolean indicating whether automatic induction should be performed for classes for</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t418" href="#t418">418</a></span><span class="t"><span class="str">              which no user's knowledge has been defined (classification only); default is False.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t419" href="#t419">419</a></span><span class="t"><span class="str">        preferred_conditions_per_rule : int = None</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t420" href="#t420">420</a></span><span class="t"><span class="str">            maximum number of preferred conditions per rule; default: unlimited,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t421" href="#t421">421</a></span><span class="t"><span class="str">        preferred_attributes_per_rule : int = None</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t422" href="#t422">422</a></span><span class="t"><span class="str">            maximum number of preferred attributes per rule; default: unlimited.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t423" href="#t423">423</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t424" href="#t424">424</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_remap_to_numeric</span> <span class="op">=</span> <span class="key">False</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t425" href="#t425">425</a></span><span class="t">        <span class="nam">RuleClassifier</span><span class="op">.</span><span class="nam">__init__</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t426" href="#t426">426</a></span><span class="t">            <span class="nam">self</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t427" href="#t427">427</a></span><span class="t">            <span class="nam">minsupp_new</span><span class="op">=</span><span class="nam">minsupp_new</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t428" href="#t428">428</a></span><span class="t">            <span class="nam">induction_measure</span><span class="op">=</span><span class="nam">induction_measure</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t429" href="#t429">429</a></span><span class="t">            <span class="nam">pruning_measure</span><span class="op">=</span><span class="nam">pruning_measure</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t430" href="#t430">430</a></span><span class="t">            <span class="nam">voting_measure</span><span class="op">=</span><span class="nam">voting_measure</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t431" href="#t431">431</a></span><span class="t">            <span class="nam">max_growing</span><span class="op">=</span><span class="nam">max_growing</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t432" href="#t432">432</a></span><span class="t">            <span class="nam">enable_pruning</span><span class="op">=</span><span class="nam">enable_pruning</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t433" href="#t433">433</a></span><span class="t">            <span class="nam">ignore_missing</span><span class="op">=</span><span class="nam">ignore_missing</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t434" href="#t434">434</a></span><span class="t">            <span class="nam">max_uncovered_fraction</span><span class="op">=</span><span class="nam">max_uncovered_fraction</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t435" href="#t435">435</a></span><span class="t">            <span class="nam">select_best_candidate</span><span class="op">=</span><span class="nam">select_best_candidate</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t436" href="#t436">436</a></span><span class="t">            <span class="nam">complementary_conditions</span><span class="op">=</span><span class="nam">complementary_conditions</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t437" href="#t437">437</a></span><span class="t">            <span class="nam">control_apriori_precision</span><span class="op">=</span><span class="nam">control_apriori_precision</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t438" href="#t438">438</a></span><span class="t">            <span class="nam">max_rule_count</span><span class="op">=</span><span class="nam">max_rule_count</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t439" href="#t439">439</a></span><span class="t">            <span class="nam">approximate_induction</span><span class="op">=</span><span class="nam">approximate_induction</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t440" href="#t440">440</a></span><span class="t">            <span class="nam">approximate_bins_count</span><span class="op">=</span><span class="nam">approximate_bins_count</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t441" href="#t441">441</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t442" href="#t442">442</a></span><span class="t">        <span class="nam">ExpertKnowledgeOperator</span><span class="op">.</span><span class="nam">__init__</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t443" href="#t443">443</a></span><span class="t">            <span class="nam">self</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t444" href="#t444">444</a></span><span class="t">            <span class="nam">minsupp_new</span><span class="op">=</span><span class="nam">minsupp_new</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t445" href="#t445">445</a></span><span class="t">            <span class="nam">induction_measure</span><span class="op">=</span><span class="nam">induction_measure</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t446" href="#t446">446</a></span><span class="t">            <span class="nam">pruning_measure</span><span class="op">=</span><span class="nam">pruning_measure</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t447" href="#t447">447</a></span><span class="t">            <span class="nam">voting_measure</span><span class="op">=</span><span class="nam">voting_measure</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t448" href="#t448">448</a></span><span class="t">            <span class="nam">max_growing</span><span class="op">=</span><span class="nam">max_growing</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t449" href="#t449">449</a></span><span class="t">            <span class="nam">enable_pruning</span><span class="op">=</span><span class="nam">enable_pruning</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t450" href="#t450">450</a></span><span class="t">            <span class="nam">ignore_missing</span><span class="op">=</span><span class="nam">ignore_missing</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t451" href="#t451">451</a></span><span class="t">            <span class="nam">max_uncovered_fraction</span><span class="op">=</span><span class="nam">max_uncovered_fraction</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t452" href="#t452">452</a></span><span class="t">            <span class="nam">select_best_candidate</span><span class="op">=</span><span class="nam">select_best_candidate</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t453" href="#t453">453</a></span><span class="t">            <span class="nam">complementary_conditions</span><span class="op">=</span><span class="nam">complementary_conditions</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t454" href="#t454">454</a></span><span class="t">            <span class="nam">extend_using_preferred</span><span class="op">=</span><span class="nam">extend_using_preferred</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t455" href="#t455">455</a></span><span class="t">            <span class="nam">extend_using_automatic</span><span class="op">=</span><span class="nam">extend_using_automatic</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t456" href="#t456">456</a></span><span class="t">            <span class="nam">induce_using_preferred</span><span class="op">=</span><span class="nam">induce_using_preferred</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t457" href="#t457">457</a></span><span class="t">            <span class="nam">induce_using_automatic</span><span class="op">=</span><span class="nam">induce_using_automatic</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t458" href="#t458">458</a></span><span class="t">            <span class="nam">consider_other_classes</span><span class="op">=</span><span class="nam">consider_other_classes</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t459" href="#t459">459</a></span><span class="t">            <span class="nam">preferred_conditions_per_rule</span><span class="op">=</span><span class="nam">preferred_conditions_per_rule</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t460" href="#t460">460</a></span><span class="t">            <span class="nam">preferred_attributes_per_rule</span><span class="op">=</span><span class="nam">preferred_attributes_per_rule</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t461" href="#t461">461</a></span><span class="t">            <span class="nam">control_apriori_precision</span><span class="op">=</span><span class="nam">control_apriori_precision</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t462" href="#t462">462</a></span><span class="t">            <span class="nam">max_rule_count</span><span class="op">=</span><span class="nam">max_rule_count</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t463" href="#t463">463</a></span><span class="t">            <span class="nam">approximate_induction</span><span class="op">=</span><span class="nam">approximate_induction</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t464" href="#t464">464</a></span><span class="t">            <span class="nam">approximate_bins_count</span><span class="op">=</span><span class="nam">approximate_bins_count</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t465" href="#t465">465</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t466" href="#t466">466</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">model</span><span class="op">:</span> <span class="nam">RuleSet</span><span class="op">[</span><span class="nam">ClassificationRule</span><span class="op">]</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t467" href="#t467">467</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t468" href="#t468">468</a></span><span class="t">    <span class="key">def</span> <span class="nam">fit</span><span class="op">(</span>  <span class="com"># pylint: disable=arguments-differ,too-many-arguments</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t469" href="#t469">469</a></span><span class="t">        <span class="nam">self</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t470" href="#t470">470</a></span><span class="t">        <span class="nam">values</span><span class="op">:</span> <span class="nam">Data</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t471" href="#t471">471</a></span><span class="t">        <span class="nam">labels</span><span class="op">:</span> <span class="nam">Data</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t472" href="#t472">472</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t473" href="#t473">473</a></span><span class="t">        <span class="nam">expert_rules</span><span class="op">:</span> <span class="nam">list</span><span class="op">[</span><span class="nam">Union</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">tuple</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">str</span><span class="op">]</span><span class="op">]</span><span class="op">]</span> <span class="op">=</span> <span class="key">None</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t474" href="#t474">474</a></span><span class="t">        <span class="nam">expert_preferred_conditions</span><span class="op">:</span> <span class="nam">list</span><span class="op">[</span><span class="nam">Union</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">tuple</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">str</span><span class="op">]</span><span class="op">]</span><span class="op">]</span> <span class="op">=</span> <span class="key">None</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t475" href="#t475">475</a></span><span class="t">        <span class="nam">expert_forbidden_conditions</span><span class="op">:</span> <span class="nam">list</span><span class="op">[</span><span class="nam">Union</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">tuple</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">str</span><span class="op">]</span><span class="op">]</span><span class="op">]</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t476" href="#t476">476</a></span><span class="t">    <span class="op">)</span> <span class="op">-></span> <span class="nam">ExpertRuleClassifier</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t477" href="#t477">477</a></span><span class="t">        <span class="str">"""Train model on given dataset.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t478" href="#t478">478</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t479" href="#t479">479</a></span><span class="t"><span class="str">        Parameters</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t480" href="#t480">480</a></span><span class="t"><span class="str">        ----------</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t481" href="#t481">481</a></span><span class="t"><span class="str">        values : :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t482" href="#t482">482</a></span><span class="t"><span class="str">            attributes</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t483" href="#t483">483</a></span><span class="t"><span class="str">        labels : :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t484" href="#t484">484</a></span><span class="t"><span class="str">            labels</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t485" href="#t485">485</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t486" href="#t486">486</a></span><span class="t"><span class="str">        expert_rules : List[Union[str, Tuple[str, str]]]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t487" href="#t487">487</a></span><span class="t"><span class="str">            set of initial rules, either passed as a list of strings representing rules or as list</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t488" href="#t488">488</a></span><span class="t"><span class="str">            of tuples where first element is name of the rule and second one is rule string.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t489" href="#t489">489</a></span><span class="t"><span class="str">        expert_preferred_conditions : List[Union[str, Tuple[str, str]]]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t490" href="#t490">490</a></span><span class="t"><span class="str">            multiset of preferred conditions (used also for specifying preferred attributes by</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t491" href="#t491">491</a></span><span class="t"><span class="str">            using special value Any). Either passed as a list of strings representing rules or as</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t492" href="#t492">492</a></span><span class="t"><span class="str">            list of tuples where first element is name of the rule and second one is rule string.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t493" href="#t493">493</a></span><span class="t"><span class="str">        expert_forbidden_conditions : List[Union[str, Tuple[str, str]]]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t494" href="#t494">494</a></span><span class="t"><span class="str">            set of forbidden conditions (used also for specifying forbidden attributes by using</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t495" href="#t495">495</a></span><span class="t"><span class="str">             special valye Any). Either passed as a list of strings representing rules or as list</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t496" href="#t496">496</a></span><span class="t"><span class="str">            of tuples where first element is name of the rule and second one is rule string.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t497" href="#t497">497</a></span><span class="t"><span class="str">        Returns</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t498" href="#t498">498</a></span><span class="t"><span class="str">        -------</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t499" href="#t499">499</a></span><span class="t"><span class="str">        self : ExpertRuleClassifier</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t500" href="#t500">500</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t501" href="#t501">501</a></span><span class="t">        <span class="key">if</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">labels</span><span class="op">,</span> <span class="op">(</span><span class="nam">pd</span><span class="op">.</span><span class="nam">DataFrame</span><span class="op">,</span> <span class="nam">pd</span><span class="op">.</span><span class="nam">Series</span><span class="op">)</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t502" href="#t502">502</a></span><span class="t">            <span class="key">if</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">labels</span><span class="op">.</span><span class="nam">iloc</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="op">,</span> <span class="nam">Number</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t503" href="#t503">503</a></span><span class="t">                <span class="nam">self</span><span class="op">.</span><span class="nam">_remap_to_numeric</span> <span class="op">=</span> <span class="key">True</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t504" href="#t504">504</a></span><span class="t">                <span class="nam">labels</span> <span class="op">=</span> <span class="nam">labels</span><span class="op">.</span><span class="nam">astype</span><span class="op">(</span><span class="nam">str</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t505" href="#t505">505</a></span><span class="t">        <span class="key">else</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t506" href="#t506">506</a></span><span class="t">            <span class="key">if</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">labels</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="op">,</span> <span class="nam">Number</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t507" href="#t507">507</a></span><span class="t">                <span class="nam">self</span><span class="op">.</span><span class="nam">_remap_to_numeric</span> <span class="op">=</span> <span class="key">True</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t508" href="#t508">508</a></span><span class="t">                <span class="nam">labels</span> <span class="op">=</span> <span class="nam">list</span><span class="op">(</span><span class="nam">map</span><span class="op">(</span><span class="nam">str</span><span class="op">,</span> <span class="nam">labels</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t509" href="#t509">509</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_get_unique_label_values</span><span class="op">(</span><span class="nam">labels</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t510" href="#t510">510</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_prepare_labels</span><span class="op">(</span><span class="nam">labels</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t511" href="#t511">511</a></span><span class="t">        <span class="key">return</span> <span class="nam">ExpertKnowledgeOperator</span><span class="op">.</span><span class="nam">fit</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t512" href="#t512">512</a></span><span class="t">            <span class="nam">self</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t513" href="#t513">513</a></span><span class="t">            <span class="nam">values</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t514" href="#t514">514</a></span><span class="t">            <span class="nam">labels</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t515" href="#t515">515</a></span><span class="t">            <span class="nam">expert_rules</span><span class="op">=</span><span class="nam">expert_rules</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t516" href="#t516">516</a></span><span class="t">            <span class="nam">expert_preferred_conditions</span><span class="op">=</span><span class="nam">expert_preferred_conditions</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t517" href="#t517">517</a></span><span class="t">            <span class="nam">expert_forbidden_conditions</span><span class="op">=</span><span class="nam">expert_forbidden_conditions</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t518" href="#t518">518</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t519" href="#t519">519</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t520" href="#t520">520</a></span><span class="t">    <span class="key">def</span> <span class="nam">predict</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t521" href="#t521">521</a></span><span class="t">        <span class="nam">self</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t522" href="#t522">522</a></span><span class="t">        <span class="nam">values</span><span class="op">:</span> <span class="nam">Data</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t523" href="#t523">523</a></span><span class="t">        <span class="nam">return_metrics</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="key">False</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t524" href="#t524">524</a></span><span class="t">    <span class="op">)</span> <span class="op">-></span> <span class="nam">Union</span><span class="op">[</span><span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span><span class="op">,</span> <span class="nam">tuple</span><span class="op">[</span><span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span><span class="op">,</span> <span class="nam">ClassificationPredictionMetrics</span><span class="op">]</span><span class="op">]</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t525" href="#t525">525</a></span><span class="t">        <span class="key">return</span> <span class="nam">RuleClassifier</span><span class="op">.</span><span class="nam">predict</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">values</span><span class="op">,</span> <span class="nam">return_metrics</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t526" href="#t526">526</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t527" href="#t527">527</a></span><span class="t">    <span class="key">def</span> <span class="nam">__getstate__</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">dict</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t528" href="#t528">528</a></span><span class="t">        <span class="key">return</span> <span class="op">{</span><span class="op">**</span><span class="nam">BaseOperator</span><span class="op">.</span><span class="nam">__getstate__</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">,</span> <span class="op">**</span><span class="op">{</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t529" href="#t529">529</a></span><span class="t">            <span class="str">'_remap_to_numeric'</span><span class="op">:</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_remap_to_numeric</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t530" href="#t530">530</a></span><span class="t">        <span class="op">}</span><span class="op">}</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t531" href="#t531">531</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t532" href="#t532">532</a></span><span class="t">    <span class="key">def</span> <span class="nam">__setstate__</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">state</span><span class="op">:</span> <span class="nam">dict</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t533" href="#t533">533</a></span><span class="t">        <span class="nam">BaseOperator</span><span class="op">.</span><span class="nam">__setstate__</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">state</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t534" href="#t534">534</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_remap_to_numeric</span> <span class="op">=</span> <span class="nam">state</span><span class="op">[</span><span class="str">'_remap_to_numeric'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t535" href="#t535">535</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t536" href="#t536">536</a></span><span class="t">    <span class="key">def</span> <span class="nam">_get_problem_type</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">ProblemType</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t537" href="#t537">537</a></span><span class="t">        <span class="key">return</span> <span class="nam">ProblemType</span><span class="op">.</span><span class="nam">CLASSIFICATION</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t538" href="#t538">538</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t539" href="#t539">539</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t540" href="#t540">540</a></span><span class="t"><span class="key">class</span> <span class="nam">ContrastSetRuleClassifier</span><span class="op">(</span><span class="nam">BaseOperator</span><span class="op">,</span> <span class="nam">BaseClassifier</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t541" href="#t541">541</a></span><span class="t">    <span class="str">"""Contrast set classification model."""</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t542" href="#t542">542</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t543" href="#t543">543</a></span><span class="t">    <span class="nam">__params_class__</span> <span class="op">=</span> <span class="nam">ContrastSetModelParams</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t544" href="#t544">544</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t545" href="#t545">545</a></span><span class="t">    <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span>  <span class="com"># pylint: disable=too-many-arguments,too-many-locals</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t546" href="#t546">546</a></span><span class="t">        <span class="nam">self</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t547" href="#t547">547</a></span><span class="t">        <span class="nam">minsupp_all</span><span class="op">:</span> <span class="nam">Tuple</span><span class="op">[</span><span class="nam">float</span><span class="op">,</span> <span class="nam">float</span><span class="op">,</span> <span class="nam">float</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t548" href="#t548">548</a></span><span class="t">                           <span class="nam">float</span><span class="op">]</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'minsupp_all'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t549" href="#t549">549</a></span><span class="t">        <span class="nam">max_neg2pos</span><span class="op">:</span> <span class="nam">float</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'max_neg2pos'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t550" href="#t550">550</a></span><span class="t">        <span class="nam">max_passes_count</span><span class="op">:</span> <span class="nam">int</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'max_passes_count'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t551" href="#t551">551</a></span><span class="t">        <span class="nam">penalty_strength</span><span class="op">:</span> <span class="nam">float</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'penalty_strength'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t552" href="#t552">552</a></span><span class="t">        <span class="nam">penalty_saturation</span><span class="op">:</span> <span class="nam">float</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'penalty_saturation'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t346" href="#t346">346</a></span><span class="t">    <span class="nam">__params_class__</span> <span class="op">=</span> <span class="nam">_ClassificationExpertParams</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t347" href="#t347">347</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t348" href="#t348">348</a></span><span class="t">    <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span>  <span class="com"># pylint: disable=too-many-arguments,too-many-locals</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t349" href="#t349">349</a></span><span class="t">        <span class="nam">self</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t350" href="#t350">350</a></span><span class="t">        <span class="nam">minsupp_new</span><span class="op">:</span> <span class="nam">float</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'minsupp_new'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t351" href="#t351">351</a></span><span class="t">        <span class="nam">induction_measure</span><span class="op">:</span> <span class="nam">Measures</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'induction_measure'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t352" href="#t352">352</a></span><span class="t">        <span class="nam">pruning_measure</span><span class="op">:</span> <span class="nam">Union</span><span class="op">[</span><span class="nam">Measures</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t353" href="#t353">353</a></span><span class="t">                               <span class="nam">str</span><span class="op">]</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'pruning_measure'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t354" href="#t354">354</a></span><span class="t">        <span class="nam">voting_measure</span><span class="op">:</span> <span class="nam">Measures</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'voting_measure'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t355" href="#t355">355</a></span><span class="t">        <span class="nam">max_growing</span><span class="op">:</span> <span class="nam">float</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'max_growing'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t356" href="#t356">356</a></span><span class="t">        <span class="nam">enable_pruning</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'enable_pruning'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t357" href="#t357">357</a></span><span class="t">        <span class="nam">ignore_missing</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'ignore_missing'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t358" href="#t358">358</a></span><span class="t">        <span class="nam">max_uncovered_fraction</span><span class="op">:</span> <span class="nam">float</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'max_uncovered_fraction'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t359" href="#t359">359</a></span><span class="t">        <span class="nam">select_best_candidate</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'select_best_candidate'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t360" href="#t360">360</a></span><span class="t">        <span class="nam">complementary_conditions</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'complementary_conditions'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t361" href="#t361">361</a></span><span class="t">        <span class="nam">control_apriori_precision</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'control_apriori_precision'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t362" href="#t362">362</a></span><span class="t">        <span class="nam">max_rule_count</span><span class="op">:</span> <span class="nam">int</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'max_rule_count'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t363" href="#t363">363</a></span><span class="t">        <span class="nam">approximate_induction</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'approximate_induction'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t364" href="#t364">364</a></span><span class="t">        <span class="nam">approximate_bins_count</span><span class="op">:</span> <span class="nam">int</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'approximate_bins_count'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t365" href="#t365">365</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t366" href="#t366">366</a></span><span class="t">        <span class="nam">extend_using_preferred</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'extend_using_preferred'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t367" href="#t367">367</a></span><span class="t">        <span class="nam">extend_using_automatic</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'extend_using_automatic'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t368" href="#t368">368</a></span><span class="t">        <span class="nam">induce_using_preferred</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'induce_using_preferred'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t369" href="#t369">369</a></span><span class="t">        <span class="nam">induce_using_automatic</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'induce_using_automatic'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t370" href="#t370">370</a></span><span class="t">        <span class="nam">consider_other_classes</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'consider_other_classes'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t371" href="#t371">371</a></span><span class="t">        <span class="nam">preferred_conditions_per_rule</span><span class="op">:</span> <span class="nam">int</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t372" href="#t372">372</a></span><span class="t">            <span class="str">'preferred_conditions_per_rule'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t373" href="#t373">373</a></span><span class="t">        <span class="nam">preferred_attributes_per_rule</span><span class="op">:</span> <span class="nam">int</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t374" href="#t374">374</a></span><span class="t">            <span class="str">'preferred_attributes_per_rule'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t375" href="#t375">375</a></span><span class="t">    <span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t376" href="#t376">376</a></span><span class="t">        <span class="str">"""</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t377" href="#t377">377</a></span><span class="t"><span class="str">        Parameters</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t378" href="#t378">378</a></span><span class="t"><span class="str">        ----------</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t379" href="#t379">379</a></span><span class="t"><span class="str">        minsupp_new : float = 5.0</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t380" href="#t380">380</a></span><span class="t"><span class="str">        a minimum number (or fraction, if value &lt; 1.0) of previously uncovered examples</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t381" href="#t381">381</a></span><span class="t"><span class="str">        to be covered by a new rule (positive examples for classification problems);</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t382" href="#t382">382</a></span><span class="t"><span class="str">        default: 5,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t383" href="#t383">383</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t384" href="#t384">384</a></span><span class="t"><span class="str">        induction_measure : :class:`rulekit.params.Measures` = \</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t385" href="#t385">385</a></span><span class="t"><span class="str">            :class:`rulekit.params.Measures.Correlation`</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t386" href="#t386">386</a></span><span class="t"><span class="str">            measure used during induction; default measure is correlation</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t387" href="#t387">387</a></span><span class="t"><span class="str">        pruning_measure : Union[:class:`rulekit.params.Measures`, str] = \</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t388" href="#t388">388</a></span><span class="t"><span class="str">            :class:`rulekit.params.Measures.Correlation`</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t389" href="#t389">389</a></span><span class="t"><span class="str">            measure used during pruning. Could be user defined (string), for example</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t390" href="#t390">390</a></span><span class="t"><span class="str">             :code:`2 * p / n`; default measure is correlation</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t391" href="#t391">391</a></span><span class="t"><span class="str">        voting_measure : :class:`rulekit.params.Measures` = \</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t392" href="#t392">392</a></span><span class="t"><span class="str">            :class:`rulekit.params.Measures.Correlation`</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t393" href="#t393">393</a></span><span class="t"><span class="str">            measure used during voting; default measure is correlation</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t394" href="#t394">394</a></span><span class="t"><span class="str">        max_growing : int = 0.0</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t395" href="#t395">395</a></span><span class="t"><span class="str">            non-negative integer representing maximum number of conditions which can be added to</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t396" href="#t396">396</a></span><span class="t"><span class="str">            the rule in the growing phase (use this parameter for large datasets if execution time</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t397" href="#t397">397</a></span><span class="t"><span class="str">            is prohibitive); 0 indicates no limit; default: 0,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t398" href="#t398">398</a></span><span class="t"><span class="str">        enable_pruning : bool = True</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t399" href="#t399">399</a></span><span class="t"><span class="str">            enable or disable pruning, default is True.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t400" href="#t400">400</a></span><span class="t"><span class="str">        ignore_missing : bool = False</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t401" href="#t401">401</a></span><span class="t"><span class="str">            boolean telling whether missing values should be ignored (by default, a missing value</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t402" href="#t402">402</a></span><span class="t"><span class="str">            of given attribute is always considered as not fulfilling the condition build upon</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t403" href="#t403">403</a></span><span class="t"><span class="str">             that attribute); default: False.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t404" href="#t404">404</a></span><span class="t"><span class="str">        max_uncovered_fraction : float = 0.0</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t405" href="#t405">405</a></span><span class="t"><span class="str">            Floating-point number from [0,1] interval representing maximum fraction of examples</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t406" href="#t406">406</a></span><span class="t"><span class="str">            that may remain uncovered by the rule set, default: 0.0.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t407" href="#t407">407</a></span><span class="t"><span class="str">        select_best_candidate : bool = False</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t408" href="#t408">408</a></span><span class="t"><span class="str">            Flag determining if best candidate should be selected from growing phase; default:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t409" href="#t409">409</a></span><span class="t"><span class="str">             False.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t410" href="#t410">410</a></span><span class="t"><span class="str">        complementary_conditions : bool = False</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t411" href="#t411">411</a></span><span class="t"><span class="str">            If enabled, complementary conditions in the form a = !{value} for nominal attributes</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t412" href="#t412">412</a></span><span class="t"><span class="str">            are supported.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t413" href="#t413">413</a></span><span class="t"><span class="str">        control_apriori_precision : bool = True</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t414" href="#t414">414</a></span><span class="t"><span class="str">            When inducing classification rules, verify if candidate precision is higher than</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t415" href="#t415">415</a></span><span class="t"><span class="str">             apriori precision of the investigated class.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t416" href="#t416">416</a></span><span class="t"><span class="str">        max_rule_count : int = 0</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t417" href="#t417">417</a></span><span class="t"><span class="str">            Maximum number of rules to be generated (for classification data sets it applies</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t418" href="#t418">418</a></span><span class="t"><span class="str">             to a single class); 0 indicates no limit.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t419" href="#t419">419</a></span><span class="t"><span class="str">        approximate_induction: bool = False</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t420" href="#t420">420</a></span><span class="t"><span class="str">            Use an approximate induction heuristic which does not check all possible splits;</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t421" href="#t421">421</a></span><span class="t"><span class="str">            note: this is an experimental feature and currently works only for classification</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t422" href="#t422">422</a></span><span class="t"><span class="str">            data sets, results may change in future;</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t423" href="#t423">423</a></span><span class="t"><span class="str">        approximate_bins_count: int = 100</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t424" href="#t424">424</a></span><span class="t"><span class="str">            maximum number of bins for an attribute evaluated in the approximate induction.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t425" href="#t425">425</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t426" href="#t426">426</a></span><span class="t"><span class="str">        extend_using_preferred : bool = False</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t427" href="#t427">427</a></span><span class="t"><span class="str">            boolean indicating whether initial rules should be extended with a use of preferred</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t428" href="#t428">428</a></span><span class="t"><span class="str">            conditions and attributes; default is False</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t429" href="#t429">429</a></span><span class="t"><span class="str">        extend_using_automatic : bool = False</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t430" href="#t430">430</a></span><span class="t"><span class="str">            boolean indicating whether initial rules should be extended with a use of automatic</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t431" href="#t431">431</a></span><span class="t"><span class="str">             conditions and attributes; default is False</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t432" href="#t432">432</a></span><span class="t"><span class="str">        induce_using_preferred : bool = False</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t433" href="#t433">433</a></span><span class="t"><span class="str">            boolean indicating whether new rules should be induced with a use of preferred</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t434" href="#t434">434</a></span><span class="t"><span class="str">             conditions and attributes; default is False</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t435" href="#t435">435</a></span><span class="t"><span class="str">        induce_using_automatic : bool = False</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t436" href="#t436">436</a></span><span class="t"><span class="str">            boolean indicating whether new rules should be induced with a use of automatic</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t437" href="#t437">437</a></span><span class="t"><span class="str">             conditions and attributes; default is False</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t438" href="#t438">438</a></span><span class="t"><span class="str">        consider_other_classes : bool = False</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t439" href="#t439">439</a></span><span class="t"><span class="str">            boolean indicating whether automatic induction should be performed for classes for</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t440" href="#t440">440</a></span><span class="t"><span class="str">              which no user's knowledge has been defined (classification only); default is False.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t441" href="#t441">441</a></span><span class="t"><span class="str">        preferred_conditions_per_rule : int = None</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t442" href="#t442">442</a></span><span class="t"><span class="str">            maximum number of preferred conditions per rule; default: unlimited,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t443" href="#t443">443</a></span><span class="t"><span class="str">        preferred_attributes_per_rule : int = None</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t444" href="#t444">444</a></span><span class="t"><span class="str">            maximum number of preferred attributes per rule; default: unlimited.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t445" href="#t445">445</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t446" href="#t446">446</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_remap_to_numeric</span> <span class="op">=</span> <span class="key">False</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t447" href="#t447">447</a></span><span class="t">        <span class="nam">RuleClassifier</span><span class="op">.</span><span class="nam">__init__</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t448" href="#t448">448</a></span><span class="t">            <span class="nam">self</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t449" href="#t449">449</a></span><span class="t">            <span class="nam">minsupp_new</span><span class="op">=</span><span class="nam">minsupp_new</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t450" href="#t450">450</a></span><span class="t">            <span class="nam">induction_measure</span><span class="op">=</span><span class="nam">induction_measure</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t451" href="#t451">451</a></span><span class="t">            <span class="nam">pruning_measure</span><span class="op">=</span><span class="nam">pruning_measure</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t452" href="#t452">452</a></span><span class="t">            <span class="nam">voting_measure</span><span class="op">=</span><span class="nam">voting_measure</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t453" href="#t453">453</a></span><span class="t">            <span class="nam">max_growing</span><span class="op">=</span><span class="nam">max_growing</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t454" href="#t454">454</a></span><span class="t">            <span class="nam">enable_pruning</span><span class="op">=</span><span class="nam">enable_pruning</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t455" href="#t455">455</a></span><span class="t">            <span class="nam">ignore_missing</span><span class="op">=</span><span class="nam">ignore_missing</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t456" href="#t456">456</a></span><span class="t">            <span class="nam">max_uncovered_fraction</span><span class="op">=</span><span class="nam">max_uncovered_fraction</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t457" href="#t457">457</a></span><span class="t">            <span class="nam">select_best_candidate</span><span class="op">=</span><span class="nam">select_best_candidate</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t458" href="#t458">458</a></span><span class="t">            <span class="nam">complementary_conditions</span><span class="op">=</span><span class="nam">complementary_conditions</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t459" href="#t459">459</a></span><span class="t">            <span class="nam">control_apriori_precision</span><span class="op">=</span><span class="nam">control_apriori_precision</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t460" href="#t460">460</a></span><span class="t">            <span class="nam">max_rule_count</span><span class="op">=</span><span class="nam">max_rule_count</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t461" href="#t461">461</a></span><span class="t">            <span class="nam">approximate_induction</span><span class="op">=</span><span class="nam">approximate_induction</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t462" href="#t462">462</a></span><span class="t">            <span class="nam">approximate_bins_count</span><span class="op">=</span><span class="nam">approximate_bins_count</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t463" href="#t463">463</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t464" href="#t464">464</a></span><span class="t">        <span class="nam">ExpertKnowledgeOperator</span><span class="op">.</span><span class="nam">__init__</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t465" href="#t465">465</a></span><span class="t">            <span class="nam">self</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t466" href="#t466">466</a></span><span class="t">            <span class="nam">minsupp_new</span><span class="op">=</span><span class="nam">minsupp_new</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t467" href="#t467">467</a></span><span class="t">            <span class="nam">induction_measure</span><span class="op">=</span><span class="nam">induction_measure</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t468" href="#t468">468</a></span><span class="t">            <span class="nam">pruning_measure</span><span class="op">=</span><span class="nam">pruning_measure</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t469" href="#t469">469</a></span><span class="t">            <span class="nam">voting_measure</span><span class="op">=</span><span class="nam">voting_measure</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t470" href="#t470">470</a></span><span class="t">            <span class="nam">max_growing</span><span class="op">=</span><span class="nam">max_growing</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t471" href="#t471">471</a></span><span class="t">            <span class="nam">enable_pruning</span><span class="op">=</span><span class="nam">enable_pruning</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t472" href="#t472">472</a></span><span class="t">            <span class="nam">ignore_missing</span><span class="op">=</span><span class="nam">ignore_missing</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t473" href="#t473">473</a></span><span class="t">            <span class="nam">max_uncovered_fraction</span><span class="op">=</span><span class="nam">max_uncovered_fraction</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t474" href="#t474">474</a></span><span class="t">            <span class="nam">select_best_candidate</span><span class="op">=</span><span class="nam">select_best_candidate</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t475" href="#t475">475</a></span><span class="t">            <span class="nam">complementary_conditions</span><span class="op">=</span><span class="nam">complementary_conditions</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t476" href="#t476">476</a></span><span class="t">            <span class="nam">extend_using_preferred</span><span class="op">=</span><span class="nam">extend_using_preferred</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t477" href="#t477">477</a></span><span class="t">            <span class="nam">extend_using_automatic</span><span class="op">=</span><span class="nam">extend_using_automatic</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t478" href="#t478">478</a></span><span class="t">            <span class="nam">induce_using_preferred</span><span class="op">=</span><span class="nam">induce_using_preferred</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t479" href="#t479">479</a></span><span class="t">            <span class="nam">induce_using_automatic</span><span class="op">=</span><span class="nam">induce_using_automatic</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t480" href="#t480">480</a></span><span class="t">            <span class="nam">consider_other_classes</span><span class="op">=</span><span class="nam">consider_other_classes</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t481" href="#t481">481</a></span><span class="t">            <span class="nam">preferred_conditions_per_rule</span><span class="op">=</span><span class="nam">preferred_conditions_per_rule</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t482" href="#t482">482</a></span><span class="t">            <span class="nam">preferred_attributes_per_rule</span><span class="op">=</span><span class="nam">preferred_attributes_per_rule</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t483" href="#t483">483</a></span><span class="t">            <span class="nam">control_apriori_precision</span><span class="op">=</span><span class="nam">control_apriori_precision</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t484" href="#t484">484</a></span><span class="t">            <span class="nam">max_rule_count</span><span class="op">=</span><span class="nam">max_rule_count</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t485" href="#t485">485</a></span><span class="t">            <span class="nam">approximate_induction</span><span class="op">=</span><span class="nam">approximate_induction</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t486" href="#t486">486</a></span><span class="t">            <span class="nam">approximate_bins_count</span><span class="op">=</span><span class="nam">approximate_bins_count</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t487" href="#t487">487</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t488" href="#t488">488</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">model</span><span class="op">:</span> <span class="nam">RuleSet</span><span class="op">[</span><span class="nam">ClassificationRule</span><span class="op">]</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t489" href="#t489">489</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t490" href="#t490">490</a></span><span class="t">    <span class="key">def</span> <span class="nam">fit</span><span class="op">(</span>  <span class="com"># pylint: disable=arguments-differ,too-many-arguments</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t491" href="#t491">491</a></span><span class="t">        <span class="nam">self</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t492" href="#t492">492</a></span><span class="t">        <span class="nam">values</span><span class="op">:</span> <span class="nam">Data</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t493" href="#t493">493</a></span><span class="t">        <span class="nam">labels</span><span class="op">:</span> <span class="nam">Data</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t494" href="#t494">494</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t495" href="#t495">495</a></span><span class="t">        <span class="nam">expert_rules</span><span class="op">:</span> <span class="nam">list</span><span class="op">[</span><span class="nam">Union</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">tuple</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">str</span><span class="op">]</span><span class="op">]</span><span class="op">]</span> <span class="op">=</span> <span class="key">None</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t496" href="#t496">496</a></span><span class="t">        <span class="nam">expert_preferred_conditions</span><span class="op">:</span> <span class="nam">list</span><span class="op">[</span><span class="nam">Union</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">tuple</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">str</span><span class="op">]</span><span class="op">]</span><span class="op">]</span> <span class="op">=</span> <span class="key">None</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t497" href="#t497">497</a></span><span class="t">        <span class="nam">expert_forbidden_conditions</span><span class="op">:</span> <span class="nam">list</span><span class="op">[</span><span class="nam">Union</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">tuple</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">str</span><span class="op">]</span><span class="op">]</span><span class="op">]</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t498" href="#t498">498</a></span><span class="t">    <span class="op">)</span> <span class="op">-></span> <span class="nam">ExpertRuleClassifier</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t499" href="#t499">499</a></span><span class="t">        <span class="str">"""Train model on given dataset.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t500" href="#t500">500</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t501" href="#t501">501</a></span><span class="t"><span class="str">        Parameters</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t502" href="#t502">502</a></span><span class="t"><span class="str">        ----------</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t503" href="#t503">503</a></span><span class="t"><span class="str">        values : :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t504" href="#t504">504</a></span><span class="t"><span class="str">            attributes</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t505" href="#t505">505</a></span><span class="t"><span class="str">        labels : :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t506" href="#t506">506</a></span><span class="t"><span class="str">            labels</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t507" href="#t507">507</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t508" href="#t508">508</a></span><span class="t"><span class="str">        expert_rules : List[Union[str, Tuple[str, str]]]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t509" href="#t509">509</a></span><span class="t"><span class="str">            set of initial rules, either passed as a list of strings representing rules or as list</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t510" href="#t510">510</a></span><span class="t"><span class="str">            of tuples where first element is name of the rule and second one is rule string.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t511" href="#t511">511</a></span><span class="t"><span class="str">        expert_preferred_conditions : List[Union[str, Tuple[str, str]]]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t512" href="#t512">512</a></span><span class="t"><span class="str">            multiset of preferred conditions (used also for specifying preferred attributes by</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t513" href="#t513">513</a></span><span class="t"><span class="str">            using special value Any). Either passed as a list of strings representing rules or as</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t514" href="#t514">514</a></span><span class="t"><span class="str">            list of tuples where first element is name of the rule and second one is rule string.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t515" href="#t515">515</a></span><span class="t"><span class="str">        expert_forbidden_conditions : List[Union[str, Tuple[str, str]]]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t516" href="#t516">516</a></span><span class="t"><span class="str">            set of forbidden conditions (used also for specifying forbidden attributes by using</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t517" href="#t517">517</a></span><span class="t"><span class="str">             special valye Any). Either passed as a list of strings representing rules or as list</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t518" href="#t518">518</a></span><span class="t"><span class="str">            of tuples where first element is name of the rule and second one is rule string.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t519" href="#t519">519</a></span><span class="t"><span class="str">        Returns</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t520" href="#t520">520</a></span><span class="t"><span class="str">        -------</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t521" href="#t521">521</a></span><span class="t"><span class="str">        self : ExpertRuleClassifier</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t522" href="#t522">522</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t523" href="#t523">523</a></span><span class="t">        <span class="key">if</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">labels</span><span class="op">,</span> <span class="op">(</span><span class="nam">pd</span><span class="op">.</span><span class="nam">DataFrame</span><span class="op">,</span> <span class="nam">pd</span><span class="op">.</span><span class="nam">Series</span><span class="op">)</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t524" href="#t524">524</a></span><span class="t">            <span class="key">if</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">labels</span><span class="op">.</span><span class="nam">iloc</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="op">,</span> <span class="nam">Number</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t525" href="#t525">525</a></span><span class="t">                <span class="nam">self</span><span class="op">.</span><span class="nam">_remap_to_numeric</span> <span class="op">=</span> <span class="key">True</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t526" href="#t526">526</a></span><span class="t">                <span class="nam">labels</span> <span class="op">=</span> <span class="nam">labels</span><span class="op">.</span><span class="nam">astype</span><span class="op">(</span><span class="nam">str</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t527" href="#t527">527</a></span><span class="t">        <span class="key">else</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t528" href="#t528">528</a></span><span class="t">            <span class="key">if</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">labels</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="op">,</span> <span class="nam">Number</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t529" href="#t529">529</a></span><span class="t">                <span class="nam">self</span><span class="op">.</span><span class="nam">_remap_to_numeric</span> <span class="op">=</span> <span class="key">True</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t530" href="#t530">530</a></span><span class="t">                <span class="nam">labels</span> <span class="op">=</span> <span class="nam">list</span><span class="op">(</span><span class="nam">map</span><span class="op">(</span><span class="nam">str</span><span class="op">,</span> <span class="nam">labels</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t531" href="#t531">531</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_get_unique_label_values</span><span class="op">(</span><span class="nam">labels</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t532" href="#t532">532</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_prepare_labels</span><span class="op">(</span><span class="nam">labels</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t533" href="#t533">533</a></span><span class="t">        <span class="key">return</span> <span class="nam">ExpertKnowledgeOperator</span><span class="op">.</span><span class="nam">fit</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t534" href="#t534">534</a></span><span class="t">            <span class="nam">self</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t535" href="#t535">535</a></span><span class="t">            <span class="nam">values</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t536" href="#t536">536</a></span><span class="t">            <span class="nam">labels</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t537" href="#t537">537</a></span><span class="t">            <span class="nam">expert_rules</span><span class="op">=</span><span class="nam">expert_rules</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t538" href="#t538">538</a></span><span class="t">            <span class="nam">expert_preferred_conditions</span><span class="op">=</span><span class="nam">expert_preferred_conditions</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t539" href="#t539">539</a></span><span class="t">            <span class="nam">expert_forbidden_conditions</span><span class="op">=</span><span class="nam">expert_forbidden_conditions</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t540" href="#t540">540</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t541" href="#t541">541</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t542" href="#t542">542</a></span><span class="t">    <span class="key">def</span> <span class="nam">predict</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t543" href="#t543">543</a></span><span class="t">        <span class="nam">self</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t544" href="#t544">544</a></span><span class="t">        <span class="nam">values</span><span class="op">:</span> <span class="nam">Data</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t545" href="#t545">545</a></span><span class="t">        <span class="nam">return_metrics</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="key">False</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t546" href="#t546">546</a></span><span class="t">    <span class="op">)</span> <span class="op">-></span> <span class="nam">Union</span><span class="op">[</span><span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span><span class="op">,</span> <span class="nam">tuple</span><span class="op">[</span><span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span><span class="op">,</span> <span class="nam">ClassificationPredictionMetrics</span><span class="op">]</span><span class="op">]</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t547" href="#t547">547</a></span><span class="t">        <span class="key">return</span> <span class="nam">RuleClassifier</span><span class="op">.</span><span class="nam">predict</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">values</span><span class="op">,</span> <span class="nam">return_metrics</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t548" href="#t548">548</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t549" href="#t549">549</a></span><span class="t">    <span class="key">def</span> <span class="nam">__getstate__</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">dict</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t550" href="#t550">550</a></span><span class="t">        <span class="key">return</span> <span class="op">{</span><span class="op">**</span><span class="nam">BaseOperator</span><span class="op">.</span><span class="nam">__getstate__</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">,</span> <span class="op">**</span><span class="op">{</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t551" href="#t551">551</a></span><span class="t">            <span class="str">'_remap_to_numeric'</span><span class="op">:</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_remap_to_numeric</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t552" href="#t552">552</a></span><span class="t">        <span class="op">}</span><span class="op">}</span>&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t553" href="#t553">553</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t554" href="#t554">554</a></span><span class="t">        <span class="nam">minsupp_new</span><span class="op">:</span> <span class="nam">float</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'minsupp_new'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t555" href="#t555">555</a></span><span class="t">        <span class="nam">induction_measure</span><span class="op">:</span> <span class="nam">Measures</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'induction_measure'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t556" href="#t556">556</a></span><span class="t">        <span class="nam">pruning_measure</span><span class="op">:</span> <span class="nam">Union</span><span class="op">[</span><span class="nam">Measures</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t557" href="#t557">557</a></span><span class="t">                               <span class="nam">str</span><span class="op">]</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'pruning_measure'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t558" href="#t558">558</a></span><span class="t">        <span class="nam">voting_measure</span><span class="op">:</span> <span class="nam">Measures</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'voting_measure'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t559" href="#t559">559</a></span><span class="t">        <span class="nam">max_growing</span><span class="op">:</span> <span class="nam">float</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'max_growing'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t560" href="#t560">560</a></span><span class="t">        <span class="nam">enable_pruning</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'enable_pruning'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t561" href="#t561">561</a></span><span class="t">        <span class="nam">ignore_missing</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'ignore_missing'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t562" href="#t562">562</a></span><span class="t">        <span class="nam">max_uncovered_fraction</span><span class="op">:</span> <span class="nam">float</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'max_uncovered_fraction'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t563" href="#t563">563</a></span><span class="t">        <span class="nam">select_best_candidate</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'select_best_candidate'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t564" href="#t564">564</a></span><span class="t">        <span class="nam">complementary_conditions</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'complementary_conditions'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t565" href="#t565">565</a></span><span class="t">        <span class="nam">control_apriori_precision</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'control_apriori_precision'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t566" href="#t566">566</a></span><span class="t">        <span class="nam">max_rule_count</span><span class="op">:</span> <span class="nam">int</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'max_rule_count'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t567" href="#t567">567</a></span><span class="t">        <span class="nam">approximate_induction</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'approximate_induction'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t568" href="#t568">568</a></span><span class="t">        <span class="nam">approximate_bins_count</span><span class="op">:</span> <span class="nam">int</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'approximate_bins_count'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t569" href="#t569">569</a></span><span class="t">    <span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t570" href="#t570">570</a></span><span class="t">        <span class="str">"""</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t571" href="#t571">571</a></span><span class="t"><span class="str">        Parameters</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t572" href="#t572">572</a></span><span class="t"><span class="str">        ----------</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t573" href="#t573">573</a></span><span class="t"><span class="str">        minsupp_all: Tuple[float, float, float, float]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t574" href="#t574">574</a></span><span class="t"><span class="str">            a minimum positive support of a contrast set (p/P). When multiple values are specified,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t575" href="#t575">575</a></span><span class="t"><span class="str">            a metainduction is performed; Default and recommended sequence is: 0.8, 0.5, 0.2, 0.1</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t576" href="#t576">576</a></span><span class="t"><span class="str">        max_neg2pos: float</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t577" href="#t577">577</a></span><span class="t"><span class="str">            a maximum ratio of negative to positive supports (nP/pN); Default is 0.5</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t578" href="#t578">578</a></span><span class="t"><span class="str">        max_passes_count: int</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t579" href="#t579">579</a></span><span class="t"><span class="str">            a maximum number of sequential covering passes for a single minsupp-all; Default is 5</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t580" href="#t580">580</a></span><span class="t"><span class="str">        penalty_strength: float</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t581" href="#t581">581</a></span><span class="t"><span class="str">            (s) - penalty strength; Default is 0.5</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t582" href="#t582">582</a></span><span class="t"><span class="str">        penalty_saturation: float</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t583" href="#t583">583</a></span><span class="t"><span class="str">            the value of p_new / P at which penalty reward saturates; Default is 0.2.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t584" href="#t584">584</a></span><span class="t"><span class="str">        minsupp_new : float = 5.0</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t585" href="#t585">585</a></span><span class="t"><span class="str">            a minimum number (or fraction, if value &lt; 1.0) of previously uncovered examples</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t586" href="#t586">586</a></span><span class="t"><span class="str">             to be covered by a new rule (positive examples for classification problems); default: 5,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t587" href="#t587">587</a></span><span class="t"><span class="str">        induction_measure : :class:`rulekit.params.Measures` = \</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t588" href="#t588">588</a></span><span class="t"><span class="str">            :class:`rulekit.params.Measures.Correlation`</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t589" href="#t589">589</a></span><span class="t"><span class="str">            measure used during induction; default measure is correlation</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t590" href="#t590">590</a></span><span class="t"><span class="str">        pruning_measure : Union[:class:`rulekit.params.Measures`, str] = \</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t591" href="#t591">591</a></span><span class="t"><span class="str">            :class:`rulekit.params.Measures.Correlation`</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t592" href="#t592">592</a></span><span class="t"><span class="str">            measure used during pruning. Could be user defined (string), for example</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t593" href="#t593">593</a></span><span class="t"><span class="str">             :code:`2 * p / n`; default measure is correlation</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t594" href="#t594">594</a></span><span class="t"><span class="str">        voting_measure : :class:`rulekit.params.Measures` = \</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t595" href="#t595">595</a></span><span class="t"><span class="str">            :class:`rulekit.params.Measures.Correlation`</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t596" href="#t596">596</a></span><span class="t"><span class="str">            measure used during voting; default measure is correlation</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t597" href="#t597">597</a></span><span class="t"><span class="str">        max_growing : int = 0.0</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t598" href="#t598">598</a></span><span class="t"><span class="str">            non-negative integer representing maximum number of conditions which can be added to</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t599" href="#t599">599</a></span><span class="t"><span class="str">            the rule in the growing phase (use this parameter for large datasets if execution time</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t600" href="#t600">600</a></span><span class="t"><span class="str">            is prohibitive); 0 indicates no limit; default: 0,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t601" href="#t601">601</a></span><span class="t"><span class="str">        enable_pruning : bool = True</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t602" href="#t602">602</a></span><span class="t"><span class="str">            enable or disable pruning, default is True.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t603" href="#t603">603</a></span><span class="t"><span class="str">        ignore_missing : bool = False</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t604" href="#t604">604</a></span><span class="t"><span class="str">            boolean telling whether missing values should be ignored (by default, a missing value</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t605" href="#t605">605</a></span><span class="t"><span class="str">            of given attribute is always considered as not fulfilling the condition build upon</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t606" href="#t606">606</a></span><span class="t"><span class="str">             that attribute); default: False.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t607" href="#t607">607</a></span><span class="t"><span class="str">        max_uncovered_fraction : float = 0.0</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t608" href="#t608">608</a></span><span class="t"><span class="str">            Floating-point number from [0,1] interval representing maximum fraction of examples</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t609" href="#t609">609</a></span><span class="t"><span class="str">             that may remain uncovered by the rule set, default: 0.0.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t610" href="#t610">610</a></span><span class="t"><span class="str">        select_best_candidate : bool = False</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t611" href="#t611">611</a></span><span class="t"><span class="str">            Flag determining if best candidate should be selected from growing phase;</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t612" href="#t612">612</a></span><span class="t"><span class="str">             default: False.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t613" href="#t613">613</a></span><span class="t"><span class="str">        complementary_conditions : bool = False</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t614" href="#t614">614</a></span><span class="t"><span class="str">            If enabled, complementary conditions in the form a = !{value} for nominal attributes</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t615" href="#t615">615</a></span><span class="t"><span class="str">            are supported.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t616" href="#t616">616</a></span><span class="t"><span class="str">        control_apriori_precision : bool = True</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t617" href="#t617">617</a></span><span class="t"><span class="str">            When inducing classification rules, verify if candidate precision is higher than</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t618" href="#t618">618</a></span><span class="t"><span class="str">             apriori precision of the investigated class.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t619" href="#t619">619</a></span><span class="t"><span class="str">        max_rule_count : int = 0</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t620" href="#t620">620</a></span><span class="t"><span class="str">            Maximum number of rules to be generated (for classification data sets it applies</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t621" href="#t621">621</a></span><span class="t"><span class="str">             to a single class); 0 indicates no limit.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t622" href="#t622">622</a></span><span class="t"><span class="str">        approximate_induction: bool = False</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t623" href="#t623">623</a></span><span class="t"><span class="str">            Use an approximate induction heuristic which does not check all possible splits;</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t624" href="#t624">624</a></span><span class="t"><span class="str">            note: this is an experimental feature and currently works only for classification</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t625" href="#t625">625</a></span><span class="t"><span class="str">            data sets, results may change in future;</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t626" href="#t626">626</a></span><span class="t"><span class="str">        approximate_bins_count: int = 100</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t627" href="#t627">627</a></span><span class="t"><span class="str">            maximum number of bins for an attribute evaluated in the approximate induction.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t628" href="#t628">628</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t629" href="#t629">629</a></span><span class="t">        <span class="nam">BaseOperator</span><span class="op">.</span><span class="nam">__init__</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t630" href="#t630">630</a></span><span class="t">            <span class="nam">self</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t631" href="#t631">631</a></span><span class="t">            <span class="nam">minsupp_all</span><span class="op">=</span><span class="nam">minsupp_all</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t632" href="#t632">632</a></span><span class="t">            <span class="nam">max_neg2pos</span><span class="op">=</span><span class="nam">max_neg2pos</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t633" href="#t633">633</a></span><span class="t">            <span class="nam">max_passes_count</span><span class="op">=</span><span class="nam">max_passes_count</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t634" href="#t634">634</a></span><span class="t">            <span class="nam">penalty_strength</span><span class="op">=</span><span class="nam">penalty_strength</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t635" href="#t635">635</a></span><span class="t">            <span class="nam">penalty_saturation</span><span class="op">=</span><span class="nam">penalty_saturation</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t636" href="#t636">636</a></span><span class="t">            <span class="nam">minsupp_new</span><span class="op">=</span><span class="nam">minsupp_new</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t637" href="#t637">637</a></span><span class="t">            <span class="nam">induction_measure</span><span class="op">=</span><span class="nam">induction_measure</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t638" href="#t638">638</a></span><span class="t">            <span class="nam">pruning_measure</span><span class="op">=</span><span class="nam">pruning_measure</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t639" href="#t639">639</a></span><span class="t">            <span class="nam">voting_measure</span><span class="op">=</span><span class="nam">voting_measure</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t640" href="#t640">640</a></span><span class="t">            <span class="nam">max_growing</span><span class="op">=</span><span class="nam">max_growing</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t641" href="#t641">641</a></span><span class="t">            <span class="nam">enable_pruning</span><span class="op">=</span><span class="nam">enable_pruning</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t642" href="#t642">642</a></span><span class="t">            <span class="nam">ignore_missing</span><span class="op">=</span><span class="nam">ignore_missing</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t643" href="#t643">643</a></span><span class="t">            <span class="nam">max_uncovered_fraction</span><span class="op">=</span><span class="nam">max_uncovered_fraction</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t644" href="#t644">644</a></span><span class="t">            <span class="nam">select_best_candidate</span><span class="op">=</span><span class="nam">select_best_candidate</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t645" href="#t645">645</a></span><span class="t">            <span class="nam">complementary_conditions</span><span class="op">=</span><span class="nam">complementary_conditions</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t646" href="#t646">646</a></span><span class="t">            <span class="nam">control_apriori_precision</span><span class="op">=</span><span class="nam">control_apriori_precision</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t647" href="#t647">647</a></span><span class="t">            <span class="nam">max_rule_count</span><span class="op">=</span><span class="nam">max_rule_count</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t648" href="#t648">648</a></span><span class="t">            <span class="nam">approximate_induction</span><span class="op">=</span><span class="nam">approximate_induction</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t649" href="#t649">649</a></span><span class="t">            <span class="nam">approximate_bins_count</span><span class="op">=</span><span class="nam">approximate_bins_count</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t650" href="#t650">650</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t651" href="#t651">651</a></span><span class="t">        <span class="nam">BaseClassifier</span><span class="op">.</span><span class="nam">__init__</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t652" href="#t652">652</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">contrast_attribute</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t653" href="#t653">653</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_remap_to_numeric</span> <span class="op">=</span> <span class="key">False</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t654" href="#t654">654</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">label_unique_values</span> <span class="op">=</span> <span class="op">[</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t655" href="#t655">655</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">model</span><span class="op">:</span> <span class="nam">RuleSet</span><span class="op">[</span><span class="nam">ClassificationRule</span><span class="op">]</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t656" href="#t656">656</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t657" href="#t657">657</a></span><span class="t">    <span class="key">def</span> <span class="nam">_map_result</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">predicted_example_set</span><span class="op">)</span> <span class="op">-></span> <span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t658" href="#t658">658</a></span><span class="t">        <span class="nam">prediction</span><span class="op">:</span> <span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t659" href="#t659">659</a></span><span class="t">        <span class="key">if</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_remap_to_numeric</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t660" href="#t660">660</a></span><span class="t">            <span class="nam">prediction</span> <span class="op">=</span> <span class="nam">PredictionResultMapper</span><span class="op">.</span><span class="nam">map_to_numerical</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t661" href="#t661">661</a></span><span class="t">                <span class="nam">predicted_example_set</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t662" href="#t662">662</a></span><span class="t">        <span class="key">else</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t663" href="#t663">663</a></span><span class="t">            <span class="nam">prediction</span> <span class="op">=</span> <span class="nam">PredictionResultMapper</span><span class="op">.</span><span class="nam">map_to_nominal</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t664" href="#t664">664</a></span><span class="t">                <span class="nam">predicted_example_set</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t665" href="#t665">665</a></span><span class="t">        <span class="key">return</span> <span class="nam">prediction</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t666" href="#t666">666</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t667" href="#t667">667</a></span><span class="t">    <span class="key">def</span> <span class="nam">_get_unique_label_values</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">labels</span><span class="op">:</span> <span class="nam">Data</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t668" href="#t668">668</a></span><span class="t">        <span class="nam">tmp</span> <span class="op">=</span> <span class="op">{</span><span class="op">}</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t669" href="#t669">669</a></span><span class="t">        <span class="key">for</span> <span class="nam">label_value</span> <span class="key">in</span> <span class="nam">labels</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t670" href="#t670">670</a></span><span class="t">            <span class="nam">tmp</span><span class="op">[</span><span class="nam">label_value</span><span class="op">]</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t671" href="#t671">671</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">label_unique_values</span> <span class="op">=</span> <span class="nam">list</span><span class="op">(</span><span class="nam">tmp</span><span class="op">.</span><span class="nam">keys</span><span class="op">(</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t672" href="#t672">672</a></span><span class="t">        <span class="key">if</span> <span class="nam">len</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">label_unique_values</span><span class="op">)</span> <span class="op">></span> <span class="num">0</span> <span class="key">and</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">label_unique_values</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="op">,</span> <span class="nam">bytes</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t673" href="#t673">673</a></span><span class="t">            <span class="nam">self</span><span class="op">.</span><span class="nam">label_unique_values</span> <span class="op">=</span> <span class="op">[</span><span class="nam">item</span><span class="op">.</span><span class="nam">decode</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t674" href="#t674">674</a></span><span class="t">                <span class="str">'utf-8'</span><span class="op">)</span> <span class="key">for</span> <span class="nam">item</span> <span class="key">in</span> <span class="nam">self</span><span class="op">.</span><span class="nam">label_unique_values</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t675" href="#t675">675</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t676" href="#t676">676</a></span><span class="t">    <span class="key">def</span> <span class="nam">fit</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">values</span><span class="op">:</span> <span class="nam">Data</span><span class="op">,</span> <span class="nam">labels</span><span class="op">:</span> <span class="nam">Data</span><span class="op">,</span> <span class="nam">contrast_attribute</span><span class="op">:</span> <span class="nam">str</span><span class="op">)</span> <span class="op">-></span> <span class="nam">ContrastSetRuleClassifier</span><span class="op">:</span>  <span class="com"># pylint: disable=arguments-differ</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t677" href="#t677">677</a></span><span class="t">        <span class="str">"""Train model on given dataset.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t554" href="#t554">554</a></span><span class="t">    <span class="key">def</span> <span class="nam">__setstate__</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">state</span><span class="op">:</span> <span class="nam">dict</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t555" href="#t555">555</a></span><span class="t">        <span class="nam">BaseOperator</span><span class="op">.</span><span class="nam">__setstate__</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">state</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t556" href="#t556">556</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_remap_to_numeric</span> <span class="op">=</span> <span class="nam">state</span><span class="op">[</span><span class="str">'_remap_to_numeric'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t557" href="#t557">557</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t558" href="#t558">558</a></span><span class="t">    <span class="key">def</span> <span class="nam">_get_problem_type</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">ProblemType</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t559" href="#t559">559</a></span><span class="t">        <span class="key">return</span> <span class="nam">ProblemType</span><span class="op">.</span><span class="nam">CLASSIFICATION</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t560" href="#t560">560</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t561" href="#t561">561</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t562" href="#t562">562</a></span><span class="t"><span class="key">class</span> <span class="nam">ContrastSetRuleClassifier</span><span class="op">(</span><span class="nam">BaseOperator</span><span class="op">,</span> <span class="nam">BaseClassifier</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t563" href="#t563">563</a></span><span class="t">    <span class="str">"""Contrast set classification model."""</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t564" href="#t564">564</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t565" href="#t565">565</a></span><span class="t">    <span class="nam">__params_class__</span> <span class="op">=</span> <span class="nam">ContrastSetModelParams</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t566" href="#t566">566</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t567" href="#t567">567</a></span><span class="t">    <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span>  <span class="com"># pylint: disable=too-many-arguments,too-many-locals</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t568" href="#t568">568</a></span><span class="t">        <span class="nam">self</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t569" href="#t569">569</a></span><span class="t">        <span class="nam">minsupp_all</span><span class="op">:</span> <span class="nam">Tuple</span><span class="op">[</span><span class="nam">float</span><span class="op">,</span> <span class="nam">float</span><span class="op">,</span> <span class="nam">float</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t570" href="#t570">570</a></span><span class="t">                           <span class="nam">float</span><span class="op">]</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'minsupp_all'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t571" href="#t571">571</a></span><span class="t">        <span class="nam">max_neg2pos</span><span class="op">:</span> <span class="nam">float</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'max_neg2pos'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t572" href="#t572">572</a></span><span class="t">        <span class="nam">max_passes_count</span><span class="op">:</span> <span class="nam">int</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'max_passes_count'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t573" href="#t573">573</a></span><span class="t">        <span class="nam">penalty_strength</span><span class="op">:</span> <span class="nam">float</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'penalty_strength'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t574" href="#t574">574</a></span><span class="t">        <span class="nam">penalty_saturation</span><span class="op">:</span> <span class="nam">float</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'penalty_saturation'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t575" href="#t575">575</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t576" href="#t576">576</a></span><span class="t">        <span class="nam">minsupp_new</span><span class="op">:</span> <span class="nam">float</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'minsupp_new'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t577" href="#t577">577</a></span><span class="t">        <span class="nam">induction_measure</span><span class="op">:</span> <span class="nam">Measures</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'induction_measure'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t578" href="#t578">578</a></span><span class="t">        <span class="nam">pruning_measure</span><span class="op">:</span> <span class="nam">Union</span><span class="op">[</span><span class="nam">Measures</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t579" href="#t579">579</a></span><span class="t">                               <span class="nam">str</span><span class="op">]</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'pruning_measure'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t580" href="#t580">580</a></span><span class="t">        <span class="nam">voting_measure</span><span class="op">:</span> <span class="nam">Measures</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'voting_measure'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t581" href="#t581">581</a></span><span class="t">        <span class="nam">max_growing</span><span class="op">:</span> <span class="nam">float</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'max_growing'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t582" href="#t582">582</a></span><span class="t">        <span class="nam">enable_pruning</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'enable_pruning'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t583" href="#t583">583</a></span><span class="t">        <span class="nam">ignore_missing</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'ignore_missing'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t584" href="#t584">584</a></span><span class="t">        <span class="nam">max_uncovered_fraction</span><span class="op">:</span> <span class="nam">float</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'max_uncovered_fraction'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t585" href="#t585">585</a></span><span class="t">        <span class="nam">select_best_candidate</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'select_best_candidate'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t586" href="#t586">586</a></span><span class="t">        <span class="nam">complementary_conditions</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'complementary_conditions'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t587" href="#t587">587</a></span><span class="t">        <span class="nam">control_apriori_precision</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'control_apriori_precision'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t588" href="#t588">588</a></span><span class="t">        <span class="nam">max_rule_count</span><span class="op">:</span> <span class="nam">int</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'max_rule_count'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t589" href="#t589">589</a></span><span class="t">        <span class="nam">approximate_induction</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'approximate_induction'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t590" href="#t590">590</a></span><span class="t">        <span class="nam">approximate_bins_count</span><span class="op">:</span> <span class="nam">int</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'approximate_bins_count'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t591" href="#t591">591</a></span><span class="t">    <span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t592" href="#t592">592</a></span><span class="t">        <span class="str">"""</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t593" href="#t593">593</a></span><span class="t"><span class="str">        Parameters</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t594" href="#t594">594</a></span><span class="t"><span class="str">        ----------</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t595" href="#t595">595</a></span><span class="t"><span class="str">        minsupp_all: Tuple[float, float, float, float]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t596" href="#t596">596</a></span><span class="t"><span class="str">            a minimum positive support of a contrast set (p/P). When multiple values are specified,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t597" href="#t597">597</a></span><span class="t"><span class="str">            a metainduction is performed; Default and recommended sequence is: 0.8, 0.5, 0.2, 0.1</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t598" href="#t598">598</a></span><span class="t"><span class="str">        max_neg2pos: float</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t599" href="#t599">599</a></span><span class="t"><span class="str">            a maximum ratio of negative to positive supports (nP/pN); Default is 0.5</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t600" href="#t600">600</a></span><span class="t"><span class="str">        max_passes_count: int</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t601" href="#t601">601</a></span><span class="t"><span class="str">            a maximum number of sequential covering passes for a single minsupp-all; Default is 5</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t602" href="#t602">602</a></span><span class="t"><span class="str">        penalty_strength: float</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t603" href="#t603">603</a></span><span class="t"><span class="str">            (s) - penalty strength; Default is 0.5</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t604" href="#t604">604</a></span><span class="t"><span class="str">        penalty_saturation: float</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t605" href="#t605">605</a></span><span class="t"><span class="str">            the value of p_new / P at which penalty reward saturates; Default is 0.2.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t606" href="#t606">606</a></span><span class="t"><span class="str">        minsupp_new : float = 5.0</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t607" href="#t607">607</a></span><span class="t"><span class="str">            a minimum number (or fraction, if value &lt; 1.0) of previously uncovered examples</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t608" href="#t608">608</a></span><span class="t"><span class="str">             to be covered by a new rule (positive examples for classification problems); default: 5,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t609" href="#t609">609</a></span><span class="t"><span class="str">        induction_measure : :class:`rulekit.params.Measures` = \</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t610" href="#t610">610</a></span><span class="t"><span class="str">            :class:`rulekit.params.Measures.Correlation`</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t611" href="#t611">611</a></span><span class="t"><span class="str">            measure used during induction; default measure is correlation</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t612" href="#t612">612</a></span><span class="t"><span class="str">        pruning_measure : Union[:class:`rulekit.params.Measures`, str] = \</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t613" href="#t613">613</a></span><span class="t"><span class="str">            :class:`rulekit.params.Measures.Correlation`</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t614" href="#t614">614</a></span><span class="t"><span class="str">            measure used during pruning. Could be user defined (string), for example</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t615" href="#t615">615</a></span><span class="t"><span class="str">             :code:`2 * p / n`; default measure is correlation</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t616" href="#t616">616</a></span><span class="t"><span class="str">        voting_measure : :class:`rulekit.params.Measures` = \</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t617" href="#t617">617</a></span><span class="t"><span class="str">            :class:`rulekit.params.Measures.Correlation`</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t618" href="#t618">618</a></span><span class="t"><span class="str">            measure used during voting; default measure is correlation</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t619" href="#t619">619</a></span><span class="t"><span class="str">        max_growing : int = 0.0</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t620" href="#t620">620</a></span><span class="t"><span class="str">            non-negative integer representing maximum number of conditions which can be added to</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t621" href="#t621">621</a></span><span class="t"><span class="str">            the rule in the growing phase (use this parameter for large datasets if execution time</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t622" href="#t622">622</a></span><span class="t"><span class="str">            is prohibitive); 0 indicates no limit; default: 0,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t623" href="#t623">623</a></span><span class="t"><span class="str">        enable_pruning : bool = True</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t624" href="#t624">624</a></span><span class="t"><span class="str">            enable or disable pruning, default is True.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t625" href="#t625">625</a></span><span class="t"><span class="str">        ignore_missing : bool = False</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t626" href="#t626">626</a></span><span class="t"><span class="str">            boolean telling whether missing values should be ignored (by default, a missing value</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t627" href="#t627">627</a></span><span class="t"><span class="str">            of given attribute is always considered as not fulfilling the condition build upon</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t628" href="#t628">628</a></span><span class="t"><span class="str">             that attribute); default: False.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t629" href="#t629">629</a></span><span class="t"><span class="str">        max_uncovered_fraction : float = 0.0</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t630" href="#t630">630</a></span><span class="t"><span class="str">            Floating-point number from [0,1] interval representing maximum fraction of examples</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t631" href="#t631">631</a></span><span class="t"><span class="str">             that may remain uncovered by the rule set, default: 0.0.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t632" href="#t632">632</a></span><span class="t"><span class="str">        select_best_candidate : bool = False</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t633" href="#t633">633</a></span><span class="t"><span class="str">            Flag determining if best candidate should be selected from growing phase;</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t634" href="#t634">634</a></span><span class="t"><span class="str">             default: False.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t635" href="#t635">635</a></span><span class="t"><span class="str">        complementary_conditions : bool = False</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t636" href="#t636">636</a></span><span class="t"><span class="str">            If enabled, complementary conditions in the form a = !{value} for nominal attributes</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t637" href="#t637">637</a></span><span class="t"><span class="str">            are supported.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t638" href="#t638">638</a></span><span class="t"><span class="str">        control_apriori_precision : bool = True</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t639" href="#t639">639</a></span><span class="t"><span class="str">            When inducing classification rules, verify if candidate precision is higher than</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t640" href="#t640">640</a></span><span class="t"><span class="str">             apriori precision of the investigated class.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t641" href="#t641">641</a></span><span class="t"><span class="str">        max_rule_count : int = 0</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t642" href="#t642">642</a></span><span class="t"><span class="str">            Maximum number of rules to be generated (for classification data sets it applies</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t643" href="#t643">643</a></span><span class="t"><span class="str">             to a single class); 0 indicates no limit.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t644" href="#t644">644</a></span><span class="t"><span class="str">        approximate_induction: bool = False</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t645" href="#t645">645</a></span><span class="t"><span class="str">            Use an approximate induction heuristic which does not check all possible splits;</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t646" href="#t646">646</a></span><span class="t"><span class="str">            note: this is an experimental feature and currently works only for classification</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t647" href="#t647">647</a></span><span class="t"><span class="str">            data sets, results may change in future;</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t648" href="#t648">648</a></span><span class="t"><span class="str">        approximate_bins_count: int = 100</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t649" href="#t649">649</a></span><span class="t"><span class="str">            maximum number of bins for an attribute evaluated in the approximate induction.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t650" href="#t650">650</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t651" href="#t651">651</a></span><span class="t">        <span class="nam">BaseOperator</span><span class="op">.</span><span class="nam">__init__</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t652" href="#t652">652</a></span><span class="t">            <span class="nam">self</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t653" href="#t653">653</a></span><span class="t">            <span class="nam">minsupp_all</span><span class="op">=</span><span class="nam">minsupp_all</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t654" href="#t654">654</a></span><span class="t">            <span class="nam">max_neg2pos</span><span class="op">=</span><span class="nam">max_neg2pos</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t655" href="#t655">655</a></span><span class="t">            <span class="nam">max_passes_count</span><span class="op">=</span><span class="nam">max_passes_count</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t656" href="#t656">656</a></span><span class="t">            <span class="nam">penalty_strength</span><span class="op">=</span><span class="nam">penalty_strength</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t657" href="#t657">657</a></span><span class="t">            <span class="nam">penalty_saturation</span><span class="op">=</span><span class="nam">penalty_saturation</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t658" href="#t658">658</a></span><span class="t">            <span class="nam">minsupp_new</span><span class="op">=</span><span class="nam">minsupp_new</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t659" href="#t659">659</a></span><span class="t">            <span class="nam">induction_measure</span><span class="op">=</span><span class="nam">induction_measure</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t660" href="#t660">660</a></span><span class="t">            <span class="nam">pruning_measure</span><span class="op">=</span><span class="nam">pruning_measure</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t661" href="#t661">661</a></span><span class="t">            <span class="nam">voting_measure</span><span class="op">=</span><span class="nam">voting_measure</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t662" href="#t662">662</a></span><span class="t">            <span class="nam">max_growing</span><span class="op">=</span><span class="nam">max_growing</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t663" href="#t663">663</a></span><span class="t">            <span class="nam">enable_pruning</span><span class="op">=</span><span class="nam">enable_pruning</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t664" href="#t664">664</a></span><span class="t">            <span class="nam">ignore_missing</span><span class="op">=</span><span class="nam">ignore_missing</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t665" href="#t665">665</a></span><span class="t">            <span class="nam">max_uncovered_fraction</span><span class="op">=</span><span class="nam">max_uncovered_fraction</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t666" href="#t666">666</a></span><span class="t">            <span class="nam">select_best_candidate</span><span class="op">=</span><span class="nam">select_best_candidate</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t667" href="#t667">667</a></span><span class="t">            <span class="nam">complementary_conditions</span><span class="op">=</span><span class="nam">complementary_conditions</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t668" href="#t668">668</a></span><span class="t">            <span class="nam">control_apriori_precision</span><span class="op">=</span><span class="nam">control_apriori_precision</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t669" href="#t669">669</a></span><span class="t">            <span class="nam">max_rule_count</span><span class="op">=</span><span class="nam">max_rule_count</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t670" href="#t670">670</a></span><span class="t">            <span class="nam">approximate_induction</span><span class="op">=</span><span class="nam">approximate_induction</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t671" href="#t671">671</a></span><span class="t">            <span class="nam">approximate_bins_count</span><span class="op">=</span><span class="nam">approximate_bins_count</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t672" href="#t672">672</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t673" href="#t673">673</a></span><span class="t">        <span class="nam">BaseClassifier</span><span class="op">.</span><span class="nam">__init__</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t674" href="#t674">674</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">contrast_attribute</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t675" href="#t675">675</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_remap_to_numeric</span> <span class="op">=</span> <span class="key">False</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t676" href="#t676">676</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">label_unique_values</span> <span class="op">=</span> <span class="op">[</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t677" href="#t677">677</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">model</span><span class="op">:</span> <span class="nam">RuleSet</span><span class="op">[</span><span class="nam">ClassificationRule</span><span class="op">]</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t678" href="#t678">678</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t679" href="#t679">679</a></span><span class="t"><span class="str">        Parameters</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t680" href="#t680">680</a></span><span class="t"><span class="str">        ----------</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t681" href="#t681">681</a></span><span class="t"><span class="str">        values : :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t682" href="#t682">682</a></span><span class="t"><span class="str">            attributes</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t683" href="#t683">683</a></span><span class="t"><span class="str">        labels : :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t684" href="#t684">684</a></span><span class="t"><span class="str">            labels</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t685" href="#t685">685</a></span><span class="t"><span class="str">        contrast_attribute: str</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t686" href="#t686">686</a></span><span class="t"><span class="str">            group attribute</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t687" href="#t687">687</a></span><span class="t"><span class="str">        Returns</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t688" href="#t688">688</a></span><span class="t"><span class="str">        -------</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t689" href="#t689">689</a></span><span class="t"><span class="str">        self : ContrastSetRuleClassifier</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t690" href="#t690">690</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t691" href="#t691">691</a></span><span class="t">        <span class="nam">RuleClassifier</span><span class="op">.</span><span class="nam">_get_unique_label_values</span><span class="op">(</span>  <span class="com"># pylint: disable=protected-access</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t692" href="#t692">692</a></span><span class="t">            <span class="nam">self</span><span class="op">,</span> <span class="nam">labels</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t693" href="#t693">693</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t694" href="#t694">694</a></span><span class="t">        <span class="nam">RuleClassifier</span><span class="op">.</span><span class="nam">_prepare_labels</span><span class="op">(</span>  <span class="com"># pylint: disable=protected-access,protected-access</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t695" href="#t695">695</a></span><span class="t">            <span class="nam">self</span><span class="op">,</span> <span class="nam">labels</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t696" href="#t696">696</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t697" href="#t697">697</a></span><span class="t">        <span class="nam">BaseOperator</span><span class="op">.</span><span class="nam">fit</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t698" href="#t698">698</a></span><span class="t">            <span class="nam">self</span><span class="op">,</span> <span class="nam">values</span><span class="op">,</span> <span class="nam">labels</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t699" href="#t699">699</a></span><span class="t">            <span class="nam">contrast_attribute</span><span class="op">=</span><span class="nam">contrast_attribute</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t700" href="#t700">700</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t701" href="#t701">701</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">contrast_attribute</span> <span class="op">=</span> <span class="nam">contrast_attribute</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t702" href="#t702">702</a></span><span class="t">        <span class="key">return</span> <span class="nam">self</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t703" href="#t703">703</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t704" href="#t704">704</a></span><span class="t">    <span class="key">def</span> <span class="nam">predict</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t705" href="#t705">705</a></span><span class="t">        <span class="nam">self</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t706" href="#t706">706</a></span><span class="t">        <span class="nam">values</span><span class="op">:</span> <span class="nam">Data</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t707" href="#t707">707</a></span><span class="t">        <span class="nam">return_metrics</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="key">False</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t708" href="#t708">708</a></span><span class="t">    <span class="op">)</span> <span class="op">-></span> <span class="nam">Union</span><span class="op">[</span><span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span><span class="op">,</span> <span class="nam">tuple</span><span class="op">[</span><span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span><span class="op">,</span> <span class="nam">ClassificationPredictionMetrics</span><span class="op">]</span><span class="op">]</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t709" href="#t709">709</a></span><span class="t">        <span class="str">"""Perform prediction and returns predicted labels.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t710" href="#t710">710</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t711" href="#t711">711</a></span><span class="t"><span class="str">        Parameters</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t712" href="#t712">712</a></span><span class="t"><span class="str">        ----------</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t713" href="#t713">713</a></span><span class="t"><span class="str">        values : :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t714" href="#t714">714</a></span><span class="t"><span class="str">            attributes</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t715" href="#t715">715</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t716" href="#t716">716</a></span><span class="t"><span class="str">        return_metrics: bool = False</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t717" href="#t717">717</a></span><span class="t"><span class="str">            Optional flag. If set to *True* method will calculate some additional model metrics.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t718" href="#t718">718</a></span><span class="t"><span class="str">             Method will then return tuple instead of just predicted labels.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t719" href="#t719">719</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t720" href="#t720">720</a></span><span class="t"><span class="str">        Returns</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t721" href="#t721">721</a></span><span class="t"><span class="str">        -------</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t722" href="#t722">722</a></span><span class="t"><span class="str">        result : Union[np.ndarray, tuple[np.ndarray, :class:`rulekit.classification.ClassificationPredictionMetrics`]]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t723" href="#t723">723</a></span><span class="t"><span class="str">            If *return_metrics* flag wasn't set it will return just prediction, otherwise a tuple</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t724" href="#t724">724</a></span><span class="t"><span class="str">            will be returned with first element being prediction and second one being metrics.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t725" href="#t725">725</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t726" href="#t726">726</a></span><span class="t">        <span class="key">return</span> <span class="nam">RuleClassifier</span><span class="op">.</span><span class="nam">predict</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">values</span><span class="op">,</span> <span class="nam">return_metrics</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t727" href="#t727">727</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t728" href="#t728">728</a></span><span class="t">    <span class="key">def</span> <span class="nam">predict_proba</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t729" href="#t729">729</a></span><span class="t">        <span class="nam">self</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t730" href="#t730">730</a></span><span class="t">        <span class="nam">values</span><span class="op">:</span> <span class="nam">Data</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t731" href="#t731">731</a></span><span class="t">        <span class="nam">return_metrics</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="key">False</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t732" href="#t732">732</a></span><span class="t">    <span class="op">)</span> <span class="op">-></span> <span class="nam">Union</span><span class="op">[</span><span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span><span class="op">,</span> <span class="nam">tuple</span><span class="op">[</span><span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span><span class="op">,</span> <span class="nam">ClassificationPredictionMetrics</span><span class="op">]</span><span class="op">]</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t733" href="#t733">733</a></span><span class="t">        <span class="str">"""Perform prediction and returns class probabilities for each example.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t734" href="#t734">734</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t735" href="#t735">735</a></span><span class="t"><span class="str">        Parameters</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t736" href="#t736">736</a></span><span class="t"><span class="str">        ----------</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t737" href="#t737">737</a></span><span class="t"><span class="str">        values : :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t738" href="#t738">738</a></span><span class="t"><span class="str">            attributes</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t739" href="#t739">739</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t740" href="#t740">740</a></span><span class="t"><span class="str">        return_metrics: bool = False</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t741" href="#t741">741</a></span><span class="t"><span class="str">            Optional flag. If set to *True* method will calculate some additional model metrics.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t742" href="#t742">742</a></span><span class="t"><span class="str">             Method will then return tuple instead of just probabilities.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t743" href="#t743">743</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t744" href="#t744">744</a></span><span class="t"><span class="str">        Returns</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t745" href="#t745">745</a></span><span class="t"><span class="str">        -------</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t746" href="#t746">746</a></span><span class="t"><span class="str">        result : Union[np.ndarray, tuple[np.ndarray, :class:`rulekit.classification.ClassificationPredictionMetrics`]]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t747" href="#t747">747</a></span><span class="t"><span class="str">            If *return_metrics* flag wasn't set it will return just probabilities matrix, otherwise</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t748" href="#t748">748</a></span><span class="t"><span class="str">            a tuple will be returned with first element being prediction and second one being</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t749" href="#t749">749</a></span><span class="t"><span class="str">            metrics.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t750" href="#t750">750</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t751" href="#t751">751</a></span><span class="t">        <span class="key">return</span> <span class="nam">RuleClassifier</span><span class="op">.</span><span class="nam">predict_proba</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">values</span><span class="op">,</span> <span class="nam">return_metrics</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t752" href="#t752">752</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t753" href="#t753">753</a></span><span class="t">    <span class="key">def</span> <span class="nam">score</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">values</span><span class="op">:</span> <span class="nam">Data</span><span class="op">,</span> <span class="nam">labels</span><span class="op">:</span> <span class="nam">Data</span><span class="op">)</span> <span class="op">-></span> <span class="nam">float</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t754" href="#t754">754</a></span><span class="t">        <span class="str">"""Return the accuracy on the given test data and labels.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t755" href="#t755">755</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t756" href="#t756">756</a></span><span class="t"><span class="str">        Parameters</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t757" href="#t757">757</a></span><span class="t"><span class="str">        ----------</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t758" href="#t758">758</a></span><span class="t"><span class="str">        values : :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t759" href="#t759">759</a></span><span class="t"><span class="str">            attributes</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t760" href="#t760">760</a></span><span class="t"><span class="str">        labels : :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t761" href="#t761">761</a></span><span class="t"><span class="str">            true labels</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t762" href="#t762">762</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t763" href="#t763">763</a></span><span class="t"><span class="str">        Returns</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t764" href="#t764">764</a></span><span class="t"><span class="str">        -------</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t765" href="#t765">765</a></span><span class="t"><span class="str">        score : float</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t766" href="#t766">766</a></span><span class="t"><span class="str">            Accuracy of self.predict(values) wrt. labels.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t767" href="#t767">767</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t768" href="#t768">768</a></span><span class="t">        <span class="key">return</span> <span class="nam">RuleClassifier</span><span class="op">.</span><span class="nam">score</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">values</span><span class="op">,</span> <span class="nam">labels</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t769" href="#t769">769</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t770" href="#t770">770</a></span><span class="t">    <span class="key">def</span> <span class="nam">__getstate__</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">dict</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t771" href="#t771">771</a></span><span class="t">        <span class="key">return</span> <span class="op">{</span><span class="op">**</span><span class="nam">BaseOperator</span><span class="op">.</span><span class="nam">__getstate__</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">,</span> <span class="op">**</span><span class="op">{</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t772" href="#t772">772</a></span><span class="t">            <span class="str">'label_unique_values'</span><span class="op">:</span> <span class="nam">self</span><span class="op">.</span><span class="nam">label_unique_values</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t773" href="#t773">773</a></span><span class="t">            <span class="str">'_remap_to_numeric'</span><span class="op">:</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_remap_to_numeric</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t774" href="#t774">774</a></span><span class="t">            <span class="str">'contrast_attribute'</span><span class="op">:</span> <span class="nam">self</span><span class="op">.</span><span class="nam">contrast_attribute</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t775" href="#t775">775</a></span><span class="t">        <span class="op">}</span><span class="op">}</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t776" href="#t776">776</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t777" href="#t777">777</a></span><span class="t">    <span class="key">def</span> <span class="nam">__setstate__</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">state</span><span class="op">:</span> <span class="nam">dict</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t778" href="#t778">778</a></span><span class="t">        <span class="nam">BaseOperator</span><span class="op">.</span><span class="nam">__setstate__</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">state</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t779" href="#t779">779</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_init_classification_rule_performance_classes</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t780" href="#t780">780</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">label_unique_values</span> <span class="op">=</span> <span class="nam">state</span><span class="op">[</span><span class="str">'label_unique_values'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t781" href="#t781">781</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_remap_to_numeric</span> <span class="op">=</span> <span class="nam">state</span><span class="op">[</span><span class="str">'_remap_to_numeric'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t782" href="#t782">782</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">contrast_attribute</span> <span class="op">=</span> <span class="nam">state</span><span class="op">[</span><span class="str">'contrast_attribute'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t783" href="#t783">783</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t784" href="#t784">784</a></span><span class="t">    <span class="key">def</span> <span class="nam">_get_problem_type</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">ProblemType</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t785" href="#t785">785</a></span><span class="t">        <span class="key">return</span> <span class="nam">ProblemType</span><span class="op">.</span><span class="nam">CONTRAST_CLASSIFICATION</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t679" href="#t679">679</a></span><span class="t">    <span class="key">def</span> <span class="nam">_map_result</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">predicted_example_set</span><span class="op">)</span> <span class="op">-></span> <span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t680" href="#t680">680</a></span><span class="t">        <span class="nam">prediction</span><span class="op">:</span> <span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t681" href="#t681">681</a></span><span class="t">        <span class="key">if</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_remap_to_numeric</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t682" href="#t682">682</a></span><span class="t">            <span class="nam">prediction</span> <span class="op">=</span> <span class="nam">PredictionResultMapper</span><span class="op">.</span><span class="nam">map_to_numerical</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t683" href="#t683">683</a></span><span class="t">                <span class="nam">predicted_example_set</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t684" href="#t684">684</a></span><span class="t">        <span class="key">else</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t685" href="#t685">685</a></span><span class="t">            <span class="nam">prediction</span> <span class="op">=</span> <span class="nam">PredictionResultMapper</span><span class="op">.</span><span class="nam">map_to_nominal</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t686" href="#t686">686</a></span><span class="t">                <span class="nam">predicted_example_set</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t687" href="#t687">687</a></span><span class="t">        <span class="key">return</span> <span class="nam">prediction</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t688" href="#t688">688</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t689" href="#t689">689</a></span><span class="t">    <span class="key">def</span> <span class="nam">_get_unique_label_values</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">labels</span><span class="op">:</span> <span class="nam">Data</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t690" href="#t690">690</a></span><span class="t">        <span class="nam">tmp</span> <span class="op">=</span> <span class="op">{</span><span class="op">}</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t691" href="#t691">691</a></span><span class="t">        <span class="key">for</span> <span class="nam">label_value</span> <span class="key">in</span> <span class="nam">labels</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t692" href="#t692">692</a></span><span class="t">            <span class="nam">tmp</span><span class="op">[</span><span class="nam">label_value</span><span class="op">]</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t693" href="#t693">693</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">label_unique_values</span> <span class="op">=</span> <span class="nam">list</span><span class="op">(</span><span class="nam">tmp</span><span class="op">.</span><span class="nam">keys</span><span class="op">(</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t694" href="#t694">694</a></span><span class="t">        <span class="key">if</span> <span class="nam">len</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">label_unique_values</span><span class="op">)</span> <span class="op">></span> <span class="num">0</span> <span class="key">and</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">label_unique_values</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="op">,</span> <span class="nam">bytes</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t695" href="#t695">695</a></span><span class="t">            <span class="nam">self</span><span class="op">.</span><span class="nam">label_unique_values</span> <span class="op">=</span> <span class="op">[</span><span class="nam">item</span><span class="op">.</span><span class="nam">decode</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t696" href="#t696">696</a></span><span class="t">                <span class="str">'utf-8'</span><span class="op">)</span> <span class="key">for</span> <span class="nam">item</span> <span class="key">in</span> <span class="nam">self</span><span class="op">.</span><span class="nam">label_unique_values</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t697" href="#t697">697</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t698" href="#t698">698</a></span><span class="t">    <span class="key">def</span> <span class="nam">fit</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">values</span><span class="op">:</span> <span class="nam">Data</span><span class="op">,</span> <span class="nam">labels</span><span class="op">:</span> <span class="nam">Data</span><span class="op">,</span> <span class="nam">contrast_attribute</span><span class="op">:</span> <span class="nam">str</span><span class="op">)</span> <span class="op">-></span> <span class="nam">ContrastSetRuleClassifier</span><span class="op">:</span>  <span class="com"># pylint: disable=arguments-differ</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t699" href="#t699">699</a></span><span class="t">        <span class="str">"""Train model on given dataset.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t700" href="#t700">700</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t701" href="#t701">701</a></span><span class="t"><span class="str">        Parameters</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t702" href="#t702">702</a></span><span class="t"><span class="str">        ----------</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t703" href="#t703">703</a></span><span class="t"><span class="str">        values : :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t704" href="#t704">704</a></span><span class="t"><span class="str">            attributes</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t705" href="#t705">705</a></span><span class="t"><span class="str">        labels : :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t706" href="#t706">706</a></span><span class="t"><span class="str">            labels</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t707" href="#t707">707</a></span><span class="t"><span class="str">        contrast_attribute: str</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t708" href="#t708">708</a></span><span class="t"><span class="str">            group attribute</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t709" href="#t709">709</a></span><span class="t"><span class="str">        Returns</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t710" href="#t710">710</a></span><span class="t"><span class="str">        -------</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t711" href="#t711">711</a></span><span class="t"><span class="str">        self : ContrastSetRuleClassifier</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t712" href="#t712">712</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t713" href="#t713">713</a></span><span class="t">        <span class="nam">RuleClassifier</span><span class="op">.</span><span class="nam">_get_unique_label_values</span><span class="op">(</span>  <span class="com"># pylint: disable=protected-access</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t714" href="#t714">714</a></span><span class="t">            <span class="nam">self</span><span class="op">,</span> <span class="nam">labels</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t715" href="#t715">715</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t716" href="#t716">716</a></span><span class="t">        <span class="nam">RuleClassifier</span><span class="op">.</span><span class="nam">_prepare_labels</span><span class="op">(</span>  <span class="com"># pylint: disable=protected-access,protected-access</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t717" href="#t717">717</a></span><span class="t">            <span class="nam">self</span><span class="op">,</span> <span class="nam">labels</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t718" href="#t718">718</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t719" href="#t719">719</a></span><span class="t">        <span class="nam">BaseOperator</span><span class="op">.</span><span class="nam">fit</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t720" href="#t720">720</a></span><span class="t">            <span class="nam">self</span><span class="op">,</span> <span class="nam">values</span><span class="op">,</span> <span class="nam">labels</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t721" href="#t721">721</a></span><span class="t">            <span class="nam">contrast_attribute</span><span class="op">=</span><span class="nam">contrast_attribute</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t722" href="#t722">722</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t723" href="#t723">723</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">contrast_attribute</span> <span class="op">=</span> <span class="nam">contrast_attribute</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t724" href="#t724">724</a></span><span class="t">        <span class="key">return</span> <span class="nam">self</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t725" href="#t725">725</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t726" href="#t726">726</a></span><span class="t">    <span class="key">def</span> <span class="nam">predict</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t727" href="#t727">727</a></span><span class="t">        <span class="nam">self</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t728" href="#t728">728</a></span><span class="t">        <span class="nam">values</span><span class="op">:</span> <span class="nam">Data</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t729" href="#t729">729</a></span><span class="t">        <span class="nam">return_metrics</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="key">False</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t730" href="#t730">730</a></span><span class="t">    <span class="op">)</span> <span class="op">-></span> <span class="nam">Union</span><span class="op">[</span><span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span><span class="op">,</span> <span class="nam">tuple</span><span class="op">[</span><span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span><span class="op">,</span> <span class="nam">ClassificationPredictionMetrics</span><span class="op">]</span><span class="op">]</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t731" href="#t731">731</a></span><span class="t">        <span class="str">"""Perform prediction and returns predicted labels.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t732" href="#t732">732</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t733" href="#t733">733</a></span><span class="t"><span class="str">        Parameters</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t734" href="#t734">734</a></span><span class="t"><span class="str">        ----------</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t735" href="#t735">735</a></span><span class="t"><span class="str">        values : :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t736" href="#t736">736</a></span><span class="t"><span class="str">            attributes</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t737" href="#t737">737</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t738" href="#t738">738</a></span><span class="t"><span class="str">        return_metrics: bool = False</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t739" href="#t739">739</a></span><span class="t"><span class="str">            Optional flag. If set to *True* method will calculate some additional model metrics.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t740" href="#t740">740</a></span><span class="t"><span class="str">             Method will then return tuple instead of just predicted labels.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t741" href="#t741">741</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t742" href="#t742">742</a></span><span class="t"><span class="str">        Returns</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t743" href="#t743">743</a></span><span class="t"><span class="str">        -------</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t744" href="#t744">744</a></span><span class="t"><span class="str">        result : Union[np.ndarray, tuple[np.ndarray, :class:`rulekit.classification.ClassificationPredictionMetrics`]]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t745" href="#t745">745</a></span><span class="t"><span class="str">            If *return_metrics* flag wasn't set it will return just prediction, otherwise a tuple</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t746" href="#t746">746</a></span><span class="t"><span class="str">            will be returned with first element being prediction and second one being metrics.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t747" href="#t747">747</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t748" href="#t748">748</a></span><span class="t">        <span class="key">return</span> <span class="nam">RuleClassifier</span><span class="op">.</span><span class="nam">predict</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">values</span><span class="op">,</span> <span class="nam">return_metrics</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t749" href="#t749">749</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t750" href="#t750">750</a></span><span class="t">    <span class="key">def</span> <span class="nam">predict_proba</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t751" href="#t751">751</a></span><span class="t">        <span class="nam">self</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t752" href="#t752">752</a></span><span class="t">        <span class="nam">values</span><span class="op">:</span> <span class="nam">Data</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t753" href="#t753">753</a></span><span class="t">        <span class="nam">return_metrics</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="key">False</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t754" href="#t754">754</a></span><span class="t">    <span class="op">)</span> <span class="op">-></span> <span class="nam">Union</span><span class="op">[</span><span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span><span class="op">,</span> <span class="nam">tuple</span><span class="op">[</span><span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span><span class="op">,</span> <span class="nam">ClassificationPredictionMetrics</span><span class="op">]</span><span class="op">]</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t755" href="#t755">755</a></span><span class="t">        <span class="str">"""Perform prediction and returns class probabilities for each example.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t756" href="#t756">756</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t757" href="#t757">757</a></span><span class="t"><span class="str">        Parameters</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t758" href="#t758">758</a></span><span class="t"><span class="str">        ----------</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t759" href="#t759">759</a></span><span class="t"><span class="str">        values : :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t760" href="#t760">760</a></span><span class="t"><span class="str">            attributes</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t761" href="#t761">761</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t762" href="#t762">762</a></span><span class="t"><span class="str">        return_metrics: bool = False</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t763" href="#t763">763</a></span><span class="t"><span class="str">            Optional flag. If set to *True* method will calculate some additional model metrics.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t764" href="#t764">764</a></span><span class="t"><span class="str">             Method will then return tuple instead of just probabilities.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t765" href="#t765">765</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t766" href="#t766">766</a></span><span class="t"><span class="str">        Returns</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t767" href="#t767">767</a></span><span class="t"><span class="str">        -------</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t768" href="#t768">768</a></span><span class="t"><span class="str">        result : Union[ \</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t769" href="#t769">769</a></span><span class="t"><span class="str">            np.ndarray,  \</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t770" href="#t770">770</a></span><span class="t"><span class="str">            tuple[np.ndarray, :class:`rulekit.classification.ClassificationPredictionMetrics`] \</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t771" href="#t771">771</a></span><span class="t"><span class="str">        ] \</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t772" href="#t772">772</a></span><span class="t"><span class="str">        If *return_metrics* flag wasn't set it will return just probabilities matrix, otherwise \</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t773" href="#t773">773</a></span><span class="t"><span class="str">        a tuple will be returned with first element being prediction and second one being \</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t774" href="#t774">774</a></span><span class="t"><span class="str">        metrics.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t775" href="#t775">775</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t776" href="#t776">776</a></span><span class="t">        <span class="key">return</span> <span class="nam">RuleClassifier</span><span class="op">.</span><span class="nam">predict_proba</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">values</span><span class="op">,</span> <span class="nam">return_metrics</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t777" href="#t777">777</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t778" href="#t778">778</a></span><span class="t">    <span class="key">def</span> <span class="nam">score</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">values</span><span class="op">:</span> <span class="nam">Data</span><span class="op">,</span> <span class="nam">labels</span><span class="op">:</span> <span class="nam">Data</span><span class="op">)</span> <span class="op">-></span> <span class="nam">float</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t779" href="#t779">779</a></span><span class="t">        <span class="str">"""Return the accuracy on the given test data and labels.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t780" href="#t780">780</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t781" href="#t781">781</a></span><span class="t"><span class="str">        Parameters</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t782" href="#t782">782</a></span><span class="t"><span class="str">        ----------</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t783" href="#t783">783</a></span><span class="t"><span class="str">        values : :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t784" href="#t784">784</a></span><span class="t"><span class="str">            attributes</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t785" href="#t785">785</a></span><span class="t"><span class="str">        labels : :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t786" href="#t786">786</a></span><span class="t"><span class="str">            true labels</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t787" href="#t787">787</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t788" href="#t788">788</a></span><span class="t"><span class="str">        Returns</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t789" href="#t789">789</a></span><span class="t"><span class="str">        -------</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t790" href="#t790">790</a></span><span class="t"><span class="str">        score : float</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t791" href="#t791">791</a></span><span class="t"><span class="str">            Accuracy of self.predict(values) wrt. labels.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t792" href="#t792">792</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t793" href="#t793">793</a></span><span class="t">        <span class="key">return</span> <span class="nam">RuleClassifier</span><span class="op">.</span><span class="nam">score</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">values</span><span class="op">,</span> <span class="nam">labels</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t794" href="#t794">794</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t795" href="#t795">795</a></span><span class="t">    <span class="key">def</span> <span class="nam">__getstate__</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">dict</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t796" href="#t796">796</a></span><span class="t">        <span class="key">return</span> <span class="op">{</span><span class="op">**</span><span class="nam">BaseOperator</span><span class="op">.</span><span class="nam">__getstate__</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">,</span> <span class="op">**</span><span class="op">{</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t797" href="#t797">797</a></span><span class="t">            <span class="str">'label_unique_values'</span><span class="op">:</span> <span class="nam">self</span><span class="op">.</span><span class="nam">label_unique_values</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t798" href="#t798">798</a></span><span class="t">            <span class="str">'_remap_to_numeric'</span><span class="op">:</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_remap_to_numeric</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t799" href="#t799">799</a></span><span class="t">            <span class="str">'contrast_attribute'</span><span class="op">:</span> <span class="nam">self</span><span class="op">.</span><span class="nam">contrast_attribute</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t800" href="#t800">800</a></span><span class="t">        <span class="op">}</span><span class="op">}</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t801" href="#t801">801</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t802" href="#t802">802</a></span><span class="t">    <span class="key">def</span> <span class="nam">__setstate__</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">state</span><span class="op">:</span> <span class="nam">dict</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t803" href="#t803">803</a></span><span class="t">        <span class="nam">BaseOperator</span><span class="op">.</span><span class="nam">__setstate__</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">state</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t804" href="#t804">804</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_init_classification_rule_performance_classes</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t805" href="#t805">805</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">label_unique_values</span> <span class="op">=</span> <span class="nam">state</span><span class="op">[</span><span class="str">'label_unique_values'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t806" href="#t806">806</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_remap_to_numeric</span> <span class="op">=</span> <span class="nam">state</span><span class="op">[</span><span class="str">'_remap_to_numeric'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t807" href="#t807">807</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">contrast_attribute</span> <span class="op">=</span> <span class="nam">state</span><span class="op">[</span><span class="str">'contrast_attribute'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t808" href="#t808">808</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t809" href="#t809">809</a></span><span class="t">    <span class="key">def</span> <span class="nam">_get_problem_type</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">ProblemType</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t810" href="#t810">810</a></span><span class="t">        <span class="key">return</span> <span class="nam">ProblemType</span><span class="op">.</span><span class="nam">CONTRAST_CLASSIFICATION</span>&nbsp;</span><span class="r"></span></p>
 </main>
 <footer>
     <div class="content">
@@ -874,7 +899,7 @@ <h2>
             <a class="nav" href="z_a87f2a4bb6695d91_events_py.html">&#xbb; next</a>
             &nbsp; &nbsp; &nbsp;
             <a class="nav" href="https://coverage.readthedocs.io/en/7.6.4">coverage.py v7.6.4</a>,
-            created at 2024-11-08 14:43 +0100
+            created at 2024-11-28 12:33 +0100
         </p>
     </div>
 </footer>
diff --git a/docs/reports/coverage/z_a87f2a4bb6695d91_events_py.html b/docs/reports/coverage/z_a87f2a4bb6695d91_events_py.html
index b4b2422..0e38568 100644
--- a/docs/reports/coverage/z_a87f2a4bb6695d91_events_py.html
+++ b/docs/reports/coverage/z_a87f2a4bb6695d91_events_py.html
@@ -54,8 +54,8 @@ <h1>
             </div>
         </aside>
         <h2>
-            <span class="text">23 statements &nbsp;</span>
-            <button type="button" class="run button_toggle_run" value="run" data-shortcut="r" title="Toggle lines run">23<span class="text"> run</span></button>
+            <span class="text">27 statements &nbsp;</span>
+            <button type="button" class="run button_toggle_run" value="run" data-shortcut="r" title="Toggle lines run">27<span class="text"> run</span></button>
             <button type="button" class="mis show_mis button_toggle_mis" value="mis" data-shortcut="m" title="Toggle lines missing">0<span class="text"> missing</span></button>
             <button type="button" class="exc show_exc button_toggle_exc" value="exc" data-shortcut="x" title="Toggle lines excluded">0<span class="text"> excluded</span></button>
         </h2>
@@ -65,7 +65,7 @@ <h2>
             <a id="nextFileLink" class="nav" href="z_a87f2a4bb6695d91_exceptions_py.html">&#xbb; next</a>
             &nbsp; &nbsp; &nbsp;
             <a class="nav" href="https://coverage.readthedocs.io/en/7.6.4">coverage.py v7.6.4</a>,
-            created at 2024-11-08 14:43 +0100
+            created at 2024-11-28 11:55 +0100
         </p>
         <aside class="hidden">
             <button type="button" class="button_next_chunk" data-shortcut="j"></button>
@@ -84,71 +84,79 @@ <h2>
     <p class="pln"><span class="n"><a id="t2" href="#t2">2</a></span><span class="t"><span class="str">"""</span>&nbsp;</span><span class="r"></span></p>
     <p class="run"><span class="n"><a id="t3" href="#t3">3</a></span><span class="t"><span class="key">from</span> <span class="nam">typing</span> <span class="key">import</span> <span class="nam">Any</span>&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t4" href="#t4">4</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t5" href="#t5">5</a></span><span class="t"><span class="key">from</span> <span class="nam">jpype</span> <span class="key">import</span> <span class="nam">JImplements</span><span class="op">,</span> <span class="nam">JInt</span><span class="op">,</span> <span class="nam">JObject</span><span class="op">,</span> <span class="nam">JOverride</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t6" href="#t6">6</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t7" href="#t7">7</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">rules</span> <span class="key">import</span> <span class="nam">BaseRule</span><span class="op">,</span> <span class="nam">_rule_factory</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t8" href="#t8">8</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t5" href="#t5">5</a></span><span class="t"><span class="key">from</span> <span class="nam">jpype</span> <span class="key">import</span> <span class="nam">JImplements</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t6" href="#t6">6</a></span><span class="t"><span class="key">from</span> <span class="nam">jpype</span> <span class="key">import</span> <span class="nam">JInt</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t7" href="#t7">7</a></span><span class="t"><span class="key">from</span> <span class="nam">jpype</span> <span class="key">import</span> <span class="nam">JObject</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t8" href="#t8">8</a></span><span class="t"><span class="key">from</span> <span class="nam">jpype</span> <span class="key">import</span> <span class="nam">JOverride</span>&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t9" href="#t9">9</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t10" href="#t10">10</a></span><span class="t"><span class="key">class</span> <span class="nam">RuleInductionProgressListener</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t11" href="#t11">11</a></span><span class="t">    <span class="str">"""Base class for rule induction progress listeners. To use it, subclass it</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t12" href="#t12">12</a></span><span class="t"><span class="str">    and implement some of the its methods. Then instantiate it and pass it to</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t13" href="#t13">13</a></span><span class="t"><span class="str">     `add_event_listener` method of the operator.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t14" href="#t14">14</a></span><span class="t"><span class="str">    """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t15" href="#t15">15</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t16" href="#t16">16</a></span><span class="t">    <span class="key">def</span> <span class="nam">on_new_rule</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">rule</span><span class="op">:</span> <span class="nam">BaseRule</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t17" href="#t17">17</a></span><span class="t">        <span class="str">"""Called when new rule is induced</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t18" href="#t18">18</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t19" href="#t19">19</a></span><span class="t"><span class="str">        Args:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t20" href="#t20">20</a></span><span class="t"><span class="str">            rule (BaseRule): Newly induced rule</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t21" href="#t21">21</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t10" href="#t10">10</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">rules</span> <span class="key">import</span> <span class="nam">_rule_factory</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t11" href="#t11">11</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">rules</span> <span class="key">import</span> <span class="nam">BaseRule</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t12" href="#t12">12</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t13" href="#t13">13</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t14" href="#t14">14</a></span><span class="t"><span class="key">class</span> <span class="nam">RuleInductionProgressListener</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t15" href="#t15">15</a></span><span class="t">    <span class="str">"""Base class for rule induction progress listeners. To use it, subclass it</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t16" href="#t16">16</a></span><span class="t"><span class="str">    and implement some of the its methods. Then instantiate it and pass it to</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t17" href="#t17">17</a></span><span class="t"><span class="str">     `add_event_listener` method of the operator.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t18" href="#t18">18</a></span><span class="t"><span class="str">    """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t19" href="#t19">19</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t20" href="#t20">20</a></span><span class="t">    <span class="key">def</span> <span class="nam">on_new_rule</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">rule</span><span class="op">:</span> <span class="nam">BaseRule</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t21" href="#t21">21</a></span><span class="t">        <span class="str">"""Called when new rule is induced</span>&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t22" href="#t22">22</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t23" href="#t23">23</a></span><span class="t">    <span class="key">def</span> <span class="nam">on_progress</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t24" href="#t24">24</a></span><span class="t">        <span class="nam">self</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t25" href="#t25">25</a></span><span class="t">        <span class="nam">total_examples_count</span><span class="op">:</span> <span class="nam">int</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t26" href="#t26">26</a></span><span class="t">        <span class="nam">uncovered_examples_count</span><span class="op">:</span> <span class="nam">int</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t27" href="#t27">27</a></span><span class="t">    <span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t28" href="#t28">28</a></span><span class="t">        <span class="str">"""Called each time a ruleset coverage changed.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t29" href="#t29">29</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t30" href="#t30">30</a></span><span class="t"><span class="str">        This method is best suited to monitor progress of rule induction.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t31" href="#t31">31</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t32" href="#t32">32</a></span><span class="t"><span class="str">        Args:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t33" href="#t33">33</a></span><span class="t"><span class="str">            total_examples_count (int): Total number of examples in training dataset</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t34" href="#t34">34</a></span><span class="t"><span class="str">            uncovered_examples_count (int): Number of examples that are not covered by any rule</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t35" href="#t35">35</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t36" href="#t36">36</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t37" href="#t37">37</a></span><span class="t">    <span class="key">def</span> <span class="nam">should_stop</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">bool</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t38" href="#t38">38</a></span><span class="t">        <span class="str">"""Method which allows to stop rule induction process at given moment. This method is</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t39" href="#t39">39</a></span><span class="t"><span class="str">         called each time a ruleset coverage changed. If it returns `True`, rule induction process</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t40" href="#t40">40</a></span><span class="t"><span class="str">        will be stopped if it return `False` it will continue.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t41" href="#t41">41</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t42" href="#t42">42</a></span><span class="t"><span class="str">        Returns:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t43" href="#t43">43</a></span><span class="t"><span class="str">            bool: whether to stop rule induction or not</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t44" href="#t44">44</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t45" href="#t45">45</a></span><span class="t">        <span class="key">return</span> <span class="key">False</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t46" href="#t46">46</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t47" href="#t47">47</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t48" href="#t48">48</a></span><span class="t"><span class="key">def</span> <span class="nam">command_listener_factory</span><span class="op">(</span><span class="nam">listener</span><span class="op">:</span> <span class="nam">RuleInductionProgressListener</span><span class="op">)</span> <span class="op">-></span> <span class="nam">Any</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t49" href="#t49">49</a></span><span class="t">    <span class="key">from</span> <span class="nam">adaa</span><span class="op">.</span><span class="nam">analytics</span><span class="op">.</span><span class="nam">rules</span><span class="op">.</span><span class="nam">logic</span><span class="op">.</span><span class="nam">rulegenerator</span> <span class="key">import</span> <span class="xx">\</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t50" href="#t50">50</a></span><span class="t">        <span class="nam">ICommandListener</span>  <span class="com"># pylint: disable=import-outside-toplevel,import-error</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t51" href="#t51">51</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t52" href="#t52">52</a></span><span class="t">    <span class="op">@</span><span class="nam">JImplements</span><span class="op">(</span><span class="nam">ICommandListener</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t53" href="#t53">53</a></span><span class="t">    <span class="key">class</span> <span class="nam">_CommandListener</span><span class="op">:</span>  <span class="com"># pylint: disable=invalid-name,missing-function-docstring</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t23" href="#t23">23</a></span><span class="t"><span class="str">        Args:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t24" href="#t24">24</a></span><span class="t"><span class="str">            rule (BaseRule): Newly induced rule</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t25" href="#t25">25</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t26" href="#t26">26</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t27" href="#t27">27</a></span><span class="t">    <span class="key">def</span> <span class="nam">on_progress</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t28" href="#t28">28</a></span><span class="t">        <span class="nam">self</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t29" href="#t29">29</a></span><span class="t">        <span class="nam">total_examples_count</span><span class="op">:</span> <span class="nam">int</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t30" href="#t30">30</a></span><span class="t">        <span class="nam">uncovered_examples_count</span><span class="op">:</span> <span class="nam">int</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t31" href="#t31">31</a></span><span class="t">    <span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t32" href="#t32">32</a></span><span class="t">        <span class="str">"""Called each time a ruleset coverage changed.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t33" href="#t33">33</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t34" href="#t34">34</a></span><span class="t"><span class="str">        This method is best suited to monitor progress of rule induction.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t35" href="#t35">35</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t36" href="#t36">36</a></span><span class="t"><span class="str">        Args:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t37" href="#t37">37</a></span><span class="t"><span class="str">            total_examples_count (int): Total number of examples in</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t38" href="#t38">38</a></span><span class="t"><span class="str">            training dataset</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t39" href="#t39">39</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t40" href="#t40">40</a></span><span class="t"><span class="str">            uncovered_examples_count (int): Number of examples that</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t41" href="#t41">41</a></span><span class="t"><span class="str">            are not covered by any rule</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t42" href="#t42">42</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t43" href="#t43">43</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t44" href="#t44">44</a></span><span class="t">    <span class="key">def</span> <span class="nam">should_stop</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">bool</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t45" href="#t45">45</a></span><span class="t">        <span class="str">"""Method which allows to stop rule induction process at given</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t46" href="#t46">46</a></span><span class="t"><span class="str">        moment. This method is called each time a ruleset coverage changed.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t47" href="#t47">47</a></span><span class="t"><span class="str">        If it returns `True`, rule induction process will be stopped if it</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t48" href="#t48">48</a></span><span class="t"><span class="str">        return `False` it will continue.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t49" href="#t49">49</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t50" href="#t50">50</a></span><span class="t"><span class="str">        Returns:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t51" href="#t51">51</a></span><span class="t"><span class="str">            bool: whether to stop rule induction or not</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t52" href="#t52">52</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t53" href="#t53">53</a></span><span class="t">        <span class="key">return</span> <span class="key">False</span>&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t54" href="#t54">54</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t55" href="#t55">55</a></span><span class="t">        <span class="op">@</span><span class="nam">JOverride</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t56" href="#t56">56</a></span><span class="t">        <span class="key">def</span> <span class="nam">onNewRule</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">rule</span><span class="op">:</span> <span class="nam">JObject</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t57" href="#t57">57</a></span><span class="t">            <span class="nam">rule</span><span class="op">:</span> <span class="nam">BaseRule</span> <span class="op">=</span> <span class="nam">_rule_factory</span><span class="op">(</span><span class="nam">rule</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t58" href="#t58">58</a></span><span class="t">            <span class="key">return</span> <span class="nam">listener</span><span class="op">.</span><span class="nam">on_new_rule</span><span class="op">(</span><span class="nam">rule</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t55" href="#t55">55</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t56" href="#t56">56</a></span><span class="t"><span class="key">def</span> <span class="nam">_command_listener_factory</span><span class="op">(</span><span class="nam">listener</span><span class="op">:</span> <span class="nam">RuleInductionProgressListener</span><span class="op">)</span> <span class="op">-></span> <span class="nam">Any</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t57" href="#t57">57</a></span><span class="t">    <span class="key">from</span> <span class="nam">adaa</span><span class="op">.</span><span class="nam">analytics</span><span class="op">.</span><span class="nam">rules</span><span class="op">.</span><span class="nam">logic</span><span class="op">.</span><span class="nam">rulegenerator</span> <span class="key">import</span> <span class="xx">\</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t58" href="#t58">58</a></span><span class="t">        <span class="nam">ICommandListener</span>  <span class="com"># pylint: disable=import-outside-toplevel,import-error,line-too-long</span>&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t59" href="#t59">59</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t60" href="#t60">60</a></span><span class="t">        <span class="op">@</span><span class="nam">JOverride</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t61" href="#t61">61</a></span><span class="t">        <span class="key">def</span> <span class="nam">onProgress</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">totalRules</span><span class="op">:</span> <span class="nam">JInt</span><span class="op">,</span> <span class="nam">uncoveredRules</span><span class="op">:</span> <span class="nam">JInt</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t62" href="#t62">62</a></span><span class="t">            <span class="key">return</span> <span class="nam">listener</span><span class="op">.</span><span class="nam">on_progress</span><span class="op">(</span><span class="nam">int</span><span class="op">(</span><span class="nam">totalRules</span><span class="op">)</span><span class="op">,</span> <span class="nam">int</span><span class="op">(</span><span class="nam">uncoveredRules</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t63" href="#t63">63</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t64" href="#t64">64</a></span><span class="t">        <span class="op">@</span><span class="nam">JOverride</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t65" href="#t65">65</a></span><span class="t">        <span class="key">def</span> <span class="nam">isRequestStop</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">bool</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t66" href="#t66">66</a></span><span class="t">            <span class="key">return</span> <span class="nam">listener</span><span class="op">.</span><span class="nam">should_stop</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t67" href="#t67">67</a></span><span class="t">            <span class="com"># return False</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t68" href="#t68">68</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t69" href="#t69">69</a></span><span class="t">    <span class="key">return</span> <span class="nam">_CommandListener</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t60" href="#t60">60</a></span><span class="t">    <span class="op">@</span><span class="nam">JImplements</span><span class="op">(</span><span class="nam">ICommandListener</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t61" href="#t61">61</a></span><span class="t">    <span class="key">class</span> <span class="nam">_CommandListener</span><span class="op">:</span>  <span class="com"># pylint: disable=invalid-name,missing-function-docstring,line-too-long</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t62" href="#t62">62</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t63" href="#t63">63</a></span><span class="t">        <span class="op">@</span><span class="nam">JOverride</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t64" href="#t64">64</a></span><span class="t">        <span class="key">def</span> <span class="nam">onNewRule</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">rule</span><span class="op">:</span> <span class="nam">JObject</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t65" href="#t65">65</a></span><span class="t">            <span class="nam">rule</span><span class="op">:</span> <span class="nam">BaseRule</span> <span class="op">=</span> <span class="nam">_rule_factory</span><span class="op">(</span><span class="nam">rule</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t66" href="#t66">66</a></span><span class="t">            <span class="key">return</span> <span class="nam">listener</span><span class="op">.</span><span class="nam">on_new_rule</span><span class="op">(</span><span class="nam">rule</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t67" href="#t67">67</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t68" href="#t68">68</a></span><span class="t">        <span class="op">@</span><span class="nam">JOverride</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t69" href="#t69">69</a></span><span class="t">        <span class="key">def</span> <span class="nam">onProgress</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">totalRules</span><span class="op">:</span> <span class="nam">JInt</span><span class="op">,</span> <span class="nam">uncoveredRules</span><span class="op">:</span> <span class="nam">JInt</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t70" href="#t70">70</a></span><span class="t">            <span class="key">return</span> <span class="nam">listener</span><span class="op">.</span><span class="nam">on_progress</span><span class="op">(</span><span class="nam">int</span><span class="op">(</span><span class="nam">totalRules</span><span class="op">)</span><span class="op">,</span> <span class="nam">int</span><span class="op">(</span><span class="nam">uncoveredRules</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t71" href="#t71">71</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t72" href="#t72">72</a></span><span class="t">        <span class="op">@</span><span class="nam">JOverride</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t73" href="#t73">73</a></span><span class="t">        <span class="key">def</span> <span class="nam">isRequestStop</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">bool</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t74" href="#t74">74</a></span><span class="t">            <span class="key">return</span> <span class="nam">listener</span><span class="op">.</span><span class="nam">should_stop</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t75" href="#t75">75</a></span><span class="t">            <span class="com"># return False</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t76" href="#t76">76</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t77" href="#t77">77</a></span><span class="t">    <span class="key">return</span> <span class="nam">_CommandListener</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
 </main>
 <footer>
     <div class="content">
@@ -158,7 +166,7 @@ <h2>
             <a class="nav" href="z_a87f2a4bb6695d91_exceptions_py.html">&#xbb; next</a>
             &nbsp; &nbsp; &nbsp;
             <a class="nav" href="https://coverage.readthedocs.io/en/7.6.4">coverage.py v7.6.4</a>,
-            created at 2024-11-08 14:43 +0100
+            created at 2024-11-28 11:55 +0100
         </p>
     </div>
 </footer>
diff --git a/docs/reports/coverage/z_a87f2a4bb6695d91_exceptions_py.html b/docs/reports/coverage/z_a87f2a4bb6695d91_exceptions_py.html
index 6031ced..6456db4 100644
--- a/docs/reports/coverage/z_a87f2a4bb6695d91_exceptions_py.html
+++ b/docs/reports/coverage/z_a87f2a4bb6695d91_exceptions_py.html
@@ -2,7 +2,7 @@
 <html lang="en">
 <head>
     <meta http-equiv="Content-Type" content="text/html; charset=utf-8">
-    <title>Coverage for rulekit\exceptions.py: 40%</title>
+    <title>Coverage for rulekit\exceptions.py: 41%</title>
     <link rel="icon" sizes="32x32" href="favicon_32_cb_58284776.png">
     <link rel="stylesheet" href="style_cb_718ce007.css" type="text/css">
     <script src="coverage_html_cb_497bf287.js" defer></script>
@@ -12,7 +12,7 @@
     <div class="content">
         <h1>
             <span class="text">Coverage for </span><b>rulekit\exceptions.py</b>:
-            <span class="pc_cov">40%</span>
+            <span class="pc_cov">41%</span>
         </h1>
         <aside id="help_panel_wrapper">
             <input id="help_panel_state" type="checkbox">
@@ -54,18 +54,18 @@ <h1>
             </div>
         </aside>
         <h2>
-            <span class="text">35 statements &nbsp;</span>
-            <button type="button" class="run button_toggle_run" value="run" data-shortcut="r" title="Toggle lines run">14<span class="text"> run</span></button>
-            <button type="button" class="mis show_mis button_toggle_mis" value="mis" data-shortcut="m" title="Toggle lines missing">21<span class="text"> missing</span></button>
+            <span class="text">37 statements &nbsp;</span>
+            <button type="button" class="run button_toggle_run" value="run" data-shortcut="r" title="Toggle lines run">15<span class="text"> run</span></button>
+            <button type="button" class="mis show_mis button_toggle_mis" value="mis" data-shortcut="m" title="Toggle lines missing">22<span class="text"> missing</span></button>
             <button type="button" class="exc show_exc button_toggle_exc" value="exc" data-shortcut="x" title="Toggle lines excluded">0<span class="text"> excluded</span></button>
         </h2>
         <p class="text">
             <a id="prevFileLink" class="nav" href="z_a87f2a4bb6695d91_events_py.html">&#xab; prev</a> &nbsp; &nbsp;
             <a id="indexLink" class="nav" href="index.html">&Hat; index</a> &nbsp; &nbsp;
-            <a id="nextFileLink" class="nav" href="z_a87f2a4bb6695d91_main_py.html">&#xbb; next</a>
+            <a id="nextFileLink" class="nav" href="z_a87f2a4bb6695d91_kaplan_meier_py.html">&#xbb; next</a>
             &nbsp; &nbsp; &nbsp;
             <a class="nav" href="https://coverage.readthedocs.io/en/7.6.4">coverage.py v7.6.4</a>,
-            created at 2024-11-05 13:43 +0100
+            created at 2024-11-28 11:55 +0100
         </p>
         <aside class="hidden">
             <button type="button" class="button_next_chunk" data-shortcut="j"></button>
@@ -82,116 +82,122 @@ <h2>
 <main id="source">
     <p class="pln"><span class="n"><a id="t1" href="#t1">1</a></span><span class="t"><span class="str">"""Module containing classes for handling exceptions."""</span>&nbsp;</span><span class="r"></span></p>
     <p class="run"><span class="n"><a id="t2" href="#t2">2</a></span><span class="t"><span class="key">from</span> <span class="nam">typing</span> <span class="key">import</span> <span class="nam">Any</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t3" href="#t3">3</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t4" href="#t4">4</a></span><span class="t"><span class="key">from</span> <span class="nam">jpype</span> <span class="key">import</span> <span class="nam">JException</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t5" href="#t5">5</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t3" href="#t3">3</a></span><span class="t"><span class="key">from</span> <span class="nam">typing</span> <span class="key">import</span> <span class="nam">Callable</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t4" href="#t4">4</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t5" href="#t5">5</a></span><span class="t"><span class="key">from</span> <span class="nam">jpype</span> <span class="key">import</span> <span class="nam">JException</span>&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t6" href="#t6">6</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t7" href="#t7">7</a></span><span class="t"><span class="key">class</span> <span class="nam">RuleKitJavaException</span><span class="op">(</span><span class="nam">Exception</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t8" href="#t8">8</a></span><span class="t">    <span class="str">"""Wrapper method for handling Java exceptions produced by RuleKit.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t9" href="#t9">9</a></span><span class="t"><span class="str">    Useful for debugging internal Java code error. It allows to access java</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t10" href="#t10">10</a></span><span class="t"><span class="str">    stack traces easily.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t11" href="#t11">11</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t12" href="#t12">12</a></span><span class="t"><span class="str">    Example:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t13" href="#t13">13</a></span><span class="t"><span class="str">        >>> from rulekit import RuleKit</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t14" href="#t14">14</a></span><span class="t"><span class="str">        >>> from rulekit.classification import RuleClassifier</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t15" href="#t15">15</a></span><span class="t"><span class="str">        >>></span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t16" href="#t16">16</a></span><span class="t"><span class="str">        >>> clf = RuleClassifier()</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t17" href="#t17">17</a></span><span class="t"><span class="str">        >>> try:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t18" href="#t18">18</a></span><span class="t"><span class="str">        >>>     clf.fit(X, y)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t19" href="#t19">19</a></span><span class="t"><span class="str">        >>> except JException as e: # catch java exceptions</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t20" href="#t20">20</a></span><span class="t"><span class="str">        >>>     e = RuleKitJavaException(e) # wrap them for easier handling</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t21" href="#t21">21</a></span><span class="t"><span class="str">        >>>     e.print_java_stack_trace() # access java stack trace</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t22" href="#t22">22</a></span><span class="t"><span class="str">    """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t23" href="#t23">23</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t24" href="#t24">24</a></span><span class="t">    <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">java_exception</span><span class="op">:</span> <span class="nam">JException</span><span class="op">)</span> <span class="op">-></span> <span class="key">None</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t25" href="#t25">25</a></span><span class="t">        <span class="str">"""</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t26" href="#t26">26</a></span><span class="t"><span class="str">        Args:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t27" href="#t27">27</a></span><span class="t"><span class="str">            java_exception (JException): original java exception</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t28" href="#t28">28</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t29" href="#t29">29</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_original_exception</span><span class="op">:</span> <span class="nam">JException</span> <span class="op">=</span> <span class="nam">java_exception</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t30" href="#t30">30</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">message</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="nam">java_exception</span><span class="op">.</span><span class="nam">message</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t31" href="#t31">31</a></span><span class="t">        <span class="nam">super</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">__init__</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">message</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t32" href="#t32">32</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t33" href="#t33">33</a></span><span class="t">    <span class="op">@</span><span class="nam">property</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t34" href="#t34">34</a></span><span class="t">    <span class="key">def</span> <span class="nam">original_exception</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">JException</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t35" href="#t35">35</a></span><span class="t">        <span class="str">"""</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t36" href="#t36">36</a></span><span class="t"><span class="str">        Original java exception</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t37" href="#t37">37</a></span><span class="t"><span class="str">        Returns:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t38" href="#t38">38</a></span><span class="t"><span class="str">            JException: original java exception</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t39" href="#t39">39</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t40" href="#t40">40</a></span><span class="t">        <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_original_exception</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t41" href="#t41">41</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t42" href="#t42">42</a></span><span class="t">    <span class="key">def</span> <span class="nam">print_java_stack_trace</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="key">None</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t43" href="#t43">43</a></span><span class="t">        <span class="str">"""Prints java exception stack trace."""</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t44" href="#t44">44</a></span><span class="t">        <span class="nam">print</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">original_exception</span><span class="op">.</span><span class="nam">stacktrace</span><span class="op">(</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t45" href="#t45">45</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t7" href="#t7">7</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t8" href="#t8">8</a></span><span class="t"><span class="key">class</span> <span class="nam">RuleKitJavaException</span><span class="op">(</span><span class="nam">Exception</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t9" href="#t9">9</a></span><span class="t">    <span class="str">"""Wrapper method for handling Java exceptions produced by RuleKit.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t10" href="#t10">10</a></span><span class="t"><span class="str">    Useful for debugging internal Java code error. It allows to access java</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t11" href="#t11">11</a></span><span class="t"><span class="str">    stack traces easily.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t12" href="#t12">12</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t13" href="#t13">13</a></span><span class="t"><span class="str">    Example:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t14" href="#t14">14</a></span><span class="t"><span class="str">        >>> from rulekit import RuleKit</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t15" href="#t15">15</a></span><span class="t"><span class="str">        >>> from rulekit.classification import RuleClassifier</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t16" href="#t16">16</a></span><span class="t"><span class="str">        >>></span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t17" href="#t17">17</a></span><span class="t"><span class="str">        >>> clf = RuleClassifier()</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t18" href="#t18">18</a></span><span class="t"><span class="str">        >>> try:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t19" href="#t19">19</a></span><span class="t"><span class="str">        >>>     clf.fit(X, y)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t20" href="#t20">20</a></span><span class="t"><span class="str">        >>> except JException as e: # catch java exceptions</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t21" href="#t21">21</a></span><span class="t"><span class="str">        >>>     e = RuleKitJavaException(e) # wrap them for easier handling</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t22" href="#t22">22</a></span><span class="t"><span class="str">        >>>     e.print_java_stack_trace() # access java stack trace</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t23" href="#t23">23</a></span><span class="t"><span class="str">    """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t24" href="#t24">24</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t25" href="#t25">25</a></span><span class="t">    <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">java_exception</span><span class="op">:</span> <span class="nam">JException</span><span class="op">)</span> <span class="op">-></span> <span class="key">None</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t26" href="#t26">26</a></span><span class="t">        <span class="str">"""</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t27" href="#t27">27</a></span><span class="t"><span class="str">        Args:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t28" href="#t28">28</a></span><span class="t"><span class="str">            java_exception (JException): original java exception</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t29" href="#t29">29</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t30" href="#t30">30</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_original_exception</span><span class="op">:</span> <span class="nam">JException</span> <span class="op">=</span> <span class="nam">java_exception</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t31" href="#t31">31</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">message</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="nam">java_exception</span><span class="op">.</span><span class="nam">message</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t32" href="#t32">32</a></span><span class="t">        <span class="nam">super</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">__init__</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">message</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t33" href="#t33">33</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t34" href="#t34">34</a></span><span class="t">    <span class="op">@</span><span class="nam">property</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t35" href="#t35">35</a></span><span class="t">    <span class="key">def</span> <span class="nam">original_exception</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">JException</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t36" href="#t36">36</a></span><span class="t">        <span class="str">"""</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t37" href="#t37">37</a></span><span class="t"><span class="str">        Original java exception</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t38" href="#t38">38</a></span><span class="t"><span class="str">        Returns:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t39" href="#t39">39</a></span><span class="t"><span class="str">            JException: original java exception</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t40" href="#t40">40</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t41" href="#t41">41</a></span><span class="t">        <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_original_exception</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t42" href="#t42">42</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t43" href="#t43">43</a></span><span class="t">    <span class="key">def</span> <span class="nam">print_java_stack_trace</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="key">None</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t44" href="#t44">44</a></span><span class="t">        <span class="str">"""Prints java exception stack trace."""</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t45" href="#t45">45</a></span><span class="t">        <span class="nam">print</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">original_exception</span><span class="op">.</span><span class="nam">stacktrace</span><span class="op">(</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t46" href="#t46">46</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t47" href="#t47">47</a></span><span class="t"><span class="key">class</span> <span class="nam">RuleKitMisconfigurationException</span><span class="op">(</span><span class="nam">Exception</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t48" href="#t48">48</a></span><span class="t">    <span class="str">"""Exception indicating that some RuleKit parameters are misconfigured -</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t49" href="#t49">49</a></span><span class="t"><span class="str">    their values were not correctly passed to java code.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t50" href="#t50">50</a></span><span class="t"><span class="str">    """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t51" href="#t51">51</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t52" href="#t52">52</a></span><span class="t">    <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t53" href="#t53">53</a></span><span class="t">        <span class="nam">self</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t54" href="#t54">54</a></span><span class="t">        <span class="nam">java_parameters</span><span class="op">:</span> <span class="nam">dict</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">Any</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t55" href="#t55">55</a></span><span class="t">        <span class="nam">python_parameters</span><span class="op">:</span> <span class="nam">dict</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">Any</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t56" href="#t56">56</a></span><span class="t">    <span class="op">)</span> <span class="op">-></span> <span class="key">None</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t57" href="#t57">57</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t58" href="#t58">58</a></span><span class="t">        <span class="nam">super</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">__init__</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">_prepare_message</span><span class="op">(</span><span class="nam">java_parameters</span><span class="op">,</span> <span class="nam">python_parameters</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t59" href="#t59">59</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_java_parameters</span><span class="op">:</span> <span class="nam">dict</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">Any</span><span class="op">]</span> <span class="op">=</span> <span class="nam">java_parameters</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t60" href="#t60">60</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_python_parameters</span><span class="op">:</span> <span class="nam">dict</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">Any</span><span class="op">]</span> <span class="op">=</span> <span class="nam">python_parameters</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t61" href="#t61">61</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t62" href="#t62">62</a></span><span class="t">    <span class="key">def</span> <span class="nam">_prepare_message</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t63" href="#t63">63</a></span><span class="t">        <span class="nam">self</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t64" href="#t64">64</a></span><span class="t">        <span class="nam">java_parameters</span><span class="op">:</span> <span class="nam">dict</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">Any</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t65" href="#t65">65</a></span><span class="t">        <span class="nam">python_parameters</span><span class="op">:</span> <span class="nam">dict</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">Any</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t66" href="#t66">66</a></span><span class="t">    <span class="op">)</span> <span class="op">-></span> <span class="nam">str</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t67" href="#t67">67</a></span><span class="t">        <span class="nam">combined_keys</span><span class="op">:</span> <span class="nam">set</span><span class="op">[</span><span class="nam">str</span><span class="op">]</span> <span class="op">=</span> <span class="nam">set</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t68" href="#t68">68</a></span><span class="t">            <span class="nam">java_parameters</span><span class="op">.</span><span class="nam">keys</span><span class="op">(</span><span class="op">)</span><span class="op">)</span> <span class="op">|</span> <span class="nam">set</span><span class="op">(</span><span class="nam">python_parameters</span><span class="op">.</span><span class="nam">keys</span><span class="op">(</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t69" href="#t69">69</a></span><span class="t">        <span class="nam">params_lines</span><span class="op">:</span> <span class="nam">list</span><span class="op">[</span><span class="nam">str</span><span class="op">]</span> <span class="op">=</span> <span class="op">[</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t70" href="#t70">70</a></span><span class="t">        <span class="key">for</span> <span class="nam">key</span> <span class="key">in</span> <span class="nam">combined_keys</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t71" href="#t71">71</a></span><span class="t">            <span class="nam">java_value</span> <span class="op">=</span> <span class="nam">java_parameters</span><span class="op">.</span><span class="nam">get</span><span class="op">(</span><span class="nam">key</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t72" href="#t72">72</a></span><span class="t">            <span class="nam">python_value</span> <span class="op">=</span> <span class="nam">python_parameters</span><span class="op">.</span><span class="nam">get</span><span class="op">(</span><span class="nam">key</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t73" href="#t73">73</a></span><span class="t">            <span class="nam">line</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="str">f'  {key}: ({java_value},  {python_value}),'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t74" href="#t74">74</a></span><span class="t">            <span class="key">if</span> <span class="nam">java_value</span> <span class="op">!=</span> <span class="nam">python_value</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t75" href="#t75">75</a></span><span class="t">                <span class="nam">line</span> <span class="op">=</span> <span class="str">f'{line} &lt;-- **DIFFERENT**'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t76" href="#t76">76</a></span><span class="t">            <span class="nam">params_lines</span><span class="op">.</span><span class="nam">append</span><span class="op">(</span><span class="nam">line</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t77" href="#t77">77</a></span><span class="t">        <span class="nam">message</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t78" href="#t78">78</a></span><span class="t">            <span class="str">'RuleKit parameters configuration error'</span> <span class="op">+</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t79" href="#t79">79</a></span><span class="t">            <span class="str">'RuleGenerator parameters configured in Java do not match with given parameters\n\n'</span> <span class="op">+</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t80" href="#t80">80</a></span><span class="t">            <span class="str">'Parameters (first value is in Java, second is in Python):\n{\n'</span> <span class="op">+</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t81" href="#t81">81</a></span><span class="t">            <span class="str">'\n'</span><span class="op">.</span><span class="nam">join</span><span class="op">(</span><span class="nam">params_lines</span><span class="op">)</span> <span class="op">+</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t82" href="#t82">82</a></span><span class="t">            <span class="str">'\n}'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t83" href="#t83">83</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t84" href="#t84">84</a></span><span class="t">        <span class="key">return</span> <span class="nam">message</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t85" href="#t85">85</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t86" href="#t86">86</a></span><span class="t">    <span class="op">@</span><span class="nam">property</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t87" href="#t87">87</a></span><span class="t">    <span class="key">def</span> <span class="nam">java_parameters</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">dict</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">Any</span><span class="op">]</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t88" href="#t88">88</a></span><span class="t">        <span class="str">"""</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t89" href="#t89">89</a></span><span class="t"><span class="str">        Configured operator parameters values extracted from java</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t90" href="#t90">90</a></span><span class="t"><span class="str">        Returns:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t91" href="#t91">91</a></span><span class="t"><span class="str">            dict[str, Any]: parameters</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t92" href="#t92">92</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t93" href="#t93">93</a></span><span class="t">        <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_java_parameters</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t94" href="#t94">94</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t95" href="#t95">95</a></span><span class="t">    <span class="op">@</span><span class="nam">property</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t96" href="#t96">96</a></span><span class="t">    <span class="key">def</span> <span class="nam">python_parameters</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">dict</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">Any</span><span class="op">]</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t97" href="#t97">97</a></span><span class="t">        <span class="str">"""</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t98" href="#t98">98</a></span><span class="t"><span class="str">        Operator parameters passed to the python operator class</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t99" href="#t99">99</a></span><span class="t"><span class="str">        Returns:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t100" href="#t100">100</a></span><span class="t"><span class="str">            dict[str, Any]: parameters</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t101" href="#t101">101</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t102" href="#t102">102</a></span><span class="t">        <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_python_parameters</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t47" href="#t47">47</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t48" href="#t48">48</a></span><span class="t"><span class="key">class</span> <span class="nam">RuleKitMisconfigurationException</span><span class="op">(</span><span class="nam">Exception</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t49" href="#t49">49</a></span><span class="t">    <span class="str">"""Exception indicating that some RuleKit parameters are misconfigured -</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t50" href="#t50">50</a></span><span class="t"><span class="str">    their values were not correctly passed to java code.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t51" href="#t51">51</a></span><span class="t"><span class="str">    """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t52" href="#t52">52</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t53" href="#t53">53</a></span><span class="t">    <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t54" href="#t54">54</a></span><span class="t">        <span class="nam">self</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t55" href="#t55">55</a></span><span class="t">        <span class="nam">java_parameters</span><span class="op">:</span> <span class="nam">dict</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">Any</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t56" href="#t56">56</a></span><span class="t">        <span class="nam">python_parameters</span><span class="op">:</span> <span class="nam">dict</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">Any</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t57" href="#t57">57</a></span><span class="t">    <span class="op">)</span> <span class="op">-></span> <span class="key">None</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t58" href="#t58">58</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t59" href="#t59">59</a></span><span class="t">        <span class="nam">super</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">__init__</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t60" href="#t60">60</a></span><span class="t">            <span class="nam">self</span><span class="op">.</span><span class="nam">_prepare_message</span><span class="op">(</span><span class="nam">java_parameters</span><span class="op">,</span> <span class="nam">python_parameters</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t61" href="#t61">61</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t62" href="#t62">62</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_java_parameters</span><span class="op">:</span> <span class="nam">dict</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">Any</span><span class="op">]</span> <span class="op">=</span> <span class="nam">java_parameters</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t63" href="#t63">63</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_python_parameters</span><span class="op">:</span> <span class="nam">dict</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">Any</span><span class="op">]</span> <span class="op">=</span> <span class="nam">python_parameters</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t64" href="#t64">64</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t65" href="#t65">65</a></span><span class="t">    <span class="key">def</span> <span class="nam">_prepare_message</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t66" href="#t66">66</a></span><span class="t">        <span class="nam">self</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t67" href="#t67">67</a></span><span class="t">        <span class="nam">java_parameters</span><span class="op">:</span> <span class="nam">dict</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">Any</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t68" href="#t68">68</a></span><span class="t">        <span class="nam">python_parameters</span><span class="op">:</span> <span class="nam">dict</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">Any</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t69" href="#t69">69</a></span><span class="t">    <span class="op">)</span> <span class="op">-></span> <span class="nam">str</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t70" href="#t70">70</a></span><span class="t">        <span class="nam">combined_keys</span><span class="op">:</span> <span class="nam">set</span><span class="op">[</span><span class="nam">str</span><span class="op">]</span> <span class="op">=</span> <span class="nam">set</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t71" href="#t71">71</a></span><span class="t">            <span class="nam">java_parameters</span><span class="op">.</span><span class="nam">keys</span><span class="op">(</span><span class="op">)</span><span class="op">)</span> <span class="op">|</span> <span class="nam">set</span><span class="op">(</span><span class="nam">python_parameters</span><span class="op">.</span><span class="nam">keys</span><span class="op">(</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t72" href="#t72">72</a></span><span class="t">        <span class="nam">params_lines</span><span class="op">:</span> <span class="nam">list</span><span class="op">[</span><span class="nam">str</span><span class="op">]</span> <span class="op">=</span> <span class="op">[</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t73" href="#t73">73</a></span><span class="t">        <span class="key">for</span> <span class="nam">key</span> <span class="key">in</span> <span class="nam">combined_keys</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t74" href="#t74">74</a></span><span class="t">            <span class="nam">java_value</span> <span class="op">=</span> <span class="nam">java_parameters</span><span class="op">.</span><span class="nam">get</span><span class="op">(</span><span class="nam">key</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t75" href="#t75">75</a></span><span class="t">            <span class="nam">python_value</span> <span class="op">=</span> <span class="nam">python_parameters</span><span class="op">.</span><span class="nam">get</span><span class="op">(</span><span class="nam">key</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t76" href="#t76">76</a></span><span class="t">            <span class="nam">line</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="str">f'  {key}: ({java_value},  {python_value}),'</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t77" href="#t77">77</a></span><span class="t">            <span class="com"># skip check for user defined measures</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t78" href="#t78">78</a></span><span class="t">            <span class="nam">skip_check</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">python_value</span><span class="op">,</span> <span class="nam">Callable</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t79" href="#t79">79</a></span><span class="t">            <span class="key">if</span> <span class="nam">java_value</span> <span class="op">!=</span> <span class="nam">python_value</span> <span class="key">and</span> <span class="key">not</span> <span class="nam">skip_check</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t80" href="#t80">80</a></span><span class="t">                <span class="nam">line</span> <span class="op">=</span> <span class="str">f'{line} &lt;-- **DIFFERENT**'</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t81" href="#t81">81</a></span><span class="t">            <span class="nam">params_lines</span><span class="op">.</span><span class="nam">append</span><span class="op">(</span><span class="nam">line</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t82" href="#t82">82</a></span><span class="t">        <span class="nam">message</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t83" href="#t83">83</a></span><span class="t">            <span class="str">'RuleKit parameters configuration error'</span> <span class="op">+</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t84" href="#t84">84</a></span><span class="t">            <span class="str">'RuleGenerator parameters configured in Java do not'</span> <span class="op">+</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t85" href="#t85">85</a></span><span class="t">            <span class="str">'match with given parameters\n\n'</span> <span class="op">+</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t86" href="#t86">86</a></span><span class="t">            <span class="str">'Parameters (first value is in Java, second is in Python):\n{\n'</span> <span class="op">+</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t87" href="#t87">87</a></span><span class="t">            <span class="str">'\n'</span><span class="op">.</span><span class="nam">join</span><span class="op">(</span><span class="nam">params_lines</span><span class="op">)</span> <span class="op">+</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t88" href="#t88">88</a></span><span class="t">            <span class="str">'\n}'</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t89" href="#t89">89</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t90" href="#t90">90</a></span><span class="t">        <span class="key">return</span> <span class="nam">message</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t91" href="#t91">91</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t92" href="#t92">92</a></span><span class="t">    <span class="op">@</span><span class="nam">property</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t93" href="#t93">93</a></span><span class="t">    <span class="key">def</span> <span class="nam">java_parameters</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">dict</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">Any</span><span class="op">]</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t94" href="#t94">94</a></span><span class="t">        <span class="str">"""</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t95" href="#t95">95</a></span><span class="t"><span class="str">        Configured operator parameters values extracted from java</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t96" href="#t96">96</a></span><span class="t"><span class="str">        Returns:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t97" href="#t97">97</a></span><span class="t"><span class="str">            dict[str, Any]: parameters</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t98" href="#t98">98</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t99" href="#t99">99</a></span><span class="t">        <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_java_parameters</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t100" href="#t100">100</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t101" href="#t101">101</a></span><span class="t">    <span class="op">@</span><span class="nam">property</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t102" href="#t102">102</a></span><span class="t">    <span class="key">def</span> <span class="nam">python_parameters</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">dict</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">Any</span><span class="op">]</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t103" href="#t103">103</a></span><span class="t">        <span class="str">"""</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t104" href="#t104">104</a></span><span class="t"><span class="str">        Operator parameters passed to the python operator class</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t105" href="#t105">105</a></span><span class="t"><span class="str">        Returns:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t106" href="#t106">106</a></span><span class="t"><span class="str">            dict[str, Any]: parameters</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t107" href="#t107">107</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t108" href="#t108">108</a></span><span class="t">        <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_python_parameters</span>&nbsp;</span><span class="r"></span></p>
 </main>
 <footer>
     <div class="content">
         <p>
             <a class="nav" href="z_a87f2a4bb6695d91_events_py.html">&#xab; prev</a> &nbsp; &nbsp;
             <a class="nav" href="index.html">&Hat; index</a> &nbsp; &nbsp;
-            <a class="nav" href="z_a87f2a4bb6695d91_main_py.html">&#xbb; next</a>
+            <a class="nav" href="z_a87f2a4bb6695d91_kaplan_meier_py.html">&#xbb; next</a>
             &nbsp; &nbsp; &nbsp;
             <a class="nav" href="https://coverage.readthedocs.io/en/7.6.4">coverage.py v7.6.4</a>,
-            created at 2024-11-05 13:43 +0100
+            created at 2024-11-28 11:55 +0100
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diff --git a/docs/reports/coverage/z_a87f2a4bb6695d91_main_py.html b/docs/reports/coverage/z_a87f2a4bb6695d91_main_py.html
index 8a41b78..442f141 100644
--- a/docs/reports/coverage/z_a87f2a4bb6695d91_main_py.html
+++ b/docs/reports/coverage/z_a87f2a4bb6695d91_main_py.html
@@ -2,7 +2,7 @@
 <html lang="en">
 <head>
     <meta http-equiv="Content-Type" content="text/html; charset=utf-8">
-    <title>Coverage for rulekit\main.py: 80%</title>
+    <title>Coverage for rulekit\main.py: 81%</title>
     <link rel="icon" sizes="32x32" href="favicon_32_cb_58284776.png">
     <link rel="stylesheet" href="style_cb_718ce007.css" type="text/css">
     <script src="coverage_html_cb_497bf287.js" defer></script>
@@ -12,7 +12,7 @@
     <div class="content">
         <h1>
             <span class="text">Coverage for </span><b>rulekit\main.py</b>:
-            <span class="pc_cov">80%</span>
+            <span class="pc_cov">81%</span>
         </h1>
         <aside id="help_panel_wrapper">
             <input id="help_panel_state" type="checkbox">
@@ -54,8 +54,8 @@ <h1>
             </div>
         </aside>
         <h2>
-            <span class="text">87 statements &nbsp;</span>
-            <button type="button" class="run button_toggle_run" value="run" data-shortcut="r" title="Toggle lines run">70<span class="text"> run</span></button>
+            <span class="text">89 statements &nbsp;</span>
+            <button type="button" class="run button_toggle_run" value="run" data-shortcut="r" title="Toggle lines run">72<span class="text"> run</span></button>
             <button type="button" class="mis show_mis button_toggle_mis" value="mis" data-shortcut="m" title="Toggle lines missing">17<span class="text"> missing</span></button>
             <button type="button" class="exc show_exc button_toggle_exc" value="exc" data-shortcut="x" title="Toggle lines excluded">0<span class="text"> excluded</span></button>
         </h2>
@@ -65,7 +65,7 @@ <h2>
             <a id="nextFileLink" class="nav" href="z_a87f2a4bb6695d91_params_py.html">&#xbb; next</a>
             &nbsp; &nbsp; &nbsp;
             <a class="nav" href="https://coverage.readthedocs.io/en/7.6.4">coverage.py v7.6.4</a>,
-            created at 2024-11-08 14:43 +0100
+            created at 2024-11-28 11:55 +0100
         </p>
         <aside class="hidden">
             <button type="button" class="button_next_chunk" data-shortcut="j"></button>
@@ -87,190 +87,192 @@ <h2>
     <p class="run"><span class="n"><a id="t5" href="#t5">5</a></span><span class="t"><span class="key">import</span> <span class="nam">re</span>&nbsp;</span><span class="r"></span></p>
     <p class="run"><span class="n"><a id="t6" href="#t6">6</a></span><span class="t"><span class="key">import</span> <span class="nam">zipfile</span>&nbsp;</span><span class="r"></span></p>
     <p class="run"><span class="n"><a id="t7" href="#t7">7</a></span><span class="t"><span class="key">from</span> <span class="nam">enum</span> <span class="key">import</span> <span class="nam">Enum</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t8" href="#t8">8</a></span><span class="t"><span class="key">from</span> <span class="nam">subprocess</span> <span class="key">import</span> <span class="nam">PIPE</span><span class="op">,</span> <span class="nam">STDOUT</span><span class="op">,</span> <span class="nam">Popen</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t9" href="#t9">9</a></span><span class="t"><span class="key">from</span> <span class="nam">typing</span> <span class="key">import</span> <span class="nam">Optional</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t10" href="#t10">10</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t11" href="#t11">11</a></span><span class="t"><span class="key">import</span> <span class="nam">jpype</span><span class="op">.</span><span class="nam">imports</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t8" href="#t8">8</a></span><span class="t"><span class="key">from</span> <span class="nam">subprocess</span> <span class="key">import</span> <span class="nam">PIPE</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t9" href="#t9">9</a></span><span class="t"><span class="key">from</span> <span class="nam">subprocess</span> <span class="key">import</span> <span class="nam">Popen</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t10" href="#t10">10</a></span><span class="t"><span class="key">from</span> <span class="nam">subprocess</span> <span class="key">import</span> <span class="nam">STDOUT</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t11" href="#t11">11</a></span><span class="t"><span class="key">from</span> <span class="nam">typing</span> <span class="key">import</span> <span class="nam">Optional</span>&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t12" href="#t12">12</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t13" href="#t13">13</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">_logging</span> <span class="key">import</span> <span class="nam">_RuleKitJavaLoggerConfig</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t13" href="#t13">13</a></span><span class="t"><span class="key">import</span> <span class="nam">jpype</span><span class="op">.</span><span class="nam">imports</span>&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t14" href="#t14">14</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t15" href="#t15">15</a></span><span class="t"><span class="nam">__RULEKIT_RELEASE_VERSION__</span> <span class="op">=</span> <span class="str">'2.1.21'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t16" href="#t16">16</a></span><span class="t"><span class="nam">__VERSION__</span> <span class="op">=</span> <span class="str">f'{__RULEKIT_RELEASE_VERSION__}.0'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t17" href="#t17">17</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t18" href="#t18">18</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t19" href="#t19">19</a></span><span class="t"><span class="key">class</span> <span class="nam">JRE_Type</span><span class="op">(</span><span class="nam">Enum</span><span class="op">)</span><span class="op">:</span>  <span class="com"># pylint: disable=invalid-name</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t20" href="#t20">20</a></span><span class="t">    <span class="str">""":meta private:"""</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t21" href="#t21">21</a></span><span class="t">    <span class="nam">OPEN_JDK</span> <span class="op">=</span> <span class="str">'open_jdk'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t22" href="#t22">22</a></span><span class="t">    <span class="nam">ORACLE</span> <span class="op">=</span> <span class="str">'oracle'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t23" href="#t23">23</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t24" href="#t24">24</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t25" href="#t25">25</a></span><span class="t"><span class="key">class</span> <span class="nam">RuleKit</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t26" href="#t26">26</a></span><span class="t">    <span class="str">"""Class used for initializing RuleKit. It starts JVM underhood and setups it with jars.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t27" href="#t27">27</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t28" href="#t28">28</a></span><span class="t"><span class="str">    .. note:: Since version 1.7.0 there is no need to manually initialize RuleKit.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t29" href="#t29">29</a></span><span class="t"><span class="str">    You may just skip the **RuleKit.init()** line. However in certain scenarios when</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t30" href="#t30">30</a></span><span class="t"><span class="str">    you want use a custom RuleKit jar file or modify Java VM parameters, this class</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t31" href="#t31">31</a></span><span class="t"><span class="str">    can be used.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t32" href="#t32">32</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t33" href="#t33">33</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t34" href="#t34">34</a></span><span class="t"><span class="str">    Attributes</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t35" href="#t35">35</a></span><span class="t"><span class="str">    ----------</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t36" href="#t36">36</a></span><span class="t"><span class="str">    version : str</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t37" href="#t37">37</a></span><span class="t"><span class="str">        version of RuleKit jar used by wrapper (not equal to python package version).</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t38" href="#t38">38</a></span><span class="t"><span class="str">    """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t39" href="#t39">39</a></span><span class="t">    <span class="nam">version</span><span class="op">:</span> <span class="nam">str</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t40" href="#t40">40</a></span><span class="t">    <span class="nam">_logger</span><span class="op">:</span> <span class="nam">logging</span><span class="op">.</span><span class="nam">Logger</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t41" href="#t41">41</a></span><span class="t">    <span class="nam">_jar_dir_path</span><span class="op">:</span> <span class="nam">str</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t42" href="#t42">42</a></span><span class="t">    <span class="nam">_class_path</span><span class="op">:</span> <span class="nam">str</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t43" href="#t43">43</a></span><span class="t">    <span class="nam">_rulekit_jar_file_path</span><span class="op">:</span> <span class="nam">str</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t44" href="#t44">44</a></span><span class="t">    <span class="nam">_jre_type</span><span class="op">:</span> <span class="nam">JRE_Type</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t45" href="#t45">45</a></span><span class="t">    <span class="nam">_java_logger_config</span><span class="op">:</span> <span class="nam">Optional</span><span class="op">[</span><span class="nam">_RuleKitJavaLoggerConfig</span><span class="op">]</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t46" href="#t46">46</a></span><span class="t">    <span class="nam">initialized</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="key">False</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t47" href="#t47">47</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t48" href="#t48">48</a></span><span class="t">    <span class="op">@</span><span class="nam">staticmethod</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t49" href="#t49">49</a></span><span class="t">    <span class="key">def</span> <span class="nam">_detect_jre_type</span><span class="op">(</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t50" href="#t50">50</a></span><span class="t">        <span class="key">try</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t51" href="#t51">51</a></span><span class="t">            <span class="key">with</span> <span class="nam">Popen</span><span class="op">(</span><span class="op">[</span><span class="str">"java"</span><span class="op">,</span> <span class="str">"-version"</span><span class="op">]</span><span class="op">,</span> <span class="nam">stderr</span><span class="op">=</span><span class="nam">STDOUT</span><span class="op">,</span> <span class="nam">stdout</span><span class="op">=</span><span class="nam">PIPE</span><span class="op">)</span> <span class="key">as</span> <span class="nam">output</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t52" href="#t52">52</a></span><span class="t">                <span class="nam">output</span> <span class="op">=</span> <span class="nam">str</span><span class="op">(</span><span class="nam">output</span><span class="op">.</span><span class="nam">communicate</span><span class="op">(</span><span class="op">)</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t53" href="#t53">53</a></span><span class="t">                <span class="key">if</span> <span class="str">'openjdk'</span> <span class="key">in</span> <span class="nam">output</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t54" href="#t54">54</a></span><span class="t">                    <span class="nam">RuleKit</span><span class="op">.</span><span class="nam">_jre_type</span> <span class="op">=</span> <span class="nam">JRE_Type</span><span class="op">.</span><span class="nam">OPEN_JDK</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t55" href="#t55">55</a></span><span class="t">                <span class="key">else</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t56" href="#t56">56</a></span><span class="t">                    <span class="nam">RuleKit</span><span class="op">.</span><span class="nam">_jre_type</span> <span class="op">=</span> <span class="nam">JRE_Type</span><span class="op">.</span><span class="nam">ORACLE</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t57" href="#t57">57</a></span><span class="t">        <span class="key">except</span> <span class="nam">FileNotFoundError</span> <span class="key">as</span> <span class="nam">error</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t58" href="#t58">58</a></span><span class="t">            <span class="key">raise</span> <span class="nam">RuntimeError</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t59" href="#t59">59</a></span><span class="t">                <span class="str">'RuletKit requires java JRE to be installed (version 1.8.0 recommended)'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t60" href="#t60">60</a></span><span class="t">            <span class="op">)</span> <span class="key">from</span> <span class="nam">error</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t61" href="#t61">61</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t62" href="#t62">62</a></span><span class="t">    <span class="op">@</span><span class="nam">staticmethod</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t63" href="#t63">63</a></span><span class="t">    <span class="key">def</span> <span class="nam">init</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t64" href="#t64">64</a></span><span class="t">        <span class="nam">initial_heap_size</span><span class="op">:</span> <span class="nam">int</span> <span class="op">=</span> <span class="key">None</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t65" href="#t65">65</a></span><span class="t">        <span class="nam">max_heap_size</span><span class="op">:</span> <span class="nam">int</span> <span class="op">=</span> <span class="key">None</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t66" href="#t66">66</a></span><span class="t">        <span class="nam">rulekit_jar_file_path</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t67" href="#t67">67</a></span><span class="t">    <span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t68" href="#t68">68</a></span><span class="t">        <span class="str">"""Initialize package.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t69" href="#t69">69</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t70" href="#t70">70</a></span><span class="t"><span class="str">        This method configure and starts JVM and load RuleKit jar file.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t15" href="#t15">15</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">_logging</span> <span class="key">import</span> <span class="nam">_RuleKitJavaLoggerConfig</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t16" href="#t16">16</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t17" href="#t17">17</a></span><span class="t"><span class="nam">__RULEKIT_RELEASE_VERSION__</span> <span class="op">=</span> <span class="str">'2.1.24'</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t18" href="#t18">18</a></span><span class="t"><span class="nam">__VERSION__</span> <span class="op">=</span> <span class="str">f'{__RULEKIT_RELEASE_VERSION__}.0'</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t19" href="#t19">19</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t20" href="#t20">20</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t21" href="#t21">21</a></span><span class="t"><span class="key">class</span> <span class="nam">JRE_Type</span><span class="op">(</span><span class="nam">Enum</span><span class="op">)</span><span class="op">:</span>  <span class="com"># pylint: disable=invalid-name</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t22" href="#t22">22</a></span><span class="t">    <span class="str">""":meta private:"""</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t23" href="#t23">23</a></span><span class="t">    <span class="nam">OPEN_JDK</span> <span class="op">=</span> <span class="str">'open_jdk'</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t24" href="#t24">24</a></span><span class="t">    <span class="nam">ORACLE</span> <span class="op">=</span> <span class="str">'oracle'</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t25" href="#t25">25</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t26" href="#t26">26</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t27" href="#t27">27</a></span><span class="t"><span class="key">class</span> <span class="nam">RuleKit</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t28" href="#t28">28</a></span><span class="t">    <span class="str">"""Class used for initializing RuleKit. It starts JVM underhood and setups it with jars.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t29" href="#t29">29</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t30" href="#t30">30</a></span><span class="t"><span class="str">    .. note:: Since version 1.7.0 there is no need to manually initialize RuleKit.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t31" href="#t31">31</a></span><span class="t"><span class="str">    You may just skip the **RuleKit.init()** line. However in certain scenarios when</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t32" href="#t32">32</a></span><span class="t"><span class="str">    you want use a custom RuleKit jar file or modify Java VM parameters, this class</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t33" href="#t33">33</a></span><span class="t"><span class="str">    can be used.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t34" href="#t34">34</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t35" href="#t35">35</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t36" href="#t36">36</a></span><span class="t"><span class="str">    Attributes</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t37" href="#t37">37</a></span><span class="t"><span class="str">    ----------</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t38" href="#t38">38</a></span><span class="t"><span class="str">    version : str</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t39" href="#t39">39</a></span><span class="t"><span class="str">        version of RuleKit jar used by wrapper (not equal to python package version).</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t40" href="#t40">40</a></span><span class="t"><span class="str">    """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t41" href="#t41">41</a></span><span class="t">    <span class="nam">version</span><span class="op">:</span> <span class="nam">str</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t42" href="#t42">42</a></span><span class="t">    <span class="nam">_logger</span><span class="op">:</span> <span class="nam">logging</span><span class="op">.</span><span class="nam">Logger</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t43" href="#t43">43</a></span><span class="t">    <span class="nam">_jar_dir_path</span><span class="op">:</span> <span class="nam">str</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t44" href="#t44">44</a></span><span class="t">    <span class="nam">_class_path</span><span class="op">:</span> <span class="nam">str</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t45" href="#t45">45</a></span><span class="t">    <span class="nam">_rulekit_jar_file_path</span><span class="op">:</span> <span class="nam">str</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t46" href="#t46">46</a></span><span class="t">    <span class="nam">_jre_type</span><span class="op">:</span> <span class="nam">JRE_Type</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t47" href="#t47">47</a></span><span class="t">    <span class="nam">_java_logger_config</span><span class="op">:</span> <span class="nam">Optional</span><span class="op">[</span><span class="nam">_RuleKitJavaLoggerConfig</span><span class="op">]</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t48" href="#t48">48</a></span><span class="t">    <span class="nam">initialized</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="key">False</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t49" href="#t49">49</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t50" href="#t50">50</a></span><span class="t">    <span class="op">@</span><span class="nam">staticmethod</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t51" href="#t51">51</a></span><span class="t">    <span class="key">def</span> <span class="nam">_detect_jre_type</span><span class="op">(</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t52" href="#t52">52</a></span><span class="t">        <span class="key">try</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t53" href="#t53">53</a></span><span class="t">            <span class="key">with</span> <span class="nam">Popen</span><span class="op">(</span><span class="op">[</span><span class="str">"java"</span><span class="op">,</span> <span class="str">"-version"</span><span class="op">]</span><span class="op">,</span> <span class="nam">stderr</span><span class="op">=</span><span class="nam">STDOUT</span><span class="op">,</span> <span class="nam">stdout</span><span class="op">=</span><span class="nam">PIPE</span><span class="op">)</span> <span class="key">as</span> <span class="nam">output</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t54" href="#t54">54</a></span><span class="t">                <span class="nam">output</span> <span class="op">=</span> <span class="nam">str</span><span class="op">(</span><span class="nam">output</span><span class="op">.</span><span class="nam">communicate</span><span class="op">(</span><span class="op">)</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t55" href="#t55">55</a></span><span class="t">                <span class="key">if</span> <span class="str">'openjdk'</span> <span class="key">in</span> <span class="nam">output</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t56" href="#t56">56</a></span><span class="t">                    <span class="nam">RuleKit</span><span class="op">.</span><span class="nam">_jre_type</span> <span class="op">=</span> <span class="nam">JRE_Type</span><span class="op">.</span><span class="nam">OPEN_JDK</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t57" href="#t57">57</a></span><span class="t">                <span class="key">else</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t58" href="#t58">58</a></span><span class="t">                    <span class="nam">RuleKit</span><span class="op">.</span><span class="nam">_jre_type</span> <span class="op">=</span> <span class="nam">JRE_Type</span><span class="op">.</span><span class="nam">ORACLE</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t59" href="#t59">59</a></span><span class="t">        <span class="key">except</span> <span class="nam">FileNotFoundError</span> <span class="key">as</span> <span class="nam">error</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t60" href="#t60">60</a></span><span class="t">            <span class="key">raise</span> <span class="nam">RuntimeError</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t61" href="#t61">61</a></span><span class="t">                <span class="str">'RuletKit requires java JRE to be installed (version 1.8.0 recommended)'</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t62" href="#t62">62</a></span><span class="t">            <span class="op">)</span> <span class="key">from</span> <span class="nam">error</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t63" href="#t63">63</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t64" href="#t64">64</a></span><span class="t">    <span class="op">@</span><span class="nam">staticmethod</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t65" href="#t65">65</a></span><span class="t">    <span class="key">def</span> <span class="nam">init</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t66" href="#t66">66</a></span><span class="t">        <span class="nam">initial_heap_size</span><span class="op">:</span> <span class="nam">int</span> <span class="op">=</span> <span class="key">None</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t67" href="#t67">67</a></span><span class="t">        <span class="nam">max_heap_size</span><span class="op">:</span> <span class="nam">int</span> <span class="op">=</span> <span class="key">None</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t68" href="#t68">68</a></span><span class="t">        <span class="nam">rulekit_jar_file_path</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t69" href="#t69">69</a></span><span class="t">    <span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t70" href="#t70">70</a></span><span class="t">        <span class="str">"""Initialize package.</span>&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t71" href="#t71">71</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t72" href="#t72">72</a></span><span class="t"><span class="str">        .. note:: Since version 1.7.0 it don't have to be called before using any operator class.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t73" href="#t73">73</a></span><span class="t"><span class="str">        However in certain scenarios when you want use a custom RuleKit jar file or modify Java VM</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t74" href="#t74">74</a></span><span class="t"><span class="str">        parameters, this method can be used.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t75" href="#t75">75</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t76" href="#t76">76</a></span><span class="t"><span class="str">        Parameters</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t77" href="#t77">77</a></span><span class="t"><span class="str">        ----------</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t78" href="#t78">78</a></span><span class="t"><span class="str">        initial_heap_size : int</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t79" href="#t79">79</a></span><span class="t"><span class="str">            JVM initial heap size in mb</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t80" href="#t80">80</a></span><span class="t"><span class="str">        max_heap_size : int</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t81" href="#t81">81</a></span><span class="t"><span class="str">            JVM max heap size in mb</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t82" href="#t82">82</a></span><span class="t"><span class="str">        rulekit_jar_file_path : str</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t83" href="#t83">83</a></span><span class="t"><span class="str">            Path to the RuleKit jar file. This parameters.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t84" href="#t84">84</a></span><span class="t"><span class="str">            .. note::</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t85" href="#t85">85</a></span><span class="t"><span class="str">                You probably don't need to use this parameter unless you want to use</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t86" href="#t86">86</a></span><span class="t"><span class="str">                your own custom version of RuleKit jar file. Otherwise leave it as it</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t87" href="#t87">87</a></span><span class="t"><span class="str">                is and the package will use the official RuleKit release jar file.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t88" href="#t88">88</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t89" href="#t89">89</a></span><span class="t"><span class="str">        Raises</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t90" href="#t90">90</a></span><span class="t"><span class="str">        ------</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t91" href="#t91">91</a></span><span class="t"><span class="str">        Exception</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t92" href="#t92">92</a></span><span class="t"><span class="str">            If failed to load RuleKit jar file.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t93" href="#t93">93</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t94" href="#t94">94</a></span><span class="t">        <span class="key">if</span> <span class="nam">RuleKit</span><span class="op">.</span><span class="nam">initialized</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t95" href="#t95">95</a></span><span class="t">            <span class="key">return</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t96" href="#t96">96</a></span><span class="t">        <span class="nam">RuleKit</span><span class="op">.</span><span class="nam">_setup_logger</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t97" href="#t97">97</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t98" href="#t98">98</a></span><span class="t">        <span class="nam">RuleKit</span><span class="op">.</span><span class="nam">_detect_jre_type</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t99" href="#t99">99</a></span><span class="t">        <span class="nam">current_path</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="nam">os</span><span class="op">.</span><span class="nam">path</span><span class="op">.</span><span class="nam">dirname</span><span class="op">(</span><span class="nam">os</span><span class="op">.</span><span class="nam">path</span><span class="op">.</span><span class="nam">realpath</span><span class="op">(</span><span class="nam">__file__</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t100" href="#t100">100</a></span><span class="t">        <span class="nam">RuleKit</span><span class="op">.</span><span class="nam">_jar_dir_path</span> <span class="op">=</span> <span class="str">f"{current_path}/jar"</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t101" href="#t101">101</a></span><span class="t">        <span class="nam">class_path_separator</span> <span class="op">=</span> <span class="nam">os</span><span class="op">.</span><span class="nam">pathsep</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t102" href="#t102">102</a></span><span class="t">        <span class="key">try</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t103" href="#t103">103</a></span><span class="t">            <span class="nam">jar_file_name</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t104" href="#t104">104</a></span><span class="t">                <span class="str">'rulekit-'</span> <span class="op">+</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t105" href="#t105">105</a></span><span class="t">                <span class="str">f'{__RULEKIT_RELEASE_VERSION__}-all.jar'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t106" href="#t106">106</a></span><span class="t">            <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t107" href="#t107">107</a></span><span class="t">            <span class="nam">RuleKit</span><span class="op">.</span><span class="nam">_rulekit_jar_file_path</span> <span class="op">=</span> <span class="nam">os</span><span class="op">.</span><span class="nam">path</span><span class="op">.</span><span class="nam">join</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t108" href="#t108">108</a></span><span class="t">                <span class="nam">RuleKit</span><span class="op">.</span><span class="nam">_jar_dir_path</span><span class="op">,</span> <span class="nam">jar_file_name</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t109" href="#t109">109</a></span><span class="t">            <span class="nam">jars_paths</span><span class="op">:</span> <span class="nam">list</span><span class="op">[</span><span class="nam">str</span><span class="op">]</span> <span class="op">=</span> <span class="op">[</span><span class="nam">RuleKit</span><span class="op">.</span><span class="nam">_rulekit_jar_file_path</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t110" href="#t110">110</a></span><span class="t">            <span class="key">if</span> <span class="nam">rulekit_jar_file_path</span> <span class="key">is</span> <span class="key">not</span> <span class="key">None</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t111" href="#t111">111</a></span><span class="t">                <span class="nam">jars_paths</span><span class="op">.</span><span class="nam">remove</span><span class="op">(</span><span class="nam">RuleKit</span><span class="op">.</span><span class="nam">_rulekit_jar_file_path</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t112" href="#t112">112</a></span><span class="t">                <span class="nam">jars_paths</span><span class="op">.</span><span class="nam">append</span><span class="op">(</span><span class="nam">rulekit_jar_file_path</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t113" href="#t113">113</a></span><span class="t">                <span class="nam">RuleKit</span><span class="op">.</span><span class="nam">_rulekit_jar_file_path</span> <span class="op">=</span> <span class="nam">rulekit_jar_file_path</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t114" href="#t114">114</a></span><span class="t">            <span class="nam">RuleKit</span><span class="op">.</span><span class="nam">_class_path</span> <span class="op">=</span> <span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t115" href="#t115">115</a></span><span class="t">                <span class="str">f'{str.join(class_path_separator, jars_paths)}'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t116" href="#t116">116</a></span><span class="t">            <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t117" href="#t117">117</a></span><span class="t">        <span class="key">except</span> <span class="nam">IndexError</span> <span class="key">as</span> <span class="nam">error</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t118" href="#t118">118</a></span><span class="t">            <span class="nam">RuleKit</span><span class="op">.</span><span class="nam">_logger</span><span class="op">.</span><span class="nam">error</span><span class="op">(</span><span class="str">'Failed to load jar files'</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t119" href="#t119">119</a></span><span class="t">            <span class="key">raise</span> <span class="nam">RuntimeError</span><span class="op">(</span><span class="str">f'''\n</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t120" href="#t120">120</a></span><span class="t"><span class="str">Failed to load RuleKit jar file. Check if valid rulekit jar file is present in "{RuleKit._jar_dir_path}" directory.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t121" href="#t121">121</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t122" href="#t122">122</a></span><span class="t"><span class="str">If you're running this package for the first time you need to download RuleKit jar file by running:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t123" href="#t123">123</a></span><span class="t"><span class="str">    python -m rulekit download_jar</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t124" href="#t124">124</a></span><span class="t"><span class="str">        '''</span><span class="op">)</span> <span class="key">from</span> <span class="nam">error</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t125" href="#t125">125</a></span><span class="t">        <span class="nam">RuleKit</span><span class="op">.</span><span class="nam">_read_versions</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t126" href="#t126">126</a></span><span class="t">        <span class="nam">RuleKit</span><span class="op">.</span><span class="nam">_launch_jvm</span><span class="op">(</span><span class="nam">initial_heap_size</span><span class="op">,</span> <span class="nam">max_heap_size</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t127" href="#t127">127</a></span><span class="t">        <span class="nam">RuleKit</span><span class="op">.</span><span class="nam">initialized</span> <span class="op">=</span> <span class="key">True</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t128" href="#t128">128</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t129" href="#t129">129</a></span><span class="t">    <span class="op">@</span><span class="nam">staticmethod</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t130" href="#t130">130</a></span><span class="t">    <span class="key">def</span> <span class="nam">_setup_logger</span><span class="op">(</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t131" href="#t131">131</a></span><span class="t">        <span class="nam">logging</span><span class="op">.</span><span class="nam">basicConfig</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t132" href="#t132">132</a></span><span class="t">        <span class="nam">RuleKit</span><span class="op">.</span><span class="nam">_logger</span> <span class="op">=</span> <span class="nam">logging</span><span class="op">.</span><span class="nam">getLogger</span><span class="op">(</span><span class="str">'RuleKit'</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t133" href="#t133">133</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t134" href="#t134">134</a></span><span class="t">    <span class="op">@</span><span class="nam">staticmethod</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t135" href="#t135">135</a></span><span class="t">    <span class="key">def</span> <span class="nam">_read_versions</span><span class="op">(</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t136" href="#t136">136</a></span><span class="t">        <span class="key">with</span> <span class="nam">zipfile</span><span class="op">.</span><span class="nam">ZipFile</span><span class="op">(</span><span class="nam">RuleKit</span><span class="op">.</span><span class="nam">_rulekit_jar_file_path</span><span class="op">,</span> <span class="str">'r'</span><span class="op">)</span> <span class="key">as</span> <span class="nam">jar_archive</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t137" href="#t137">137</a></span><span class="t">            <span class="key">try</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t138" href="#t138">138</a></span><span class="t">                <span class="nam">manifest_file_content</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="nam">jar_archive</span><span class="op">.</span><span class="nam">read</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t139" href="#t139">139</a></span><span class="t">                    <span class="str">'META-INF/MANIFEST.MF'</span><span class="op">)</span><span class="op">.</span><span class="nam">decode</span><span class="op">(</span><span class="str">'utf-8'</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t140" href="#t140">140</a></span><span class="t">                <span class="nam">RuleKit</span><span class="op">.</span><span class="nam">version</span> <span class="op">=</span> <span class="nam">re</span><span class="op">.</span><span class="nam">findall</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t141" href="#t141">141</a></span><span class="t">                    <span class="str">r'Implementation-Version: \S+\r'</span><span class="op">,</span> <span class="nam">manifest_file_content</span><span class="op">)</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="op">.</span><span class="nam">split</span><span class="op">(</span><span class="str">' '</span><span class="op">)</span><span class="op">[</span><span class="num">1</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t142" href="#t142">142</a></span><span class="t">            <span class="key">except</span> <span class="nam">Exception</span> <span class="key">as</span> <span class="nam">error</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t143" href="#t143">143</a></span><span class="t">                <span class="nam">RuleKit</span><span class="op">.</span><span class="nam">_logger</span><span class="op">.</span><span class="nam">error</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t144" href="#t144">144</a></span><span class="t">                    <span class="str">'Failed to read RuleKit versions from jar file'</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t145" href="#t145">145</a></span><span class="t">                <span class="nam">RuleKit</span><span class="op">.</span><span class="nam">_logger</span><span class="op">.</span><span class="nam">error</span><span class="op">(</span><span class="nam">error</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t146" href="#t146">146</a></span><span class="t">                <span class="key">raise</span> <span class="nam">error</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t147" href="#t147">147</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t148" href="#t148">148</a></span><span class="t">    <span class="op">@</span><span class="nam">staticmethod</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t149" href="#t149">149</a></span><span class="t">    <span class="key">def</span> <span class="nam">_launch_jvm</span><span class="op">(</span><span class="nam">initial_heap_size</span><span class="op">:</span> <span class="nam">int</span><span class="op">,</span> <span class="nam">max_heap_size</span><span class="op">:</span> <span class="nam">int</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t150" href="#t150">150</a></span><span class="t">        <span class="key">if</span> <span class="nam">jpype</span><span class="op">.</span><span class="nam">isJVMStarted</span><span class="op">(</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t151" href="#t151">151</a></span><span class="t">            <span class="nam">RuleKit</span><span class="op">.</span><span class="nam">_logger</span><span class="op">.</span><span class="nam">info</span><span class="op">(</span><span class="str">'JVM already running'</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t152" href="#t152">152</a></span><span class="t">        <span class="key">else</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t153" href="#t153">153</a></span><span class="t">            <span class="nam">params</span> <span class="op">=</span> <span class="op">[</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t154" href="#t154">154</a></span><span class="t">                <span class="str">f'-Djava.class.path={RuleKit._class_path}'</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t155" href="#t155">155</a></span><span class="t">            <span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t156" href="#t156">156</a></span><span class="t">            <span class="key">if</span> <span class="nam">initial_heap_size</span> <span class="key">is</span> <span class="key">not</span> <span class="key">None</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t157" href="#t157">157</a></span><span class="t">                <span class="nam">params</span><span class="op">.</span><span class="nam">append</span><span class="op">(</span><span class="str">f'-Xms{initial_heap_size}m'</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t158" href="#t158">158</a></span><span class="t">            <span class="key">if</span> <span class="nam">max_heap_size</span> <span class="key">is</span> <span class="key">not</span> <span class="key">None</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t159" href="#t159">159</a></span><span class="t">                <span class="nam">params</span><span class="op">.</span><span class="nam">append</span><span class="op">(</span><span class="str">f'-Xmx{max_heap_size}m'</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t160" href="#t160">160</a></span><span class="t">            <span class="nam">jpype</span><span class="op">.</span><span class="nam">startJVM</span><span class="op">(</span><span class="nam">jpype</span><span class="op">.</span><span class="nam">getDefaultJVMPath</span><span class="op">(</span><span class="op">)</span><span class="op">,</span> <span class="op">*</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t161" href="#t161">161</a></span><span class="t">                           <span class="nam">params</span><span class="op">,</span> <span class="nam">convertStrings</span><span class="op">=</span><span class="key">False</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t162" href="#t162">162</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t163" href="#t163">163</a></span><span class="t">    <span class="op">@</span><span class="nam">staticmethod</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t164" href="#t164">164</a></span><span class="t">    <span class="key">def</span> <span class="nam">configure_java_logger</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t165" href="#t165">165</a></span><span class="t">        <span class="nam">log_file_path</span><span class="op">:</span> <span class="nam">str</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t166" href="#t166">166</a></span><span class="t">        <span class="nam">verbosity_level</span><span class="op">:</span> <span class="nam">int</span> <span class="op">=</span> <span class="num">1</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t167" href="#t167">167</a></span><span class="t">    <span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t168" href="#t168">168</a></span><span class="t">        <span class="str">"""Enable Java debug logging. You probably don't need to use this</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t169" href="#t169">169</a></span><span class="t"><span class="str">        method unless you want too deep dive into the process of rules inductions</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t170" href="#t170">170</a></span><span class="t"><span class="str">         or your're debugging some issues.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t171" href="#t171">171</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t172" href="#t172">172</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t173" href="#t173">173</a></span><span class="t"><span class="str">        Args:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t174" href="#t174">174</a></span><span class="t"><span class="str">            log_file_path (str): Path to the file where logs will be stored</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t175" href="#t175">175</a></span><span class="t"><span class="str">            verbosity_level (int, optional): Verbosity level.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t176" href="#t176">176</a></span><span class="t"><span class="str">                Minimum value is 1, maximum value is 2, default value is 1.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t177" href="#t177">177</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t178" href="#t178">178</a></span><span class="t">        <span class="nam">RuleKit</span><span class="op">.</span><span class="nam">_java_logger_config</span> <span class="op">=</span> <span class="nam">_RuleKitJavaLoggerConfig</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t179" href="#t179">179</a></span><span class="t">            <span class="nam">verbosity_level</span><span class="op">=</span><span class="nam">verbosity_level</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t180" href="#t180">180</a></span><span class="t">            <span class="nam">log_file_path</span><span class="op">=</span><span class="nam">log_file_path</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t181" href="#t181">181</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t182" href="#t182">182</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t183" href="#t183">183</a></span><span class="t">    <span class="op">@</span><span class="nam">staticmethod</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t184" href="#t184">184</a></span><span class="t">    <span class="key">def</span> <span class="nam">get_java_logger_config</span><span class="op">(</span><span class="op">)</span> <span class="op">-></span> <span class="nam">Optional</span><span class="op">[</span><span class="nam">_RuleKitJavaLoggerConfig</span><span class="op">]</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t185" href="#t185">185</a></span><span class="t">        <span class="str">"""Returns the Java logger configuration configured using `configure_java_logger`</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t186" href="#t186">186</a></span><span class="t"><span class="str">        method</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t187" href="#t187">187</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t188" href="#t188">188</a></span><span class="t"><span class="str">        Returns:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t189" href="#t189">189</a></span><span class="t"><span class="str">            Optional[_RuleKitJavaLoggerConfig]: Java logger configuration</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t190" href="#t190">190</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t191" href="#t191">191</a></span><span class="t">        <span class="key">return</span> <span class="nam">RuleKit</span><span class="op">.</span><span class="nam">_java_logger_config</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t72" href="#t72">72</a></span><span class="t"><span class="str">        This method configure and starts JVM and load RuleKit jar file.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t73" href="#t73">73</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t74" href="#t74">74</a></span><span class="t"><span class="str">        .. note:: Since version 1.7.0 it don't have to be called before using any operator class.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t75" href="#t75">75</a></span><span class="t"><span class="str">        However in certain scenarios when you want use a custom RuleKit jar file or modify Java VM</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t76" href="#t76">76</a></span><span class="t"><span class="str">        parameters, this method can be used.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t77" href="#t77">77</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t78" href="#t78">78</a></span><span class="t"><span class="str">        Parameters</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t79" href="#t79">79</a></span><span class="t"><span class="str">        ----------</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t80" href="#t80">80</a></span><span class="t"><span class="str">        initial_heap_size : int</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t81" href="#t81">81</a></span><span class="t"><span class="str">            JVM initial heap size in mb</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t82" href="#t82">82</a></span><span class="t"><span class="str">        max_heap_size : int</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t83" href="#t83">83</a></span><span class="t"><span class="str">            JVM max heap size in mb</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t84" href="#t84">84</a></span><span class="t"><span class="str">        rulekit_jar_file_path : str</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t85" href="#t85">85</a></span><span class="t"><span class="str">            Path to the RuleKit jar file. This parameters.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t86" href="#t86">86</a></span><span class="t"><span class="str">            .. note::</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t87" href="#t87">87</a></span><span class="t"><span class="str">                You probably don't need to use this parameter unless you want to use</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t88" href="#t88">88</a></span><span class="t"><span class="str">                your own custom version of RuleKit jar file. Otherwise leave it as it</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t89" href="#t89">89</a></span><span class="t"><span class="str">                is and the package will use the official RuleKit release jar file.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t90" href="#t90">90</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t91" href="#t91">91</a></span><span class="t"><span class="str">        Raises</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t92" href="#t92">92</a></span><span class="t"><span class="str">        ------</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t93" href="#t93">93</a></span><span class="t"><span class="str">        Exception</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t94" href="#t94">94</a></span><span class="t"><span class="str">            If failed to load RuleKit jar file.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t95" href="#t95">95</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t96" href="#t96">96</a></span><span class="t">        <span class="key">if</span> <span class="nam">RuleKit</span><span class="op">.</span><span class="nam">initialized</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t97" href="#t97">97</a></span><span class="t">            <span class="key">return</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t98" href="#t98">98</a></span><span class="t">        <span class="nam">RuleKit</span><span class="op">.</span><span class="nam">_setup_logger</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t99" href="#t99">99</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t100" href="#t100">100</a></span><span class="t">        <span class="nam">RuleKit</span><span class="op">.</span><span class="nam">_detect_jre_type</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t101" href="#t101">101</a></span><span class="t">        <span class="nam">current_path</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="nam">os</span><span class="op">.</span><span class="nam">path</span><span class="op">.</span><span class="nam">dirname</span><span class="op">(</span><span class="nam">os</span><span class="op">.</span><span class="nam">path</span><span class="op">.</span><span class="nam">realpath</span><span class="op">(</span><span class="nam">__file__</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t102" href="#t102">102</a></span><span class="t">        <span class="nam">RuleKit</span><span class="op">.</span><span class="nam">_jar_dir_path</span> <span class="op">=</span> <span class="str">f"{current_path}/jar"</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t103" href="#t103">103</a></span><span class="t">        <span class="nam">class_path_separator</span> <span class="op">=</span> <span class="nam">os</span><span class="op">.</span><span class="nam">pathsep</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t104" href="#t104">104</a></span><span class="t">        <span class="key">try</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t105" href="#t105">105</a></span><span class="t">            <span class="nam">jar_file_name</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t106" href="#t106">106</a></span><span class="t">                <span class="str">'rulekit-'</span> <span class="op">+</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t107" href="#t107">107</a></span><span class="t">                <span class="str">f'{__RULEKIT_RELEASE_VERSION__}-all.jar'</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t108" href="#t108">108</a></span><span class="t">            <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t109" href="#t109">109</a></span><span class="t">            <span class="nam">RuleKit</span><span class="op">.</span><span class="nam">_rulekit_jar_file_path</span> <span class="op">=</span> <span class="nam">os</span><span class="op">.</span><span class="nam">path</span><span class="op">.</span><span class="nam">join</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t110" href="#t110">110</a></span><span class="t">                <span class="nam">RuleKit</span><span class="op">.</span><span class="nam">_jar_dir_path</span><span class="op">,</span> <span class="nam">jar_file_name</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t111" href="#t111">111</a></span><span class="t">            <span class="nam">jars_paths</span><span class="op">:</span> <span class="nam">list</span><span class="op">[</span><span class="nam">str</span><span class="op">]</span> <span class="op">=</span> <span class="op">[</span><span class="nam">RuleKit</span><span class="op">.</span><span class="nam">_rulekit_jar_file_path</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t112" href="#t112">112</a></span><span class="t">            <span class="key">if</span> <span class="nam">rulekit_jar_file_path</span> <span class="key">is</span> <span class="key">not</span> <span class="key">None</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t113" href="#t113">113</a></span><span class="t">                <span class="nam">jars_paths</span><span class="op">.</span><span class="nam">remove</span><span class="op">(</span><span class="nam">RuleKit</span><span class="op">.</span><span class="nam">_rulekit_jar_file_path</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t114" href="#t114">114</a></span><span class="t">                <span class="nam">jars_paths</span><span class="op">.</span><span class="nam">append</span><span class="op">(</span><span class="nam">rulekit_jar_file_path</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t115" href="#t115">115</a></span><span class="t">                <span class="nam">RuleKit</span><span class="op">.</span><span class="nam">_rulekit_jar_file_path</span> <span class="op">=</span> <span class="nam">rulekit_jar_file_path</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t116" href="#t116">116</a></span><span class="t">            <span class="nam">RuleKit</span><span class="op">.</span><span class="nam">_class_path</span> <span class="op">=</span> <span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t117" href="#t117">117</a></span><span class="t">                <span class="str">f'{str.join(class_path_separator, jars_paths)}'</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t118" href="#t118">118</a></span><span class="t">            <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t119" href="#t119">119</a></span><span class="t">        <span class="key">except</span> <span class="nam">IndexError</span> <span class="key">as</span> <span class="nam">error</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t120" href="#t120">120</a></span><span class="t">            <span class="nam">RuleKit</span><span class="op">.</span><span class="nam">_logger</span><span class="op">.</span><span class="nam">error</span><span class="op">(</span><span class="str">'Failed to load jar files'</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t121" href="#t121">121</a></span><span class="t">            <span class="key">raise</span> <span class="nam">RuntimeError</span><span class="op">(</span><span class="str">f'''\n</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t122" href="#t122">122</a></span><span class="t"><span class="str">Failed to load RuleKit jar file. Check if valid rulekit jar file is present in "{RuleKit._jar_dir_path}" directory.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t123" href="#t123">123</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t124" href="#t124">124</a></span><span class="t"><span class="str">If you're running this package for the first time you need to download RuleKit jar file by running:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t125" href="#t125">125</a></span><span class="t"><span class="str">    python -m rulekit download_jar</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t126" href="#t126">126</a></span><span class="t"><span class="str">        '''</span><span class="op">)</span> <span class="key">from</span> <span class="nam">error</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t127" href="#t127">127</a></span><span class="t">        <span class="nam">RuleKit</span><span class="op">.</span><span class="nam">_read_versions</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t128" href="#t128">128</a></span><span class="t">        <span class="nam">RuleKit</span><span class="op">.</span><span class="nam">_launch_jvm</span><span class="op">(</span><span class="nam">initial_heap_size</span><span class="op">,</span> <span class="nam">max_heap_size</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t129" href="#t129">129</a></span><span class="t">        <span class="nam">RuleKit</span><span class="op">.</span><span class="nam">initialized</span> <span class="op">=</span> <span class="key">True</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t130" href="#t130">130</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t131" href="#t131">131</a></span><span class="t">    <span class="op">@</span><span class="nam">staticmethod</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t132" href="#t132">132</a></span><span class="t">    <span class="key">def</span> <span class="nam">_setup_logger</span><span class="op">(</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t133" href="#t133">133</a></span><span class="t">        <span class="nam">logging</span><span class="op">.</span><span class="nam">basicConfig</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t134" href="#t134">134</a></span><span class="t">        <span class="nam">RuleKit</span><span class="op">.</span><span class="nam">_logger</span> <span class="op">=</span> <span class="nam">logging</span><span class="op">.</span><span class="nam">getLogger</span><span class="op">(</span><span class="str">'RuleKit'</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t135" href="#t135">135</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t136" href="#t136">136</a></span><span class="t">    <span class="op">@</span><span class="nam">staticmethod</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t137" href="#t137">137</a></span><span class="t">    <span class="key">def</span> <span class="nam">_read_versions</span><span class="op">(</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t138" href="#t138">138</a></span><span class="t">        <span class="key">with</span> <span class="nam">zipfile</span><span class="op">.</span><span class="nam">ZipFile</span><span class="op">(</span><span class="nam">RuleKit</span><span class="op">.</span><span class="nam">_rulekit_jar_file_path</span><span class="op">,</span> <span class="str">'r'</span><span class="op">)</span> <span class="key">as</span> <span class="nam">jar_archive</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t139" href="#t139">139</a></span><span class="t">            <span class="key">try</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t140" href="#t140">140</a></span><span class="t">                <span class="nam">manifest_file_content</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="nam">jar_archive</span><span class="op">.</span><span class="nam">read</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t141" href="#t141">141</a></span><span class="t">                    <span class="str">'META-INF/MANIFEST.MF'</span><span class="op">)</span><span class="op">.</span><span class="nam">decode</span><span class="op">(</span><span class="str">'utf-8'</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t142" href="#t142">142</a></span><span class="t">                <span class="nam">RuleKit</span><span class="op">.</span><span class="nam">version</span> <span class="op">=</span> <span class="nam">re</span><span class="op">.</span><span class="nam">findall</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t143" href="#t143">143</a></span><span class="t">                    <span class="str">r'Implementation-Version: \S+\r'</span><span class="op">,</span> <span class="nam">manifest_file_content</span><span class="op">)</span><span class="op">[</span><span class="num">0</span><span class="op">]</span><span class="op">.</span><span class="nam">split</span><span class="op">(</span><span class="str">' '</span><span class="op">)</span><span class="op">[</span><span class="num">1</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t144" href="#t144">144</a></span><span class="t">            <span class="key">except</span> <span class="nam">Exception</span> <span class="key">as</span> <span class="nam">error</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t145" href="#t145">145</a></span><span class="t">                <span class="nam">RuleKit</span><span class="op">.</span><span class="nam">_logger</span><span class="op">.</span><span class="nam">error</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t146" href="#t146">146</a></span><span class="t">                    <span class="str">'Failed to read RuleKit versions from jar file'</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t147" href="#t147">147</a></span><span class="t">                <span class="nam">RuleKit</span><span class="op">.</span><span class="nam">_logger</span><span class="op">.</span><span class="nam">error</span><span class="op">(</span><span class="nam">error</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t148" href="#t148">148</a></span><span class="t">                <span class="key">raise</span> <span class="nam">error</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t149" href="#t149">149</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t150" href="#t150">150</a></span><span class="t">    <span class="op">@</span><span class="nam">staticmethod</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t151" href="#t151">151</a></span><span class="t">    <span class="key">def</span> <span class="nam">_launch_jvm</span><span class="op">(</span><span class="nam">initial_heap_size</span><span class="op">:</span> <span class="nam">int</span><span class="op">,</span> <span class="nam">max_heap_size</span><span class="op">:</span> <span class="nam">int</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t152" href="#t152">152</a></span><span class="t">        <span class="key">if</span> <span class="nam">jpype</span><span class="op">.</span><span class="nam">isJVMStarted</span><span class="op">(</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t153" href="#t153">153</a></span><span class="t">            <span class="nam">RuleKit</span><span class="op">.</span><span class="nam">_logger</span><span class="op">.</span><span class="nam">info</span><span class="op">(</span><span class="str">'JVM already running'</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t154" href="#t154">154</a></span><span class="t">        <span class="key">else</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t155" href="#t155">155</a></span><span class="t">            <span class="nam">params</span> <span class="op">=</span> <span class="op">[</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t156" href="#t156">156</a></span><span class="t">                <span class="str">f'-Djava.class.path={RuleKit._class_path}'</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t157" href="#t157">157</a></span><span class="t">            <span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t158" href="#t158">158</a></span><span class="t">            <span class="key">if</span> <span class="nam">initial_heap_size</span> <span class="key">is</span> <span class="key">not</span> <span class="key">None</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t159" href="#t159">159</a></span><span class="t">                <span class="nam">params</span><span class="op">.</span><span class="nam">append</span><span class="op">(</span><span class="str">f'-Xms{initial_heap_size}m'</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t160" href="#t160">160</a></span><span class="t">            <span class="key">if</span> <span class="nam">max_heap_size</span> <span class="key">is</span> <span class="key">not</span> <span class="key">None</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t161" href="#t161">161</a></span><span class="t">                <span class="nam">params</span><span class="op">.</span><span class="nam">append</span><span class="op">(</span><span class="str">f'-Xmx{max_heap_size}m'</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t162" href="#t162">162</a></span><span class="t">            <span class="nam">jpype</span><span class="op">.</span><span class="nam">startJVM</span><span class="op">(</span><span class="nam">jpype</span><span class="op">.</span><span class="nam">getDefaultJVMPath</span><span class="op">(</span><span class="op">)</span><span class="op">,</span> <span class="op">*</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t163" href="#t163">163</a></span><span class="t">                           <span class="nam">params</span><span class="op">,</span> <span class="nam">convertStrings</span><span class="op">=</span><span class="key">False</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t164" href="#t164">164</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t165" href="#t165">165</a></span><span class="t">    <span class="op">@</span><span class="nam">staticmethod</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t166" href="#t166">166</a></span><span class="t">    <span class="key">def</span> <span class="nam">configure_java_logger</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t167" href="#t167">167</a></span><span class="t">        <span class="nam">log_file_path</span><span class="op">:</span> <span class="nam">str</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t168" href="#t168">168</a></span><span class="t">        <span class="nam">verbosity_level</span><span class="op">:</span> <span class="nam">int</span> <span class="op">=</span> <span class="num">1</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t169" href="#t169">169</a></span><span class="t">    <span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t170" href="#t170">170</a></span><span class="t">        <span class="str">"""Enable Java debug logging. You probably don't need to use this</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t171" href="#t171">171</a></span><span class="t"><span class="str">        method unless you want too deep dive into the process of rules inductions</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t172" href="#t172">172</a></span><span class="t"><span class="str">         or your're debugging some issues.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t173" href="#t173">173</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t174" href="#t174">174</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t175" href="#t175">175</a></span><span class="t"><span class="str">        Args:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t176" href="#t176">176</a></span><span class="t"><span class="str">            log_file_path (str): Path to the file where logs will be stored</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t177" href="#t177">177</a></span><span class="t"><span class="str">            verbosity_level (int, optional): Verbosity level.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t178" href="#t178">178</a></span><span class="t"><span class="str">                Minimum value is 1, maximum value is 2, default value is 1.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t179" href="#t179">179</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t180" href="#t180">180</a></span><span class="t">        <span class="nam">RuleKit</span><span class="op">.</span><span class="nam">_java_logger_config</span> <span class="op">=</span> <span class="nam">_RuleKitJavaLoggerConfig</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t181" href="#t181">181</a></span><span class="t">            <span class="nam">verbosity_level</span><span class="op">=</span><span class="nam">verbosity_level</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t182" href="#t182">182</a></span><span class="t">            <span class="nam">log_file_path</span><span class="op">=</span><span class="nam">log_file_path</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t183" href="#t183">183</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t184" href="#t184">184</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t185" href="#t185">185</a></span><span class="t">    <span class="op">@</span><span class="nam">staticmethod</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t186" href="#t186">186</a></span><span class="t">    <span class="key">def</span> <span class="nam">get_java_logger_config</span><span class="op">(</span><span class="op">)</span> <span class="op">-></span> <span class="nam">Optional</span><span class="op">[</span><span class="nam">_RuleKitJavaLoggerConfig</span><span class="op">]</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t187" href="#t187">187</a></span><span class="t">        <span class="str">"""Returns the Java logger configuration configured using `configure_java_logger`</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t188" href="#t188">188</a></span><span class="t"><span class="str">        method</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t189" href="#t189">189</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t190" href="#t190">190</a></span><span class="t"><span class="str">        Returns:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t191" href="#t191">191</a></span><span class="t"><span class="str">            Optional[_RuleKitJavaLoggerConfig]: Java logger configuration</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t192" href="#t192">192</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t193" href="#t193">193</a></span><span class="t">        <span class="key">return</span> <span class="nam">RuleKit</span><span class="op">.</span><span class="nam">_java_logger_config</span>&nbsp;</span><span class="r"></span></p>
 </main>
 <footer>
     <div class="content">
@@ -280,7 +282,7 @@ <h2>
             <a class="nav" href="z_a87f2a4bb6695d91_params_py.html">&#xbb; next</a>
             &nbsp; &nbsp; &nbsp;
             <a class="nav" href="https://coverage.readthedocs.io/en/7.6.4">coverage.py v7.6.4</a>,
-            created at 2024-11-08 14:43 +0100
+            created at 2024-11-28 11:55 +0100
         </p>
     </div>
 </footer>
diff --git a/docs/reports/coverage/z_a87f2a4bb6695d91_params_py.html b/docs/reports/coverage/z_a87f2a4bb6695d91_params_py.html
index 58302ff..4832639 100644
--- a/docs/reports/coverage/z_a87f2a4bb6695d91_params_py.html
+++ b/docs/reports/coverage/z_a87f2a4bb6695d91_params_py.html
@@ -2,7 +2,7 @@
 <html lang="en">
 <head>
     <meta http-equiv="Content-Type" content="text/html; charset=utf-8">
-    <title>Coverage for rulekit\params.py: 100%</title>
+    <title>Coverage for rulekit\params.py: 92%</title>
     <link rel="icon" sizes="32x32" href="favicon_32_cb_58284776.png">
     <link rel="stylesheet" href="style_cb_718ce007.css" type="text/css">
     <script src="coverage_html_cb_497bf287.js" defer></script>
@@ -12,7 +12,7 @@
     <div class="content">
         <h1>
             <span class="text">Coverage for </span><b>rulekit\params.py</b>:
-            <span class="pc_cov">100%</span>
+            <span class="pc_cov">92%</span>
         </h1>
         <aside id="help_panel_wrapper">
             <input id="help_panel_state" type="checkbox">
@@ -54,9 +54,9 @@ <h1>
             </div>
         </aside>
         <h2>
-            <span class="text">73 statements &nbsp;</span>
-            <button type="button" class="run button_toggle_run" value="run" data-shortcut="r" title="Toggle lines run">73<span class="text"> run</span></button>
-            <button type="button" class="mis show_mis button_toggle_mis" value="mis" data-shortcut="m" title="Toggle lines missing">0<span class="text"> missing</span></button>
+            <span class="text">88 statements &nbsp;</span>
+            <button type="button" class="run button_toggle_run" value="run" data-shortcut="r" title="Toggle lines run">81<span class="text"> run</span></button>
+            <button type="button" class="mis show_mis button_toggle_mis" value="mis" data-shortcut="m" title="Toggle lines missing">7<span class="text"> missing</span></button>
             <button type="button" class="exc show_exc button_toggle_exc" value="exc" data-shortcut="x" title="Toggle lines excluded">0<span class="text"> excluded</span></button>
         </h2>
         <p class="text">
@@ -65,7 +65,7 @@ <h2>
             <a id="nextFileLink" class="nav" href="z_a87f2a4bb6695d91_regression_py.html">&#xbb; next</a>
             &nbsp; &nbsp; &nbsp;
             <a class="nav" href="https://coverage.readthedocs.io/en/7.6.4">coverage.py v7.6.4</a>,
-            created at 2024-11-05 13:43 +0100
+            created at 2024-11-28 11:55 +0100
         </p>
         <aside class="hidden">
             <button type="button" class="button_next_chunk" data-shortcut="j"></button>
@@ -83,133 +83,161 @@ <h2>
     <p class="pln"><span class="n"><a id="t1" href="#t1">1</a></span><span class="t"><span class="str">"""Contains constants and classes for specyfing models parameters</span>&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t2" href="#t2">2</a></span><span class="t"><span class="str">"""</span>&nbsp;</span><span class="r"></span></p>
     <p class="run"><span class="n"><a id="t3" href="#t3">3</a></span><span class="t"><span class="key">from</span> <span class="nam">enum</span> <span class="key">import</span> <span class="nam">Enum</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t4" href="#t4">4</a></span><span class="t"><span class="key">from</span> <span class="nam">typing</span> <span class="key">import</span> <span class="nam">Optional</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t5" href="#t5">5</a></span><span class="t"><span class="key">from</span> <span class="nam">typing</span> <span class="key">import</span> <span class="nam">Tuple</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t6" href="#t6">6</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t7" href="#t7">7</a></span><span class="t"><span class="key">from</span> <span class="nam">pydantic</span> <span class="key">import</span> <span class="nam">BaseModel</span>  <span class="com"># pylint: disable=no-name-in-module</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t4" href="#t4">4</a></span><span class="t"><span class="key">from</span> <span class="nam">typing</span> <span class="key">import</span> <span class="nam">Callable</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t5" href="#t5">5</a></span><span class="t"><span class="key">from</span> <span class="nam">typing</span> <span class="key">import</span> <span class="nam">Optional</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t6" href="#t6">6</a></span><span class="t"><span class="key">from</span> <span class="nam">typing</span> <span class="key">import</span> <span class="nam">Tuple</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t7" href="#t7">7</a></span><span class="t"><span class="key">from</span> <span class="nam">typing</span> <span class="key">import</span> <span class="nam">Union</span>&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t8" href="#t8">8</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t9" href="#t9">9</a></span><span class="t"><span class="nam">MAX_INT</span><span class="op">:</span> <span class="nam">int</span> <span class="op">=</span> <span class="num">2147483647</span>  <span class="com"># max integer value in Java</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t10" href="#t10">10</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t11" href="#t11">11</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t12" href="#t12">12</a></span><span class="t"><span class="key">class</span> <span class="nam">Measures</span><span class="op">(</span><span class="nam">Enum</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t13" href="#t13">13</a></span><span class="t">    <span class="com"># pylint: disable=invalid-name</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t14" href="#t14">14</a></span><span class="t">    <span class="str">"""Enum for different measures used during induction, pruning and voting.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t9" href="#t9">9</a></span><span class="t"><span class="key">from</span> <span class="nam">jpype</span> <span class="key">import</span> <span class="nam">JImplements</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t10" href="#t10">10</a></span><span class="t"><span class="key">from</span> <span class="nam">jpype</span> <span class="key">import</span> <span class="nam">JOverride</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t11" href="#t11">11</a></span><span class="t"><span class="key">from</span> <span class="nam">jpype</span><span class="op">.</span><span class="nam">types</span> <span class="key">import</span> <span class="nam">JDouble</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t12" href="#t12">12</a></span><span class="t"><span class="key">from</span> <span class="nam">pydantic</span> <span class="key">import</span> <span class="nam">BaseModel</span>  <span class="com"># pylint: disable=no-name-in-module</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t13" href="#t13">13</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t14" href="#t14">14</a></span><span class="t"><span class="nam">MAX_INT</span><span class="op">:</span> <span class="nam">int</span> <span class="op">=</span> <span class="num">2147483647</span>  <span class="com"># max integer value in Java</span>&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t15" href="#t15">15</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t16" href="#t16">16</a></span><span class="t"><span class="str">    You can ream more about each measure and its implementation</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t17" href="#t17">17</a></span><span class="t"><span class="str">    #41-rule-quality>`_ .</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t18" href="#t18">18</a></span><span class="t"><span class="str">    `here &lt;https://github.com/adaa-polsl/RuleKit/wiki/4-Quality-and-evaluation</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t19" href="#t19">19</a></span><span class="t"><span class="str">    """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t20" href="#t20">20</a></span><span class="t">    <span class="nam">Accuracy</span> <span class="op">=</span> <span class="str">'Accuracy'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t21" href="#t21">21</a></span><span class="t">    <span class="nam">BinaryEntropy</span> <span class="op">=</span> <span class="str">'BinaryEntropy'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t22" href="#t22">22</a></span><span class="t">    <span class="nam">C1</span> <span class="op">=</span> <span class="str">'C1'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t23" href="#t23">23</a></span><span class="t">    <span class="nam">C2</span> <span class="op">=</span> <span class="str">'C2'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t24" href="#t24">24</a></span><span class="t">    <span class="nam">CFoil</span> <span class="op">=</span> <span class="str">'CFoil'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t25" href="#t25">25</a></span><span class="t">    <span class="nam">CN2Significnce</span> <span class="op">=</span> <span class="str">'CN2Significnce'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t26" href="#t26">26</a></span><span class="t">    <span class="nam">Correlation</span> <span class="op">=</span> <span class="str">'Correlation'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t27" href="#t27">27</a></span><span class="t">    <span class="nam">Coverage</span> <span class="op">=</span> <span class="str">'Coverage'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t28" href="#t28">28</a></span><span class="t">    <span class="nam">FBayesianConfirmation</span> <span class="op">=</span> <span class="str">'FBayesianConfirmation'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t29" href="#t29">29</a></span><span class="t">    <span class="nam">FMeasure</span> <span class="op">=</span> <span class="str">'FMeasure'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t30" href="#t30">30</a></span><span class="t">    <span class="nam">FullCoverage</span> <span class="op">=</span> <span class="str">'FullCoverage'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t31" href="#t31">31</a></span><span class="t">    <span class="nam">GeoRSS</span> <span class="op">=</span> <span class="str">'GeoRSS'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t32" href="#t32">32</a></span><span class="t">    <span class="nam">GMeasure</span> <span class="op">=</span> <span class="str">'GMeasure'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t33" href="#t33">33</a></span><span class="t">    <span class="nam">InformationGain</span> <span class="op">=</span> <span class="str">'InformationGain'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t34" href="#t34">34</a></span><span class="t">    <span class="nam">JMeasure</span> <span class="op">=</span> <span class="str">'JMeasure'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t35" href="#t35">35</a></span><span class="t">    <span class="nam">Kappa</span> <span class="op">=</span> <span class="str">'Kappa'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t36" href="#t36">36</a></span><span class="t">    <span class="nam">Klosgen</span> <span class="op">=</span> <span class="str">'Klosgen'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t37" href="#t37">37</a></span><span class="t">    <span class="nam">Laplace</span> <span class="op">=</span> <span class="str">'Laplace'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t38" href="#t38">38</a></span><span class="t">    <span class="nam">Lift</span> <span class="op">=</span> <span class="str">'Lift'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t39" href="#t39">39</a></span><span class="t">    <span class="nam">LogicalSufficiency</span> <span class="op">=</span> <span class="str">'LogicalSufficiency'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t40" href="#t40">40</a></span><span class="t">    <span class="nam">LogRank</span> <span class="op">=</span> <span class="str">'LogRank'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t41" href="#t41">41</a></span><span class="t">    <span class="nam">MEstimate</span> <span class="op">=</span> <span class="str">'MEstimate'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t42" href="#t42">42</a></span><span class="t">    <span class="nam">MutualSupport</span> <span class="op">=</span> <span class="str">'MutualSupport'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t43" href="#t43">43</a></span><span class="t">    <span class="nam">Novelty</span> <span class="op">=</span> <span class="str">'Novelty'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t44" href="#t44">44</a></span><span class="t">    <span class="nam">OddsRatio</span> <span class="op">=</span> <span class="str">'OddsRatio'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t45" href="#t45">45</a></span><span class="t">    <span class="nam">OneWaySupport</span> <span class="op">=</span> <span class="str">'OneWaySupport'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t46" href="#t46">46</a></span><span class="t">    <span class="nam">PawlakDependencyFactor</span> <span class="op">=</span> <span class="str">'PawlakDependencyFactor'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t47" href="#t47">47</a></span><span class="t">    <span class="nam">Precision</span> <span class="op">=</span> <span class="str">'Precision'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t48" href="#t48">48</a></span><span class="t">    <span class="nam">Q2</span> <span class="op">=</span> <span class="str">'Q2'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t49" href="#t49">49</a></span><span class="t">    <span class="nam">RelativeRisk</span> <span class="op">=</span> <span class="str">'RelativeRisk'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t50" href="#t50">50</a></span><span class="t">    <span class="nam">Ripper</span> <span class="op">=</span> <span class="str">'Ripper'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t51" href="#t51">51</a></span><span class="t">    <span class="nam">RSS</span> <span class="op">=</span> <span class="str">'RSS'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t52" href="#t52">52</a></span><span class="t">    <span class="nam">RuleInterest</span> <span class="op">=</span> <span class="str">'RuleInterest'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t53" href="#t53">53</a></span><span class="t">    <span class="nam">SBayesian</span> <span class="op">=</span> <span class="str">'SBayesian'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t54" href="#t54">54</a></span><span class="t">    <span class="nam">Sensitivity</span> <span class="op">=</span> <span class="str">'Sensitivity'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t55" href="#t55">55</a></span><span class="t">    <span class="nam">Specificity</span> <span class="op">=</span> <span class="str">'Specificity'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t56" href="#t56">56</a></span><span class="t">    <span class="nam">TwoWaySupport</span> <span class="op">=</span> <span class="str">'TwoWaySupport'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t57" href="#t57">57</a></span><span class="t">    <span class="nam">WeightedLaplace</span> <span class="op">=</span> <span class="str">'WeightedLaplace'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t58" href="#t58">58</a></span><span class="t">    <span class="nam">WeightedRelativeAccuracy</span> <span class="op">=</span> <span class="str">'WeightedRelativeAccuracy'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t59" href="#t59">59</a></span><span class="t">    <span class="nam">YAILS</span> <span class="op">=</span> <span class="str">'YAILS'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t60" href="#t60">60</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t61" href="#t61">61</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t62" href="#t62">62</a></span><span class="t"><span class="nam">DEFAULT_PARAMS_VALUE</span> <span class="op">=</span> <span class="op">{</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t63" href="#t63">63</a></span><span class="t">    <span class="str">'minsupp_new'</span><span class="op">:</span> <span class="num">0.05</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t64" href="#t64">64</a></span><span class="t">    <span class="str">'induction_measure'</span><span class="op">:</span> <span class="nam">Measures</span><span class="op">.</span><span class="nam">Correlation</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t65" href="#t65">65</a></span><span class="t">    <span class="str">'pruning_measure'</span><span class="op">:</span>  <span class="nam">Measures</span><span class="op">.</span><span class="nam">Correlation</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t66" href="#t66">66</a></span><span class="t">    <span class="str">'voting_measure'</span><span class="op">:</span> <span class="nam">Measures</span><span class="op">.</span><span class="nam">Correlation</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t67" href="#t67">67</a></span><span class="t">    <span class="str">'max_growing'</span><span class="op">:</span> <span class="num">0.0</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t68" href="#t68">68</a></span><span class="t">    <span class="str">'enable_pruning'</span><span class="op">:</span> <span class="key">True</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t69" href="#t69">69</a></span><span class="t">    <span class="str">'ignore_missing'</span><span class="op">:</span> <span class="key">False</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t70" href="#t70">70</a></span><span class="t">    <span class="str">'max_uncovered_fraction'</span><span class="op">:</span> <span class="num">0.0</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t71" href="#t71">71</a></span><span class="t">    <span class="str">'select_best_candidate'</span><span class="op">:</span> <span class="key">False</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t72" href="#t72">72</a></span><span class="t">    <span class="str">'complementary_conditions'</span><span class="op">:</span> <span class="key">False</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t73" href="#t73">73</a></span><span class="t">    <span class="str">'control_apriori_precision'</span><span class="op">:</span> <span class="key">True</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t74" href="#t74">74</a></span><span class="t">    <span class="str">'max_rule_count'</span><span class="op">:</span> <span class="num">0</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t75" href="#t75">75</a></span><span class="t">    <span class="str">'approximate_induction'</span><span class="op">:</span> <span class="key">False</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t76" href="#t76">76</a></span><span class="t">    <span class="str">'approximate_bins_count'</span><span class="op">:</span> <span class="num">100</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t77" href="#t77">77</a></span><span class="t">    <span class="str">'mean_based_regression'</span><span class="op">:</span> <span class="key">True</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t78" href="#t78">78</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t79" href="#t79">79</a></span><span class="t">    <span class="str">'extend_using_preferred'</span><span class="op">:</span> <span class="key">False</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t80" href="#t80">80</a></span><span class="t">    <span class="str">'extend_using_automatic'</span><span class="op">:</span> <span class="key">False</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t81" href="#t81">81</a></span><span class="t">    <span class="str">'induce_using_preferred'</span><span class="op">:</span> <span class="key">False</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t82" href="#t82">82</a></span><span class="t">    <span class="str">'induce_using_automatic'</span><span class="op">:</span> <span class="key">False</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t83" href="#t83">83</a></span><span class="t">    <span class="str">'consider_other_classes'</span><span class="op">:</span> <span class="key">False</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t84" href="#t84">84</a></span><span class="t">    <span class="str">'preferred_conditions_per_rule'</span><span class="op">:</span> <span class="nam">MAX_INT</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t85" href="#t85">85</a></span><span class="t">    <span class="str">'preferred_attributes_per_rule'</span><span class="op">:</span> <span class="nam">MAX_INT</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t86" href="#t86">86</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t87" href="#t87">87</a></span><span class="t">    <span class="com"># Contrast sets</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t88" href="#t88">88</a></span><span class="t">    <span class="str">'minsupp_all'</span><span class="op">:</span> <span class="op">(</span><span class="num">0.8</span><span class="op">,</span> <span class="num">0.5</span><span class="op">,</span> <span class="num">0.2</span><span class="op">,</span> <span class="num">0.1</span><span class="op">)</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t89" href="#t89">89</a></span><span class="t">    <span class="str">'max_neg2pos'</span><span class="op">:</span> <span class="num">0.5</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t90" href="#t90">90</a></span><span class="t">    <span class="str">'max_passes_count'</span><span class="op">:</span> <span class="num">5</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t91" href="#t91">91</a></span><span class="t">    <span class="str">'penalty_strength'</span><span class="op">:</span> <span class="num">0.5</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t92" href="#t92">92</a></span><span class="t">    <span class="str">'penalty_saturation'</span><span class="op">:</span> <span class="num">0.2</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t93" href="#t93">93</a></span><span class="t"><span class="op">}</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t94" href="#t94">94</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t95" href="#t95">95</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t96" href="#t96">96</a></span><span class="t"><span class="key">class</span> <span class="nam">ModelsParams</span><span class="op">(</span><span class="nam">BaseModel</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t97" href="#t97">97</a></span><span class="t">    <span class="str">"""Model for validating models hyperparameters</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t98" href="#t98">98</a></span><span class="t"><span class="str">    """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t99" href="#t99">99</a></span><span class="t">    <span class="nam">minsupp_new</span><span class="op">:</span> <span class="nam">Optional</span><span class="op">[</span><span class="nam">float</span><span class="op">]</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'minsupp_new'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t100" href="#t100">100</a></span><span class="t">    <span class="nam">induction_measure</span><span class="op">:</span> <span class="nam">Optional</span><span class="op">[</span><span class="nam">Measures</span><span class="op">]</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'induction_measure'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t101" href="#t101">101</a></span><span class="t">    <span class="nam">pruning_measure</span><span class="op">:</span> <span class="nam">Optional</span><span class="op">[</span><span class="nam">Measures</span><span class="op">]</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'pruning_measure'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t102" href="#t102">102</a></span><span class="t">    <span class="nam">voting_measure</span><span class="op">:</span> <span class="nam">Optional</span><span class="op">[</span><span class="nam">Measures</span><span class="op">]</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'voting_measure'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t103" href="#t103">103</a></span><span class="t">    <span class="nam">max_growing</span><span class="op">:</span> <span class="nam">Optional</span><span class="op">[</span><span class="nam">float</span><span class="op">]</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'max_growing'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t104" href="#t104">104</a></span><span class="t">    <span class="nam">enable_pruning</span><span class="op">:</span> <span class="nam">Optional</span><span class="op">[</span><span class="nam">bool</span><span class="op">]</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'enable_pruning'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t105" href="#t105">105</a></span><span class="t">    <span class="nam">ignore_missing</span><span class="op">:</span> <span class="nam">Optional</span><span class="op">[</span><span class="nam">bool</span><span class="op">]</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'ignore_missing'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t106" href="#t106">106</a></span><span class="t">    <span class="nam">max_uncovered_fraction</span><span class="op">:</span> <span class="nam">Optional</span><span class="op">[</span><span class="nam">float</span><span class="op">]</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'max_uncovered_fraction'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t107" href="#t107">107</a></span><span class="t">    <span class="nam">select_best_candidate</span><span class="op">:</span> <span class="nam">Optional</span><span class="op">[</span><span class="nam">bool</span><span class="op">]</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'select_best_candidate'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t108" href="#t108">108</a></span><span class="t">    <span class="nam">complementary_conditions</span><span class="op">:</span> <span class="nam">Optional</span><span class="op">[</span><span class="nam">bool</span><span class="op">]</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'complementary_conditions'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t109" href="#t109">109</a></span><span class="t">    <span class="nam">max_rule_count</span><span class="op">:</span> <span class="nam">int</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'max_rule_count'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t110" href="#t110">110</a></span><span class="t">    <span class="nam">minsupp_all</span><span class="op">:</span> <span class="nam">Tuple</span><span class="op">[</span><span class="nam">float</span><span class="op">,</span> <span class="nam">float</span><span class="op">,</span> <span class="nam">float</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t111" href="#t111">111</a></span><span class="t">                       <span class="nam">float</span><span class="op">]</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'minsupp_all'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t112" href="#t112">112</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t113" href="#t113">113</a></span><span class="t">    <span class="nam">extend_using_preferred</span><span class="op">:</span> <span class="nam">Optional</span><span class="op">[</span><span class="nam">bool</span><span class="op">]</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'extend_using_preferred'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t114" href="#t114">114</a></span><span class="t">    <span class="nam">extend_using_automatic</span><span class="op">:</span> <span class="nam">Optional</span><span class="op">[</span><span class="nam">bool</span><span class="op">]</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'extend_using_automatic'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t115" href="#t115">115</a></span><span class="t">    <span class="nam">induce_using_preferred</span><span class="op">:</span> <span class="nam">Optional</span><span class="op">[</span><span class="nam">bool</span><span class="op">]</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'induce_using_preferred'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t116" href="#t116">116</a></span><span class="t">    <span class="nam">induce_using_automatic</span><span class="op">:</span> <span class="nam">Optional</span><span class="op">[</span><span class="nam">bool</span><span class="op">]</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'induce_using_automatic'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t117" href="#t117">117</a></span><span class="t">    <span class="nam">consider_other_classes</span><span class="op">:</span> <span class="nam">Optional</span><span class="op">[</span><span class="nam">bool</span><span class="op">]</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'consider_other_classes'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t118" href="#t118">118</a></span><span class="t">    <span class="nam">preferred_conditions_per_rule</span><span class="op">:</span> <span class="nam">Optional</span><span class="op">[</span><span class="nam">int</span><span class="op">]</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'preferred_conditions_per_rule'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t119" href="#t119">119</a></span><span class="t">    <span class="nam">preferred_attributes_per_rule</span><span class="op">:</span> <span class="nam">Optional</span><span class="op">[</span><span class="nam">int</span><span class="op">]</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'preferred_attributes_per_rule'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t16" href="#t16">16</a></span><span class="t"><span class="nam">_UserDefinedMeasure</span> <span class="op">=</span> <span class="nam">Callable</span><span class="op">[</span><span class="op">[</span><span class="nam">float</span><span class="op">,</span> <span class="nam">float</span><span class="op">,</span> <span class="nam">float</span><span class="op">,</span> <span class="nam">float</span><span class="op">]</span><span class="op">,</span> <span class="nam">float</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t17" href="#t17">17</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t18" href="#t18">18</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t19" href="#t19">19</a></span><span class="t"><span class="key">def</span> <span class="nam">_user_defined_measure_factory</span><span class="op">(</span><span class="nam">measure_function</span><span class="op">:</span> <span class="nam">_UserDefinedMeasure</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t20" href="#t20">20</a></span><span class="t">    <span class="key">from</span> <span class="nam">adaa</span><span class="op">.</span><span class="nam">analytics</span><span class="op">.</span><span class="nam">rules</span><span class="op">.</span><span class="nam">logic</span><span class="op">.</span><span class="nam">quality</span> <span class="key">import</span> <span class="xx">\</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t21" href="#t21">21</a></span><span class="t">        <span class="nam">IUserMeasure</span>  <span class="com"># pylint: disable=import-outside-toplevel,import-error</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t22" href="#t22">22</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t23" href="#t23">23</a></span><span class="t">    <span class="op">@</span><span class="nam">JImplements</span><span class="op">(</span><span class="nam">IUserMeasure</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t24" href="#t24">24</a></span><span class="t">    <span class="key">class</span> <span class="nam">_UserMeasure</span><span class="op">:</span>  <span class="com"># pylint: disable=invalid-name,missing-function-docstring</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t25" href="#t25">25</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t26" href="#t26">26</a></span><span class="t">        <span class="op">@</span><span class="nam">JOverride</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t27" href="#t27">27</a></span><span class="t">        <span class="key">def</span> <span class="nam">getResult</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">p</span><span class="op">:</span> <span class="nam">JDouble</span><span class="op">,</span> <span class="nam">n</span><span class="op">:</span> <span class="nam">JDouble</span><span class="op">,</span> <span class="nam">P</span><span class="op">:</span> <span class="nam">JDouble</span><span class="op">,</span> <span class="nam">N</span><span class="op">:</span> <span class="nam">JDouble</span><span class="op">)</span> <span class="op">-></span> <span class="nam">float</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t28" href="#t28">28</a></span><span class="t">            <span class="key">return</span> <span class="nam">measure_function</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t29" href="#t29">29</a></span><span class="t">                <span class="nam">float</span><span class="op">(</span><span class="nam">p</span><span class="op">)</span><span class="op">,</span> <span class="nam">float</span><span class="op">(</span><span class="nam">n</span><span class="op">)</span><span class="op">,</span> <span class="nam">float</span><span class="op">(</span><span class="nam">P</span><span class="op">)</span><span class="op">,</span> <span class="nam">float</span><span class="op">(</span><span class="nam">N</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t30" href="#t30">30</a></span><span class="t">            <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t31" href="#t31">31</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t32" href="#t32">32</a></span><span class="t">    <span class="key">return</span> <span class="nam">_UserMeasure</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t33" href="#t33">33</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t34" href="#t34">34</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t35" href="#t35">35</a></span><span class="t"><span class="key">class</span> <span class="nam">Measures</span><span class="op">(</span><span class="nam">Enum</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t36" href="#t36">36</a></span><span class="t">    <span class="com"># pylint: disable=invalid-name</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t37" href="#t37">37</a></span><span class="t">    <span class="str">"""Enum for different measures used during induction, pruning and voting.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t38" href="#t38">38</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t39" href="#t39">39</a></span><span class="t"><span class="str">    You can ream more about each measure and its implementation</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t40" href="#t40">40</a></span><span class="t"><span class="str">    #41-rule-quality>`_ .</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t41" href="#t41">41</a></span><span class="t"><span class="str">    `here &lt;https://github.com/adaa-polsl/RuleKit/wiki/4-Quality-and-evaluation</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t42" href="#t42">42</a></span><span class="t"><span class="str">    """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t43" href="#t43">43</a></span><span class="t">    <span class="nam">Accuracy</span> <span class="op">=</span> <span class="str">'Accuracy'</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t44" href="#t44">44</a></span><span class="t">    <span class="nam">BinaryEntropy</span> <span class="op">=</span> <span class="str">'BinaryEntropy'</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t45" href="#t45">45</a></span><span class="t">    <span class="nam">C1</span> <span class="op">=</span> <span class="str">'C1'</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t46" href="#t46">46</a></span><span class="t">    <span class="nam">C2</span> <span class="op">=</span> <span class="str">'C2'</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t47" href="#t47">47</a></span><span class="t">    <span class="nam">CFoil</span> <span class="op">=</span> <span class="str">'CFoil'</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t48" href="#t48">48</a></span><span class="t">    <span class="nam">CN2Significnce</span> <span class="op">=</span> <span class="str">'CN2Significnce'</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t49" href="#t49">49</a></span><span class="t">    <span class="nam">Correlation</span> <span class="op">=</span> <span class="str">'Correlation'</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t50" href="#t50">50</a></span><span class="t">    <span class="nam">Coverage</span> <span class="op">=</span> <span class="str">'Coverage'</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t51" href="#t51">51</a></span><span class="t">    <span class="nam">FBayesianConfirmation</span> <span class="op">=</span> <span class="str">'FBayesianConfirmation'</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t52" href="#t52">52</a></span><span class="t">    <span class="nam">FMeasure</span> <span class="op">=</span> <span class="str">'FMeasure'</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t53" href="#t53">53</a></span><span class="t">    <span class="nam">FullCoverage</span> <span class="op">=</span> <span class="str">'FullCoverage'</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t54" href="#t54">54</a></span><span class="t">    <span class="nam">GeoRSS</span> <span class="op">=</span> <span class="str">'GeoRSS'</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t55" href="#t55">55</a></span><span class="t">    <span class="nam">GMeasure</span> <span class="op">=</span> <span class="str">'GMeasure'</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t56" href="#t56">56</a></span><span class="t">    <span class="nam">InformationGain</span> <span class="op">=</span> <span class="str">'InformationGain'</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t57" href="#t57">57</a></span><span class="t">    <span class="nam">JMeasure</span> <span class="op">=</span> <span class="str">'JMeasure'</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t58" href="#t58">58</a></span><span class="t">    <span class="nam">Kappa</span> <span class="op">=</span> <span class="str">'Kappa'</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t59" href="#t59">59</a></span><span class="t">    <span class="nam">Klosgen</span> <span class="op">=</span> <span class="str">'Klosgen'</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t60" href="#t60">60</a></span><span class="t">    <span class="nam">Laplace</span> <span class="op">=</span> <span class="str">'Laplace'</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t61" href="#t61">61</a></span><span class="t">    <span class="nam">Lift</span> <span class="op">=</span> <span class="str">'Lift'</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t62" href="#t62">62</a></span><span class="t">    <span class="nam">LogicalSufficiency</span> <span class="op">=</span> <span class="str">'LogicalSufficiency'</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t63" href="#t63">63</a></span><span class="t">    <span class="nam">LogRank</span> <span class="op">=</span> <span class="str">'LogRank'</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t64" href="#t64">64</a></span><span class="t">    <span class="nam">MEstimate</span> <span class="op">=</span> <span class="str">'MEstimate'</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t65" href="#t65">65</a></span><span class="t">    <span class="nam">MutualSupport</span> <span class="op">=</span> <span class="str">'MutualSupport'</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t66" href="#t66">66</a></span><span class="t">    <span class="nam">Novelty</span> <span class="op">=</span> <span class="str">'Novelty'</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t67" href="#t67">67</a></span><span class="t">    <span class="nam">OddsRatio</span> <span class="op">=</span> <span class="str">'OddsRatio'</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t68" href="#t68">68</a></span><span class="t">    <span class="nam">OneWaySupport</span> <span class="op">=</span> <span class="str">'OneWaySupport'</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t69" href="#t69">69</a></span><span class="t">    <span class="nam">PawlakDependencyFactor</span> <span class="op">=</span> <span class="str">'PawlakDependencyFactor'</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t70" href="#t70">70</a></span><span class="t">    <span class="nam">Precision</span> <span class="op">=</span> <span class="str">'Precision'</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t71" href="#t71">71</a></span><span class="t">    <span class="nam">Q2</span> <span class="op">=</span> <span class="str">'Q2'</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t72" href="#t72">72</a></span><span class="t">    <span class="nam">RelativeRisk</span> <span class="op">=</span> <span class="str">'RelativeRisk'</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t73" href="#t73">73</a></span><span class="t">    <span class="nam">Ripper</span> <span class="op">=</span> <span class="str">'Ripper'</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t74" href="#t74">74</a></span><span class="t">    <span class="nam">RSS</span> <span class="op">=</span> <span class="str">'RSS'</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t75" href="#t75">75</a></span><span class="t">    <span class="nam">RuleInterest</span> <span class="op">=</span> <span class="str">'RuleInterest'</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t76" href="#t76">76</a></span><span class="t">    <span class="nam">SBayesian</span> <span class="op">=</span> <span class="str">'SBayesian'</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t77" href="#t77">77</a></span><span class="t">    <span class="nam">Sensitivity</span> <span class="op">=</span> <span class="str">'Sensitivity'</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t78" href="#t78">78</a></span><span class="t">    <span class="nam">Specificity</span> <span class="op">=</span> <span class="str">'Specificity'</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t79" href="#t79">79</a></span><span class="t">    <span class="nam">TwoWaySupport</span> <span class="op">=</span> <span class="str">'TwoWaySupport'</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t80" href="#t80">80</a></span><span class="t">    <span class="nam">WeightedLaplace</span> <span class="op">=</span> <span class="str">'WeightedLaplace'</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t81" href="#t81">81</a></span><span class="t">    <span class="nam">WeightedRelativeAccuracy</span> <span class="op">=</span> <span class="str">'WeightedRelativeAccuracy'</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t82" href="#t82">82</a></span><span class="t">    <span class="nam">YAILS</span> <span class="op">=</span> <span class="str">'YAILS'</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t83" href="#t83">83</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t84" href="#t84">84</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t85" href="#t85">85</a></span><span class="t"><span class="nam">DEFAULT_PARAMS_VALUE</span> <span class="op">=</span> <span class="op">{</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t86" href="#t86">86</a></span><span class="t">    <span class="str">'minsupp_new'</span><span class="op">:</span> <span class="num">0.05</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t87" href="#t87">87</a></span><span class="t">    <span class="str">'induction_measure'</span><span class="op">:</span> <span class="nam">Measures</span><span class="op">.</span><span class="nam">Correlation</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t88" href="#t88">88</a></span><span class="t">    <span class="str">'pruning_measure'</span><span class="op">:</span>  <span class="nam">Measures</span><span class="op">.</span><span class="nam">Correlation</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t89" href="#t89">89</a></span><span class="t">    <span class="str">'voting_measure'</span><span class="op">:</span> <span class="nam">Measures</span><span class="op">.</span><span class="nam">Correlation</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t90" href="#t90">90</a></span><span class="t">    <span class="str">'max_growing'</span><span class="op">:</span> <span class="num">0.0</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t91" href="#t91">91</a></span><span class="t">    <span class="str">'enable_pruning'</span><span class="op">:</span> <span class="key">True</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t92" href="#t92">92</a></span><span class="t">    <span class="str">'ignore_missing'</span><span class="op">:</span> <span class="key">False</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t93" href="#t93">93</a></span><span class="t">    <span class="str">'max_uncovered_fraction'</span><span class="op">:</span> <span class="num">0.0</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t94" href="#t94">94</a></span><span class="t">    <span class="str">'select_best_candidate'</span><span class="op">:</span> <span class="key">False</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t95" href="#t95">95</a></span><span class="t">    <span class="str">'complementary_conditions'</span><span class="op">:</span> <span class="key">False</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t96" href="#t96">96</a></span><span class="t">    <span class="str">'control_apriori_precision'</span><span class="op">:</span> <span class="key">True</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t97" href="#t97">97</a></span><span class="t">    <span class="str">'max_rule_count'</span><span class="op">:</span> <span class="num">0</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t98" href="#t98">98</a></span><span class="t">    <span class="str">'approximate_induction'</span><span class="op">:</span> <span class="key">False</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t99" href="#t99">99</a></span><span class="t">    <span class="str">'approximate_bins_count'</span><span class="op">:</span> <span class="num">100</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t100" href="#t100">100</a></span><span class="t">    <span class="str">'mean_based_regression'</span><span class="op">:</span> <span class="key">True</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t101" href="#t101">101</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t102" href="#t102">102</a></span><span class="t">    <span class="str">'extend_using_preferred'</span><span class="op">:</span> <span class="key">False</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t103" href="#t103">103</a></span><span class="t">    <span class="str">'extend_using_automatic'</span><span class="op">:</span> <span class="key">False</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t104" href="#t104">104</a></span><span class="t">    <span class="str">'induce_using_preferred'</span><span class="op">:</span> <span class="key">False</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t105" href="#t105">105</a></span><span class="t">    <span class="str">'induce_using_automatic'</span><span class="op">:</span> <span class="key">False</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t106" href="#t106">106</a></span><span class="t">    <span class="str">'consider_other_classes'</span><span class="op">:</span> <span class="key">False</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t107" href="#t107">107</a></span><span class="t">    <span class="str">'preferred_conditions_per_rule'</span><span class="op">:</span> <span class="nam">MAX_INT</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t108" href="#t108">108</a></span><span class="t">    <span class="str">'preferred_attributes_per_rule'</span><span class="op">:</span> <span class="nam">MAX_INT</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t109" href="#t109">109</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t110" href="#t110">110</a></span><span class="t">    <span class="com"># Contrast sets</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t111" href="#t111">111</a></span><span class="t">    <span class="str">'minsupp_all'</span><span class="op">:</span> <span class="op">(</span><span class="num">0.8</span><span class="op">,</span> <span class="num">0.5</span><span class="op">,</span> <span class="num">0.2</span><span class="op">,</span> <span class="num">0.1</span><span class="op">)</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t112" href="#t112">112</a></span><span class="t">    <span class="str">'max_neg2pos'</span><span class="op">:</span> <span class="num">0.5</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t113" href="#t113">113</a></span><span class="t">    <span class="str">'max_passes_count'</span><span class="op">:</span> <span class="num">5</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t114" href="#t114">114</a></span><span class="t">    <span class="str">'penalty_strength'</span><span class="op">:</span> <span class="num">0.5</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t115" href="#t115">115</a></span><span class="t">    <span class="str">'penalty_saturation'</span><span class="op">:</span> <span class="num">0.2</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t116" href="#t116">116</a></span><span class="t"><span class="op">}</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t117" href="#t117">117</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t118" href="#t118">118</a></span><span class="t"><span class="nam">_QualityMeasure</span> <span class="op">=</span> <span class="nam">Union</span><span class="op">[</span><span class="nam">Measures</span><span class="op">,</span> <span class="nam">_UserDefinedMeasure</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t119" href="#t119">119</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t120" href="#t120">120</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t121" href="#t121">121</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t122" href="#t122">122</a></span><span class="t"><span class="key">class</span> <span class="nam">ContrastSetModelParams</span><span class="op">(</span><span class="nam">ModelsParams</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t123" href="#t123">123</a></span><span class="t">    <span class="str">"""Model for validating contrast set models hyperparameters</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t124" href="#t124">124</a></span><span class="t"><span class="str">    """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t125" href="#t125">125</a></span><span class="t">    <span class="nam">minsupp_all</span><span class="op">:</span> <span class="nam">Tuple</span><span class="op">[</span><span class="nam">float</span><span class="op">,</span> <span class="nam">float</span><span class="op">,</span> <span class="nam">float</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t126" href="#t126">126</a></span><span class="t">                       <span class="nam">float</span><span class="op">]</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'minsupp_all'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t127" href="#t127">127</a></span><span class="t">    <span class="nam">max_neg2pos</span><span class="op">:</span> <span class="nam">Optional</span><span class="op">[</span><span class="nam">float</span><span class="op">]</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'max_neg2pos'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t128" href="#t128">128</a></span><span class="t">    <span class="nam">max_passes_count</span><span class="op">:</span> <span class="nam">Optional</span><span class="op">[</span><span class="nam">int</span><span class="op">]</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'max_passes_count'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t129" href="#t129">129</a></span><span class="t">    <span class="nam">penalty_strength</span><span class="op">:</span> <span class="nam">Optional</span><span class="op">[</span><span class="nam">float</span><span class="op">]</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'penalty_strength'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t130" href="#t130">130</a></span><span class="t">    <span class="nam">penalty_saturation</span><span class="op">:</span> <span class="nam">Optional</span><span class="op">[</span><span class="nam">float</span><span class="op">]</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'penalty_saturation'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t121" href="#t121">121</a></span><span class="t"><span class="key">class</span> <span class="nam">ModelsParams</span><span class="op">(</span><span class="nam">BaseModel</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t122" href="#t122">122</a></span><span class="t">    <span class="str">"""Model for validating models hyperparameters</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t123" href="#t123">123</a></span><span class="t"><span class="str">    """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t124" href="#t124">124</a></span><span class="t">    <span class="nam">minsupp_new</span><span class="op">:</span> <span class="nam">Optional</span><span class="op">[</span><span class="nam">float</span><span class="op">]</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'minsupp_new'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t125" href="#t125">125</a></span><span class="t">    <span class="nam">induction_measure</span><span class="op">:</span> <span class="nam">Optional</span><span class="op">[</span><span class="nam">_QualityMeasure</span><span class="op">]</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'induction_measure'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t126" href="#t126">126</a></span><span class="t">    <span class="nam">pruning_measure</span><span class="op">:</span> <span class="nam">Optional</span><span class="op">[</span><span class="nam">_QualityMeasure</span><span class="op">]</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'pruning_measure'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t127" href="#t127">127</a></span><span class="t">    <span class="nam">voting_measure</span><span class="op">:</span> <span class="nam">Optional</span><span class="op">[</span><span class="nam">_QualityMeasure</span><span class="op">]</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'voting_measure'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t128" href="#t128">128</a></span><span class="t">    <span class="nam">max_growing</span><span class="op">:</span> <span class="nam">Optional</span><span class="op">[</span><span class="nam">float</span><span class="op">]</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'max_growing'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t129" href="#t129">129</a></span><span class="t">    <span class="nam">enable_pruning</span><span class="op">:</span> <span class="nam">Optional</span><span class="op">[</span><span class="nam">bool</span><span class="op">]</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'enable_pruning'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t130" href="#t130">130</a></span><span class="t">    <span class="nam">ignore_missing</span><span class="op">:</span> <span class="nam">Optional</span><span class="op">[</span><span class="nam">bool</span><span class="op">]</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'ignore_missing'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t131" href="#t131">131</a></span><span class="t">    <span class="nam">max_uncovered_fraction</span><span class="op">:</span> <span class="nam">Optional</span><span class="op">[</span><span class="nam">float</span><span class="op">]</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'max_uncovered_fraction'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t132" href="#t132">132</a></span><span class="t">    <span class="nam">select_best_candidate</span><span class="op">:</span> <span class="nam">Optional</span><span class="op">[</span><span class="nam">bool</span><span class="op">]</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'select_best_candidate'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t133" href="#t133">133</a></span><span class="t">    <span class="nam">complementary_conditions</span><span class="op">:</span> <span class="nam">Optional</span><span class="op">[</span><span class="nam">bool</span><span class="op">]</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'complementary_conditions'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t134" href="#t134">134</a></span><span class="t">    <span class="nam">max_rule_count</span><span class="op">:</span> <span class="nam">int</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'max_rule_count'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t135" href="#t135">135</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t136" href="#t136">136</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t137" href="#t137">137</a></span><span class="t"><span class="key">class</span> <span class="nam">ExpertModelParams</span><span class="op">(</span><span class="nam">ModelsParams</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t138" href="#t138">138</a></span><span class="t">    <span class="str">"""Model for validating expert models hyperparameters</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t139" href="#t139">139</a></span><span class="t"><span class="str">    """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t140" href="#t140">140</a></span><span class="t">    <span class="nam">extend_using_preferred</span><span class="op">:</span> <span class="nam">Optional</span><span class="op">[</span><span class="nam">bool</span><span class="op">]</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'extend_using_preferred'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t141" href="#t141">141</a></span><span class="t">    <span class="nam">extend_using_automatic</span><span class="op">:</span> <span class="nam">Optional</span><span class="op">[</span><span class="nam">bool</span><span class="op">]</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'extend_using_automatic'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t142" href="#t142">142</a></span><span class="t">    <span class="nam">induce_using_preferred</span><span class="op">:</span> <span class="nam">Optional</span><span class="op">[</span><span class="nam">bool</span><span class="op">]</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'induce_using_preferred'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t143" href="#t143">143</a></span><span class="t">    <span class="nam">induce_using_automatic</span><span class="op">:</span> <span class="nam">Optional</span><span class="op">[</span><span class="nam">bool</span><span class="op">]</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'induce_using_automatic'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t144" href="#t144">144</a></span><span class="t">    <span class="nam">consider_other_classes</span><span class="op">:</span> <span class="nam">Optional</span><span class="op">[</span><span class="nam">bool</span><span class="op">]</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'consider_other_classes'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t145" href="#t145">145</a></span><span class="t">    <span class="nam">preferred_conditions_per_rule</span><span class="op">:</span> <span class="nam">Optional</span><span class="op">[</span><span class="nam">int</span><span class="op">]</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'preferred_conditions_per_rule'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t146" href="#t146">146</a></span><span class="t">    <span class="nam">preferred_attributes_per_rule</span><span class="op">:</span> <span class="nam">Optional</span><span class="op">[</span><span class="nam">int</span><span class="op">]</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'preferred_attributes_per_rule'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t147" href="#t147">147</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t148" href="#t148">148</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t149" href="#t149">149</a></span><span class="t"><span class="key">class</span> <span class="nam">ContrastSetModelParams</span><span class="op">(</span><span class="nam">ModelsParams</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t150" href="#t150">150</a></span><span class="t">    <span class="str">"""Model for validating contrast set models hyperparameters</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t151" href="#t151">151</a></span><span class="t"><span class="str">    """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t152" href="#t152">152</a></span><span class="t">    <span class="nam">minsupp_all</span><span class="op">:</span> <span class="nam">Tuple</span><span class="op">[</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t153" href="#t153">153</a></span><span class="t">        <span class="nam">float</span><span class="op">,</span> <span class="nam">float</span><span class="op">,</span> <span class="nam">float</span><span class="op">,</span> <span class="nam">float</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t154" href="#t154">154</a></span><span class="t">    <span class="op">]</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'minsupp_all'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t155" href="#t155">155</a></span><span class="t">    <span class="nam">max_neg2pos</span><span class="op">:</span> <span class="nam">Optional</span><span class="op">[</span><span class="nam">float</span><span class="op">]</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'max_neg2pos'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t156" href="#t156">156</a></span><span class="t">    <span class="nam">max_passes_count</span><span class="op">:</span> <span class="nam">Optional</span><span class="op">[</span><span class="nam">int</span><span class="op">]</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'max_passes_count'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t157" href="#t157">157</a></span><span class="t">    <span class="nam">penalty_strength</span><span class="op">:</span> <span class="nam">Optional</span><span class="op">[</span><span class="nam">float</span><span class="op">]</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'penalty_strength'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t158" href="#t158">158</a></span><span class="t">    <span class="nam">penalty_saturation</span><span class="op">:</span> <span class="nam">Optional</span><span class="op">[</span><span class="nam">float</span><span class="op">]</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'penalty_saturation'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
 </main>
 <footer>
     <div class="content">
@@ -219,7 +247,7 @@ <h2>
             <a class="nav" href="z_a87f2a4bb6695d91_regression_py.html">&#xbb; next</a>
             &nbsp; &nbsp; &nbsp;
             <a class="nav" href="https://coverage.readthedocs.io/en/7.6.4">coverage.py v7.6.4</a>,
-            created at 2024-11-05 13:43 +0100
+            created at 2024-11-28 11:55 +0100
         </p>
     </div>
 </footer>
diff --git a/docs/reports/coverage/z_a87f2a4bb6695d91_regression_py.html b/docs/reports/coverage/z_a87f2a4bb6695d91_regression_py.html
index 22a6b9f..1ceccfd 100644
--- a/docs/reports/coverage/z_a87f2a4bb6695d91_regression_py.html
+++ b/docs/reports/coverage/z_a87f2a4bb6695d91_regression_py.html
@@ -2,7 +2,7 @@
 <html lang="en">
 <head>
     <meta http-equiv="Content-Type" content="text/html; charset=utf-8">
-    <title>Coverage for rulekit\regression.py: 78%</title>
+    <title>Coverage for rulekit\regression.py: 80%</title>
     <link rel="icon" sizes="32x32" href="favicon_32_cb_58284776.png">
     <link rel="stylesheet" href="style_cb_718ce007.css" type="text/css">
     <script src="coverage_html_cb_497bf287.js" defer></script>
@@ -12,7 +12,7 @@
     <div class="content">
         <h1>
             <span class="text">Coverage for </span><b>rulekit\regression.py</b>:
-            <span class="pc_cov">78%</span>
+            <span class="pc_cov">80%</span>
         </h1>
         <aside id="help_panel_wrapper">
             <input id="help_panel_state" type="checkbox">
@@ -54,8 +54,8 @@ <h1>
             </div>
         </aside>
         <h2>
-            <span class="text">72 statements &nbsp;</span>
-            <button type="button" class="run button_toggle_run" value="run" data-shortcut="r" title="Toggle lines run">56<span class="text"> run</span></button>
+            <span class="text">82 statements &nbsp;</span>
+            <button type="button" class="run button_toggle_run" value="run" data-shortcut="r" title="Toggle lines run">66<span class="text"> run</span></button>
             <button type="button" class="mis show_mis button_toggle_mis" value="mis" data-shortcut="m" title="Toggle lines missing">16<span class="text"> missing</span></button>
             <button type="button" class="exc show_exc button_toggle_exc" value="exc" data-shortcut="x" title="Toggle lines excluded">0<span class="text"> excluded</span></button>
         </h2>
@@ -65,7 +65,7 @@ <h2>
             <a id="nextFileLink" class="nav" href="z_a87f2a4bb6695d91_rules_py.html">&#xbb; next</a>
             &nbsp; &nbsp; &nbsp;
             <a class="nav" href="https://coverage.readthedocs.io/en/7.6.4">coverage.py v7.6.4</a>,
-            created at 2024-11-08 14:43 +0100
+            created at 2024-11-28 11:55 +0100
         </p>
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@@ -85,512 +85,523 @@ <h2>
     <p class="run"><span class="n"><a id="t3" href="#t3">3</a></span><span class="t"><span class="key">from</span> <span class="nam">__future__</span> <span class="key">import</span> <span class="nam">annotations</span>&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t4" href="#t4">4</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
     <p class="run"><span class="n"><a id="t5" href="#t5">5</a></span><span class="t"><span class="key">from</span> <span class="nam">numbers</span> <span class="key">import</span> <span class="nam">Number</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t6" href="#t6">6</a></span><span class="t"><span class="key">from</span> <span class="nam">typing</span> <span class="key">import</span> <span class="nam">Tuple</span><span class="op">,</span> <span class="nam">Union</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t7" href="#t7">7</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t8" href="#t8">8</a></span><span class="t"><span class="key">import</span> <span class="nam">numpy</span> <span class="key">as</span> <span class="nam">np</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t9" href="#t9">9</a></span><span class="t"><span class="key">import</span> <span class="nam">pandas</span> <span class="key">as</span> <span class="nam">pd</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t10" href="#t10">10</a></span><span class="t"><span class="key">from</span> <span class="nam">sklearn</span> <span class="key">import</span> <span class="nam">metrics</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t11" href="#t11">11</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t12" href="#t12">12</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">_helpers</span> <span class="key">import</span> <span class="nam">PredictionResultMapper</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t13" href="#t13">13</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">_operator</span> <span class="key">import</span> <span class="nam">BaseOperator</span><span class="op">,</span> <span class="nam">Data</span><span class="op">,</span> <span class="nam">ExpertKnowledgeOperator</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t14" href="#t14">14</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">_problem_types</span> <span class="key">import</span> <span class="nam">ProblemType</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t15" href="#t15">15</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">params</span> <span class="key">import</span> <span class="op">(</span><span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">,</span> <span class="nam">ContrastSetModelParams</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t16" href="#t16">16</a></span><span class="t">                            <span class="nam">Measures</span><span class="op">,</span> <span class="nam">ModelsParams</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t17" href="#t17">17</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">rules</span> <span class="key">import</span> <span class="nam">RegressionRule</span><span class="op">,</span> <span class="nam">RuleSet</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t18" href="#t18">18</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t19" href="#t19">19</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t20" href="#t20">20</a></span><span class="t"><span class="key">class</span> <span class="nam">_RegressionParams</span><span class="op">(</span><span class="nam">ModelsParams</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t21" href="#t21">21</a></span><span class="t">    <span class="nam">mean_based_regression</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'mean_based_regression'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t22" href="#t22">22</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t23" href="#t23">23</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t24" href="#t24">24</a></span><span class="t"><span class="key">class</span> <span class="nam">RuleRegressor</span><span class="op">(</span><span class="nam">BaseOperator</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t25" href="#t25">25</a></span><span class="t">    <span class="str">"""Regression model."""</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t6" href="#t6">6</a></span><span class="t"><span class="key">from</span> <span class="nam">typing</span> <span class="key">import</span> <span class="nam">Tuple</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t7" href="#t7">7</a></span><span class="t"><span class="key">from</span> <span class="nam">typing</span> <span class="key">import</span> <span class="nam">Union</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t8" href="#t8">8</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t9" href="#t9">9</a></span><span class="t"><span class="key">import</span> <span class="nam">numpy</span> <span class="key">as</span> <span class="nam">np</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t10" href="#t10">10</a></span><span class="t"><span class="key">import</span> <span class="nam">pandas</span> <span class="key">as</span> <span class="nam">pd</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t11" href="#t11">11</a></span><span class="t"><span class="key">from</span> <span class="nam">sklearn</span> <span class="key">import</span> <span class="nam">metrics</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t12" href="#t12">12</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t13" href="#t13">13</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">_helpers</span> <span class="key">import</span> <span class="nam">PredictionResultMapper</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t14" href="#t14">14</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">_operator</span> <span class="key">import</span> <span class="nam">BaseOperator</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t15" href="#t15">15</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">_operator</span> <span class="key">import</span> <span class="nam">Data</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t16" href="#t16">16</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">_operator</span> <span class="key">import</span> <span class="nam">ExpertKnowledgeOperator</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t17" href="#t17">17</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">_problem_types</span> <span class="key">import</span> <span class="nam">ProblemType</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t18" href="#t18">18</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">params</span> <span class="key">import</span> <span class="nam">ContrastSetModelParams</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t19" href="#t19">19</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">params</span> <span class="key">import</span> <span class="nam">DEFAULT_PARAMS_VALUE</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t20" href="#t20">20</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">params</span> <span class="key">import</span> <span class="nam">ExpertModelParams</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t21" href="#t21">21</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">params</span> <span class="key">import</span> <span class="nam">Measures</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t22" href="#t22">22</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">params</span> <span class="key">import</span> <span class="nam">ModelsParams</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t23" href="#t23">23</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">rules</span> <span class="key">import</span> <span class="nam">RegressionRule</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t24" href="#t24">24</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">rules</span> <span class="key">import</span> <span class="nam">RuleSet</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t25" href="#t25">25</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t26" href="#t26">26</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t27" href="#t27">27</a></span><span class="t">    <span class="nam">__params_class__</span> <span class="op">=</span> <span class="nam">_RegressionParams</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t28" href="#t28">28</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t29" href="#t29">29</a></span><span class="t">    <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span>  <span class="com"># pylint: disable=too-many-arguments</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t30" href="#t30">30</a></span><span class="t">        <span class="nam">self</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t31" href="#t31">31</a></span><span class="t">        <span class="nam">minsupp_new</span><span class="op">:</span> <span class="nam">float</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'minsupp_new'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t32" href="#t32">32</a></span><span class="t">        <span class="nam">induction_measure</span><span class="op">:</span> <span class="nam">Measures</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'induction_measure'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t33" href="#t33">33</a></span><span class="t">        <span class="nam">pruning_measure</span><span class="op">:</span> <span class="nam">Union</span><span class="op">[</span><span class="nam">Measures</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t34" href="#t34">34</a></span><span class="t">                               <span class="nam">str</span><span class="op">]</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'pruning_measure'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t35" href="#t35">35</a></span><span class="t">        <span class="nam">voting_measure</span><span class="op">:</span> <span class="nam">Measures</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'voting_measure'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t36" href="#t36">36</a></span><span class="t">        <span class="nam">max_growing</span><span class="op">:</span> <span class="nam">float</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'max_growing'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t37" href="#t37">37</a></span><span class="t">        <span class="nam">enable_pruning</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'enable_pruning'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t38" href="#t38">38</a></span><span class="t">        <span class="nam">ignore_missing</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'ignore_missing'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t39" href="#t39">39</a></span><span class="t">        <span class="nam">max_uncovered_fraction</span><span class="op">:</span> <span class="nam">float</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'max_uncovered_fraction'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t40" href="#t40">40</a></span><span class="t">        <span class="nam">select_best_candidate</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'select_best_candidate'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t41" href="#t41">41</a></span><span class="t">        <span class="nam">complementary_conditions</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'complementary_conditions'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t42" href="#t42">42</a></span><span class="t">        <span class="nam">mean_based_regression</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'mean_based_regression'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t43" href="#t43">43</a></span><span class="t">        <span class="nam">max_rule_count</span><span class="op">:</span> <span class="nam">int</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'max_rule_count'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t44" href="#t44">44</a></span><span class="t">    <span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t45" href="#t45">45</a></span><span class="t">        <span class="str">"""</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t46" href="#t46">46</a></span><span class="t"><span class="str">        Parameters</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t47" href="#t47">47</a></span><span class="t"><span class="str">        ----------</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t48" href="#t48">48</a></span><span class="t"><span class="str">        minsupp_new : float = 5.0</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t49" href="#t49">49</a></span><span class="t"><span class="str">            a minimum number (or fraction, if value &lt; 1.0) of previously uncovered examples</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t50" href="#t50">50</a></span><span class="t"><span class="str">             to be covered by a new rule (positive examples for classification problems); default: 5,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t51" href="#t51">51</a></span><span class="t"><span class="str">        induction_measure : :class:`rulekit.params.Measures` = \</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t52" href="#t52">52</a></span><span class="t"><span class="str">            :class:`rulekit.params.Measures.Correlation`</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t53" href="#t53">53</a></span><span class="t"><span class="str">            measure used during induction; default measure is correlation</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t54" href="#t54">54</a></span><span class="t"><span class="str">        pruning_measure : Union[:class:`rulekit.params.Measures`, str] = \</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t55" href="#t55">55</a></span><span class="t"><span class="str">            :class:`rulekit.params.Measures.Correlation`</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t56" href="#t56">56</a></span><span class="t"><span class="str">            measure used during pruning. Could be user defined (string), for example</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t57" href="#t57">57</a></span><span class="t"><span class="str">             :code:`2 * p / n`; default measure is correlation</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t58" href="#t58">58</a></span><span class="t"><span class="str">        voting_measure : :class:`rulekit.params.Measures` = \</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t59" href="#t59">59</a></span><span class="t"><span class="str">            :class:`rulekit.params.Measures.Correlation`</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t60" href="#t60">60</a></span><span class="t"><span class="str">            measure used during voting; default measure is correlation</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t61" href="#t61">61</a></span><span class="t"><span class="str">        max_growing : int = 0.0</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t62" href="#t62">62</a></span><span class="t"><span class="str">            non-negative integer representing maximum number of conditions which can be added to</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t63" href="#t63">63</a></span><span class="t"><span class="str">            the rule in the growing phase (use this parameter for large datasets if execution time</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t64" href="#t64">64</a></span><span class="t"><span class="str">            is prohibitive); 0 indicates no limit; default: 0,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t65" href="#t65">65</a></span><span class="t"><span class="str">        enable_pruning : bool = True</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t66" href="#t66">66</a></span><span class="t"><span class="str">            enable or disable pruning, default is True.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t67" href="#t67">67</a></span><span class="t"><span class="str">        ignore_missing : bool = False</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t68" href="#t68">68</a></span><span class="t"><span class="str">            boolean telling whether missing values should be ignored (by default, a missing value</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t69" href="#t69">69</a></span><span class="t"><span class="str">            of given attribute is always considered as not fulfilling the condition build upon that</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t70" href="#t70">70</a></span><span class="t"><span class="str">            attribute); default: False.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t71" href="#t71">71</a></span><span class="t"><span class="str">        max_uncovered_fraction : float = 0.0</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t72" href="#t72">72</a></span><span class="t"><span class="str">            Floating-point number from [0,1] interval representing maximum fraction of examples</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t73" href="#t73">73</a></span><span class="t"><span class="str">             that may remain uncovered by the rule set, default: 0.0.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t74" href="#t74">74</a></span><span class="t"><span class="str">        select_best_candidate : bool = False</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t75" href="#t75">75</a></span><span class="t"><span class="str">            Flag determining if best candidate should be selected from growing phase;</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t76" href="#t76">76</a></span><span class="t"><span class="str">             default: False.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t77" href="#t77">77</a></span><span class="t"><span class="str">        complementary_conditions : bool = False</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t78" href="#t78">78</a></span><span class="t"><span class="str">            If enabled, complementary conditions in the form a = !{value} for nominal attributes</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t79" href="#t79">79</a></span><span class="t"><span class="str">            are supported.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t80" href="#t80">80</a></span><span class="t"><span class="str">        mean_based_regression : bool = True</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t81" href="#t81">81</a></span><span class="t"><span class="str">            Enable fast induction of mean-based regression rules instead of default median-based.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t82" href="#t82">82</a></span><span class="t"><span class="str">        max_rule_count : int = 0</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t83" href="#t83">83</a></span><span class="t"><span class="str">            Maximum number of rules to be generated (for classification data sets it applies</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t84" href="#t84">84</a></span><span class="t"><span class="str">             to a single class); 0 indicates no limit.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t85" href="#t85">85</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t86" href="#t86">86</a></span><span class="t">        <span class="nam">super</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">__init__</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t87" href="#t87">87</a></span><span class="t">            <span class="nam">minsupp_new</span><span class="op">=</span><span class="nam">minsupp_new</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t88" href="#t88">88</a></span><span class="t">            <span class="nam">induction_measure</span><span class="op">=</span><span class="nam">induction_measure</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t89" href="#t89">89</a></span><span class="t">            <span class="nam">pruning_measure</span><span class="op">=</span><span class="nam">pruning_measure</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t90" href="#t90">90</a></span><span class="t">            <span class="nam">voting_measure</span><span class="op">=</span><span class="nam">voting_measure</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t91" href="#t91">91</a></span><span class="t">            <span class="nam">max_growing</span><span class="op">=</span><span class="nam">max_growing</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t92" href="#t92">92</a></span><span class="t">            <span class="nam">enable_pruning</span><span class="op">=</span><span class="nam">enable_pruning</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t93" href="#t93">93</a></span><span class="t">            <span class="nam">ignore_missing</span><span class="op">=</span><span class="nam">ignore_missing</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t94" href="#t94">94</a></span><span class="t">            <span class="nam">max_uncovered_fraction</span><span class="op">=</span><span class="nam">max_uncovered_fraction</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t95" href="#t95">95</a></span><span class="t">            <span class="nam">select_best_candidate</span><span class="op">=</span><span class="nam">select_best_candidate</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t96" href="#t96">96</a></span><span class="t">            <span class="nam">complementary_conditions</span><span class="op">=</span><span class="nam">complementary_conditions</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t97" href="#t97">97</a></span><span class="t">            <span class="nam">mean_based_regression</span><span class="op">=</span><span class="nam">mean_based_regression</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t98" href="#t98">98</a></span><span class="t">            <span class="nam">max_rule_count</span><span class="op">=</span><span class="nam">max_rule_count</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t99" href="#t99">99</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t100" href="#t100">100</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">model</span><span class="op">:</span> <span class="nam">RuleSet</span><span class="op">[</span><span class="nam">RegressionRule</span><span class="op">]</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t101" href="#t101">101</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t102" href="#t102">102</a></span><span class="t">    <span class="key">def</span> <span class="nam">_validate_labels</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">labels</span><span class="op">:</span> <span class="nam">Data</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t103" href="#t103">103</a></span><span class="t">        <span class="key">if</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">labels</span><span class="op">,</span> <span class="op">(</span><span class="nam">pd</span><span class="op">.</span><span class="nam">DataFrame</span><span class="op">,</span> <span class="nam">pd</span><span class="op">.</span><span class="nam">Series</span><span class="op">)</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t104" href="#t104">104</a></span><span class="t">            <span class="nam">first_label</span> <span class="op">=</span> <span class="nam">labels</span><span class="op">.</span><span class="nam">iloc</span><span class="op">[</span><span class="num">0</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t105" href="#t105">105</a></span><span class="t">        <span class="key">else</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t106" href="#t106">106</a></span><span class="t">            <span class="nam">first_label</span> <span class="op">=</span> <span class="nam">labels</span><span class="op">[</span><span class="num">0</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t107" href="#t107">107</a></span><span class="t">        <span class="key">if</span> <span class="key">not</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">first_label</span><span class="op">,</span> <span class="nam">Number</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t108" href="#t108">108</a></span><span class="t">            <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t109" href="#t109">109</a></span><span class="t">                <span class="str">f'{self.__class__.__name__} requires lables values to be numeric'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t110" href="#t110">110</a></span><span class="t">            <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t111" href="#t111">111</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t112" href="#t112">112</a></span><span class="t">    <span class="key">def</span> <span class="nam">fit</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">values</span><span class="op">:</span> <span class="nam">Data</span><span class="op">,</span> <span class="nam">labels</span><span class="op">:</span> <span class="nam">Data</span><span class="op">)</span> <span class="op">-></span> <span class="nam">RuleRegressor</span><span class="op">:</span>  <span class="com"># pylint: disable=arguments-differ</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t113" href="#t113">113</a></span><span class="t">        <span class="str">"""Train model on given dataset.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t114" href="#t114">114</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t115" href="#t115">115</a></span><span class="t"><span class="str">        Parameters</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t116" href="#t116">116</a></span><span class="t"><span class="str">        ----------</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t117" href="#t117">117</a></span><span class="t"><span class="str">        values : :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t118" href="#t118">118</a></span><span class="t"><span class="str">            attributes</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t119" href="#t119">119</a></span><span class="t"><span class="str">        labels : :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t120" href="#t120">120</a></span><span class="t"><span class="str">            target values</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t121" href="#t121">121</a></span><span class="t"><span class="str">        Returns</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t122" href="#t122">122</a></span><span class="t"><span class="str">        -------</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t123" href="#t123">123</a></span><span class="t"><span class="str">        self : RuleRegressor</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t124" href="#t124">124</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t125" href="#t125">125</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_validate_labels</span><span class="op">(</span><span class="nam">labels</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t126" href="#t126">126</a></span><span class="t">        <span class="nam">super</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">fit</span><span class="op">(</span><span class="nam">values</span><span class="op">,</span> <span class="nam">labels</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t127" href="#t127">127</a></span><span class="t">        <span class="key">return</span> <span class="nam">self</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t128" href="#t128">128</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t129" href="#t129">129</a></span><span class="t">    <span class="key">def</span> <span class="nam">predict</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">values</span><span class="op">:</span> <span class="nam">Data</span><span class="op">)</span> <span class="op">-></span> <span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t130" href="#t130">130</a></span><span class="t">        <span class="str">"""Perform prediction and returns predicted values.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t131" href="#t131">131</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t132" href="#t132">132</a></span><span class="t"><span class="str">        Parameters</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t133" href="#t133">133</a></span><span class="t"><span class="str">        ----------</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t134" href="#t134">134</a></span><span class="t"><span class="str">        values : :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t135" href="#t135">135</a></span><span class="t"><span class="str">            attributes</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t136" href="#t136">136</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t137" href="#t137">137</a></span><span class="t"><span class="str">        Returns</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t138" href="#t138">138</a></span><span class="t"><span class="str">        -------</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t139" href="#t139">139</a></span><span class="t"><span class="str">        result : np.ndarray</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t140" href="#t140">140</a></span><span class="t"><span class="str">            predicted values</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t141" href="#t141">141</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t142" href="#t142">142</a></span><span class="t">        <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_map_result</span><span class="op">(</span><span class="nam">super</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">predict</span><span class="op">(</span><span class="nam">values</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t143" href="#t143">143</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t144" href="#t144">144</a></span><span class="t">    <span class="key">def</span> <span class="nam">score</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">values</span><span class="op">:</span> <span class="nam">Data</span><span class="op">,</span> <span class="nam">labels</span><span class="op">:</span> <span class="nam">Data</span><span class="op">)</span> <span class="op">-></span> <span class="nam">float</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t145" href="#t145">145</a></span><span class="t">        <span class="str">"""Return the coefficient of determination R2 of the prediction</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t146" href="#t146">146</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t147" href="#t147">147</a></span><span class="t"><span class="str">        Parameters</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t148" href="#t148">148</a></span><span class="t"><span class="str">        ----------</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t149" href="#t149">149</a></span><span class="t"><span class="str">        values : :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t150" href="#t150">150</a></span><span class="t"><span class="str">            attributes</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t151" href="#t151">151</a></span><span class="t"><span class="str">        labels : :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t152" href="#t152">152</a></span><span class="t"><span class="str">            true target values</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t153" href="#t153">153</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t154" href="#t154">154</a></span><span class="t"><span class="str">        Returns</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t155" href="#t155">155</a></span><span class="t"><span class="str">        -------</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t156" href="#t156">156</a></span><span class="t"><span class="str">        score : float</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t157" href="#t157">157</a></span><span class="t"><span class="str">            R2 of self.predict(values) wrt. labels.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t158" href="#t158">158</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t159" href="#t159">159</a></span><span class="t">        <span class="nam">predicted_labels</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">predict</span><span class="op">(</span><span class="nam">values</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t160" href="#t160">160</a></span><span class="t">        <span class="key">return</span> <span class="nam">metrics</span><span class="op">.</span><span class="nam">r2_score</span><span class="op">(</span><span class="nam">labels</span><span class="op">,</span> <span class="nam">predicted_labels</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t161" href="#t161">161</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t162" href="#t162">162</a></span><span class="t">    <span class="key">def</span> <span class="nam">_map_result</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">predicted_example_set</span><span class="op">)</span> <span class="op">-></span> <span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t163" href="#t163">163</a></span><span class="t">        <span class="key">return</span> <span class="nam">PredictionResultMapper</span><span class="op">.</span><span class="nam">map_to_numerical</span><span class="op">(</span><span class="nam">predicted_example_set</span><span class="op">,</span> <span class="nam">remap</span><span class="op">=</span><span class="key">False</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t27" href="#t27">27</a></span><span class="t"><span class="key">class</span> <span class="nam">_RegressionModelParams</span><span class="op">(</span><span class="nam">ModelsParams</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t28" href="#t28">28</a></span><span class="t">    <span class="nam">mean_based_regression</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'mean_based_regression'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t29" href="#t29">29</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t30" href="#t30">30</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t31" href="#t31">31</a></span><span class="t"><span class="key">class</span> <span class="nam">_RegressionExpertModelParams</span><span class="op">(</span><span class="nam">_RegressionModelParams</span><span class="op">,</span> <span class="nam">ExpertModelParams</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t32" href="#t32">32</a></span><span class="t">    <span class="key">pass</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t33" href="#t33">33</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t34" href="#t34">34</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t35" href="#t35">35</a></span><span class="t"><span class="key">class</span> <span class="nam">RuleRegressor</span><span class="op">(</span><span class="nam">BaseOperator</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t36" href="#t36">36</a></span><span class="t">    <span class="str">"""Regression model."""</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t37" href="#t37">37</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t38" href="#t38">38</a></span><span class="t">    <span class="nam">__params_class__</span> <span class="op">=</span> <span class="nam">_RegressionModelParams</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t39" href="#t39">39</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t40" href="#t40">40</a></span><span class="t">    <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span>  <span class="com"># pylint: disable=too-many-arguments</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t41" href="#t41">41</a></span><span class="t">        <span class="nam">self</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t42" href="#t42">42</a></span><span class="t">        <span class="nam">minsupp_new</span><span class="op">:</span> <span class="nam">float</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'minsupp_new'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t43" href="#t43">43</a></span><span class="t">        <span class="nam">induction_measure</span><span class="op">:</span> <span class="nam">Measures</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'induction_measure'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t44" href="#t44">44</a></span><span class="t">        <span class="nam">pruning_measure</span><span class="op">:</span> <span class="nam">Union</span><span class="op">[</span><span class="nam">Measures</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t45" href="#t45">45</a></span><span class="t">                               <span class="nam">str</span><span class="op">]</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'pruning_measure'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t46" href="#t46">46</a></span><span class="t">        <span class="nam">voting_measure</span><span class="op">:</span> <span class="nam">Measures</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'voting_measure'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t47" href="#t47">47</a></span><span class="t">        <span class="nam">max_growing</span><span class="op">:</span> <span class="nam">float</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'max_growing'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t48" href="#t48">48</a></span><span class="t">        <span class="nam">enable_pruning</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'enable_pruning'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t49" href="#t49">49</a></span><span class="t">        <span class="nam">ignore_missing</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'ignore_missing'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t50" href="#t50">50</a></span><span class="t">        <span class="nam">max_uncovered_fraction</span><span class="op">:</span> <span class="nam">float</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'max_uncovered_fraction'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t51" href="#t51">51</a></span><span class="t">        <span class="nam">select_best_candidate</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'select_best_candidate'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t52" href="#t52">52</a></span><span class="t">        <span class="nam">complementary_conditions</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'complementary_conditions'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t53" href="#t53">53</a></span><span class="t">        <span class="nam">mean_based_regression</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'mean_based_regression'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t54" href="#t54">54</a></span><span class="t">        <span class="nam">max_rule_count</span><span class="op">:</span> <span class="nam">int</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'max_rule_count'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t55" href="#t55">55</a></span><span class="t">    <span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t56" href="#t56">56</a></span><span class="t">        <span class="str">"""</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t57" href="#t57">57</a></span><span class="t"><span class="str">        Parameters</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t58" href="#t58">58</a></span><span class="t"><span class="str">        ----------</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t59" href="#t59">59</a></span><span class="t"><span class="str">        minsupp_new : float = 5.0</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t60" href="#t60">60</a></span><span class="t"><span class="str">            a minimum number (or fraction, if value &lt; 1.0) of previously uncovered examples</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t61" href="#t61">61</a></span><span class="t"><span class="str">             to be covered by a new rule (positive examples for classification problems); default: 5,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t62" href="#t62">62</a></span><span class="t"><span class="str">        induction_measure : :class:`rulekit.params.Measures` = \</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t63" href="#t63">63</a></span><span class="t"><span class="str">            :class:`rulekit.params.Measures.Correlation`</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t64" href="#t64">64</a></span><span class="t"><span class="str">            measure used during induction; default measure is correlation</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t65" href="#t65">65</a></span><span class="t"><span class="str">        pruning_measure : Union[:class:`rulekit.params.Measures`, str] = \</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t66" href="#t66">66</a></span><span class="t"><span class="str">            :class:`rulekit.params.Measures.Correlation`</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t67" href="#t67">67</a></span><span class="t"><span class="str">            measure used during pruning. Could be user defined (string), for example</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t68" href="#t68">68</a></span><span class="t"><span class="str">             :code:`2 * p / n`; default measure is correlation</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t69" href="#t69">69</a></span><span class="t"><span class="str">        voting_measure : :class:`rulekit.params.Measures` = \</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t70" href="#t70">70</a></span><span class="t"><span class="str">            :class:`rulekit.params.Measures.Correlation`</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t71" href="#t71">71</a></span><span class="t"><span class="str">            measure used during voting; default measure is correlation</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t72" href="#t72">72</a></span><span class="t"><span class="str">        max_growing : int = 0.0</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t73" href="#t73">73</a></span><span class="t"><span class="str">            non-negative integer representing maximum number of conditions which can be added to</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t74" href="#t74">74</a></span><span class="t"><span class="str">            the rule in the growing phase (use this parameter for large datasets if execution time</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t75" href="#t75">75</a></span><span class="t"><span class="str">            is prohibitive); 0 indicates no limit; default: 0,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t76" href="#t76">76</a></span><span class="t"><span class="str">        enable_pruning : bool = True</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t77" href="#t77">77</a></span><span class="t"><span class="str">            enable or disable pruning, default is True.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t78" href="#t78">78</a></span><span class="t"><span class="str">        ignore_missing : bool = False</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t79" href="#t79">79</a></span><span class="t"><span class="str">            boolean telling whether missing values should be ignored (by default, a missing value</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t80" href="#t80">80</a></span><span class="t"><span class="str">            of given attribute is always considered as not fulfilling the condition build upon that</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t81" href="#t81">81</a></span><span class="t"><span class="str">            attribute); default: False.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t82" href="#t82">82</a></span><span class="t"><span class="str">        max_uncovered_fraction : float = 0.0</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t83" href="#t83">83</a></span><span class="t"><span class="str">            Floating-point number from [0,1] interval representing maximum fraction of examples</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t84" href="#t84">84</a></span><span class="t"><span class="str">             that may remain uncovered by the rule set, default: 0.0.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t85" href="#t85">85</a></span><span class="t"><span class="str">        select_best_candidate : bool = False</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t86" href="#t86">86</a></span><span class="t"><span class="str">            Flag determining if best candidate should be selected from growing phase;</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t87" href="#t87">87</a></span><span class="t"><span class="str">             default: False.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t88" href="#t88">88</a></span><span class="t"><span class="str">        complementary_conditions : bool = False</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t89" href="#t89">89</a></span><span class="t"><span class="str">            If enabled, complementary conditions in the form a = !{value} for nominal attributes</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t90" href="#t90">90</a></span><span class="t"><span class="str">            are supported.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t91" href="#t91">91</a></span><span class="t"><span class="str">        mean_based_regression : bool = True</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t92" href="#t92">92</a></span><span class="t"><span class="str">            Enable fast induction of mean-based regression rules instead of default median-based.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t93" href="#t93">93</a></span><span class="t"><span class="str">        max_rule_count : int = 0</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t94" href="#t94">94</a></span><span class="t"><span class="str">            Maximum number of rules to be generated (for classification data sets it applies</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t95" href="#t95">95</a></span><span class="t"><span class="str">             to a single class); 0 indicates no limit.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t96" href="#t96">96</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t97" href="#t97">97</a></span><span class="t">        <span class="nam">super</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">__init__</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t98" href="#t98">98</a></span><span class="t">            <span class="nam">minsupp_new</span><span class="op">=</span><span class="nam">minsupp_new</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t99" href="#t99">99</a></span><span class="t">            <span class="nam">induction_measure</span><span class="op">=</span><span class="nam">induction_measure</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t100" href="#t100">100</a></span><span class="t">            <span class="nam">pruning_measure</span><span class="op">=</span><span class="nam">pruning_measure</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t101" href="#t101">101</a></span><span class="t">            <span class="nam">voting_measure</span><span class="op">=</span><span class="nam">voting_measure</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t102" href="#t102">102</a></span><span class="t">            <span class="nam">max_growing</span><span class="op">=</span><span class="nam">max_growing</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t103" href="#t103">103</a></span><span class="t">            <span class="nam">enable_pruning</span><span class="op">=</span><span class="nam">enable_pruning</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t104" href="#t104">104</a></span><span class="t">            <span class="nam">ignore_missing</span><span class="op">=</span><span class="nam">ignore_missing</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t105" href="#t105">105</a></span><span class="t">            <span class="nam">max_uncovered_fraction</span><span class="op">=</span><span class="nam">max_uncovered_fraction</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t106" href="#t106">106</a></span><span class="t">            <span class="nam">select_best_candidate</span><span class="op">=</span><span class="nam">select_best_candidate</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t107" href="#t107">107</a></span><span class="t">            <span class="nam">complementary_conditions</span><span class="op">=</span><span class="nam">complementary_conditions</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t108" href="#t108">108</a></span><span class="t">            <span class="nam">mean_based_regression</span><span class="op">=</span><span class="nam">mean_based_regression</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t109" href="#t109">109</a></span><span class="t">            <span class="nam">max_rule_count</span><span class="op">=</span><span class="nam">max_rule_count</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t110" href="#t110">110</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t111" href="#t111">111</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">model</span><span class="op">:</span> <span class="nam">RuleSet</span><span class="op">[</span><span class="nam">RegressionRule</span><span class="op">]</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t112" href="#t112">112</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t113" href="#t113">113</a></span><span class="t">    <span class="key">def</span> <span class="nam">_validate_labels</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">labels</span><span class="op">:</span> <span class="nam">Data</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t114" href="#t114">114</a></span><span class="t">        <span class="key">if</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">labels</span><span class="op">,</span> <span class="op">(</span><span class="nam">pd</span><span class="op">.</span><span class="nam">DataFrame</span><span class="op">,</span> <span class="nam">pd</span><span class="op">.</span><span class="nam">Series</span><span class="op">)</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t115" href="#t115">115</a></span><span class="t">            <span class="nam">first_label</span> <span class="op">=</span> <span class="nam">labels</span><span class="op">.</span><span class="nam">iloc</span><span class="op">[</span><span class="num">0</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t116" href="#t116">116</a></span><span class="t">        <span class="key">else</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t117" href="#t117">117</a></span><span class="t">            <span class="nam">first_label</span> <span class="op">=</span> <span class="nam">labels</span><span class="op">[</span><span class="num">0</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t118" href="#t118">118</a></span><span class="t">        <span class="key">if</span> <span class="key">not</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">first_label</span><span class="op">,</span> <span class="nam">Number</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t119" href="#t119">119</a></span><span class="t">            <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t120" href="#t120">120</a></span><span class="t">                <span class="str">f'{self.__class__.__name__} requires lables values to be numeric'</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t121" href="#t121">121</a></span><span class="t">            <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t122" href="#t122">122</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t123" href="#t123">123</a></span><span class="t">    <span class="key">def</span> <span class="nam">fit</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">values</span><span class="op">:</span> <span class="nam">Data</span><span class="op">,</span> <span class="nam">labels</span><span class="op">:</span> <span class="nam">Data</span><span class="op">)</span> <span class="op">-></span> <span class="nam">RuleRegressor</span><span class="op">:</span>  <span class="com"># pylint: disable=arguments-differ</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t124" href="#t124">124</a></span><span class="t">        <span class="str">"""Train model on given dataset.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t125" href="#t125">125</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t126" href="#t126">126</a></span><span class="t"><span class="str">        Parameters</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t127" href="#t127">127</a></span><span class="t"><span class="str">        ----------</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t128" href="#t128">128</a></span><span class="t"><span class="str">        values : :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t129" href="#t129">129</a></span><span class="t"><span class="str">            attributes</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t130" href="#t130">130</a></span><span class="t"><span class="str">        labels : :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t131" href="#t131">131</a></span><span class="t"><span class="str">            target values</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t132" href="#t132">132</a></span><span class="t"><span class="str">        Returns</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t133" href="#t133">133</a></span><span class="t"><span class="str">        -------</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t134" href="#t134">134</a></span><span class="t"><span class="str">        self : RuleRegressor</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t135" href="#t135">135</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t136" href="#t136">136</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_validate_labels</span><span class="op">(</span><span class="nam">labels</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t137" href="#t137">137</a></span><span class="t">        <span class="nam">super</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">fit</span><span class="op">(</span><span class="nam">values</span><span class="op">,</span> <span class="nam">labels</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t138" href="#t138">138</a></span><span class="t">        <span class="key">return</span> <span class="nam">self</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t139" href="#t139">139</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t140" href="#t140">140</a></span><span class="t">    <span class="key">def</span> <span class="nam">predict</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">values</span><span class="op">:</span> <span class="nam">Data</span><span class="op">)</span> <span class="op">-></span> <span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t141" href="#t141">141</a></span><span class="t">        <span class="str">"""Perform prediction and returns predicted values.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t142" href="#t142">142</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t143" href="#t143">143</a></span><span class="t"><span class="str">        Parameters</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t144" href="#t144">144</a></span><span class="t"><span class="str">        ----------</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t145" href="#t145">145</a></span><span class="t"><span class="str">        values : :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t146" href="#t146">146</a></span><span class="t"><span class="str">            attributes</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t147" href="#t147">147</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t148" href="#t148">148</a></span><span class="t"><span class="str">        Returns</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t149" href="#t149">149</a></span><span class="t"><span class="str">        -------</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t150" href="#t150">150</a></span><span class="t"><span class="str">        result : np.ndarray</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t151" href="#t151">151</a></span><span class="t"><span class="str">            predicted values</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t152" href="#t152">152</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t153" href="#t153">153</a></span><span class="t">        <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_map_result</span><span class="op">(</span><span class="nam">super</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">predict</span><span class="op">(</span><span class="nam">values</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t154" href="#t154">154</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t155" href="#t155">155</a></span><span class="t">    <span class="key">def</span> <span class="nam">score</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">values</span><span class="op">:</span> <span class="nam">Data</span><span class="op">,</span> <span class="nam">labels</span><span class="op">:</span> <span class="nam">Data</span><span class="op">)</span> <span class="op">-></span> <span class="nam">float</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t156" href="#t156">156</a></span><span class="t">        <span class="str">"""Return the coefficient of determination R2 of the prediction</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t157" href="#t157">157</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t158" href="#t158">158</a></span><span class="t"><span class="str">        Parameters</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t159" href="#t159">159</a></span><span class="t"><span class="str">        ----------</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t160" href="#t160">160</a></span><span class="t"><span class="str">        values : :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t161" href="#t161">161</a></span><span class="t"><span class="str">            attributes</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t162" href="#t162">162</a></span><span class="t"><span class="str">        labels : :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t163" href="#t163">163</a></span><span class="t"><span class="str">            true target values</span>&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t164" href="#t164">164</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t165" href="#t165">165</a></span><span class="t">    <span class="key">def</span> <span class="nam">_get_problem_type</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">ProblemType</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t166" href="#t166">166</a></span><span class="t">        <span class="key">return</span> <span class="nam">ProblemType</span><span class="op">.</span><span class="nam">REGRESSION</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t167" href="#t167">167</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t168" href="#t168">168</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t169" href="#t169">169</a></span><span class="t"><span class="key">class</span> <span class="nam">ExpertRuleRegressor</span><span class="op">(</span><span class="nam">ExpertKnowledgeOperator</span><span class="op">,</span> <span class="nam">RuleRegressor</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t170" href="#t170">170</a></span><span class="t">    <span class="str">"""Expert Regression model."""</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t171" href="#t171">171</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t172" href="#t172">172</a></span><span class="t">    <span class="nam">__params_class__</span> <span class="op">=</span> <span class="nam">_RegressionParams</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t173" href="#t173">173</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t174" href="#t174">174</a></span><span class="t">    <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span>   <span class="com"># pylint: disable=too-many-arguments,too-many-locals</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t175" href="#t175">175</a></span><span class="t">        <span class="nam">self</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t176" href="#t176">176</a></span><span class="t">        <span class="nam">minsupp_new</span><span class="op">:</span> <span class="nam">float</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'minsupp_new'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t177" href="#t177">177</a></span><span class="t">        <span class="nam">induction_measure</span><span class="op">:</span> <span class="nam">Measures</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'induction_measure'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t178" href="#t178">178</a></span><span class="t">        <span class="nam">pruning_measure</span><span class="op">:</span> <span class="nam">Union</span><span class="op">[</span><span class="nam">Measures</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t179" href="#t179">179</a></span><span class="t">                               <span class="nam">str</span><span class="op">]</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'pruning_measure'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t180" href="#t180">180</a></span><span class="t">        <span class="nam">voting_measure</span><span class="op">:</span> <span class="nam">Measures</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'voting_measure'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t181" href="#t181">181</a></span><span class="t">        <span class="nam">max_growing</span><span class="op">:</span> <span class="nam">float</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'max_growing'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t182" href="#t182">182</a></span><span class="t">        <span class="nam">enable_pruning</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'enable_pruning'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t183" href="#t183">183</a></span><span class="t">        <span class="nam">ignore_missing</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'ignore_missing'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t184" href="#t184">184</a></span><span class="t">        <span class="nam">max_uncovered_fraction</span><span class="op">:</span> <span class="nam">float</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'max_uncovered_fraction'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t185" href="#t185">185</a></span><span class="t">        <span class="nam">select_best_candidate</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'select_best_candidate'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t186" href="#t186">186</a></span><span class="t">        <span class="nam">complementary_conditions</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'complementary_conditions'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t187" href="#t187">187</a></span><span class="t">        <span class="nam">mean_based_regression</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'mean_based_regression'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t188" href="#t188">188</a></span><span class="t">        <span class="nam">max_rule_count</span><span class="op">:</span> <span class="nam">int</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'max_rule_count'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t189" href="#t189">189</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t190" href="#t190">190</a></span><span class="t">        <span class="nam">extend_using_preferred</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'extend_using_preferred'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t191" href="#t191">191</a></span><span class="t">        <span class="nam">extend_using_automatic</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'extend_using_automatic'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t192" href="#t192">192</a></span><span class="t">        <span class="nam">induce_using_preferred</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'induce_using_preferred'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t193" href="#t193">193</a></span><span class="t">        <span class="nam">induce_using_automatic</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'induce_using_automatic'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t194" href="#t194">194</a></span><span class="t">        <span class="nam">preferred_conditions_per_rule</span><span class="op">:</span> <span class="nam">int</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t195" href="#t195">195</a></span><span class="t">            <span class="str">'preferred_conditions_per_rule'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t196" href="#t196">196</a></span><span class="t">        <span class="nam">preferred_attributes_per_rule</span><span class="op">:</span> <span class="nam">int</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t197" href="#t197">197</a></span><span class="t">            <span class="str">'preferred_attributes_per_rule'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t198" href="#t198">198</a></span><span class="t">    <span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t199" href="#t199">199</a></span><span class="t">        <span class="str">"""</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t200" href="#t200">200</a></span><span class="t"><span class="str">        Parameters</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t201" href="#t201">201</a></span><span class="t"><span class="str">        ----------</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t202" href="#t202">202</a></span><span class="t"><span class="str">        minsupp_new : float = 5.0</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t203" href="#t203">203</a></span><span class="t"><span class="str">            a minimum number (or fraction, if value &lt; 1.0) of previously uncovered examples</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t204" href="#t204">204</a></span><span class="t"><span class="str">             to be covered by a new rule (positive examples for classification problems); default: 5,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t205" href="#t205">205</a></span><span class="t"><span class="str">        induction_measure : :class:`rulekit.params.Measures` = \</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t206" href="#t206">206</a></span><span class="t"><span class="str">            :class:`rulekit.params.Measures.Correlation`</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t207" href="#t207">207</a></span><span class="t"><span class="str">            measure used during induction; default measure is correlation</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t208" href="#t208">208</a></span><span class="t"><span class="str">        pruning_measure : Union[:class:`rulekit.params.Measures`, str] = \</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t209" href="#t209">209</a></span><span class="t"><span class="str">            :class:`rulekit.params.Measures.Correlation`</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t210" href="#t210">210</a></span><span class="t"><span class="str">            measure used during pruning. Could be user defined (string), for example</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t211" href="#t211">211</a></span><span class="t"><span class="str">             :code:`2 * p / n`; default measure is correlation</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t212" href="#t212">212</a></span><span class="t"><span class="str">        voting_measure : :class:`rulekit.params.Measures` = \</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t213" href="#t213">213</a></span><span class="t"><span class="str">            :class:`rulekit.params.Measures.Correlation`</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t214" href="#t214">214</a></span><span class="t"><span class="str">            measure used during voting; default measure is correlation</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t215" href="#t215">215</a></span><span class="t"><span class="str">        max_growing : int = 0.0</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t216" href="#t216">216</a></span><span class="t"><span class="str">            non-negative integer representing maximum number of conditions which can be added to</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t217" href="#t217">217</a></span><span class="t"><span class="str">            the rule in the growing phase (use this parameter for large datasets if execution time</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t218" href="#t218">218</a></span><span class="t"><span class="str">             is prohibitive); 0 indicates no limit; default: 0,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t219" href="#t219">219</a></span><span class="t"><span class="str">        enable_pruning : bool = True</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t220" href="#t220">220</a></span><span class="t"><span class="str">            enable or disable pruning, default is True.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t221" href="#t221">221</a></span><span class="t"><span class="str">        ignore_missing : bool = False</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t222" href="#t222">222</a></span><span class="t"><span class="str">            boolean telling whether missing values should be ignored (by default, a missing value</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t223" href="#t223">223</a></span><span class="t"><span class="str">            of given attribute is always considered as not fulfilling the condition build upon that</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t224" href="#t224">224</a></span><span class="t"><span class="str">            attribute); default: False.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t225" href="#t225">225</a></span><span class="t"><span class="str">        max_uncovered_fraction : float = 0.0</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t226" href="#t226">226</a></span><span class="t"><span class="str">            Floating-point number from [0,1] interval representing maximum fraction of examples</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t227" href="#t227">227</a></span><span class="t"><span class="str">            that may remain uncovered by the rule set, default: 0.0.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t228" href="#t228">228</a></span><span class="t"><span class="str">        select_best_candidate : bool = False</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t229" href="#t229">229</a></span><span class="t"><span class="str">            Flag determining if best candidate should be selected from growing phase;</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t230" href="#t230">230</a></span><span class="t"><span class="str">            default: False.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t231" href="#t231">231</a></span><span class="t"><span class="str">        complementary_conditions : bool = False</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t232" href="#t232">232</a></span><span class="t"><span class="str">            If enabled, complementary conditions in the form a = !{value} for nominal attributes</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t233" href="#t233">233</a></span><span class="t"><span class="str">            are supported.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t234" href="#t234">234</a></span><span class="t"><span class="str">        mean_based_regression : bool = True</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t235" href="#t235">235</a></span><span class="t"><span class="str">            Enable fast induction of mean-based regression rules instead of default median-based.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t236" href="#t236">236</a></span><span class="t"><span class="str">        max_rule_count : int = 0</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t237" href="#t237">237</a></span><span class="t"><span class="str">            Maximum number of rules to be generated (for classification data sets it applies</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t238" href="#t238">238</a></span><span class="t"><span class="str">             to a single class); 0 indicates no limit.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t239" href="#t239">239</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t240" href="#t240">240</a></span><span class="t"><span class="str">        extend_using_preferred : bool = False</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t241" href="#t241">241</a></span><span class="t"><span class="str">            boolean indicating whether initial rules should be extended with a use of preferred</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t242" href="#t242">242</a></span><span class="t"><span class="str">            conditions and attributes; default is False</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t243" href="#t243">243</a></span><span class="t"><span class="str">        extend_using_automatic : bool = False</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t244" href="#t244">244</a></span><span class="t"><span class="str">            boolean indicating whether initial rules should be extended with a use of automatic</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t245" href="#t245">245</a></span><span class="t"><span class="str">            conditions and attributes; default is False</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t246" href="#t246">246</a></span><span class="t"><span class="str">        induce_using_preferred : bool = False</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t247" href="#t247">247</a></span><span class="t"><span class="str">            boolean indicating whether new rules should be induced with a use of preferred</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t248" href="#t248">248</a></span><span class="t"><span class="str">            conditions and attributes; default is False</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t249" href="#t249">249</a></span><span class="t"><span class="str">        induce_using_automatic : bool = False</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t250" href="#t250">250</a></span><span class="t"><span class="str">            boolean indicating whether new rules should be induced with a use of automatic</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t251" href="#t251">251</a></span><span class="t"><span class="str">            conditions and attributes; default is False</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t252" href="#t252">252</a></span><span class="t"><span class="str">        preferred_conditions_per_rule : int = None</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t253" href="#t253">253</a></span><span class="t"><span class="str">            maximum number of preferred conditions per rule; default: unlimited,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t254" href="#t254">254</a></span><span class="t"><span class="str">        preferred_attributes_per_rule : int = None</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t255" href="#t255">255</a></span><span class="t"><span class="str">            maximum number of preferred attributes per rule; default: unlimited.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t256" href="#t256">256</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t257" href="#t257">257</a></span><span class="t">        <span class="nam">RuleRegressor</span><span class="op">.</span><span class="nam">__init__</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t258" href="#t258">258</a></span><span class="t">            <span class="nam">self</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t259" href="#t259">259</a></span><span class="t">            <span class="nam">minsupp_new</span><span class="op">=</span><span class="nam">minsupp_new</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t260" href="#t260">260</a></span><span class="t">            <span class="nam">induction_measure</span><span class="op">=</span><span class="nam">induction_measure</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t261" href="#t261">261</a></span><span class="t">            <span class="nam">pruning_measure</span><span class="op">=</span><span class="nam">pruning_measure</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t262" href="#t262">262</a></span><span class="t">            <span class="nam">voting_measure</span><span class="op">=</span><span class="nam">voting_measure</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t263" href="#t263">263</a></span><span class="t">            <span class="nam">max_growing</span><span class="op">=</span><span class="nam">max_growing</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t264" href="#t264">264</a></span><span class="t">            <span class="nam">enable_pruning</span><span class="op">=</span><span class="nam">enable_pruning</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t265" href="#t265">265</a></span><span class="t">            <span class="nam">ignore_missing</span><span class="op">=</span><span class="nam">ignore_missing</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t266" href="#t266">266</a></span><span class="t">            <span class="nam">max_uncovered_fraction</span><span class="op">=</span><span class="nam">max_uncovered_fraction</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t267" href="#t267">267</a></span><span class="t">            <span class="nam">select_best_candidate</span><span class="op">=</span><span class="nam">select_best_candidate</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t268" href="#t268">268</a></span><span class="t">            <span class="nam">complementary_conditions</span><span class="op">=</span><span class="nam">complementary_conditions</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t269" href="#t269">269</a></span><span class="t">            <span class="nam">mean_based_regression</span><span class="op">=</span><span class="nam">mean_based_regression</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t270" href="#t270">270</a></span><span class="t">            <span class="nam">max_rule_count</span><span class="op">=</span><span class="nam">max_rule_count</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t271" href="#t271">271</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t272" href="#t272">272</a></span><span class="t">        <span class="nam">ExpertKnowledgeOperator</span><span class="op">.</span><span class="nam">__init__</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t273" href="#t273">273</a></span><span class="t">            <span class="nam">self</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t274" href="#t274">274</a></span><span class="t">            <span class="nam">minsupp_new</span><span class="op">=</span><span class="nam">minsupp_new</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t275" href="#t275">275</a></span><span class="t">            <span class="nam">induction_measure</span><span class="op">=</span><span class="nam">induction_measure</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t276" href="#t276">276</a></span><span class="t">            <span class="nam">pruning_measure</span><span class="op">=</span><span class="nam">pruning_measure</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t277" href="#t277">277</a></span><span class="t">            <span class="nam">voting_measure</span><span class="op">=</span><span class="nam">voting_measure</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t278" href="#t278">278</a></span><span class="t">            <span class="nam">max_growing</span><span class="op">=</span><span class="nam">max_growing</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t279" href="#t279">279</a></span><span class="t">            <span class="nam">enable_pruning</span><span class="op">=</span><span class="nam">enable_pruning</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t280" href="#t280">280</a></span><span class="t">            <span class="nam">ignore_missing</span><span class="op">=</span><span class="nam">ignore_missing</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t281" href="#t281">281</a></span><span class="t">            <span class="nam">max_uncovered_fraction</span><span class="op">=</span><span class="nam">max_uncovered_fraction</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t282" href="#t282">282</a></span><span class="t">            <span class="nam">select_best_candidate</span><span class="op">=</span><span class="nam">select_best_candidate</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t283" href="#t283">283</a></span><span class="t">            <span class="nam">extend_using_preferred</span><span class="op">=</span><span class="nam">extend_using_preferred</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t284" href="#t284">284</a></span><span class="t">            <span class="nam">extend_using_automatic</span><span class="op">=</span><span class="nam">extend_using_automatic</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t285" href="#t285">285</a></span><span class="t">            <span class="nam">induce_using_preferred</span><span class="op">=</span><span class="nam">induce_using_preferred</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t286" href="#t286">286</a></span><span class="t">            <span class="nam">induce_using_automatic</span><span class="op">=</span><span class="nam">induce_using_automatic</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t287" href="#t287">287</a></span><span class="t">            <span class="nam">preferred_conditions_per_rule</span><span class="op">=</span><span class="nam">preferred_conditions_per_rule</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t288" href="#t288">288</a></span><span class="t">            <span class="nam">preferred_attributes_per_rule</span><span class="op">=</span><span class="nam">preferred_attributes_per_rule</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t289" href="#t289">289</a></span><span class="t">            <span class="nam">complementary_conditions</span><span class="op">=</span><span class="nam">complementary_conditions</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t290" href="#t290">290</a></span><span class="t">            <span class="nam">mean_based_regression</span><span class="op">=</span><span class="nam">mean_based_regression</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t291" href="#t291">291</a></span><span class="t">            <span class="nam">max_rule_count</span><span class="op">=</span><span class="nam">max_rule_count</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t292" href="#t292">292</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t293" href="#t293">293</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">model</span><span class="op">:</span> <span class="nam">RuleSet</span><span class="op">[</span><span class="nam">RegressionRule</span><span class="op">]</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t294" href="#t294">294</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t295" href="#t295">295</a></span><span class="t">    <span class="key">def</span> <span class="nam">fit</span><span class="op">(</span>  <span class="com"># pylint: disable=arguments-differ,too-many-arguments</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t296" href="#t296">296</a></span><span class="t">        <span class="nam">self</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t297" href="#t297">297</a></span><span class="t">        <span class="nam">values</span><span class="op">:</span> <span class="nam">Data</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t298" href="#t298">298</a></span><span class="t">        <span class="nam">labels</span><span class="op">:</span> <span class="nam">Data</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t299" href="#t299">299</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t300" href="#t300">300</a></span><span class="t">        <span class="nam">expert_rules</span><span class="op">:</span> <span class="nam">list</span><span class="op">[</span><span class="nam">Union</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">tuple</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">str</span><span class="op">]</span><span class="op">]</span><span class="op">]</span> <span class="op">=</span> <span class="key">None</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t301" href="#t301">301</a></span><span class="t">        <span class="nam">expert_preferred_conditions</span><span class="op">:</span> <span class="nam">list</span><span class="op">[</span><span class="nam">Union</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">tuple</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">str</span><span class="op">]</span><span class="op">]</span><span class="op">]</span> <span class="op">=</span> <span class="key">None</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t302" href="#t302">302</a></span><span class="t">        <span class="nam">expert_forbidden_conditions</span><span class="op">:</span> <span class="nam">list</span><span class="op">[</span><span class="nam">Union</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">tuple</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">str</span><span class="op">]</span><span class="op">]</span><span class="op">]</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t303" href="#t303">303</a></span><span class="t">    <span class="op">)</span> <span class="op">-></span> <span class="nam">ExpertRuleRegressor</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t304" href="#t304">304</a></span><span class="t">        <span class="str">"""Train model on given dataset.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t165" href="#t165">165</a></span><span class="t"><span class="str">        Returns</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t166" href="#t166">166</a></span><span class="t"><span class="str">        -------</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t167" href="#t167">167</a></span><span class="t"><span class="str">        score : float</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t168" href="#t168">168</a></span><span class="t"><span class="str">            R2 of self.predict(values) wrt. labels.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t169" href="#t169">169</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t170" href="#t170">170</a></span><span class="t">        <span class="nam">predicted_labels</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">predict</span><span class="op">(</span><span class="nam">values</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t171" href="#t171">171</a></span><span class="t">        <span class="key">return</span> <span class="nam">metrics</span><span class="op">.</span><span class="nam">r2_score</span><span class="op">(</span><span class="nam">labels</span><span class="op">,</span> <span class="nam">predicted_labels</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t172" href="#t172">172</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t173" href="#t173">173</a></span><span class="t">    <span class="key">def</span> <span class="nam">_map_result</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">predicted_example_set</span><span class="op">)</span> <span class="op">-></span> <span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t174" href="#t174">174</a></span><span class="t">        <span class="key">return</span> <span class="nam">PredictionResultMapper</span><span class="op">.</span><span class="nam">map_to_numerical</span><span class="op">(</span><span class="nam">predicted_example_set</span><span class="op">,</span> <span class="nam">remap</span><span class="op">=</span><span class="key">False</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t175" href="#t175">175</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t176" href="#t176">176</a></span><span class="t">    <span class="key">def</span> <span class="nam">_get_problem_type</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">ProblemType</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t177" href="#t177">177</a></span><span class="t">        <span class="key">return</span> <span class="nam">ProblemType</span><span class="op">.</span><span class="nam">REGRESSION</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t178" href="#t178">178</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t179" href="#t179">179</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t180" href="#t180">180</a></span><span class="t"><span class="key">class</span> <span class="nam">ExpertRuleRegressor</span><span class="op">(</span><span class="nam">ExpertKnowledgeOperator</span><span class="op">,</span> <span class="nam">RuleRegressor</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t181" href="#t181">181</a></span><span class="t">    <span class="str">"""Expert Regression model."""</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t182" href="#t182">182</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t183" href="#t183">183</a></span><span class="t">    <span class="nam">__params_class__</span> <span class="op">=</span> <span class="nam">_RegressionExpertModelParams</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t184" href="#t184">184</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t185" href="#t185">185</a></span><span class="t">    <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span>   <span class="com"># pylint: disable=too-many-arguments,too-many-locals</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t186" href="#t186">186</a></span><span class="t">        <span class="nam">self</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t187" href="#t187">187</a></span><span class="t">        <span class="nam">minsupp_new</span><span class="op">:</span> <span class="nam">float</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'minsupp_new'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t188" href="#t188">188</a></span><span class="t">        <span class="nam">induction_measure</span><span class="op">:</span> <span class="nam">Measures</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'induction_measure'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t189" href="#t189">189</a></span><span class="t">        <span class="nam">pruning_measure</span><span class="op">:</span> <span class="nam">Union</span><span class="op">[</span><span class="nam">Measures</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t190" href="#t190">190</a></span><span class="t">                               <span class="nam">str</span><span class="op">]</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'pruning_measure'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t191" href="#t191">191</a></span><span class="t">        <span class="nam">voting_measure</span><span class="op">:</span> <span class="nam">Measures</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'voting_measure'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t192" href="#t192">192</a></span><span class="t">        <span class="nam">max_growing</span><span class="op">:</span> <span class="nam">float</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'max_growing'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t193" href="#t193">193</a></span><span class="t">        <span class="nam">enable_pruning</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'enable_pruning'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t194" href="#t194">194</a></span><span class="t">        <span class="nam">ignore_missing</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'ignore_missing'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t195" href="#t195">195</a></span><span class="t">        <span class="nam">max_uncovered_fraction</span><span class="op">:</span> <span class="nam">float</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'max_uncovered_fraction'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t196" href="#t196">196</a></span><span class="t">        <span class="nam">select_best_candidate</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'select_best_candidate'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t197" href="#t197">197</a></span><span class="t">        <span class="nam">complementary_conditions</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'complementary_conditions'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t198" href="#t198">198</a></span><span class="t">        <span class="nam">mean_based_regression</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'mean_based_regression'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t199" href="#t199">199</a></span><span class="t">        <span class="nam">max_rule_count</span><span class="op">:</span> <span class="nam">int</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'max_rule_count'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t200" href="#t200">200</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t201" href="#t201">201</a></span><span class="t">        <span class="nam">extend_using_preferred</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'extend_using_preferred'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t202" href="#t202">202</a></span><span class="t">        <span class="nam">extend_using_automatic</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'extend_using_automatic'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t203" href="#t203">203</a></span><span class="t">        <span class="nam">induce_using_preferred</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'induce_using_preferred'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t204" href="#t204">204</a></span><span class="t">        <span class="nam">induce_using_automatic</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'induce_using_automatic'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t205" href="#t205">205</a></span><span class="t">        <span class="nam">preferred_conditions_per_rule</span><span class="op">:</span> <span class="nam">int</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t206" href="#t206">206</a></span><span class="t">            <span class="str">'preferred_conditions_per_rule'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t207" href="#t207">207</a></span><span class="t">        <span class="nam">preferred_attributes_per_rule</span><span class="op">:</span> <span class="nam">int</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t208" href="#t208">208</a></span><span class="t">            <span class="str">'preferred_attributes_per_rule'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t209" href="#t209">209</a></span><span class="t">    <span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t210" href="#t210">210</a></span><span class="t">        <span class="str">"""</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t211" href="#t211">211</a></span><span class="t"><span class="str">        Parameters</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t212" href="#t212">212</a></span><span class="t"><span class="str">        ----------</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t213" href="#t213">213</a></span><span class="t"><span class="str">        minsupp_new : float = 5.0</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t214" href="#t214">214</a></span><span class="t"><span class="str">            a minimum number (or fraction, if value &lt; 1.0) of previously uncovered examples</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t215" href="#t215">215</a></span><span class="t"><span class="str">             to be covered by a new rule (positive examples for classification problems); default: 5,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t216" href="#t216">216</a></span><span class="t"><span class="str">        induction_measure : :class:`rulekit.params.Measures` = \</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t217" href="#t217">217</a></span><span class="t"><span class="str">            :class:`rulekit.params.Measures.Correlation`</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t218" href="#t218">218</a></span><span class="t"><span class="str">            measure used during induction; default measure is correlation</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t219" href="#t219">219</a></span><span class="t"><span class="str">        pruning_measure : Union[:class:`rulekit.params.Measures`, str] = \</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t220" href="#t220">220</a></span><span class="t"><span class="str">            :class:`rulekit.params.Measures.Correlation`</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t221" href="#t221">221</a></span><span class="t"><span class="str">            measure used during pruning. Could be user defined (string), for example</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t222" href="#t222">222</a></span><span class="t"><span class="str">             :code:`2 * p / n`; default measure is correlation</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t223" href="#t223">223</a></span><span class="t"><span class="str">        voting_measure : :class:`rulekit.params.Measures` = \</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t224" href="#t224">224</a></span><span class="t"><span class="str">            :class:`rulekit.params.Measures.Correlation`</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t225" href="#t225">225</a></span><span class="t"><span class="str">            measure used during voting; default measure is correlation</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t226" href="#t226">226</a></span><span class="t"><span class="str">        max_growing : int = 0.0</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t227" href="#t227">227</a></span><span class="t"><span class="str">            non-negative integer representing maximum number of conditions which can be added to</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t228" href="#t228">228</a></span><span class="t"><span class="str">            the rule in the growing phase (use this parameter for large datasets if execution time</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t229" href="#t229">229</a></span><span class="t"><span class="str">             is prohibitive); 0 indicates no limit; default: 0,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t230" href="#t230">230</a></span><span class="t"><span class="str">        enable_pruning : bool = True</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t231" href="#t231">231</a></span><span class="t"><span class="str">            enable or disable pruning, default is True.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t232" href="#t232">232</a></span><span class="t"><span class="str">        ignore_missing : bool = False</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t233" href="#t233">233</a></span><span class="t"><span class="str">            boolean telling whether missing values should be ignored (by default, a missing value</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t234" href="#t234">234</a></span><span class="t"><span class="str">            of given attribute is always considered as not fulfilling the condition build upon that</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t235" href="#t235">235</a></span><span class="t"><span class="str">            attribute); default: False.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t236" href="#t236">236</a></span><span class="t"><span class="str">        max_uncovered_fraction : float = 0.0</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t237" href="#t237">237</a></span><span class="t"><span class="str">            Floating-point number from [0,1] interval representing maximum fraction of examples</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t238" href="#t238">238</a></span><span class="t"><span class="str">            that may remain uncovered by the rule set, default: 0.0.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t239" href="#t239">239</a></span><span class="t"><span class="str">        select_best_candidate : bool = False</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t240" href="#t240">240</a></span><span class="t"><span class="str">            Flag determining if best candidate should be selected from growing phase;</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t241" href="#t241">241</a></span><span class="t"><span class="str">            default: False.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t242" href="#t242">242</a></span><span class="t"><span class="str">        complementary_conditions : bool = False</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t243" href="#t243">243</a></span><span class="t"><span class="str">            If enabled, complementary conditions in the form a = !{value} for nominal attributes</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t244" href="#t244">244</a></span><span class="t"><span class="str">            are supported.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t245" href="#t245">245</a></span><span class="t"><span class="str">        mean_based_regression : bool = True</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t246" href="#t246">246</a></span><span class="t"><span class="str">            Enable fast induction of mean-based regression rules instead of default median-based.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t247" href="#t247">247</a></span><span class="t"><span class="str">        max_rule_count : int = 0</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t248" href="#t248">248</a></span><span class="t"><span class="str">            Maximum number of rules to be generated (for classification data sets it applies</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t249" href="#t249">249</a></span><span class="t"><span class="str">             to a single class); 0 indicates no limit.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t250" href="#t250">250</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t251" href="#t251">251</a></span><span class="t"><span class="str">        extend_using_preferred : bool = False</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t252" href="#t252">252</a></span><span class="t"><span class="str">            boolean indicating whether initial rules should be extended with a use of preferred</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t253" href="#t253">253</a></span><span class="t"><span class="str">            conditions and attributes; default is False</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t254" href="#t254">254</a></span><span class="t"><span class="str">        extend_using_automatic : bool = False</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t255" href="#t255">255</a></span><span class="t"><span class="str">            boolean indicating whether initial rules should be extended with a use of automatic</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t256" href="#t256">256</a></span><span class="t"><span class="str">            conditions and attributes; default is False</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t257" href="#t257">257</a></span><span class="t"><span class="str">        induce_using_preferred : bool = False</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t258" href="#t258">258</a></span><span class="t"><span class="str">            boolean indicating whether new rules should be induced with a use of preferred</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t259" href="#t259">259</a></span><span class="t"><span class="str">            conditions and attributes; default is False</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t260" href="#t260">260</a></span><span class="t"><span class="str">        induce_using_automatic : bool = False</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t261" href="#t261">261</a></span><span class="t"><span class="str">            boolean indicating whether new rules should be induced with a use of automatic</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t262" href="#t262">262</a></span><span class="t"><span class="str">            conditions and attributes; default is False</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t263" href="#t263">263</a></span><span class="t"><span class="str">        preferred_conditions_per_rule : int = None</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t264" href="#t264">264</a></span><span class="t"><span class="str">            maximum number of preferred conditions per rule; default: unlimited,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t265" href="#t265">265</a></span><span class="t"><span class="str">        preferred_attributes_per_rule : int = None</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t266" href="#t266">266</a></span><span class="t"><span class="str">            maximum number of preferred attributes per rule; default: unlimited.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t267" href="#t267">267</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t268" href="#t268">268</a></span><span class="t">        <span class="nam">RuleRegressor</span><span class="op">.</span><span class="nam">__init__</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t269" href="#t269">269</a></span><span class="t">            <span class="nam">self</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t270" href="#t270">270</a></span><span class="t">            <span class="nam">minsupp_new</span><span class="op">=</span><span class="nam">minsupp_new</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t271" href="#t271">271</a></span><span class="t">            <span class="nam">induction_measure</span><span class="op">=</span><span class="nam">induction_measure</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t272" href="#t272">272</a></span><span class="t">            <span class="nam">pruning_measure</span><span class="op">=</span><span class="nam">pruning_measure</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t273" href="#t273">273</a></span><span class="t">            <span class="nam">voting_measure</span><span class="op">=</span><span class="nam">voting_measure</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t274" href="#t274">274</a></span><span class="t">            <span class="nam">max_growing</span><span class="op">=</span><span class="nam">max_growing</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t275" href="#t275">275</a></span><span class="t">            <span class="nam">enable_pruning</span><span class="op">=</span><span class="nam">enable_pruning</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t276" href="#t276">276</a></span><span class="t">            <span class="nam">ignore_missing</span><span class="op">=</span><span class="nam">ignore_missing</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t277" href="#t277">277</a></span><span class="t">            <span class="nam">max_uncovered_fraction</span><span class="op">=</span><span class="nam">max_uncovered_fraction</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t278" href="#t278">278</a></span><span class="t">            <span class="nam">select_best_candidate</span><span class="op">=</span><span class="nam">select_best_candidate</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t279" href="#t279">279</a></span><span class="t">            <span class="nam">complementary_conditions</span><span class="op">=</span><span class="nam">complementary_conditions</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t280" href="#t280">280</a></span><span class="t">            <span class="nam">mean_based_regression</span><span class="op">=</span><span class="nam">mean_based_regression</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t281" href="#t281">281</a></span><span class="t">            <span class="nam">max_rule_count</span><span class="op">=</span><span class="nam">max_rule_count</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t282" href="#t282">282</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t283" href="#t283">283</a></span><span class="t">        <span class="nam">ExpertKnowledgeOperator</span><span class="op">.</span><span class="nam">__init__</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t284" href="#t284">284</a></span><span class="t">            <span class="nam">self</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t285" href="#t285">285</a></span><span class="t">            <span class="nam">minsupp_new</span><span class="op">=</span><span class="nam">minsupp_new</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t286" href="#t286">286</a></span><span class="t">            <span class="nam">induction_measure</span><span class="op">=</span><span class="nam">induction_measure</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t287" href="#t287">287</a></span><span class="t">            <span class="nam">pruning_measure</span><span class="op">=</span><span class="nam">pruning_measure</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t288" href="#t288">288</a></span><span class="t">            <span class="nam">voting_measure</span><span class="op">=</span><span class="nam">voting_measure</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t289" href="#t289">289</a></span><span class="t">            <span class="nam">max_growing</span><span class="op">=</span><span class="nam">max_growing</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t290" href="#t290">290</a></span><span class="t">            <span class="nam">enable_pruning</span><span class="op">=</span><span class="nam">enable_pruning</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t291" href="#t291">291</a></span><span class="t">            <span class="nam">ignore_missing</span><span class="op">=</span><span class="nam">ignore_missing</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t292" href="#t292">292</a></span><span class="t">            <span class="nam">max_uncovered_fraction</span><span class="op">=</span><span class="nam">max_uncovered_fraction</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t293" href="#t293">293</a></span><span class="t">            <span class="nam">select_best_candidate</span><span class="op">=</span><span class="nam">select_best_candidate</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t294" href="#t294">294</a></span><span class="t">            <span class="nam">extend_using_preferred</span><span class="op">=</span><span class="nam">extend_using_preferred</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t295" href="#t295">295</a></span><span class="t">            <span class="nam">extend_using_automatic</span><span class="op">=</span><span class="nam">extend_using_automatic</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t296" href="#t296">296</a></span><span class="t">            <span class="nam">induce_using_preferred</span><span class="op">=</span><span class="nam">induce_using_preferred</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t297" href="#t297">297</a></span><span class="t">            <span class="nam">induce_using_automatic</span><span class="op">=</span><span class="nam">induce_using_automatic</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t298" href="#t298">298</a></span><span class="t">            <span class="nam">preferred_conditions_per_rule</span><span class="op">=</span><span class="nam">preferred_conditions_per_rule</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t299" href="#t299">299</a></span><span class="t">            <span class="nam">preferred_attributes_per_rule</span><span class="op">=</span><span class="nam">preferred_attributes_per_rule</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t300" href="#t300">300</a></span><span class="t">            <span class="nam">complementary_conditions</span><span class="op">=</span><span class="nam">complementary_conditions</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t301" href="#t301">301</a></span><span class="t">            <span class="nam">mean_based_regression</span><span class="op">=</span><span class="nam">mean_based_regression</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t302" href="#t302">302</a></span><span class="t">            <span class="nam">max_rule_count</span><span class="op">=</span><span class="nam">max_rule_count</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t303" href="#t303">303</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t304" href="#t304">304</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">model</span><span class="op">:</span> <span class="nam">RuleSet</span><span class="op">[</span><span class="nam">RegressionRule</span><span class="op">]</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t305" href="#t305">305</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t306" href="#t306">306</a></span><span class="t"><span class="str">        Parameters</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t307" href="#t307">307</a></span><span class="t"><span class="str">        ----------</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t308" href="#t308">308</a></span><span class="t"><span class="str">        values : :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t309" href="#t309">309</a></span><span class="t"><span class="str">            attributes</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t310" href="#t310">310</a></span><span class="t"><span class="str">        labels : :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t311" href="#t311">311</a></span><span class="t"><span class="str">            target values</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t312" href="#t312">312</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t313" href="#t313">313</a></span><span class="t"><span class="str">        expert_rules : List[Union[str, Tuple[str, str]]]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t314" href="#t314">314</a></span><span class="t"><span class="str">            set of initial rules, either passed as a list of strings representing rules or as list</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t315" href="#t315">315</a></span><span class="t"><span class="str">            of tuples where first element is name of the rule and second one is rule string.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t316" href="#t316">316</a></span><span class="t"><span class="str">        expert_preferred_conditions : List[Union[str, Tuple[str, str]]]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t317" href="#t317">317</a></span><span class="t"><span class="str">            multiset of preferred conditions (used also for specifying preferred attributes by</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t318" href="#t318">318</a></span><span class="t"><span class="str">             using special value Any). Either passed as a list of strings representing rules or as</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t319" href="#t319">319</a></span><span class="t"><span class="str">             list of tuples where first element is name of the rule and second one is rule string.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t320" href="#t320">320</a></span><span class="t"><span class="str">        expert_forbidden_conditions : List[Union[str, Tuple[str, str]]]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t321" href="#t321">321</a></span><span class="t"><span class="str">            set of forbidden conditions (used also for specifying forbidden attributes by using</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t322" href="#t322">322</a></span><span class="t"><span class="str">             special valye Any). Either passed as a list of strings representing rules or as list</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t323" href="#t323">323</a></span><span class="t"><span class="str">             of tuples where first element is name of the rule and second one is rule string.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t324" href="#t324">324</a></span><span class="t"><span class="str">        Returns</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t325" href="#t325">325</a></span><span class="t"><span class="str">        -------</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t326" href="#t326">326</a></span><span class="t"><span class="str">        self : ExpertRuleRegressor</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t327" href="#t327">327</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t328" href="#t328">328</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_validate_labels</span><span class="op">(</span><span class="nam">labels</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t329" href="#t329">329</a></span><span class="t">        <span class="key">return</span> <span class="nam">ExpertKnowledgeOperator</span><span class="op">.</span><span class="nam">fit</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t330" href="#t330">330</a></span><span class="t">            <span class="nam">self</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t331" href="#t331">331</a></span><span class="t">            <span class="nam">values</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t332" href="#t332">332</a></span><span class="t">            <span class="nam">labels</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t333" href="#t333">333</a></span><span class="t">            <span class="nam">expert_rules</span><span class="op">=</span><span class="nam">expert_rules</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t334" href="#t334">334</a></span><span class="t">            <span class="nam">expert_preferred_conditions</span><span class="op">=</span><span class="nam">expert_preferred_conditions</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t335" href="#t335">335</a></span><span class="t">            <span class="nam">expert_forbidden_conditions</span><span class="op">=</span><span class="nam">expert_forbidden_conditions</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t336" href="#t336">336</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t337" href="#t337">337</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t338" href="#t338">338</a></span><span class="t">    <span class="key">def</span> <span class="nam">predict</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">values</span><span class="op">:</span> <span class="nam">Data</span><span class="op">)</span> <span class="op">-></span> <span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t339" href="#t339">339</a></span><span class="t">        <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_map_result</span><span class="op">(</span><span class="nam">ExpertKnowledgeOperator</span><span class="op">.</span><span class="nam">predict</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">values</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t340" href="#t340">340</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t341" href="#t341">341</a></span><span class="t">    <span class="key">def</span> <span class="nam">_get_problem_type</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">ProblemType</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t342" href="#t342">342</a></span><span class="t">        <span class="key">return</span> <span class="nam">ProblemType</span><span class="op">.</span><span class="nam">REGRESSION</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t343" href="#t343">343</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t344" href="#t344">344</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t345" href="#t345">345</a></span><span class="t"><span class="key">class</span> <span class="nam">ContrastSetRuleRegressor</span><span class="op">(</span><span class="nam">BaseOperator</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t346" href="#t346">346</a></span><span class="t">    <span class="str">"""Contrast set regression model."""</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t347" href="#t347">347</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t348" href="#t348">348</a></span><span class="t">    <span class="nam">__params_class__</span> <span class="op">=</span> <span class="nam">ContrastSetModelParams</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t349" href="#t349">349</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t350" href="#t350">350</a></span><span class="t">    <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span>  <span class="com"># pylint: disable=too-many-arguments,too-many-locals</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t351" href="#t351">351</a></span><span class="t">        <span class="nam">self</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t352" href="#t352">352</a></span><span class="t">        <span class="nam">minsupp_all</span><span class="op">:</span> <span class="nam">Tuple</span><span class="op">[</span><span class="nam">float</span><span class="op">,</span> <span class="nam">float</span><span class="op">,</span> <span class="nam">float</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t353" href="#t353">353</a></span><span class="t">                           <span class="nam">float</span><span class="op">]</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'minsupp_all'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t354" href="#t354">354</a></span><span class="t">        <span class="nam">max_neg2pos</span><span class="op">:</span> <span class="nam">float</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'max_neg2pos'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t355" href="#t355">355</a></span><span class="t">        <span class="nam">max_passes_count</span><span class="op">:</span> <span class="nam">int</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'max_passes_count'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t356" href="#t356">356</a></span><span class="t">        <span class="nam">penalty_strength</span><span class="op">:</span> <span class="nam">float</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'penalty_strength'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t357" href="#t357">357</a></span><span class="t">        <span class="nam">penalty_saturation</span><span class="op">:</span> <span class="nam">float</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'penalty_saturation'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t306" href="#t306">306</a></span><span class="t">    <span class="key">def</span> <span class="nam">fit</span><span class="op">(</span>  <span class="com"># pylint: disable=arguments-differ,too-many-arguments</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t307" href="#t307">307</a></span><span class="t">        <span class="nam">self</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t308" href="#t308">308</a></span><span class="t">        <span class="nam">values</span><span class="op">:</span> <span class="nam">Data</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t309" href="#t309">309</a></span><span class="t">        <span class="nam">labels</span><span class="op">:</span> <span class="nam">Data</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t310" href="#t310">310</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t311" href="#t311">311</a></span><span class="t">        <span class="nam">expert_rules</span><span class="op">:</span> <span class="nam">list</span><span class="op">[</span><span class="nam">Union</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">tuple</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">str</span><span class="op">]</span><span class="op">]</span><span class="op">]</span> <span class="op">=</span> <span class="key">None</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t312" href="#t312">312</a></span><span class="t">        <span class="nam">expert_preferred_conditions</span><span class="op">:</span> <span class="nam">list</span><span class="op">[</span><span class="nam">Union</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">tuple</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">str</span><span class="op">]</span><span class="op">]</span><span class="op">]</span> <span class="op">=</span> <span class="key">None</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t313" href="#t313">313</a></span><span class="t">        <span class="nam">expert_forbidden_conditions</span><span class="op">:</span> <span class="nam">list</span><span class="op">[</span><span class="nam">Union</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">tuple</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">str</span><span class="op">]</span><span class="op">]</span><span class="op">]</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t314" href="#t314">314</a></span><span class="t">    <span class="op">)</span> <span class="op">-></span> <span class="nam">ExpertRuleRegressor</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t315" href="#t315">315</a></span><span class="t">        <span class="str">"""Train model on given dataset.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t316" href="#t316">316</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t317" href="#t317">317</a></span><span class="t"><span class="str">        Parameters</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t318" href="#t318">318</a></span><span class="t"><span class="str">        ----------</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t319" href="#t319">319</a></span><span class="t"><span class="str">        values : :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t320" href="#t320">320</a></span><span class="t"><span class="str">            attributes</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t321" href="#t321">321</a></span><span class="t"><span class="str">        labels : :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t322" href="#t322">322</a></span><span class="t"><span class="str">            target values</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t323" href="#t323">323</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t324" href="#t324">324</a></span><span class="t"><span class="str">        expert_rules : List[Union[str, Tuple[str, str]]]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t325" href="#t325">325</a></span><span class="t"><span class="str">            set of initial rules, either passed as a list of strings representing rules or as list</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t326" href="#t326">326</a></span><span class="t"><span class="str">            of tuples where first element is name of the rule and second one is rule string.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t327" href="#t327">327</a></span><span class="t"><span class="str">        expert_preferred_conditions : List[Union[str, Tuple[str, str]]]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t328" href="#t328">328</a></span><span class="t"><span class="str">            multiset of preferred conditions (used also for specifying preferred attributes by</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t329" href="#t329">329</a></span><span class="t"><span class="str">             using special value Any). Either passed as a list of strings representing rules or as</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t330" href="#t330">330</a></span><span class="t"><span class="str">             list of tuples where first element is name of the rule and second one is rule string.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t331" href="#t331">331</a></span><span class="t"><span class="str">        expert_forbidden_conditions : List[Union[str, Tuple[str, str]]]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t332" href="#t332">332</a></span><span class="t"><span class="str">            set of forbidden conditions (used also for specifying forbidden attributes by using</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t333" href="#t333">333</a></span><span class="t"><span class="str">             special valye Any). Either passed as a list of strings representing rules or as list</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t334" href="#t334">334</a></span><span class="t"><span class="str">             of tuples where first element is name of the rule and second one is rule string.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t335" href="#t335">335</a></span><span class="t"><span class="str">        Returns</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t336" href="#t336">336</a></span><span class="t"><span class="str">        -------</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t337" href="#t337">337</a></span><span class="t"><span class="str">        self : ExpertRuleRegressor</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t338" href="#t338">338</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t339" href="#t339">339</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_validate_labels</span><span class="op">(</span><span class="nam">labels</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t340" href="#t340">340</a></span><span class="t">        <span class="key">return</span> <span class="nam">ExpertKnowledgeOperator</span><span class="op">.</span><span class="nam">fit</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t341" href="#t341">341</a></span><span class="t">            <span class="nam">self</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t342" href="#t342">342</a></span><span class="t">            <span class="nam">values</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t343" href="#t343">343</a></span><span class="t">            <span class="nam">labels</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t344" href="#t344">344</a></span><span class="t">            <span class="nam">expert_rules</span><span class="op">=</span><span class="nam">expert_rules</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t345" href="#t345">345</a></span><span class="t">            <span class="nam">expert_preferred_conditions</span><span class="op">=</span><span class="nam">expert_preferred_conditions</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t346" href="#t346">346</a></span><span class="t">            <span class="nam">expert_forbidden_conditions</span><span class="op">=</span><span class="nam">expert_forbidden_conditions</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t347" href="#t347">347</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t348" href="#t348">348</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t349" href="#t349">349</a></span><span class="t">    <span class="key">def</span> <span class="nam">predict</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">values</span><span class="op">:</span> <span class="nam">Data</span><span class="op">)</span> <span class="op">-></span> <span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t350" href="#t350">350</a></span><span class="t">        <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_map_result</span><span class="op">(</span><span class="nam">ExpertKnowledgeOperator</span><span class="op">.</span><span class="nam">predict</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">values</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t351" href="#t351">351</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t352" href="#t352">352</a></span><span class="t">    <span class="key">def</span> <span class="nam">_get_problem_type</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">ProblemType</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t353" href="#t353">353</a></span><span class="t">        <span class="key">return</span> <span class="nam">ProblemType</span><span class="op">.</span><span class="nam">REGRESSION</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t354" href="#t354">354</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t355" href="#t355">355</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t356" href="#t356">356</a></span><span class="t"><span class="key">class</span> <span class="nam">ContrastSetRuleRegressor</span><span class="op">(</span><span class="nam">BaseOperator</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t357" href="#t357">357</a></span><span class="t">    <span class="str">"""Contrast set regression model."""</span>&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t358" href="#t358">358</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t359" href="#t359">359</a></span><span class="t">        <span class="nam">minsupp_new</span><span class="op">:</span> <span class="nam">float</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'minsupp_new'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t360" href="#t360">360</a></span><span class="t">        <span class="nam">induction_measure</span><span class="op">:</span> <span class="nam">Measures</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'induction_measure'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t361" href="#t361">361</a></span><span class="t">        <span class="nam">pruning_measure</span><span class="op">:</span> <span class="nam">Union</span><span class="op">[</span><span class="nam">Measures</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t362" href="#t362">362</a></span><span class="t">                               <span class="nam">str</span><span class="op">]</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'pruning_measure'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t363" href="#t363">363</a></span><span class="t">        <span class="nam">voting_measure</span><span class="op">:</span> <span class="nam">Measures</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'voting_measure'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t364" href="#t364">364</a></span><span class="t">        <span class="nam">max_growing</span><span class="op">:</span> <span class="nam">float</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'max_growing'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t365" href="#t365">365</a></span><span class="t">        <span class="nam">enable_pruning</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'enable_pruning'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t366" href="#t366">366</a></span><span class="t">        <span class="nam">ignore_missing</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'ignore_missing'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t367" href="#t367">367</a></span><span class="t">        <span class="nam">max_uncovered_fraction</span><span class="op">:</span> <span class="nam">float</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'max_uncovered_fraction'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t368" href="#t368">368</a></span><span class="t">        <span class="nam">select_best_candidate</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'select_best_candidate'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t369" href="#t369">369</a></span><span class="t">        <span class="nam">complementary_conditions</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'complementary_conditions'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t370" href="#t370">370</a></span><span class="t">        <span class="nam">mean_based_regression</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'mean_based_regression'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t371" href="#t371">371</a></span><span class="t">        <span class="nam">max_rule_count</span><span class="op">:</span> <span class="nam">int</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'max_rule_count'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t372" href="#t372">372</a></span><span class="t">    <span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t373" href="#t373">373</a></span><span class="t">        <span class="str">"""</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t374" href="#t374">374</a></span><span class="t"><span class="str">        Parameters</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t375" href="#t375">375</a></span><span class="t"><span class="str">        ----------</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t376" href="#t376">376</a></span><span class="t"><span class="str">        minsupp_all: Tuple[float, float, float, float]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t377" href="#t377">377</a></span><span class="t"><span class="str">            a minimum positive support of a contrast set (p/P). When multiple values are specified,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t378" href="#t378">378</a></span><span class="t"><span class="str">            a metainduction is performed; Default and recommended sequence is: 0.8, 0.5, 0.2, 0.1</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t379" href="#t379">379</a></span><span class="t"><span class="str">        max_neg2pos: float</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t380" href="#t380">380</a></span><span class="t"><span class="str">            a maximum ratio of negative to positive supports (nP/pN); Default is 0.5</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t381" href="#t381">381</a></span><span class="t"><span class="str">        max_passes_count: int</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t382" href="#t382">382</a></span><span class="t"><span class="str">            a maximum number of sequential covering passes for a single minsupp-all; Default is 5</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t383" href="#t383">383</a></span><span class="t"><span class="str">        penalty_strength: float</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t384" href="#t384">384</a></span><span class="t"><span class="str">            (s) - penalty strength; Default is 0.5</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t385" href="#t385">385</a></span><span class="t"><span class="str">        penalty_saturation: float</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t386" href="#t386">386</a></span><span class="t"><span class="str">            the value of p_new / P at which penalty reward saturates; Default is 0.2.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t387" href="#t387">387</a></span><span class="t"><span class="str">        minsupp_new : float = 5.0</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t388" href="#t388">388</a></span><span class="t"><span class="str">            a minimum number (or fraction, if value &lt; 1.0) of previously uncovered examples</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t389" href="#t389">389</a></span><span class="t"><span class="str">             to be covered by a new rule (positive examples for classification problems); default: 5,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t390" href="#t390">390</a></span><span class="t"><span class="str">        induction_measure : :class:`rulekit.params.Measures` = \</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t391" href="#t391">391</a></span><span class="t"><span class="str">            :class:`rulekit.params.Measures.Correlation`</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t392" href="#t392">392</a></span><span class="t"><span class="str">            measure used during induction; default measure is correlation</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t393" href="#t393">393</a></span><span class="t"><span class="str">        pruning_measure : Union[:class:`rulekit.params.Measures`, str] = \</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t394" href="#t394">394</a></span><span class="t"><span class="str">            :class:`rulekit.params.Measures.Correlation`</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t395" href="#t395">395</a></span><span class="t"><span class="str">            measure used during pruning. Could be user defined (string), for example</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t396" href="#t396">396</a></span><span class="t"><span class="str">            :code:`2 * p / n`; default measure is correlation</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t397" href="#t397">397</a></span><span class="t"><span class="str">        voting_measure : :class:`rulekit.params.Measures` = \</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t398" href="#t398">398</a></span><span class="t"><span class="str">            :class:`rulekit.params.Measures.Correlation`</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t399" href="#t399">399</a></span><span class="t"><span class="str">            measure used during voting; default measure is correlation</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t400" href="#t400">400</a></span><span class="t"><span class="str">        max_growing : int = 0.0</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t401" href="#t401">401</a></span><span class="t"><span class="str">            non-negative integer representing maximum number of conditions which can be added to</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t402" href="#t402">402</a></span><span class="t"><span class="str">            the rule in the growing phase (use this parameter for large datasets if execution time</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t403" href="#t403">403</a></span><span class="t"><span class="str">            is prohibitive); 0 indicates no limit; default: 0,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t404" href="#t404">404</a></span><span class="t"><span class="str">        enable_pruning : bool = True</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t405" href="#t405">405</a></span><span class="t"><span class="str">            enable or disable pruning, default is True.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t406" href="#t406">406</a></span><span class="t"><span class="str">        ignore_missing : bool = False</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t407" href="#t407">407</a></span><span class="t"><span class="str">            boolean telling whether missing values should be ignored (by default, a missing value</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t408" href="#t408">408</a></span><span class="t"><span class="str">             of given attribute is always considered as not fulfilling the condition build upon that</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t409" href="#t409">409</a></span><span class="t"><span class="str">            attribute); default: False.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t410" href="#t410">410</a></span><span class="t"><span class="str">        max_uncovered_fraction : float = 0.0</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t411" href="#t411">411</a></span><span class="t"><span class="str">            Floating-point number from [0,1] interval representing maximum fraction of examples</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t412" href="#t412">412</a></span><span class="t"><span class="str">            that may remain uncovered by the rule set, default: 0.0.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t413" href="#t413">413</a></span><span class="t"><span class="str">        select_best_candidate : bool = False</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t414" href="#t414">414</a></span><span class="t"><span class="str">            Flag determining if best candidate should be selected from growing phase;</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t415" href="#t415">415</a></span><span class="t"><span class="str">            default: False.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t416" href="#t416">416</a></span><span class="t"><span class="str">        complementary_conditions : bool = False</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t417" href="#t417">417</a></span><span class="t"><span class="str">            If enabled, complementary conditions in the form a = !{value} for nominal attributes</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t418" href="#t418">418</a></span><span class="t"><span class="str">            are supported.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t419" href="#t419">419</a></span><span class="t"><span class="str">        mean_based_regression : bool = True</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t420" href="#t420">420</a></span><span class="t"><span class="str">            Enable fast induction of mean-based regression rules instead of default median-based.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t421" href="#t421">421</a></span><span class="t"><span class="str">        max_rule_count : int = 0</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t422" href="#t422">422</a></span><span class="t"><span class="str">            Maximum number of rules to be generated (for classification data sets it applies</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t423" href="#t423">423</a></span><span class="t"><span class="str">             to a single class); 0 indicates no limit.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t424" href="#t424">424</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t425" href="#t425">425</a></span><span class="t">        <span class="nam">super</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">__init__</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t426" href="#t426">426</a></span><span class="t">            <span class="nam">minsupp_all</span><span class="op">=</span><span class="nam">minsupp_all</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t427" href="#t427">427</a></span><span class="t">            <span class="nam">max_neg2pos</span><span class="op">=</span><span class="nam">max_neg2pos</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t428" href="#t428">428</a></span><span class="t">            <span class="nam">max_passes_count</span><span class="op">=</span><span class="nam">max_passes_count</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t429" href="#t429">429</a></span><span class="t">            <span class="nam">penalty_strength</span><span class="op">=</span><span class="nam">penalty_strength</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t430" href="#t430">430</a></span><span class="t">            <span class="nam">penalty_saturation</span><span class="op">=</span><span class="nam">penalty_saturation</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t431" href="#t431">431</a></span><span class="t">            <span class="nam">minsupp_new</span><span class="op">=</span><span class="nam">minsupp_new</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t432" href="#t432">432</a></span><span class="t">            <span class="nam">induction_measure</span><span class="op">=</span><span class="nam">induction_measure</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t433" href="#t433">433</a></span><span class="t">            <span class="nam">pruning_measure</span><span class="op">=</span><span class="nam">pruning_measure</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t434" href="#t434">434</a></span><span class="t">            <span class="nam">voting_measure</span><span class="op">=</span><span class="nam">voting_measure</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t435" href="#t435">435</a></span><span class="t">            <span class="nam">max_growing</span><span class="op">=</span><span class="nam">max_growing</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t436" href="#t436">436</a></span><span class="t">            <span class="nam">enable_pruning</span><span class="op">=</span><span class="nam">enable_pruning</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t437" href="#t437">437</a></span><span class="t">            <span class="nam">ignore_missing</span><span class="op">=</span><span class="nam">ignore_missing</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t438" href="#t438">438</a></span><span class="t">            <span class="nam">max_uncovered_fraction</span><span class="op">=</span><span class="nam">max_uncovered_fraction</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t439" href="#t439">439</a></span><span class="t">            <span class="nam">select_best_candidate</span><span class="op">=</span><span class="nam">select_best_candidate</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t440" href="#t440">440</a></span><span class="t">            <span class="nam">complementary_conditions</span><span class="op">=</span><span class="nam">complementary_conditions</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t441" href="#t441">441</a></span><span class="t">            <span class="nam">mean_based_regression</span><span class="op">=</span><span class="nam">mean_based_regression</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t442" href="#t442">442</a></span><span class="t">            <span class="nam">max_rule_count</span><span class="op">=</span><span class="nam">max_rule_count</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t443" href="#t443">443</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t444" href="#t444">444</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">contrast_attribute</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t445" href="#t445">445</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">model</span><span class="op">:</span> <span class="nam">RuleSet</span><span class="op">[</span><span class="nam">RegressionRule</span><span class="op">]</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t446" href="#t446">446</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t447" href="#t447">447</a></span><span class="t">    <span class="key">def</span> <span class="nam">fit</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">values</span><span class="op">:</span> <span class="nam">Data</span><span class="op">,</span> <span class="nam">labels</span><span class="op">:</span> <span class="nam">Data</span><span class="op">,</span> <span class="nam">contrast_attribute</span><span class="op">:</span> <span class="nam">str</span><span class="op">)</span> <span class="op">-></span> <span class="nam">ContrastSetRuleRegressor</span><span class="op">:</span>  <span class="com"># pylint: disable=arguments-differ</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t448" href="#t448">448</a></span><span class="t">        <span class="str">"""Train model on given dataset.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t449" href="#t449">449</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t450" href="#t450">450</a></span><span class="t"><span class="str">        Parameters</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t451" href="#t451">451</a></span><span class="t"><span class="str">        ----------</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t452" href="#t452">452</a></span><span class="t"><span class="str">        values : :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t453" href="#t453">453</a></span><span class="t"><span class="str">            attributes</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t454" href="#t454">454</a></span><span class="t"><span class="str">        labels : :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t455" href="#t455">455</a></span><span class="t"><span class="str">            target values</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t456" href="#t456">456</a></span><span class="t"><span class="str">        contrast_attribute: str</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t457" href="#t457">457</a></span><span class="t"><span class="str">            group attribute</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t458" href="#t458">458</a></span><span class="t"><span class="str">        Returns</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t459" href="#t459">459</a></span><span class="t"><span class="str">        -------</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t460" href="#t460">460</a></span><span class="t"><span class="str">        self : ContrastSetRuleRegressor</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t461" href="#t461">461</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t462" href="#t462">462</a></span><span class="t">        <span class="nam">RuleRegressor</span><span class="op">.</span><span class="nam">_validate_labels</span><span class="op">(</span>  <span class="com"># pylint: disable=protected-access</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t463" href="#t463">463</a></span><span class="t">            <span class="nam">self</span><span class="op">,</span> <span class="nam">labels</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t464" href="#t464">464</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t465" href="#t465">465</a></span><span class="t">        <span class="nam">super</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">fit</span><span class="op">(</span><span class="nam">values</span><span class="op">,</span> <span class="nam">labels</span><span class="op">,</span> <span class="nam">contrast_attribute</span><span class="op">=</span><span class="nam">contrast_attribute</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t466" href="#t466">466</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">contrast_attribute</span> <span class="op">=</span> <span class="nam">contrast_attribute</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t467" href="#t467">467</a></span><span class="t">        <span class="key">return</span> <span class="nam">self</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t468" href="#t468">468</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t469" href="#t469">469</a></span><span class="t">    <span class="key">def</span> <span class="nam">predict</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">values</span><span class="op">:</span> <span class="nam">Data</span><span class="op">)</span> <span class="op">-></span> <span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t470" href="#t470">470</a></span><span class="t">        <span class="str">"""Perform prediction and returns predicted values.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t471" href="#t471">471</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t472" href="#t472">472</a></span><span class="t"><span class="str">        Parameters</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t473" href="#t473">473</a></span><span class="t"><span class="str">        ----------</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t474" href="#t474">474</a></span><span class="t"><span class="str">        values : :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t475" href="#t475">475</a></span><span class="t"><span class="str">            attributes</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t476" href="#t476">476</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t477" href="#t477">477</a></span><span class="t"><span class="str">        Returns</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t478" href="#t478">478</a></span><span class="t"><span class="str">        -------</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t479" href="#t479">479</a></span><span class="t"><span class="str">        result : np.ndarray</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t480" href="#t480">480</a></span><span class="t"><span class="str">            predicted values</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t481" href="#t481">481</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t482" href="#t482">482</a></span><span class="t">        <span class="key">return</span> <span class="nam">RuleRegressor</span><span class="op">.</span><span class="nam">predict</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">values</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t483" href="#t483">483</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t484" href="#t484">484</a></span><span class="t">    <span class="key">def</span> <span class="nam">score</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">values</span><span class="op">:</span> <span class="nam">Data</span><span class="op">,</span> <span class="nam">labels</span><span class="op">:</span> <span class="nam">Data</span><span class="op">)</span> <span class="op">-></span> <span class="nam">float</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t485" href="#t485">485</a></span><span class="t">        <span class="str">"""Return the coefficient of determination R2 of the prediction</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t486" href="#t486">486</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t487" href="#t487">487</a></span><span class="t"><span class="str">        Parameters</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t488" href="#t488">488</a></span><span class="t"><span class="str">        ----------</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t489" href="#t489">489</a></span><span class="t"><span class="str">        values : :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t490" href="#t490">490</a></span><span class="t"><span class="str">            attributes</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t491" href="#t491">491</a></span><span class="t"><span class="str">        labels : :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t492" href="#t492">492</a></span><span class="t"><span class="str">            true target values</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t493" href="#t493">493</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t494" href="#t494">494</a></span><span class="t"><span class="str">        Returns</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t495" href="#t495">495</a></span><span class="t"><span class="str">        -------</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t496" href="#t496">496</a></span><span class="t"><span class="str">        score : float</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t497" href="#t497">497</a></span><span class="t"><span class="str">            R2 of self.predict(values) wrt. labels.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t498" href="#t498">498</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t499" href="#t499">499</a></span><span class="t">        <span class="key">return</span> <span class="nam">RuleRegressor</span><span class="op">.</span><span class="nam">score</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">values</span><span class="op">,</span> <span class="nam">labels</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t500" href="#t500">500</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t501" href="#t501">501</a></span><span class="t">    <span class="key">def</span> <span class="nam">__getstate__</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">dict</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t502" href="#t502">502</a></span><span class="t">        <span class="key">return</span> <span class="op">{</span><span class="op">**</span><span class="nam">BaseOperator</span><span class="op">.</span><span class="nam">__getstate__</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">,</span> <span class="op">**</span><span class="op">{</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t503" href="#t503">503</a></span><span class="t">            <span class="str">'contrast_attribute'</span><span class="op">:</span> <span class="nam">self</span><span class="op">.</span><span class="nam">contrast_attribute</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t504" href="#t504">504</a></span><span class="t">        <span class="op">}</span><span class="op">}</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t505" href="#t505">505</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t506" href="#t506">506</a></span><span class="t">    <span class="key">def</span> <span class="nam">__setstate__</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">state</span><span class="op">:</span> <span class="nam">dict</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t507" href="#t507">507</a></span><span class="t">        <span class="nam">BaseOperator</span><span class="op">.</span><span class="nam">__setstate__</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">state</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t508" href="#t508">508</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">contrast_attribute</span> <span class="op">=</span> <span class="nam">state</span><span class="op">[</span><span class="str">'contrast_attribute'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t509" href="#t509">509</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t510" href="#t510">510</a></span><span class="t">    <span class="key">def</span> <span class="nam">_get_problem_type</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">ProblemType</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t511" href="#t511">511</a></span><span class="t">        <span class="key">return</span> <span class="nam">ProblemType</span><span class="op">.</span><span class="nam">CONTRAST_REGRESSION</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t359" href="#t359">359</a></span><span class="t">    <span class="nam">__params_class__</span> <span class="op">=</span> <span class="nam">ContrastSetModelParams</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t360" href="#t360">360</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t361" href="#t361">361</a></span><span class="t">    <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span>  <span class="com"># pylint: disable=too-many-arguments,too-many-locals</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t362" href="#t362">362</a></span><span class="t">        <span class="nam">self</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t363" href="#t363">363</a></span><span class="t">        <span class="nam">minsupp_all</span><span class="op">:</span> <span class="nam">Tuple</span><span class="op">[</span><span class="nam">float</span><span class="op">,</span> <span class="nam">float</span><span class="op">,</span> <span class="nam">float</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t364" href="#t364">364</a></span><span class="t">                           <span class="nam">float</span><span class="op">]</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'minsupp_all'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t365" href="#t365">365</a></span><span class="t">        <span class="nam">max_neg2pos</span><span class="op">:</span> <span class="nam">float</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'max_neg2pos'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t366" href="#t366">366</a></span><span class="t">        <span class="nam">max_passes_count</span><span class="op">:</span> <span class="nam">int</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'max_passes_count'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t367" href="#t367">367</a></span><span class="t">        <span class="nam">penalty_strength</span><span class="op">:</span> <span class="nam">float</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'penalty_strength'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t368" href="#t368">368</a></span><span class="t">        <span class="nam">penalty_saturation</span><span class="op">:</span> <span class="nam">float</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'penalty_saturation'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t369" href="#t369">369</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t370" href="#t370">370</a></span><span class="t">        <span class="nam">minsupp_new</span><span class="op">:</span> <span class="nam">float</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'minsupp_new'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t371" href="#t371">371</a></span><span class="t">        <span class="nam">induction_measure</span><span class="op">:</span> <span class="nam">Measures</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'induction_measure'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t372" href="#t372">372</a></span><span class="t">        <span class="nam">pruning_measure</span><span class="op">:</span> <span class="nam">Union</span><span class="op">[</span><span class="nam">Measures</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t373" href="#t373">373</a></span><span class="t">                               <span class="nam">str</span><span class="op">]</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'pruning_measure'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t374" href="#t374">374</a></span><span class="t">        <span class="nam">voting_measure</span><span class="op">:</span> <span class="nam">Measures</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'voting_measure'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t375" href="#t375">375</a></span><span class="t">        <span class="nam">max_growing</span><span class="op">:</span> <span class="nam">float</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'max_growing'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t376" href="#t376">376</a></span><span class="t">        <span class="nam">enable_pruning</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'enable_pruning'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t377" href="#t377">377</a></span><span class="t">        <span class="nam">ignore_missing</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'ignore_missing'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t378" href="#t378">378</a></span><span class="t">        <span class="nam">max_uncovered_fraction</span><span class="op">:</span> <span class="nam">float</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'max_uncovered_fraction'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t379" href="#t379">379</a></span><span class="t">        <span class="nam">select_best_candidate</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'select_best_candidate'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t380" href="#t380">380</a></span><span class="t">        <span class="nam">complementary_conditions</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'complementary_conditions'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t381" href="#t381">381</a></span><span class="t">        <span class="nam">mean_based_regression</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'mean_based_regression'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t382" href="#t382">382</a></span><span class="t">        <span class="nam">max_rule_count</span><span class="op">:</span> <span class="nam">int</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'max_rule_count'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t383" href="#t383">383</a></span><span class="t">    <span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t384" href="#t384">384</a></span><span class="t">        <span class="str">"""</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t385" href="#t385">385</a></span><span class="t"><span class="str">        Parameters</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t386" href="#t386">386</a></span><span class="t"><span class="str">        ----------</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t387" href="#t387">387</a></span><span class="t"><span class="str">        minsupp_all: Tuple[float, float, float, float]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t388" href="#t388">388</a></span><span class="t"><span class="str">            a minimum positive support of a contrast set (p/P). When multiple values are specified,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t389" href="#t389">389</a></span><span class="t"><span class="str">            a metainduction is performed; Default and recommended sequence is: 0.8, 0.5, 0.2, 0.1</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t390" href="#t390">390</a></span><span class="t"><span class="str">        max_neg2pos: float</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t391" href="#t391">391</a></span><span class="t"><span class="str">            a maximum ratio of negative to positive supports (nP/pN); Default is 0.5</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t392" href="#t392">392</a></span><span class="t"><span class="str">        max_passes_count: int</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t393" href="#t393">393</a></span><span class="t"><span class="str">            a maximum number of sequential covering passes for a single minsupp-all; Default is 5</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t394" href="#t394">394</a></span><span class="t"><span class="str">        penalty_strength: float</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t395" href="#t395">395</a></span><span class="t"><span class="str">            (s) - penalty strength; Default is 0.5</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t396" href="#t396">396</a></span><span class="t"><span class="str">        penalty_saturation: float</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t397" href="#t397">397</a></span><span class="t"><span class="str">            the value of p_new / P at which penalty reward saturates; Default is 0.2.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t398" href="#t398">398</a></span><span class="t"><span class="str">        minsupp_new : float = 5.0</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t399" href="#t399">399</a></span><span class="t"><span class="str">            a minimum number (or fraction, if value &lt; 1.0) of previously uncovered examples</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t400" href="#t400">400</a></span><span class="t"><span class="str">             to be covered by a new rule (positive examples for classification problems); default: 5,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t401" href="#t401">401</a></span><span class="t"><span class="str">        induction_measure : :class:`rulekit.params.Measures` = \</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t402" href="#t402">402</a></span><span class="t"><span class="str">            :class:`rulekit.params.Measures.Correlation`</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t403" href="#t403">403</a></span><span class="t"><span class="str">            measure used during induction; default measure is correlation</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t404" href="#t404">404</a></span><span class="t"><span class="str">        pruning_measure : Union[:class:`rulekit.params.Measures`, str] = \</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t405" href="#t405">405</a></span><span class="t"><span class="str">            :class:`rulekit.params.Measures.Correlation`</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t406" href="#t406">406</a></span><span class="t"><span class="str">            measure used during pruning. Could be user defined (string), for example</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t407" href="#t407">407</a></span><span class="t"><span class="str">            :code:`2 * p / n`; default measure is correlation</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t408" href="#t408">408</a></span><span class="t"><span class="str">        voting_measure : :class:`rulekit.params.Measures` = \</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t409" href="#t409">409</a></span><span class="t"><span class="str">            :class:`rulekit.params.Measures.Correlation`</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t410" href="#t410">410</a></span><span class="t"><span class="str">            measure used during voting; default measure is correlation</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t411" href="#t411">411</a></span><span class="t"><span class="str">        max_growing : int = 0.0</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t412" href="#t412">412</a></span><span class="t"><span class="str">            non-negative integer representing maximum number of conditions which can be added to</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t413" href="#t413">413</a></span><span class="t"><span class="str">            the rule in the growing phase (use this parameter for large datasets if execution time</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t414" href="#t414">414</a></span><span class="t"><span class="str">            is prohibitive); 0 indicates no limit; default: 0,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t415" href="#t415">415</a></span><span class="t"><span class="str">        enable_pruning : bool = True</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t416" href="#t416">416</a></span><span class="t"><span class="str">            enable or disable pruning, default is True.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t417" href="#t417">417</a></span><span class="t"><span class="str">        ignore_missing : bool = False</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t418" href="#t418">418</a></span><span class="t"><span class="str">            boolean telling whether missing values should be ignored (by default, a missing value</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t419" href="#t419">419</a></span><span class="t"><span class="str">             of given attribute is always considered as not fulfilling the condition build upon that</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t420" href="#t420">420</a></span><span class="t"><span class="str">            attribute); default: False.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t421" href="#t421">421</a></span><span class="t"><span class="str">        max_uncovered_fraction : float = 0.0</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t422" href="#t422">422</a></span><span class="t"><span class="str">            Floating-point number from [0,1] interval representing maximum fraction of examples</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t423" href="#t423">423</a></span><span class="t"><span class="str">            that may remain uncovered by the rule set, default: 0.0.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t424" href="#t424">424</a></span><span class="t"><span class="str">        select_best_candidate : bool = False</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t425" href="#t425">425</a></span><span class="t"><span class="str">            Flag determining if best candidate should be selected from growing phase;</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t426" href="#t426">426</a></span><span class="t"><span class="str">            default: False.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t427" href="#t427">427</a></span><span class="t"><span class="str">        complementary_conditions : bool = False</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t428" href="#t428">428</a></span><span class="t"><span class="str">            If enabled, complementary conditions in the form a = !{value} for nominal attributes</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t429" href="#t429">429</a></span><span class="t"><span class="str">            are supported.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t430" href="#t430">430</a></span><span class="t"><span class="str">        mean_based_regression : bool = True</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t431" href="#t431">431</a></span><span class="t"><span class="str">            Enable fast induction of mean-based regression rules instead of default median-based.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t432" href="#t432">432</a></span><span class="t"><span class="str">        max_rule_count : int = 0</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t433" href="#t433">433</a></span><span class="t"><span class="str">            Maximum number of rules to be generated (for classification data sets it applies</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t434" href="#t434">434</a></span><span class="t"><span class="str">             to a single class); 0 indicates no limit.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t435" href="#t435">435</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t436" href="#t436">436</a></span><span class="t">        <span class="nam">super</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">__init__</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t437" href="#t437">437</a></span><span class="t">            <span class="nam">minsupp_all</span><span class="op">=</span><span class="nam">minsupp_all</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t438" href="#t438">438</a></span><span class="t">            <span class="nam">max_neg2pos</span><span class="op">=</span><span class="nam">max_neg2pos</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t439" href="#t439">439</a></span><span class="t">            <span class="nam">max_passes_count</span><span class="op">=</span><span class="nam">max_passes_count</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t440" href="#t440">440</a></span><span class="t">            <span class="nam">penalty_strength</span><span class="op">=</span><span class="nam">penalty_strength</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t441" href="#t441">441</a></span><span class="t">            <span class="nam">penalty_saturation</span><span class="op">=</span><span class="nam">penalty_saturation</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t442" href="#t442">442</a></span><span class="t">            <span class="nam">minsupp_new</span><span class="op">=</span><span class="nam">minsupp_new</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t443" href="#t443">443</a></span><span class="t">            <span class="nam">induction_measure</span><span class="op">=</span><span class="nam">induction_measure</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t444" href="#t444">444</a></span><span class="t">            <span class="nam">pruning_measure</span><span class="op">=</span><span class="nam">pruning_measure</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t445" href="#t445">445</a></span><span class="t">            <span class="nam">voting_measure</span><span class="op">=</span><span class="nam">voting_measure</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t446" href="#t446">446</a></span><span class="t">            <span class="nam">max_growing</span><span class="op">=</span><span class="nam">max_growing</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t447" href="#t447">447</a></span><span class="t">            <span class="nam">enable_pruning</span><span class="op">=</span><span class="nam">enable_pruning</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t448" href="#t448">448</a></span><span class="t">            <span class="nam">ignore_missing</span><span class="op">=</span><span class="nam">ignore_missing</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t449" href="#t449">449</a></span><span class="t">            <span class="nam">max_uncovered_fraction</span><span class="op">=</span><span class="nam">max_uncovered_fraction</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t450" href="#t450">450</a></span><span class="t">            <span class="nam">select_best_candidate</span><span class="op">=</span><span class="nam">select_best_candidate</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t451" href="#t451">451</a></span><span class="t">            <span class="nam">complementary_conditions</span><span class="op">=</span><span class="nam">complementary_conditions</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t452" href="#t452">452</a></span><span class="t">            <span class="nam">mean_based_regression</span><span class="op">=</span><span class="nam">mean_based_regression</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t453" href="#t453">453</a></span><span class="t">            <span class="nam">max_rule_count</span><span class="op">=</span><span class="nam">max_rule_count</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t454" href="#t454">454</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t455" href="#t455">455</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">contrast_attribute</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t456" href="#t456">456</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">model</span><span class="op">:</span> <span class="nam">RuleSet</span><span class="op">[</span><span class="nam">RegressionRule</span><span class="op">]</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t457" href="#t457">457</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t458" href="#t458">458</a></span><span class="t">    <span class="key">def</span> <span class="nam">fit</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">values</span><span class="op">:</span> <span class="nam">Data</span><span class="op">,</span> <span class="nam">labels</span><span class="op">:</span> <span class="nam">Data</span><span class="op">,</span> <span class="nam">contrast_attribute</span><span class="op">:</span> <span class="nam">str</span><span class="op">)</span> <span class="op">-></span> <span class="nam">ContrastSetRuleRegressor</span><span class="op">:</span>  <span class="com"># pylint: disable=arguments-differ</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t459" href="#t459">459</a></span><span class="t">        <span class="str">"""Train model on given dataset.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t460" href="#t460">460</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t461" href="#t461">461</a></span><span class="t"><span class="str">        Parameters</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t462" href="#t462">462</a></span><span class="t"><span class="str">        ----------</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t463" href="#t463">463</a></span><span class="t"><span class="str">        values : :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t464" href="#t464">464</a></span><span class="t"><span class="str">            attributes</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t465" href="#t465">465</a></span><span class="t"><span class="str">        labels : :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t466" href="#t466">466</a></span><span class="t"><span class="str">            target values</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t467" href="#t467">467</a></span><span class="t"><span class="str">        contrast_attribute: str</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t468" href="#t468">468</a></span><span class="t"><span class="str">            group attribute</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t469" href="#t469">469</a></span><span class="t"><span class="str">        Returns</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t470" href="#t470">470</a></span><span class="t"><span class="str">        -------</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t471" href="#t471">471</a></span><span class="t"><span class="str">        self : ContrastSetRuleRegressor</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t472" href="#t472">472</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t473" href="#t473">473</a></span><span class="t">        <span class="nam">RuleRegressor</span><span class="op">.</span><span class="nam">_validate_labels</span><span class="op">(</span>  <span class="com"># pylint: disable=protected-access</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t474" href="#t474">474</a></span><span class="t">            <span class="nam">self</span><span class="op">,</span> <span class="nam">labels</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t475" href="#t475">475</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t476" href="#t476">476</a></span><span class="t">        <span class="nam">super</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">fit</span><span class="op">(</span><span class="nam">values</span><span class="op">,</span> <span class="nam">labels</span><span class="op">,</span> <span class="nam">contrast_attribute</span><span class="op">=</span><span class="nam">contrast_attribute</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t477" href="#t477">477</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">contrast_attribute</span> <span class="op">=</span> <span class="nam">contrast_attribute</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t478" href="#t478">478</a></span><span class="t">        <span class="key">return</span> <span class="nam">self</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t479" href="#t479">479</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t480" href="#t480">480</a></span><span class="t">    <span class="key">def</span> <span class="nam">predict</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">values</span><span class="op">:</span> <span class="nam">Data</span><span class="op">)</span> <span class="op">-></span> <span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t481" href="#t481">481</a></span><span class="t">        <span class="str">"""Perform prediction and returns predicted values.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t482" href="#t482">482</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t483" href="#t483">483</a></span><span class="t"><span class="str">        Parameters</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t484" href="#t484">484</a></span><span class="t"><span class="str">        ----------</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t485" href="#t485">485</a></span><span class="t"><span class="str">        values : :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t486" href="#t486">486</a></span><span class="t"><span class="str">            attributes</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t487" href="#t487">487</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t488" href="#t488">488</a></span><span class="t"><span class="str">        Returns</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t489" href="#t489">489</a></span><span class="t"><span class="str">        -------</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t490" href="#t490">490</a></span><span class="t"><span class="str">        result : np.ndarray</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t491" href="#t491">491</a></span><span class="t"><span class="str">            predicted values</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t492" href="#t492">492</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t493" href="#t493">493</a></span><span class="t">        <span class="key">return</span> <span class="nam">RuleRegressor</span><span class="op">.</span><span class="nam">predict</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">values</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t494" href="#t494">494</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t495" href="#t495">495</a></span><span class="t">    <span class="key">def</span> <span class="nam">score</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">values</span><span class="op">:</span> <span class="nam">Data</span><span class="op">,</span> <span class="nam">labels</span><span class="op">:</span> <span class="nam">Data</span><span class="op">)</span> <span class="op">-></span> <span class="nam">float</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t496" href="#t496">496</a></span><span class="t">        <span class="str">"""Return the coefficient of determination R2 of the prediction</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t497" href="#t497">497</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t498" href="#t498">498</a></span><span class="t"><span class="str">        Parameters</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t499" href="#t499">499</a></span><span class="t"><span class="str">        ----------</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t500" href="#t500">500</a></span><span class="t"><span class="str">        values : :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t501" href="#t501">501</a></span><span class="t"><span class="str">            attributes</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t502" href="#t502">502</a></span><span class="t"><span class="str">        labels : :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t503" href="#t503">503</a></span><span class="t"><span class="str">            true target values</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t504" href="#t504">504</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t505" href="#t505">505</a></span><span class="t"><span class="str">        Returns</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t506" href="#t506">506</a></span><span class="t"><span class="str">        -------</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t507" href="#t507">507</a></span><span class="t"><span class="str">        score : float</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t508" href="#t508">508</a></span><span class="t"><span class="str">            R2 of self.predict(values) wrt. labels.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t509" href="#t509">509</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t510" href="#t510">510</a></span><span class="t">        <span class="key">return</span> <span class="nam">RuleRegressor</span><span class="op">.</span><span class="nam">score</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">values</span><span class="op">,</span> <span class="nam">labels</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t511" href="#t511">511</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t512" href="#t512">512</a></span><span class="t">    <span class="key">def</span> <span class="nam">__getstate__</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">dict</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t513" href="#t513">513</a></span><span class="t">        <span class="key">return</span> <span class="op">{</span><span class="op">**</span><span class="nam">BaseOperator</span><span class="op">.</span><span class="nam">__getstate__</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">,</span> <span class="op">**</span><span class="op">{</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t514" href="#t514">514</a></span><span class="t">            <span class="str">'contrast_attribute'</span><span class="op">:</span> <span class="nam">self</span><span class="op">.</span><span class="nam">contrast_attribute</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t515" href="#t515">515</a></span><span class="t">        <span class="op">}</span><span class="op">}</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t516" href="#t516">516</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t517" href="#t517">517</a></span><span class="t">    <span class="key">def</span> <span class="nam">__setstate__</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">state</span><span class="op">:</span> <span class="nam">dict</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t518" href="#t518">518</a></span><span class="t">        <span class="nam">BaseOperator</span><span class="op">.</span><span class="nam">__setstate__</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">state</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t519" href="#t519">519</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">contrast_attribute</span> <span class="op">=</span> <span class="nam">state</span><span class="op">[</span><span class="str">'contrast_attribute'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t520" href="#t520">520</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t521" href="#t521">521</a></span><span class="t">    <span class="key">def</span> <span class="nam">_get_problem_type</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">ProblemType</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t522" href="#t522">522</a></span><span class="t">        <span class="key">return</span> <span class="nam">ProblemType</span><span class="op">.</span><span class="nam">CONTRAST_REGRESSION</span>&nbsp;</span><span class="r"></span></p>
 </main>
 <footer>
     <div class="content">
@@ -600,7 +611,7 @@ <h2>
             <a class="nav" href="z_a87f2a4bb6695d91_rules_py.html">&#xbb; next</a>
             &nbsp; &nbsp; &nbsp;
             <a class="nav" href="https://coverage.readthedocs.io/en/7.6.4">coverage.py v7.6.4</a>,
-            created at 2024-11-08 14:43 +0100
+            created at 2024-11-28 11:55 +0100
         </p>
     </div>
 </footer>
diff --git a/docs/reports/coverage/z_a87f2a4bb6695d91_rules_py.html b/docs/reports/coverage/z_a87f2a4bb6695d91_rules_py.html
index bb96f77..bc453ff 100644
--- a/docs/reports/coverage/z_a87f2a4bb6695d91_rules_py.html
+++ b/docs/reports/coverage/z_a87f2a4bb6695d91_rules_py.html
@@ -54,8 +54,8 @@ <h1>
             </div>
         </aside>
         <h2>
-            <span class="text">149 statements &nbsp;</span>
-            <button type="button" class="run button_toggle_run" value="run" data-shortcut="r" title="Toggle lines run">128<span class="text"> run</span></button>
+            <span class="text">152 statements &nbsp;</span>
+            <button type="button" class="run button_toggle_run" value="run" data-shortcut="r" title="Toggle lines run">131<span class="text"> run</span></button>
             <button type="button" class="mis show_mis button_toggle_mis" value="mis" data-shortcut="m" title="Toggle lines missing">21<span class="text"> missing</span></button>
             <button type="button" class="exc show_exc button_toggle_exc" value="exc" data-shortcut="x" title="Toggle lines excluded">0<span class="text"> excluded</span></button>
         </h2>
@@ -65,7 +65,7 @@ <h2>
             <a id="nextFileLink" class="nav" href="z_a87f2a4bb6695d91_stats_py.html">&#xbb; next</a>
             &nbsp; &nbsp; &nbsp;
             <a class="nav" href="https://coverage.readthedocs.io/en/7.6.4">coverage.py v7.6.4</a>,
-            created at 2024-11-08 14:43 +0100
+            created at 2024-11-28 11:55 +0100
         </p>
         <aside class="hidden">
             <button type="button" class="button_next_chunk" data-shortcut="j"></button>
@@ -82,350 +82,354 @@ <h2>
 <main id="source">
     <p class="pln"><span class="n"><a id="t1" href="#t1">1</a></span><span class="t"><span class="str">"""Contains classes representing rules and rulesets.</span>&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t2" href="#t2">2</a></span><span class="t"><span class="str">"""</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t3" href="#t3">3</a></span><span class="t"><span class="key">from</span> <span class="nam">typing</span> <span class="key">import</span> <span class="nam">Generic</span><span class="op">,</span> <span class="nam">TypeVar</span><span class="op">,</span> <span class="nam">Union</span><span class="op">,</span> <span class="nam">get_origin</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t4" href="#t4">4</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t5" href="#t5">5</a></span><span class="t"><span class="key">import</span> <span class="nam">numpy</span> <span class="key">as</span> <span class="nam">np</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t6" href="#t6">6</a></span><span class="t"><span class="key">from</span> <span class="nam">jpype</span> <span class="key">import</span> <span class="nam">JObject</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t7" href="#t7">7</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t8" href="#t8">8</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">kaplan_meier</span> <span class="key">import</span> <span class="nam">KaplanMeierEstimator</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t9" href="#t9">9</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">params</span> <span class="key">import</span> <span class="nam">Measures</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t10" href="#t10">10</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">stats</span> <span class="key">import</span> <span class="nam">RuleSetStatistics</span><span class="op">,</span> <span class="nam">RuleStatistics</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t11" href="#t11">11</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t12" href="#t12">12</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t13" href="#t13">13</a></span><span class="t"><span class="key">class</span> <span class="nam">InductionParameters</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t14" href="#t14">14</a></span><span class="t">    <span class="str">"""Induction parameters.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t15" href="#t15">15</a></span><span class="t"><span class="str">    """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t16" href="#t16">16</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t17" href="#t17">17</a></span><span class="t">    <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">java_object</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t18" href="#t18">18</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_java_object</span> <span class="op">=</span> <span class="nam">java_object</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t3" href="#t3">3</a></span><span class="t"><span class="key">from</span> <span class="nam">typing</span> <span class="key">import</span> <span class="nam">Generic</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t4" href="#t4">4</a></span><span class="t"><span class="key">from</span> <span class="nam">typing</span> <span class="key">import</span> <span class="nam">TypeVar</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t5" href="#t5">5</a></span><span class="t"><span class="key">from</span> <span class="nam">typing</span> <span class="key">import</span> <span class="nam">Union</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t6" href="#t6">6</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t7" href="#t7">7</a></span><span class="t"><span class="key">import</span> <span class="nam">numpy</span> <span class="key">as</span> <span class="nam">np</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t8" href="#t8">8</a></span><span class="t"><span class="key">from</span> <span class="nam">jpype</span> <span class="key">import</span> <span class="nam">JObject</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t9" href="#t9">9</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t10" href="#t10">10</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">kaplan_meier</span> <span class="key">import</span> <span class="nam">KaplanMeierEstimator</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t11" href="#t11">11</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">params</span> <span class="key">import</span> <span class="nam">Measures</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t12" href="#t12">12</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">stats</span> <span class="key">import</span> <span class="nam">RuleSetStatistics</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t13" href="#t13">13</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">stats</span> <span class="key">import</span> <span class="nam">RuleStatistics</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t14" href="#t14">14</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t15" href="#t15">15</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t16" href="#t16">16</a></span><span class="t"><span class="key">class</span> <span class="nam">InductionParameters</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t17" href="#t17">17</a></span><span class="t">    <span class="str">"""Induction parameters.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t18" href="#t18">18</a></span><span class="t"><span class="str">    """</span>&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t19" href="#t19">19</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t20" href="#t20">20</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">minimum_covered</span><span class="op">:</span> <span class="nam">float</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_java_object</span><span class="op">.</span><span class="nam">getMinimumCovered</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t21" href="#t21">21</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">maximum_uncovered_fraction</span><span class="op">:</span> <span class="nam">float</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_java_object</span><span class="op">.</span><span class="nam">getMaximumUncoveredFraction</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t22" href="#t22">22</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">ignore_missing</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_java_object</span><span class="op">.</span><span class="nam">isIgnoreMissing</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t23" href="#t23">23</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">pruning_enabled</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_java_object</span><span class="op">.</span><span class="nam">isPruningEnabled</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t24" href="#t24">24</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">max_growing_condition</span><span class="op">:</span> <span class="nam">float</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_java_object</span><span class="op">.</span><span class="nam">getMaxGrowingConditions</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t25" href="#t25">25</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t26" href="#t26">26</a></span><span class="t">    <span class="op">@</span><span class="nam">property</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t27" href="#t27">27</a></span><span class="t">    <span class="key">def</span> <span class="nam">induction_measure</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">Union</span><span class="op">[</span><span class="nam">Measures</span><span class="op">,</span> <span class="nam">str</span><span class="op">]</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t28" href="#t28">28</a></span><span class="t">        <span class="str">"""</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t29" href="#t29">29</a></span><span class="t"><span class="str">        Returns:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t30" href="#t30">30</a></span><span class="t"><span class="str">            Union[Measures, str]: Measure used for induction</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t31" href="#t31">31</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t32" href="#t32">32</a></span><span class="t">        <span class="key">return</span> <span class="nam">InductionParameters</span><span class="op">.</span><span class="nam">_get_measure_str</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">_java_object</span><span class="op">.</span><span class="nam">getInductionMeasure</span><span class="op">(</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t33" href="#t33">33</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t34" href="#t34">34</a></span><span class="t">    <span class="op">@</span><span class="nam">property</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t35" href="#t35">35</a></span><span class="t">    <span class="key">def</span> <span class="nam">pruning_measure</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">Union</span><span class="op">[</span><span class="nam">Measures</span><span class="op">,</span> <span class="nam">str</span><span class="op">]</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t36" href="#t36">36</a></span><span class="t">        <span class="str">"""</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t37" href="#t37">37</a></span><span class="t"><span class="str">        Returns:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t38" href="#t38">38</a></span><span class="t"><span class="str">            Union[Measures, str]: Measure used for pruning</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t39" href="#t39">39</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t40" href="#t40">40</a></span><span class="t">        <span class="key">return</span> <span class="nam">InductionParameters</span><span class="op">.</span><span class="nam">_get_measure_str</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">_java_object</span><span class="op">.</span><span class="nam">getPruningMeasure</span><span class="op">(</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t41" href="#t41">41</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t42" href="#t42">42</a></span><span class="t">    <span class="op">@</span><span class="nam">property</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t43" href="#t43">43</a></span><span class="t">    <span class="key">def</span> <span class="nam">voting_measure</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">Union</span><span class="op">[</span><span class="nam">Measures</span><span class="op">,</span> <span class="nam">str</span><span class="op">]</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t44" href="#t44">44</a></span><span class="t">        <span class="str">"""</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t45" href="#t45">45</a></span><span class="t"><span class="str">        Returns:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t46" href="#t46">46</a></span><span class="t"><span class="str">            Union[Measures, str]: Measure used for voting</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t47" href="#t47">47</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t48" href="#t48">48</a></span><span class="t">        <span class="key">return</span> <span class="nam">InductionParameters</span><span class="op">.</span><span class="nam">_get_measure_str</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">_java_object</span><span class="op">.</span><span class="nam">getVotingMeasure</span><span class="op">(</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t49" href="#t49">49</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t50" href="#t50">50</a></span><span class="t">    <span class="op">@</span><span class="nam">staticmethod</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t51" href="#t51">51</a></span><span class="t">    <span class="key">def</span> <span class="nam">_get_measure_str</span><span class="op">(</span><span class="nam">measure</span><span class="op">)</span> <span class="op">-></span> <span class="nam">Union</span><span class="op">[</span><span class="nam">Measures</span><span class="op">,</span> <span class="nam">str</span><span class="op">]</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t52" href="#t52">52</a></span><span class="t">        <span class="nam">name</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="nam">measure</span><span class="op">.</span><span class="nam">getName</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t53" href="#t53">53</a></span><span class="t">        <span class="key">if</span> <span class="nam">name</span> <span class="op">==</span> <span class="str">'UserDefined'</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t54" href="#t54">54</a></span><span class="t">            <span class="key">return</span> <span class="str">'UserDefined'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t55" href="#t55">55</a></span><span class="t">        <span class="key">return</span> <span class="nam">Measures</span><span class="op">[</span><span class="nam">name</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t56" href="#t56">56</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t57" href="#t57">57</a></span><span class="t">    <span class="key">def</span> <span class="nam">__str__</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t58" href="#t58">58</a></span><span class="t">        <span class="key">return</span> <span class="nam">str</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">_java_object</span><span class="op">.</span><span class="nam">toString</span><span class="op">(</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t20" href="#t20">20</a></span><span class="t">    <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">java_object</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t21" href="#t21">21</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_java_object</span> <span class="op">=</span> <span class="nam">java_object</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t22" href="#t22">22</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t23" href="#t23">23</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">minimum_covered</span><span class="op">:</span> <span class="nam">float</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_java_object</span><span class="op">.</span><span class="nam">getMinimumCovered</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t24" href="#t24">24</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">maximum_uncovered_fraction</span><span class="op">:</span> <span class="nam">float</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_java_object</span><span class="op">.</span><span class="nam">getMaximumUncoveredFraction</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t25" href="#t25">25</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">ignore_missing</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_java_object</span><span class="op">.</span><span class="nam">isIgnoreMissing</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t26" href="#t26">26</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">pruning_enabled</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_java_object</span><span class="op">.</span><span class="nam">isPruningEnabled</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t27" href="#t27">27</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">max_growing_condition</span><span class="op">:</span> <span class="nam">float</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_java_object</span><span class="op">.</span><span class="nam">getMaxGrowingConditions</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t28" href="#t28">28</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t29" href="#t29">29</a></span><span class="t">    <span class="op">@</span><span class="nam">property</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t30" href="#t30">30</a></span><span class="t">    <span class="key">def</span> <span class="nam">induction_measure</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">Union</span><span class="op">[</span><span class="nam">Measures</span><span class="op">,</span> <span class="nam">str</span><span class="op">]</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t31" href="#t31">31</a></span><span class="t">        <span class="str">"""</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t32" href="#t32">32</a></span><span class="t"><span class="str">        Returns:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t33" href="#t33">33</a></span><span class="t"><span class="str">            Union[Measures, str]: Measure used for induction</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t34" href="#t34">34</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t35" href="#t35">35</a></span><span class="t">        <span class="key">return</span> <span class="nam">InductionParameters</span><span class="op">.</span><span class="nam">_get_measure_str</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">_java_object</span><span class="op">.</span><span class="nam">getInductionMeasure</span><span class="op">(</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t36" href="#t36">36</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t37" href="#t37">37</a></span><span class="t">    <span class="op">@</span><span class="nam">property</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t38" href="#t38">38</a></span><span class="t">    <span class="key">def</span> <span class="nam">pruning_measure</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">Union</span><span class="op">[</span><span class="nam">Measures</span><span class="op">,</span> <span class="nam">str</span><span class="op">]</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t39" href="#t39">39</a></span><span class="t">        <span class="str">"""</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t40" href="#t40">40</a></span><span class="t"><span class="str">        Returns:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t41" href="#t41">41</a></span><span class="t"><span class="str">            Union[Measures, str]: Measure used for pruning</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t42" href="#t42">42</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t43" href="#t43">43</a></span><span class="t">        <span class="key">return</span> <span class="nam">InductionParameters</span><span class="op">.</span><span class="nam">_get_measure_str</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">_java_object</span><span class="op">.</span><span class="nam">getPruningMeasure</span><span class="op">(</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t44" href="#t44">44</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t45" href="#t45">45</a></span><span class="t">    <span class="op">@</span><span class="nam">property</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t46" href="#t46">46</a></span><span class="t">    <span class="key">def</span> <span class="nam">voting_measure</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">Union</span><span class="op">[</span><span class="nam">Measures</span><span class="op">,</span> <span class="nam">str</span><span class="op">]</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t47" href="#t47">47</a></span><span class="t">        <span class="str">"""</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t48" href="#t48">48</a></span><span class="t"><span class="str">        Returns:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t49" href="#t49">49</a></span><span class="t"><span class="str">            Union[Measures, str]: Measure used for voting</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t50" href="#t50">50</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t51" href="#t51">51</a></span><span class="t">        <span class="key">return</span> <span class="nam">InductionParameters</span><span class="op">.</span><span class="nam">_get_measure_str</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">_java_object</span><span class="op">.</span><span class="nam">getVotingMeasure</span><span class="op">(</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t52" href="#t52">52</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t53" href="#t53">53</a></span><span class="t">    <span class="op">@</span><span class="nam">staticmethod</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t54" href="#t54">54</a></span><span class="t">    <span class="key">def</span> <span class="nam">_get_measure_str</span><span class="op">(</span><span class="nam">measure</span><span class="op">)</span> <span class="op">-></span> <span class="nam">Union</span><span class="op">[</span><span class="nam">Measures</span><span class="op">,</span> <span class="nam">str</span><span class="op">]</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t55" href="#t55">55</a></span><span class="t">        <span class="nam">name</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="nam">measure</span><span class="op">.</span><span class="nam">getName</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t56" href="#t56">56</a></span><span class="t">        <span class="key">if</span> <span class="nam">name</span> <span class="op">==</span> <span class="str">'UserDefined'</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t57" href="#t57">57</a></span><span class="t">            <span class="key">return</span> <span class="str">'UserDefined'</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t58" href="#t58">58</a></span><span class="t">        <span class="key">return</span> <span class="nam">Measures</span><span class="op">[</span><span class="nam">name</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t59" href="#t59">59</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t60" href="#t60">60</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t61" href="#t61">61</a></span><span class="t"><span class="key">class</span> <span class="nam">BaseRule</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t62" href="#t62">62</a></span><span class="t">    <span class="str">"""Base class representing single rule."""</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t60" href="#t60">60</a></span><span class="t">    <span class="key">def</span> <span class="nam">__str__</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t61" href="#t61">61</a></span><span class="t">        <span class="key">return</span> <span class="nam">str</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">_java_object</span><span class="op">.</span><span class="nam">toString</span><span class="op">(</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t62" href="#t62">62</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t63" href="#t63">63</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t64" href="#t64">64</a></span><span class="t">    <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">java_object</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t65" href="#t65">65</a></span><span class="t">        <span class="str">""":meta private:"""</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t66" href="#t66">66</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_java_object</span> <span class="op">=</span> <span class="nam">java_object</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t67" href="#t67">67</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_stats</span><span class="op">:</span> <span class="nam">RuleStatistics</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t68" href="#t68">68</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t69" href="#t69">69</a></span><span class="t">    <span class="op">@</span><span class="nam">property</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t70" href="#t70">70</a></span><span class="t">    <span class="key">def</span> <span class="nam">weight</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">float</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t71" href="#t71">71</a></span><span class="t">        <span class="str">"""Rule weight"""</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t72" href="#t72">72</a></span><span class="t">        <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_java_object</span><span class="op">.</span><span class="nam">getWeight</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t73" href="#t73">73</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t74" href="#t74">74</a></span><span class="t">    <span class="op">@</span><span class="nam">property</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t75" href="#t75">75</a></span><span class="t">    <span class="key">def</span> <span class="nam">weighted_p</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">float</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t76" href="#t76">76</a></span><span class="t">        <span class="str">"""Number of positives covered by the rule (accounting weights)."""</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t77" href="#t77">77</a></span><span class="t">        <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_java_object</span><span class="op">.</span><span class="nam">getWeighted_p</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t78" href="#t78">78</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t79" href="#t79">79</a></span><span class="t">    <span class="op">@</span><span class="nam">property</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t80" href="#t80">80</a></span><span class="t">    <span class="key">def</span> <span class="nam">weighted_n</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">float</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t81" href="#t81">81</a></span><span class="t">        <span class="str">"""Number of negatives covered by the rule (accounting weights)."""</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t82" href="#t82">82</a></span><span class="t">        <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_java_object</span><span class="op">.</span><span class="nam">getWeighted_n</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t83" href="#t83">83</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t84" href="#t84">84</a></span><span class="t">    <span class="op">@</span><span class="nam">property</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t85" href="#t85">85</a></span><span class="t">    <span class="key">def</span> <span class="nam">weighted_P</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">float</span><span class="op">:</span>  <span class="com"># pylint: disable=invalid-name</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t86" href="#t86">86</a></span><span class="t">        <span class="str">"""Number of positives in the training set (accounting weights)."""</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t87" href="#t87">87</a></span><span class="t">        <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_java_object</span><span class="op">.</span><span class="nam">getWeighted_P</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t88" href="#t88">88</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t89" href="#t89">89</a></span><span class="t">    <span class="op">@</span><span class="nam">property</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t90" href="#t90">90</a></span><span class="t">    <span class="key">def</span> <span class="nam">weighted_N</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">float</span><span class="op">:</span>  <span class="com"># pylint: disable=invalid-name</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t91" href="#t91">91</a></span><span class="t">        <span class="str">"""Number of negatives in the training set (accounting weights)."""</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t92" href="#t92">92</a></span><span class="t">        <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_java_object</span><span class="op">.</span><span class="nam">getWeighted_N</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t93" href="#t93">93</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t94" href="#t94">94</a></span><span class="t">    <span class="op">@</span><span class="nam">property</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t95" href="#t95">95</a></span><span class="t">    <span class="key">def</span> <span class="nam">pvalue</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">float</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t96" href="#t96">96</a></span><span class="t">        <span class="str">"""Rule significance."""</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t97" href="#t97">97</a></span><span class="t">        <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_java_object</span><span class="op">.</span><span class="nam">getPValue</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t98" href="#t98">98</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t99" href="#t99">99</a></span><span class="t">    <span class="op">@</span><span class="nam">property</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t100" href="#t100">100</a></span><span class="t">    <span class="key">def</span> <span class="nam">stats</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">RuleStatistics</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t101" href="#t101">101</a></span><span class="t">        <span class="str">"""Rule statistics."""</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t102" href="#t102">102</a></span><span class="t">        <span class="key">if</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_stats</span> <span class="key">is</span> <span class="key">None</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t103" href="#t103">103</a></span><span class="t">            <span class="nam">self</span><span class="op">.</span><span class="nam">_stats</span> <span class="op">=</span> <span class="nam">RuleStatistics</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t104" href="#t104">104</a></span><span class="t">        <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_stats</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t105" href="#t105">105</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t106" href="#t106">106</a></span><span class="t">    <span class="key">def</span> <span class="nam">get_covering_information</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">dict</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t107" href="#t107">107</a></span><span class="t">        <span class="str">"""Returns information about rule covering</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t64" href="#t64">64</a></span><span class="t"><span class="key">class</span> <span class="nam">BaseRule</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t65" href="#t65">65</a></span><span class="t">    <span class="str">"""Base class representing single rule."""</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t66" href="#t66">66</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t67" href="#t67">67</a></span><span class="t">    <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">java_object</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t68" href="#t68">68</a></span><span class="t">        <span class="str">""":meta private:"""</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t69" href="#t69">69</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_java_object</span> <span class="op">=</span> <span class="nam">java_object</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t70" href="#t70">70</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_stats</span><span class="op">:</span> <span class="nam">RuleStatistics</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t71" href="#t71">71</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t72" href="#t72">72</a></span><span class="t">    <span class="op">@</span><span class="nam">property</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t73" href="#t73">73</a></span><span class="t">    <span class="key">def</span> <span class="nam">weight</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">float</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t74" href="#t74">74</a></span><span class="t">        <span class="str">"""Rule weight"""</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t75" href="#t75">75</a></span><span class="t">        <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_java_object</span><span class="op">.</span><span class="nam">getWeight</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t76" href="#t76">76</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t77" href="#t77">77</a></span><span class="t">    <span class="op">@</span><span class="nam">property</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t78" href="#t78">78</a></span><span class="t">    <span class="key">def</span> <span class="nam">weighted_p</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">float</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t79" href="#t79">79</a></span><span class="t">        <span class="str">"""Number of positives covered by the rule (accounting weights)."""</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t80" href="#t80">80</a></span><span class="t">        <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_java_object</span><span class="op">.</span><span class="nam">getWeighted_p</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t81" href="#t81">81</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t82" href="#t82">82</a></span><span class="t">    <span class="op">@</span><span class="nam">property</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t83" href="#t83">83</a></span><span class="t">    <span class="key">def</span> <span class="nam">weighted_n</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">float</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t84" href="#t84">84</a></span><span class="t">        <span class="str">"""Number of negatives covered by the rule (accounting weights)."""</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t85" href="#t85">85</a></span><span class="t">        <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_java_object</span><span class="op">.</span><span class="nam">getWeighted_n</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t86" href="#t86">86</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t87" href="#t87">87</a></span><span class="t">    <span class="op">@</span><span class="nam">property</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t88" href="#t88">88</a></span><span class="t">    <span class="key">def</span> <span class="nam">weighted_P</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">float</span><span class="op">:</span>  <span class="com"># pylint: disable=invalid-name</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t89" href="#t89">89</a></span><span class="t">        <span class="str">"""Number of positives in the training set (accounting weights)."""</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t90" href="#t90">90</a></span><span class="t">        <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_java_object</span><span class="op">.</span><span class="nam">getWeighted_P</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t91" href="#t91">91</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t92" href="#t92">92</a></span><span class="t">    <span class="op">@</span><span class="nam">property</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t93" href="#t93">93</a></span><span class="t">    <span class="key">def</span> <span class="nam">weighted_N</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">float</span><span class="op">:</span>  <span class="com"># pylint: disable=invalid-name</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t94" href="#t94">94</a></span><span class="t">        <span class="str">"""Number of negatives in the training set (accounting weights)."""</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t95" href="#t95">95</a></span><span class="t">        <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_java_object</span><span class="op">.</span><span class="nam">getWeighted_N</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t96" href="#t96">96</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t97" href="#t97">97</a></span><span class="t">    <span class="op">@</span><span class="nam">property</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t98" href="#t98">98</a></span><span class="t">    <span class="key">def</span> <span class="nam">pvalue</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">float</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t99" href="#t99">99</a></span><span class="t">        <span class="str">"""Rule significance."""</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t100" href="#t100">100</a></span><span class="t">        <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_java_object</span><span class="op">.</span><span class="nam">getPValue</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t101" href="#t101">101</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t102" href="#t102">102</a></span><span class="t">    <span class="op">@</span><span class="nam">property</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t103" href="#t103">103</a></span><span class="t">    <span class="key">def</span> <span class="nam">stats</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">RuleStatistics</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t104" href="#t104">104</a></span><span class="t">        <span class="str">"""Rule statistics."""</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t105" href="#t105">105</a></span><span class="t">        <span class="key">if</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_stats</span> <span class="key">is</span> <span class="key">None</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t106" href="#t106">106</a></span><span class="t">            <span class="nam">self</span><span class="op">.</span><span class="nam">_stats</span> <span class="op">=</span> <span class="nam">RuleStatistics</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t107" href="#t107">107</a></span><span class="t">        <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_stats</span>&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t108" href="#t108">108</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t109" href="#t109">109</a></span><span class="t"><span class="str">        Returns</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t110" href="#t110">110</a></span><span class="t"><span class="str">        -------</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t111" href="#t111">111</a></span><span class="t"><span class="str">        covering_data : dict</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t112" href="#t112">112</a></span><span class="t"><span class="str">            Dictionary containing covering information.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t113" href="#t113">113</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t114" href="#t114">114</a></span><span class="t">        <span class="key">return</span> <span class="op">{</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t115" href="#t115">115</a></span><span class="t">            <span class="str">'weighted_n'</span><span class="op">:</span> <span class="nam">self</span><span class="op">.</span><span class="nam">weighted_n</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t116" href="#t116">116</a></span><span class="t">            <span class="str">'weighted_p'</span><span class="op">:</span> <span class="nam">self</span><span class="op">.</span><span class="nam">weighted_p</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t117" href="#t117">117</a></span><span class="t">            <span class="str">'weighted_N'</span><span class="op">:</span> <span class="nam">self</span><span class="op">.</span><span class="nam">weighted_N</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t118" href="#t118">118</a></span><span class="t">            <span class="str">'weighted_P'</span><span class="op">:</span> <span class="nam">self</span><span class="op">.</span><span class="nam">weighted_P</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t119" href="#t119">119</a></span><span class="t">        <span class="op">}</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t120" href="#t120">120</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t121" href="#t121">121</a></span><span class="t">    <span class="key">def</span> <span class="nam">print_stats</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t122" href="#t122">122</a></span><span class="t">        <span class="str">"""Prints rule statistics as formatted text."""</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t123" href="#t123">123</a></span><span class="t">        <span class="nam">print</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">stats</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t124" href="#t124">124</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t125" href="#t125">125</a></span><span class="t">    <span class="key">def</span> <span class="nam">__str__</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t126" href="#t126">126</a></span><span class="t">        <span class="str">"""Returns string representation of the rule."""</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t127" href="#t127">127</a></span><span class="t">        <span class="key">return</span> <span class="nam">str</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">_java_object</span><span class="op">.</span><span class="nam">toString</span><span class="op">(</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t128" href="#t128">128</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t129" href="#t129">129</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t130" href="#t130">130</a></span><span class="t"><span class="key">class</span> <span class="nam">ClassificationRule</span><span class="op">(</span><span class="nam">BaseRule</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t131" href="#t131">131</a></span><span class="t">    <span class="str">"""Class representing classification rule</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t132" href="#t132">132</a></span><span class="t"><span class="str">    """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t133" href="#t133">133</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t134" href="#t134">134</a></span><span class="t">    <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">java_object</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t135" href="#t135">135</a></span><span class="t">        <span class="nam">super</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">__init__</span><span class="op">(</span><span class="nam">java_object</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t109" href="#t109">109</a></span><span class="t">    <span class="key">def</span> <span class="nam">get_covering_information</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">dict</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t110" href="#t110">110</a></span><span class="t">        <span class="str">"""Returns information about rule covering</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t111" href="#t111">111</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t112" href="#t112">112</a></span><span class="t"><span class="str">        Returns</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t113" href="#t113">113</a></span><span class="t"><span class="str">        -------</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t114" href="#t114">114</a></span><span class="t"><span class="str">        covering_data : dict</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t115" href="#t115">115</a></span><span class="t"><span class="str">            Dictionary containing covering information.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t116" href="#t116">116</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t117" href="#t117">117</a></span><span class="t">        <span class="key">return</span> <span class="op">{</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t118" href="#t118">118</a></span><span class="t">            <span class="str">'weighted_n'</span><span class="op">:</span> <span class="nam">self</span><span class="op">.</span><span class="nam">weighted_n</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t119" href="#t119">119</a></span><span class="t">            <span class="str">'weighted_p'</span><span class="op">:</span> <span class="nam">self</span><span class="op">.</span><span class="nam">weighted_p</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t120" href="#t120">120</a></span><span class="t">            <span class="str">'weighted_N'</span><span class="op">:</span> <span class="nam">self</span><span class="op">.</span><span class="nam">weighted_N</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t121" href="#t121">121</a></span><span class="t">            <span class="str">'weighted_P'</span><span class="op">:</span> <span class="nam">self</span><span class="op">.</span><span class="nam">weighted_P</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t122" href="#t122">122</a></span><span class="t">        <span class="op">}</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t123" href="#t123">123</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t124" href="#t124">124</a></span><span class="t">    <span class="key">def</span> <span class="nam">print_stats</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t125" href="#t125">125</a></span><span class="t">        <span class="str">"""Prints rule statistics as formatted text."""</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t126" href="#t126">126</a></span><span class="t">        <span class="nam">print</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">stats</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t127" href="#t127">127</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t128" href="#t128">128</a></span><span class="t">    <span class="key">def</span> <span class="nam">__str__</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t129" href="#t129">129</a></span><span class="t">        <span class="str">"""Returns string representation of the rule."""</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t130" href="#t130">130</a></span><span class="t">        <span class="key">return</span> <span class="nam">str</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">_java_object</span><span class="op">.</span><span class="nam">toString</span><span class="op">(</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t131" href="#t131">131</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t132" href="#t132">132</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t133" href="#t133">133</a></span><span class="t"><span class="key">class</span> <span class="nam">ClassificationRule</span><span class="op">(</span><span class="nam">BaseRule</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t134" href="#t134">134</a></span><span class="t">    <span class="str">"""Class representing classification rule</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t135" href="#t135">135</a></span><span class="t"><span class="str">    """</span>&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t136" href="#t136">136</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t137" href="#t137">137</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_decision_class</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="nam">str</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">_java_object</span><span class="op">.</span><span class="nam">getClassLabel</span><span class="op">(</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t138" href="#t138">138</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t139" href="#t139">139</a></span><span class="t">    <span class="op">@</span><span class="nam">property</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t140" href="#t140">140</a></span><span class="t">    <span class="key">def</span> <span class="nam">decision_class</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">str</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t141" href="#t141">141</a></span><span class="t">        <span class="str">"""Decision class of the rule</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t142" href="#t142">142</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t143" href="#t143">143</a></span><span class="t">        <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_decision_class</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t144" href="#t144">144</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t145" href="#t145">145</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t146" href="#t146">146</a></span><span class="t"><span class="key">class</span> <span class="nam">RegressionRule</span><span class="op">(</span><span class="nam">BaseRule</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t147" href="#t147">147</a></span><span class="t">    <span class="str">"""Class representing regression rule</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t148" href="#t148">148</a></span><span class="t"><span class="str">    """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t149" href="#t149">149</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t150" href="#t150">150</a></span><span class="t">    <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">java_object</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t151" href="#t151">151</a></span><span class="t">        <span class="nam">super</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">__init__</span><span class="op">(</span><span class="nam">java_object</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t137" href="#t137">137</a></span><span class="t">    <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">java_object</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t138" href="#t138">138</a></span><span class="t">        <span class="nam">super</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">__init__</span><span class="op">(</span><span class="nam">java_object</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t139" href="#t139">139</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t140" href="#t140">140</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_decision_class</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="nam">str</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">_java_object</span><span class="op">.</span><span class="nam">getClassLabel</span><span class="op">(</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t141" href="#t141">141</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t142" href="#t142">142</a></span><span class="t">    <span class="op">@</span><span class="nam">property</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t143" href="#t143">143</a></span><span class="t">    <span class="key">def</span> <span class="nam">decision_class</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">str</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t144" href="#t144">144</a></span><span class="t">        <span class="str">"""Decision class of the rule</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t145" href="#t145">145</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t146" href="#t146">146</a></span><span class="t">        <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_decision_class</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t147" href="#t147">147</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t148" href="#t148">148</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t149" href="#t149">149</a></span><span class="t"><span class="key">class</span> <span class="nam">RegressionRule</span><span class="op">(</span><span class="nam">BaseRule</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t150" href="#t150">150</a></span><span class="t">    <span class="str">"""Class representing regression rule</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t151" href="#t151">151</a></span><span class="t"><span class="str">    """</span>&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t152" href="#t152">152</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t153" href="#t153">153</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_conclusion_value</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="nam">float</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t154" href="#t154">154</a></span><span class="t">            <span class="nam">self</span><span class="op">.</span><span class="nam">_java_object</span><span class="op">.</span><span class="nam">getConsequenceValue</span><span class="op">(</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t153" href="#t153">153</a></span><span class="t">    <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">java_object</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t154" href="#t154">154</a></span><span class="t">        <span class="nam">super</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">__init__</span><span class="op">(</span><span class="nam">java_object</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t155" href="#t155">155</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t156" href="#t156">156</a></span><span class="t">    <span class="op">@</span><span class="nam">property</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t157" href="#t157">157</a></span><span class="t">    <span class="key">def</span> <span class="nam">conclusion_value</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">float</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t158" href="#t158">158</a></span><span class="t">        <span class="str">"""Value from the rule's conclusion</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t159" href="#t159">159</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t160" href="#t160">160</a></span><span class="t">        <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_conclusion_value</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t161" href="#t161">161</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t162" href="#t162">162</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t163" href="#t163">163</a></span><span class="t"><span class="key">class</span> <span class="nam">SurvivalRule</span><span class="op">(</span><span class="nam">BaseRule</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t164" href="#t164">164</a></span><span class="t">    <span class="str">"""Class representing survival rule</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t165" href="#t165">165</a></span><span class="t"><span class="str">    """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t166" href="#t166">166</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t167" href="#t167">167</a></span><span class="t">    <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">java_object</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t168" href="#t168">168</a></span><span class="t">        <span class="nam">super</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">__init__</span><span class="op">(</span><span class="nam">java_object</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t156" href="#t156">156</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_conclusion_value</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="nam">float</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t157" href="#t157">157</a></span><span class="t">            <span class="nam">self</span><span class="op">.</span><span class="nam">_java_object</span><span class="op">.</span><span class="nam">getConsequenceValue</span><span class="op">(</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t158" href="#t158">158</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t159" href="#t159">159</a></span><span class="t">    <span class="op">@</span><span class="nam">property</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t160" href="#t160">160</a></span><span class="t">    <span class="key">def</span> <span class="nam">conclusion_value</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">float</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t161" href="#t161">161</a></span><span class="t">        <span class="str">"""Value from the rule's conclusion</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t162" href="#t162">162</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t163" href="#t163">163</a></span><span class="t">        <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_conclusion_value</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t164" href="#t164">164</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t165" href="#t165">165</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t166" href="#t166">166</a></span><span class="t"><span class="key">class</span> <span class="nam">SurvivalRule</span><span class="op">(</span><span class="nam">BaseRule</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t167" href="#t167">167</a></span><span class="t">    <span class="str">"""Class representing survival rule</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t168" href="#t168">168</a></span><span class="t"><span class="str">    """</span>&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t169" href="#t169">169</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t170" href="#t170">170</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_kaplan_meier_estimator</span><span class="op">:</span> <span class="nam">KaplanMeierEstimator</span> <span class="op">=</span> <span class="nam">KaplanMeierEstimator</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t171" href="#t171">171</a></span><span class="t">            <span class="nam">java_object</span><span class="op">.</span><span class="nam">getEstimator</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t172" href="#t172">172</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t173" href="#t173">173</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t174" href="#t174">174</a></span><span class="t">    <span class="op">@</span><span class="nam">property</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t175" href="#t175">175</a></span><span class="t">    <span class="key">def</span> <span class="nam">kaplan_meier_estimator</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">KaplanMeierEstimator</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t176" href="#t176">176</a></span><span class="t">        <span class="str">"""Kaplan-Meier estimator from the rule concslusion</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t177" href="#t177">177</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t178" href="#t178">178</a></span><span class="t">        <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_kaplan_meier_estimator</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t179" href="#t179">179</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t180" href="#t180">180</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t181" href="#t181">181</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t182" href="#t182">182</a></span><span class="t"><span class="key">def</span> <span class="nam">_rule_factory</span><span class="op">(</span><span class="nam">java_object</span><span class="op">:</span> <span class="nam">JObject</span><span class="op">)</span> <span class="op">-></span> <span class="nam">BaseRule</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t183" href="#t183">183</a></span><span class="t">    <span class="nam">class_name</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="nam">str</span><span class="op">(</span><span class="nam">java_object</span><span class="op">.</span><span class="nam">getClass</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">getName</span><span class="op">(</span><span class="op">)</span><span class="op">)</span><span class="op">.</span><span class="nam">lower</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t184" href="#t184">184</a></span><span class="t">    <span class="key">if</span> <span class="str">'regression'</span> <span class="key">in</span> <span class="nam">class_name</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t185" href="#t185">185</a></span><span class="t">        <span class="key">return</span> <span class="nam">RegressionRule</span><span class="op">(</span><span class="nam">java_object</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t186" href="#t186">186</a></span><span class="t">    <span class="key">elif</span> <span class="str">'survival'</span> <span class="key">in</span> <span class="nam">class_name</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t187" href="#t187">187</a></span><span class="t">        <span class="key">return</span> <span class="nam">SurvivalRule</span><span class="op">(</span><span class="nam">java_object</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t188" href="#t188">188</a></span><span class="t">    <span class="key">return</span> <span class="nam">ClassificationRule</span><span class="op">(</span><span class="nam">java_object</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t189" href="#t189">189</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t190" href="#t190">190</a></span><span class="t"><span class="nam">T</span> <span class="op">=</span> <span class="nam">TypeVar</span><span class="op">(</span><span class="str">'T'</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t170" href="#t170">170</a></span><span class="t">    <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">java_object</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t171" href="#t171">171</a></span><span class="t">        <span class="nam">super</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">__init__</span><span class="op">(</span><span class="nam">java_object</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t172" href="#t172">172</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t173" href="#t173">173</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_kaplan_meier_estimator</span><span class="op">:</span> <span class="nam">KaplanMeierEstimator</span> <span class="op">=</span> <span class="nam">KaplanMeierEstimator</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t174" href="#t174">174</a></span><span class="t">            <span class="nam">java_object</span><span class="op">.</span><span class="nam">getEstimator</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t175" href="#t175">175</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t176" href="#t176">176</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t177" href="#t177">177</a></span><span class="t">    <span class="op">@</span><span class="nam">property</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t178" href="#t178">178</a></span><span class="t">    <span class="key">def</span> <span class="nam">kaplan_meier_estimator</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">KaplanMeierEstimator</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t179" href="#t179">179</a></span><span class="t">        <span class="str">"""Kaplan-Meier estimator from the rule concslusion</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t180" href="#t180">180</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t181" href="#t181">181</a></span><span class="t">        <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_kaplan_meier_estimator</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t182" href="#t182">182</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t183" href="#t183">183</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t184" href="#t184">184</a></span><span class="t"><span class="key">def</span> <span class="nam">_rule_factory</span><span class="op">(</span><span class="nam">java_object</span><span class="op">:</span> <span class="nam">JObject</span><span class="op">)</span> <span class="op">-></span> <span class="nam">BaseRule</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t185" href="#t185">185</a></span><span class="t">    <span class="nam">class_name</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="nam">str</span><span class="op">(</span><span class="nam">java_object</span><span class="op">.</span><span class="nam">getClass</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">getName</span><span class="op">(</span><span class="op">)</span><span class="op">)</span><span class="op">.</span><span class="nam">lower</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t186" href="#t186">186</a></span><span class="t">    <span class="key">if</span> <span class="str">'regression'</span> <span class="key">in</span> <span class="nam">class_name</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t187" href="#t187">187</a></span><span class="t">        <span class="key">return</span> <span class="nam">RegressionRule</span><span class="op">(</span><span class="nam">java_object</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t188" href="#t188">188</a></span><span class="t">    <span class="key">elif</span> <span class="str">'survival'</span> <span class="key">in</span> <span class="nam">class_name</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t189" href="#t189">189</a></span><span class="t">        <span class="key">return</span> <span class="nam">SurvivalRule</span><span class="op">(</span><span class="nam">java_object</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t190" href="#t190">190</a></span><span class="t">    <span class="key">return</span> <span class="nam">ClassificationRule</span><span class="op">(</span><span class="nam">java_object</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t191" href="#t191">191</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t192" href="#t192">192</a></span><span class="t"><span class="key">class</span> <span class="nam">RuleSet</span><span class="op">(</span><span class="nam">Generic</span><span class="op">[</span><span class="nam">T</span><span class="op">]</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t193" href="#t193">193</a></span><span class="t">    <span class="str">"""Class representing ruleset."""</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t192" href="#t192">192</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t193" href="#t193">193</a></span><span class="t"><span class="nam">T</span> <span class="op">=</span> <span class="nam">TypeVar</span><span class="op">(</span><span class="str">'T'</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t194" href="#t194">194</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t195" href="#t195">195</a></span><span class="t">    <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">java_object</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t196" href="#t196">196</a></span><span class="t">        <span class="str">""":meta private:"""</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t197" href="#t197">197</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_java_object</span> <span class="op">=</span> <span class="nam">java_object</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t198" href="#t198">198</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_stats</span><span class="op">:</span> <span class="nam">RuleSetStatistics</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t199" href="#t199">199</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t200" href="#t200">200</a></span><span class="t">    <span class="op">@</span><span class="nam">property</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t201" href="#t201">201</a></span><span class="t">    <span class="key">def</span> <span class="nam">total_time</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">float</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t202" href="#t202">202</a></span><span class="t">        <span class="str">"""Time of constructing the rule set in seconds"""</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t203" href="#t203">203</a></span><span class="t">        <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_java_object</span><span class="op">.</span><span class="nam">getTotalTime</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t204" href="#t204">204</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t205" href="#t205">205</a></span><span class="t">    <span class="op">@</span><span class="nam">property</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t206" href="#t206">206</a></span><span class="t">    <span class="key">def</span> <span class="nam">growing_time</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">float</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t207" href="#t207">207</a></span><span class="t">        <span class="str">"""Time of growing in seconds"""</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t208" href="#t208">208</a></span><span class="t">        <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_java_object</span><span class="op">.</span><span class="nam">getGrowingTime</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t209" href="#t209">209</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t210" href="#t210">210</a></span><span class="t">    <span class="op">@</span><span class="nam">property</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t211" href="#t211">211</a></span><span class="t">    <span class="key">def</span> <span class="nam">pruning_time</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">float</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t212" href="#t212">212</a></span><span class="t">        <span class="str">"""Time of pruning in seconds"""</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t213" href="#t213">213</a></span><span class="t">        <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_java_object</span><span class="op">.</span><span class="nam">getPruningTime</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t214" href="#t214">214</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t215" href="#t215">215</a></span><span class="t">    <span class="op">@</span><span class="nam">property</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t216" href="#t216">216</a></span><span class="t">    <span class="key">def</span> <span class="nam">is_voting</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">bool</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t217" href="#t217">217</a></span><span class="t">        <span class="str">"""Value indicating whether rules are voting."""</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t218" href="#t218">218</a></span><span class="t">        <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_java_object</span><span class="op">.</span><span class="nam">getIsVoting</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t219" href="#t219">219</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t220" href="#t220">220</a></span><span class="t">    <span class="op">@</span><span class="nam">property</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t221" href="#t221">221</a></span><span class="t">    <span class="key">def</span> <span class="nam">parameters</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">object</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t222" href="#t222">222</a></span><span class="t">        <span class="str">"""Parameters used during rule set induction."""</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t223" href="#t223">223</a></span><span class="t">        <span class="key">return</span> <span class="nam">InductionParameters</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">_java_object</span><span class="op">.</span><span class="nam">getParams</span><span class="op">(</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t224" href="#t224">224</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t225" href="#t225">225</a></span><span class="t">    <span class="op">@</span><span class="nam">property</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t226" href="#t226">226</a></span><span class="t">    <span class="key">def</span> <span class="nam">stats</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">RuleSetStatistics</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t227" href="#t227">227</a></span><span class="t">        <span class="str">"""Rule set statistics."""</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t228" href="#t228">228</a></span><span class="t">        <span class="key">if</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_stats</span> <span class="key">is</span> <span class="key">None</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t229" href="#t229">229</a></span><span class="t">            <span class="nam">self</span><span class="op">.</span><span class="nam">_stats</span> <span class="op">=</span> <span class="nam">RuleSetStatistics</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t230" href="#t230">230</a></span><span class="t">        <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_stats</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t231" href="#t231">231</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t232" href="#t232">232</a></span><span class="t">    <span class="key">def</span> <span class="nam">covering</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">example_set</span><span class="op">)</span> <span class="op">-></span> <span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t233" href="#t233">233</a></span><span class="t">        <span class="str">""":meta private:"""</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t234" href="#t234">234</a></span><span class="t">        <span class="nam">res</span> <span class="op">=</span> <span class="op">[</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t235" href="#t235">235</a></span><span class="t">        <span class="key">for</span> <span class="nam">rule</span> <span class="key">in</span> <span class="nam">self</span><span class="op">.</span><span class="nam">rules</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t236" href="#t236">236</a></span><span class="t">            <span class="nam">covering_info</span> <span class="op">=</span> <span class="nam">rule</span><span class="op">.</span><span class="nam">_java_object</span><span class="op">.</span><span class="nam">coversUnlabelled</span><span class="op">(</span>  <span class="com"># pylint: disable=protected-access</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t237" href="#t237">237</a></span><span class="t">                <span class="nam">example_set</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t238" href="#t238">238</a></span><span class="t">            <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t239" href="#t239">239</a></span><span class="t">            <span class="nam">covered_examples_indexes</span> <span class="op">=</span> <span class="op">[</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t240" href="#t240">240</a></span><span class="t">            <span class="nam">covered_examples_indexes</span> <span class="op">+=</span> <span class="nam">covering_info</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t241" href="#t241">241</a></span><span class="t">            <span class="nam">res</span><span class="op">.</span><span class="nam">append</span><span class="op">(</span><span class="nam">covered_examples_indexes</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t242" href="#t242">242</a></span><span class="t">        <span class="key">return</span> <span class="nam">np</span><span class="op">.</span><span class="nam">array</span><span class="op">(</span><span class="nam">res</span><span class="op">,</span> <span class="nam">dtype</span><span class="op">=</span><span class="nam">object</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t243" href="#t243">243</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t244" href="#t244">244</a></span><span class="t">    <span class="op">@</span><span class="nam">property</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t245" href="#t245">245</a></span><span class="t">    <span class="key">def</span> <span class="nam">rules</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">list</span><span class="op">[</span><span class="nam">T</span><span class="op">]</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t246" href="#t246">246</a></span><span class="t">        <span class="str">"""List of rules objects."""</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t247" href="#t247">247</a></span><span class="t">        <span class="key">return</span> <span class="op">[</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t248" href="#t248">248</a></span><span class="t">            <span class="nam">_rule_factory</span><span class="op">(</span><span class="nam">java_rule</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t249" href="#t249">249</a></span><span class="t">            <span class="key">for</span> <span class="nam">java_rule</span> <span class="key">in</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_java_object</span><span class="op">.</span><span class="nam">getRules</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t250" href="#t250">250</a></span><span class="t">        <span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t251" href="#t251">251</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t252" href="#t252">252</a></span><span class="t">    <span class="key">def</span> <span class="nam">calculate_conditions_count</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">float</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t253" href="#t253">253</a></span><span class="t">        <span class="str">"""</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t254" href="#t254">254</a></span><span class="t"><span class="str">        Returns</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t255" href="#t255">255</a></span><span class="t"><span class="str">        -------</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t256" href="#t256">256</a></span><span class="t"><span class="str">        count: float</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t257" href="#t257">257</a></span><span class="t"><span class="str">            Number of conditions.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t258" href="#t258">258</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t259" href="#t259">259</a></span><span class="t">        <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_java_object</span><span class="op">.</span><span class="nam">calculateConditionsCount</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t260" href="#t260">260</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t261" href="#t261">261</a></span><span class="t">    <span class="key">def</span> <span class="nam">calculate_induced_conditions_count</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">float</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t262" href="#t262">262</a></span><span class="t">        <span class="str">"""</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t263" href="#t263">263</a></span><span class="t"><span class="str">        Returns</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t264" href="#t264">264</a></span><span class="t"><span class="str">        -------</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t265" href="#t265">265</a></span><span class="t"><span class="str">        count: float</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t266" href="#t266">266</a></span><span class="t"><span class="str">            Number of induced conditions.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t267" href="#t267">267</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t268" href="#t268">268</a></span><span class="t">        <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_java_object</span><span class="op">.</span><span class="nam">calculateInducedCondtionsCount</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t269" href="#t269">269</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t270" href="#t270">270</a></span><span class="t">    <span class="key">def</span> <span class="nam">calculate_avg_rule_coverage</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">float</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t271" href="#t271">271</a></span><span class="t">        <span class="str">"""</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t272" href="#t272">272</a></span><span class="t"><span class="str">        Returns</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t273" href="#t273">273</a></span><span class="t"><span class="str">        -------</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t274" href="#t274">274</a></span><span class="t"><span class="str">        count: float</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t275" href="#t275">275</a></span><span class="t"><span class="str">            Average rule coverage.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t276" href="#t276">276</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t277" href="#t277">277</a></span><span class="t">        <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_java_object</span><span class="op">.</span><span class="nam">calculateAvgRuleCoverage</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t278" href="#t278">278</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t279" href="#t279">279</a></span><span class="t">    <span class="key">def</span> <span class="nam">calculate_avg_rule_precision</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">float</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t280" href="#t280">280</a></span><span class="t">        <span class="str">"""</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t281" href="#t281">281</a></span><span class="t"><span class="str">        Returns</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t282" href="#t282">282</a></span><span class="t"><span class="str">        -------</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t283" href="#t283">283</a></span><span class="t"><span class="str">        count: float</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t284" href="#t284">284</a></span><span class="t"><span class="str">            Average rule precision.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t285" href="#t285">285</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t286" href="#t286">286</a></span><span class="t">        <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_java_object</span><span class="op">.</span><span class="nam">calculateAvgRulePrecision</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t287" href="#t287">287</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t288" href="#t288">288</a></span><span class="t">    <span class="key">def</span> <span class="nam">calculate_avg_rule_quality</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">float</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t289" href="#t289">289</a></span><span class="t">        <span class="str">"""</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t290" href="#t290">290</a></span><span class="t"><span class="str">        Returns</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t291" href="#t291">291</a></span><span class="t"><span class="str">        -------</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t292" href="#t292">292</a></span><span class="t"><span class="str">        count: float</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t293" href="#t293">293</a></span><span class="t"><span class="str">            Average rule quality.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t294" href="#t294">294</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t295" href="#t295">295</a></span><span class="t">        <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_java_object</span><span class="op">.</span><span class="nam">calculateAvgRuleQuality</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t296" href="#t296">296</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t297" href="#t297">297</a></span><span class="t">    <span class="key">def</span> <span class="nam">calculate_significance</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">alpha</span><span class="op">:</span> <span class="nam">float</span><span class="op">)</span> <span class="op">-></span> <span class="nam">dict</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t298" href="#t298">298</a></span><span class="t">        <span class="str">"""</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t299" href="#t299">299</a></span><span class="t"><span class="str">        Parameters</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t300" href="#t300">300</a></span><span class="t"><span class="str">        ----------</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t301" href="#t301">301</a></span><span class="t"><span class="str">        alpha : float</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t302" href="#t302">302</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t303" href="#t303">303</a></span><span class="t"><span class="str">        Returns</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t304" href="#t304">304</a></span><span class="t"><span class="str">        -------</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t305" href="#t305">305</a></span><span class="t"><span class="str">        count: float</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t306" href="#t306">306</a></span><span class="t"><span class="str">            Significance of the rule set.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t307" href="#t307">307</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t308" href="#t308">308</a></span><span class="t">        <span class="nam">significance</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_java_object</span><span class="op">.</span><span class="nam">calculateSignificance</span><span class="op">(</span><span class="nam">alpha</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t309" href="#t309">309</a></span><span class="t">        <span class="key">return</span> <span class="op">{</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t310" href="#t310">310</a></span><span class="t">            <span class="str">'p'</span><span class="op">:</span> <span class="nam">significance</span><span class="op">.</span><span class="nam">p</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t311" href="#t311">311</a></span><span class="t">            <span class="str">'fraction'</span><span class="op">:</span> <span class="nam">significance</span><span class="op">.</span><span class="nam">fraction</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t312" href="#t312">312</a></span><span class="t">        <span class="op">}</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t313" href="#t313">313</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t314" href="#t314">314</a></span><span class="t">    <span class="key">def</span> <span class="nam">calculate_significance_fdr</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">alpha</span><span class="op">:</span> <span class="nam">float</span><span class="op">)</span> <span class="op">-></span> <span class="nam">dict</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t315" href="#t315">315</a></span><span class="t">        <span class="str">"""</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t316" href="#t316">316</a></span><span class="t"><span class="str">        Returns</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t317" href="#t317">317</a></span><span class="t"><span class="str">        -------</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t318" href="#t318">318</a></span><span class="t"><span class="str">        count: dict</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t319" href="#t319">319</a></span><span class="t"><span class="str">            Significance of the rule set with false discovery rate correction. Dictionary contains</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t320" href="#t320">320</a></span><span class="t"><span class="str">            two fields: *fraction* (fraction of rules significant at assumed level) and *p*</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t321" href="#t321">321</a></span><span class="t"><span class="str">             (average p-value of all rules).</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t322" href="#t322">322</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t323" href="#t323">323</a></span><span class="t">        <span class="nam">significance</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_java_object</span><span class="op">.</span><span class="nam">calculateSignificanceFDR</span><span class="op">(</span><span class="nam">alpha</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t324" href="#t324">324</a></span><span class="t">        <span class="key">return</span> <span class="op">{</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t325" href="#t325">325</a></span><span class="t">            <span class="str">'p'</span><span class="op">:</span> <span class="nam">significance</span><span class="op">.</span><span class="nam">p</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t326" href="#t326">326</a></span><span class="t">            <span class="str">'fraction'</span><span class="op">:</span> <span class="nam">significance</span><span class="op">.</span><span class="nam">fraction</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t327" href="#t327">327</a></span><span class="t">        <span class="op">}</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t328" href="#t328">328</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t329" href="#t329">329</a></span><span class="t">    <span class="key">def</span> <span class="nam">calculate_significance_fwer</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">alpha</span><span class="op">:</span> <span class="nam">float</span><span class="op">)</span> <span class="op">-></span> <span class="nam">dict</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t330" href="#t330">330</a></span><span class="t">        <span class="str">"""</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t331" href="#t331">331</a></span><span class="t"><span class="str">        Returns</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t332" href="#t332">332</a></span><span class="t"><span class="str">        -------</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t333" href="#t333">333</a></span><span class="t"><span class="str">        count: dict</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t334" href="#t334">334</a></span><span class="t"><span class="str">            Significance of the rule set with familiy-wise error rate correction. Dictionary</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t335" href="#t335">335</a></span><span class="t"><span class="str">             contains two fields: *fraction* (fraction of rules significant at assumed level)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t336" href="#t336">336</a></span><span class="t"><span class="str">             and *p* (average p-value of all rules).</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t337" href="#t337">337</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t338" href="#t338">338</a></span><span class="t">        <span class="nam">significance</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_java_object</span><span class="op">.</span><span class="nam">calculateSignificanceFWER</span><span class="op">(</span><span class="nam">alpha</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t339" href="#t339">339</a></span><span class="t">        <span class="key">return</span> <span class="op">{</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t340" href="#t340">340</a></span><span class="t">            <span class="str">'p'</span><span class="op">:</span> <span class="nam">significance</span><span class="op">.</span><span class="nam">p</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t341" href="#t341">341</a></span><span class="t">            <span class="str">'fraction'</span><span class="op">:</span> <span class="nam">significance</span><span class="op">.</span><span class="nam">fraction</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t342" href="#t342">342</a></span><span class="t">        <span class="op">}</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t343" href="#t343">343</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t344" href="#t344">344</a></span><span class="t">    <span class="key">def</span> <span class="nam">__str__</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t345" href="#t345">345</a></span><span class="t">        <span class="str">"""Returns string representation of the object."""</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t346" href="#t346">346</a></span><span class="t">        <span class="key">return</span> <span class="nam">str</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">_java_object</span><span class="op">.</span><span class="nam">toString</span><span class="op">(</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t195" href="#t195">195</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t196" href="#t196">196</a></span><span class="t"><span class="key">class</span> <span class="nam">RuleSet</span><span class="op">(</span><span class="nam">Generic</span><span class="op">[</span><span class="nam">T</span><span class="op">]</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t197" href="#t197">197</a></span><span class="t">    <span class="str">"""Class representing ruleset."""</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t198" href="#t198">198</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t199" href="#t199">199</a></span><span class="t">    <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">java_object</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t200" href="#t200">200</a></span><span class="t">        <span class="str">""":meta private:"""</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t201" href="#t201">201</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_java_object</span> <span class="op">=</span> <span class="nam">java_object</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t202" href="#t202">202</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_stats</span><span class="op">:</span> <span class="nam">RuleSetStatistics</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t203" href="#t203">203</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t204" href="#t204">204</a></span><span class="t">    <span class="op">@</span><span class="nam">property</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t205" href="#t205">205</a></span><span class="t">    <span class="key">def</span> <span class="nam">total_time</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">float</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t206" href="#t206">206</a></span><span class="t">        <span class="str">"""Time of constructing the rule set in seconds"""</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t207" href="#t207">207</a></span><span class="t">        <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_java_object</span><span class="op">.</span><span class="nam">getTotalTime</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t208" href="#t208">208</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t209" href="#t209">209</a></span><span class="t">    <span class="op">@</span><span class="nam">property</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t210" href="#t210">210</a></span><span class="t">    <span class="key">def</span> <span class="nam">growing_time</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">float</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t211" href="#t211">211</a></span><span class="t">        <span class="str">"""Time of growing in seconds"""</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t212" href="#t212">212</a></span><span class="t">        <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_java_object</span><span class="op">.</span><span class="nam">getGrowingTime</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t213" href="#t213">213</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t214" href="#t214">214</a></span><span class="t">    <span class="op">@</span><span class="nam">property</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t215" href="#t215">215</a></span><span class="t">    <span class="key">def</span> <span class="nam">pruning_time</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">float</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t216" href="#t216">216</a></span><span class="t">        <span class="str">"""Time of pruning in seconds"""</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t217" href="#t217">217</a></span><span class="t">        <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_java_object</span><span class="op">.</span><span class="nam">getPruningTime</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t218" href="#t218">218</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t219" href="#t219">219</a></span><span class="t">    <span class="op">@</span><span class="nam">property</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t220" href="#t220">220</a></span><span class="t">    <span class="key">def</span> <span class="nam">is_voting</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">bool</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t221" href="#t221">221</a></span><span class="t">        <span class="str">"""Value indicating whether rules are voting."""</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t222" href="#t222">222</a></span><span class="t">        <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_java_object</span><span class="op">.</span><span class="nam">getIsVoting</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t223" href="#t223">223</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t224" href="#t224">224</a></span><span class="t">    <span class="op">@</span><span class="nam">property</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t225" href="#t225">225</a></span><span class="t">    <span class="key">def</span> <span class="nam">parameters</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">object</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t226" href="#t226">226</a></span><span class="t">        <span class="str">"""Parameters used during rule set induction."""</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t227" href="#t227">227</a></span><span class="t">        <span class="key">return</span> <span class="nam">InductionParameters</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">_java_object</span><span class="op">.</span><span class="nam">getParams</span><span class="op">(</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t228" href="#t228">228</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t229" href="#t229">229</a></span><span class="t">    <span class="op">@</span><span class="nam">property</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t230" href="#t230">230</a></span><span class="t">    <span class="key">def</span> <span class="nam">stats</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">RuleSetStatistics</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t231" href="#t231">231</a></span><span class="t">        <span class="str">"""Rule set statistics."""</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t232" href="#t232">232</a></span><span class="t">        <span class="key">if</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_stats</span> <span class="key">is</span> <span class="key">None</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t233" href="#t233">233</a></span><span class="t">            <span class="nam">self</span><span class="op">.</span><span class="nam">_stats</span> <span class="op">=</span> <span class="nam">RuleSetStatistics</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t234" href="#t234">234</a></span><span class="t">        <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_stats</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t235" href="#t235">235</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t236" href="#t236">236</a></span><span class="t">    <span class="key">def</span> <span class="nam">covering</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">example_set</span><span class="op">)</span> <span class="op">-></span> <span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t237" href="#t237">237</a></span><span class="t">        <span class="str">""":meta private:"""</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t238" href="#t238">238</a></span><span class="t">        <span class="nam">res</span> <span class="op">=</span> <span class="op">[</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t239" href="#t239">239</a></span><span class="t">        <span class="key">for</span> <span class="nam">rule</span> <span class="key">in</span> <span class="nam">self</span><span class="op">.</span><span class="nam">rules</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t240" href="#t240">240</a></span><span class="t">            <span class="nam">covering_info</span> <span class="op">=</span> <span class="nam">rule</span><span class="op">.</span><span class="nam">_java_object</span><span class="op">.</span><span class="nam">coversUnlabelled</span><span class="op">(</span>  <span class="com"># pylint: disable=protected-access</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t241" href="#t241">241</a></span><span class="t">                <span class="nam">example_set</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t242" href="#t242">242</a></span><span class="t">            <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t243" href="#t243">243</a></span><span class="t">            <span class="nam">covered_examples_indexes</span> <span class="op">=</span> <span class="op">[</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t244" href="#t244">244</a></span><span class="t">            <span class="nam">covered_examples_indexes</span> <span class="op">+=</span> <span class="nam">covering_info</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t245" href="#t245">245</a></span><span class="t">            <span class="nam">res</span><span class="op">.</span><span class="nam">append</span><span class="op">(</span><span class="nam">covered_examples_indexes</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t246" href="#t246">246</a></span><span class="t">        <span class="key">return</span> <span class="nam">np</span><span class="op">.</span><span class="nam">array</span><span class="op">(</span><span class="nam">res</span><span class="op">,</span> <span class="nam">dtype</span><span class="op">=</span><span class="nam">object</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t247" href="#t247">247</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t248" href="#t248">248</a></span><span class="t">    <span class="op">@</span><span class="nam">property</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t249" href="#t249">249</a></span><span class="t">    <span class="key">def</span> <span class="nam">rules</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">list</span><span class="op">[</span><span class="nam">T</span><span class="op">]</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t250" href="#t250">250</a></span><span class="t">        <span class="str">"""List of rules objects."""</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t251" href="#t251">251</a></span><span class="t">        <span class="key">return</span> <span class="op">[</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t252" href="#t252">252</a></span><span class="t">            <span class="nam">_rule_factory</span><span class="op">(</span><span class="nam">java_rule</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t253" href="#t253">253</a></span><span class="t">            <span class="key">for</span> <span class="nam">java_rule</span> <span class="key">in</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_java_object</span><span class="op">.</span><span class="nam">getRules</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t254" href="#t254">254</a></span><span class="t">        <span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t255" href="#t255">255</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t256" href="#t256">256</a></span><span class="t">    <span class="key">def</span> <span class="nam">calculate_conditions_count</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">float</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t257" href="#t257">257</a></span><span class="t">        <span class="str">"""</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t258" href="#t258">258</a></span><span class="t"><span class="str">        Returns</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t259" href="#t259">259</a></span><span class="t"><span class="str">        -------</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t260" href="#t260">260</a></span><span class="t"><span class="str">        count: float</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t261" href="#t261">261</a></span><span class="t"><span class="str">            Number of conditions.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t262" href="#t262">262</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t263" href="#t263">263</a></span><span class="t">        <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_java_object</span><span class="op">.</span><span class="nam">calculateConditionsCount</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t264" href="#t264">264</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t265" href="#t265">265</a></span><span class="t">    <span class="key">def</span> <span class="nam">calculate_induced_conditions_count</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">float</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t266" href="#t266">266</a></span><span class="t">        <span class="str">"""</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t267" href="#t267">267</a></span><span class="t"><span class="str">        Returns</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t268" href="#t268">268</a></span><span class="t"><span class="str">        -------</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t269" href="#t269">269</a></span><span class="t"><span class="str">        count: float</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t270" href="#t270">270</a></span><span class="t"><span class="str">            Number of induced conditions.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t271" href="#t271">271</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t272" href="#t272">272</a></span><span class="t">        <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_java_object</span><span class="op">.</span><span class="nam">calculateInducedCondtionsCount</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t273" href="#t273">273</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t274" href="#t274">274</a></span><span class="t">    <span class="key">def</span> <span class="nam">calculate_avg_rule_coverage</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">float</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t275" href="#t275">275</a></span><span class="t">        <span class="str">"""</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t276" href="#t276">276</a></span><span class="t"><span class="str">        Returns</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t277" href="#t277">277</a></span><span class="t"><span class="str">        -------</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t278" href="#t278">278</a></span><span class="t"><span class="str">        count: float</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t279" href="#t279">279</a></span><span class="t"><span class="str">            Average rule coverage.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t280" href="#t280">280</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t281" href="#t281">281</a></span><span class="t">        <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_java_object</span><span class="op">.</span><span class="nam">calculateAvgRuleCoverage</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t282" href="#t282">282</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t283" href="#t283">283</a></span><span class="t">    <span class="key">def</span> <span class="nam">calculate_avg_rule_precision</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">float</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t284" href="#t284">284</a></span><span class="t">        <span class="str">"""</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t285" href="#t285">285</a></span><span class="t"><span class="str">        Returns</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t286" href="#t286">286</a></span><span class="t"><span class="str">        -------</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t287" href="#t287">287</a></span><span class="t"><span class="str">        count: float</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t288" href="#t288">288</a></span><span class="t"><span class="str">            Average rule precision.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t289" href="#t289">289</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t290" href="#t290">290</a></span><span class="t">        <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_java_object</span><span class="op">.</span><span class="nam">calculateAvgRulePrecision</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t291" href="#t291">291</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t292" href="#t292">292</a></span><span class="t">    <span class="key">def</span> <span class="nam">calculate_avg_rule_quality</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">float</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t293" href="#t293">293</a></span><span class="t">        <span class="str">"""</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t294" href="#t294">294</a></span><span class="t"><span class="str">        Returns</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t295" href="#t295">295</a></span><span class="t"><span class="str">        -------</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t296" href="#t296">296</a></span><span class="t"><span class="str">        count: float</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t297" href="#t297">297</a></span><span class="t"><span class="str">            Average rule quality.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t298" href="#t298">298</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t299" href="#t299">299</a></span><span class="t">        <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_java_object</span><span class="op">.</span><span class="nam">calculateAvgRuleQuality</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t300" href="#t300">300</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t301" href="#t301">301</a></span><span class="t">    <span class="key">def</span> <span class="nam">calculate_significance</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">alpha</span><span class="op">:</span> <span class="nam">float</span><span class="op">)</span> <span class="op">-></span> <span class="nam">dict</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t302" href="#t302">302</a></span><span class="t">        <span class="str">"""</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t303" href="#t303">303</a></span><span class="t"><span class="str">        Parameters</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t304" href="#t304">304</a></span><span class="t"><span class="str">        ----------</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t305" href="#t305">305</a></span><span class="t"><span class="str">        alpha : float</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t306" href="#t306">306</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t307" href="#t307">307</a></span><span class="t"><span class="str">        Returns</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t308" href="#t308">308</a></span><span class="t"><span class="str">        -------</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t309" href="#t309">309</a></span><span class="t"><span class="str">        count: float</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t310" href="#t310">310</a></span><span class="t"><span class="str">            Significance of the rule set.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t311" href="#t311">311</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t312" href="#t312">312</a></span><span class="t">        <span class="nam">significance</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_java_object</span><span class="op">.</span><span class="nam">calculateSignificance</span><span class="op">(</span><span class="nam">alpha</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t313" href="#t313">313</a></span><span class="t">        <span class="key">return</span> <span class="op">{</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t314" href="#t314">314</a></span><span class="t">            <span class="str">'p'</span><span class="op">:</span> <span class="nam">significance</span><span class="op">.</span><span class="nam">p</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t315" href="#t315">315</a></span><span class="t">            <span class="str">'fraction'</span><span class="op">:</span> <span class="nam">significance</span><span class="op">.</span><span class="nam">fraction</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t316" href="#t316">316</a></span><span class="t">        <span class="op">}</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t317" href="#t317">317</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t318" href="#t318">318</a></span><span class="t">    <span class="key">def</span> <span class="nam">calculate_significance_fdr</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">alpha</span><span class="op">:</span> <span class="nam">float</span><span class="op">)</span> <span class="op">-></span> <span class="nam">dict</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t319" href="#t319">319</a></span><span class="t">        <span class="str">"""</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t320" href="#t320">320</a></span><span class="t"><span class="str">        Returns</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t321" href="#t321">321</a></span><span class="t"><span class="str">        -------</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t322" href="#t322">322</a></span><span class="t"><span class="str">        count: dict</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t323" href="#t323">323</a></span><span class="t"><span class="str">            Significance of the rule set with false discovery rate correction. Dictionary contains</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t324" href="#t324">324</a></span><span class="t"><span class="str">            two fields: *fraction* (fraction of rules significant at assumed level) and *p*</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t325" href="#t325">325</a></span><span class="t"><span class="str">             (average p-value of all rules).</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t326" href="#t326">326</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t327" href="#t327">327</a></span><span class="t">        <span class="nam">significance</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_java_object</span><span class="op">.</span><span class="nam">calculateSignificanceFDR</span><span class="op">(</span><span class="nam">alpha</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t328" href="#t328">328</a></span><span class="t">        <span class="key">return</span> <span class="op">{</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t329" href="#t329">329</a></span><span class="t">            <span class="str">'p'</span><span class="op">:</span> <span class="nam">significance</span><span class="op">.</span><span class="nam">p</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t330" href="#t330">330</a></span><span class="t">            <span class="str">'fraction'</span><span class="op">:</span> <span class="nam">significance</span><span class="op">.</span><span class="nam">fraction</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t331" href="#t331">331</a></span><span class="t">        <span class="op">}</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t332" href="#t332">332</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t333" href="#t333">333</a></span><span class="t">    <span class="key">def</span> <span class="nam">calculate_significance_fwer</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">alpha</span><span class="op">:</span> <span class="nam">float</span><span class="op">)</span> <span class="op">-></span> <span class="nam">dict</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t334" href="#t334">334</a></span><span class="t">        <span class="str">"""</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t335" href="#t335">335</a></span><span class="t"><span class="str">        Returns</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t336" href="#t336">336</a></span><span class="t"><span class="str">        -------</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t337" href="#t337">337</a></span><span class="t"><span class="str">        count: dict</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t338" href="#t338">338</a></span><span class="t"><span class="str">            Significance of the rule set with familiy-wise error rate correction. Dictionary</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t339" href="#t339">339</a></span><span class="t"><span class="str">             contains two fields: *fraction* (fraction of rules significant at assumed level)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t340" href="#t340">340</a></span><span class="t"><span class="str">             and *p* (average p-value of all rules).</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t341" href="#t341">341</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t342" href="#t342">342</a></span><span class="t">        <span class="nam">significance</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_java_object</span><span class="op">.</span><span class="nam">calculateSignificanceFWER</span><span class="op">(</span><span class="nam">alpha</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t343" href="#t343">343</a></span><span class="t">        <span class="key">return</span> <span class="op">{</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t344" href="#t344">344</a></span><span class="t">            <span class="str">'p'</span><span class="op">:</span> <span class="nam">significance</span><span class="op">.</span><span class="nam">p</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t345" href="#t345">345</a></span><span class="t">            <span class="str">'fraction'</span><span class="op">:</span> <span class="nam">significance</span><span class="op">.</span><span class="nam">fraction</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t346" href="#t346">346</a></span><span class="t">        <span class="op">}</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t347" href="#t347">347</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t348" href="#t348">348</a></span><span class="t">    <span class="key">def</span> <span class="nam">__str__</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t349" href="#t349">349</a></span><span class="t">        <span class="str">"""Returns string representation of the object."""</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t350" href="#t350">350</a></span><span class="t">        <span class="key">return</span> <span class="nam">str</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">_java_object</span><span class="op">.</span><span class="nam">toString</span><span class="op">(</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
 </main>
 <footer>
     <div class="content">
@@ -435,7 +439,7 @@ <h2>
             <a class="nav" href="z_a87f2a4bb6695d91_stats_py.html">&#xbb; next</a>
             &nbsp; &nbsp; &nbsp;
             <a class="nav" href="https://coverage.readthedocs.io/en/7.6.4">coverage.py v7.6.4</a>,
-            created at 2024-11-08 14:43 +0100
+            created at 2024-11-28 11:55 +0100
         </p>
     </div>
 </footer>
diff --git a/docs/reports/coverage/z_a87f2a4bb6695d91_stats_py.html b/docs/reports/coverage/z_a87f2a4bb6695d91_stats_py.html
index 35729c6..11eb019 100644
--- a/docs/reports/coverage/z_a87f2a4bb6695d91_stats_py.html
+++ b/docs/reports/coverage/z_a87f2a4bb6695d91_stats_py.html
@@ -65,7 +65,7 @@ <h2>
             <a id="nextFileLink" class="nav" href="z_a87f2a4bb6695d91_survival_py.html">&#xbb; next</a>
             &nbsp; &nbsp; &nbsp;
             <a class="nav" href="https://coverage.readthedocs.io/en/7.6.4">coverage.py v7.6.4</a>,
-            created at 2024-11-05 13:43 +0100
+            created at 2024-11-28 11:55 +0100
         </p>
         <aside class="hidden">
             <button type="button" class="button_next_chunk" data-shortcut="j"></button>
@@ -115,7 +115,7 @@ <h2>
     <p class="run"><span class="n"><a id="t33" href="#t33">33</a></span><span class="t">    <span class="key">def</span> <span class="nam">__str__</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t34" href="#t34">34</a></span><span class="t">        <span class="str">"""Returns string representation of the object."""</span>&nbsp;</span><span class="r"></span></p>
     <p class="mis show_mis"><span class="n"><a id="t35" href="#t35">35</a></span><span class="t">        <span class="key">return</span> <span class="str">f'(p = {self.p}, n = {self.n}, P = {self.P}, '</span> <span class="op">+</span> <span class="xx">\</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t36" href="#t36">36</a></span><span class="t">               <span class="str">f'N = {self.N}, weight = {self.weight}, pvalue = {self.pvalue})'</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t36" href="#t36">36</a></span><span class="t">            <span class="str">f'N = {self.N}, weight = {self.weight}, pvalue = {self.pvalue})'</span>&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t37" href="#t37">37</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t38" href="#t38">38</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
     <p class="run"><span class="n"><a id="t39" href="#t39">39</a></span><span class="t"><span class="key">class</span> <span class="nam">RuleSetStatistics</span><span class="op">:</span>  <span class="com"># pylint: disable=too-many-instance-attributes</span>&nbsp;</span><span class="r"></span></p>
@@ -154,11 +154,11 @@ <h2>
     <p class="pln"><span class="n"><a id="t72" href="#t72">72</a></span><span class="t"><span class="str">    fraction_significant : float</span>&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t73" href="#t73">73</a></span><span class="t"><span class="str">        Fraction of rules significant at assumed level</span>&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t74" href="#t74">74</a></span><span class="t"><span class="str">    fraction_FDR_significant : float</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t75" href="#t75">75</a></span><span class="t"><span class="str">        Fraction of rules significant, set with false discovery rate correction,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t76" href="#t76">76</a></span><span class="t"><span class="str">        at assumed level.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t75" href="#t75">75</a></span><span class="t"><span class="str">        Fraction of rules significant, set with false \</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t76" href="#t76">76</a></span><span class="t"><span class="str">        discovery rate correction, at assumed level.</span>&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t77" href="#t77">77</a></span><span class="t"><span class="str">    fraction_FWER_significant : float</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t78" href="#t78">78</a></span><span class="t"><span class="str">        Fraction of rules significant, set with familiy-wise error rate correction,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t79" href="#t79">79</a></span><span class="t"><span class="str">        at assumed level.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t78" href="#t78">78</a></span><span class="t"><span class="str">        Fraction of rules significant, set with familiy-wise \</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t79" href="#t79">79</a></span><span class="t"><span class="str">        error rate correction, at assumed level.</span>&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t80" href="#t80">80</a></span><span class="t"><span class="str">    """</span>&nbsp;</span><span class="r"></span></p>
     <p class="run"><span class="n"><a id="t81" href="#t81">81</a></span><span class="t">    <span class="nam">SIGNIFICANCE_LEVEL</span> <span class="op">=</span> <span class="num">0.05</span>&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t82" href="#t82">82</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
@@ -170,59 +170,61 @@ <h2>
     <p class="pln"><span class="n"><a id="t88" href="#t88">88</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
     <p class="run"><span class="n"><a id="t89" href="#t89">89</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">rules_count</span> <span class="op">=</span> <span class="nam">len</span><span class="op">(</span><span class="nam">ruleset</span><span class="op">.</span><span class="nam">rules</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
     <p class="run"><span class="n"><a id="t90" href="#t90">90</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">conditions_per_rule</span> <span class="op">=</span> <span class="nam">ruleset</span><span class="op">.</span><span class="nam">calculate_conditions_count</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t91" href="#t91">91</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">induced_conditions_per_rule</span> <span class="op">=</span> <span class="nam">ruleset</span><span class="op">.</span><span class="nam">calculate_induced_conditions_count</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t92" href="#t92">92</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t93" href="#t93">93</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">avg_rule_coverage</span> <span class="op">=</span> <span class="nam">ruleset</span><span class="op">.</span><span class="nam">calculate_avg_rule_coverage</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t94" href="#t94">94</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">avg_rule_precision</span> <span class="op">=</span> <span class="nam">ruleset</span><span class="op">.</span><span class="nam">calculate_avg_rule_precision</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t95" href="#t95">95</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">avg_rule_quality</span> <span class="op">=</span> <span class="nam">ruleset</span><span class="op">.</span><span class="nam">calculate_avg_rule_quality</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t96" href="#t96">96</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t97" href="#t97">97</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">pvalue</span> <span class="op">=</span> <span class="nam">ruleset</span><span class="op">.</span><span class="nam">calculate_significance</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t98" href="#t98">98</a></span><span class="t">            <span class="nam">RuleSetStatistics</span><span class="op">.</span><span class="nam">SIGNIFICANCE_LEVEL</span><span class="op">)</span><span class="op">[</span><span class="str">'p'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t99" href="#t99">99</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">FDR_pvalue</span> <span class="op">=</span> <span class="nam">ruleset</span><span class="op">.</span><span class="nam">calculate_significance_fdr</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t100" href="#t100">100</a></span><span class="t">            <span class="nam">RuleSetStatistics</span><span class="op">.</span><span class="nam">SIGNIFICANCE_LEVEL</span><span class="op">)</span><span class="op">[</span><span class="str">'p'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t101" href="#t101">101</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">FWER_pvalue</span> <span class="op">=</span> <span class="nam">ruleset</span><span class="op">.</span><span class="nam">calculate_significance_fwer</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t102" href="#t102">102</a></span><span class="t">            <span class="nam">RuleSetStatistics</span><span class="op">.</span><span class="nam">SIGNIFICANCE_LEVEL</span><span class="op">)</span><span class="op">[</span><span class="str">'p'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t103" href="#t103">103</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t104" href="#t104">104</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">fraction_significant</span> <span class="op">=</span> <span class="nam">ruleset</span><span class="op">.</span><span class="nam">calculate_significance</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t105" href="#t105">105</a></span><span class="t">            <span class="nam">RuleSetStatistics</span><span class="op">.</span><span class="nam">SIGNIFICANCE_LEVEL</span><span class="op">)</span><span class="op">[</span><span class="str">'fraction'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t106" href="#t106">106</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">fraction_FDR_significant</span> <span class="op">=</span> <span class="nam">ruleset</span><span class="op">.</span><span class="nam">calculate_significance_fdr</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t107" href="#t107">107</a></span><span class="t">            <span class="nam">RuleSetStatistics</span><span class="op">.</span><span class="nam">SIGNIFICANCE_LEVEL</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t108" href="#t108">108</a></span><span class="t">        <span class="op">)</span><span class="op">[</span><span class="str">'fraction'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t109" href="#t109">109</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">fraction_FWER_significant</span> <span class="op">=</span> <span class="nam">ruleset</span><span class="op">.</span><span class="nam">calculate_significance_fwer</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t110" href="#t110">110</a></span><span class="t">            <span class="nam">RuleSetStatistics</span><span class="op">.</span><span class="nam">SIGNIFICANCE_LEVEL</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t111" href="#t111">111</a></span><span class="t">        <span class="op">)</span><span class="op">[</span><span class="str">'fraction'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t112" href="#t112">112</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t113" href="#t113">113</a></span><span class="t">    <span class="key">def</span> <span class="nam">__str__</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t114" href="#t114">114</a></span><span class="t">        <span class="key">return</span> <span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t115" href="#t115">115</a></span><span class="t">            <span class="str">f'Time total [s]: {self.time_total_s}\n'</span> <span class="op">+</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t116" href="#t116">116</a></span><span class="t">            <span class="str">f'Time growing [s]: {self.time_growing_s}\n'</span> <span class="op">+</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t117" href="#t117">117</a></span><span class="t">            <span class="str">f'Time pruning [s]: {self.time_pruning_s}\n'</span> <span class="op">+</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t118" href="#t118">118</a></span><span class="t">            <span class="str">'\n'</span> <span class="op">+</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t119" href="#t119">119</a></span><span class="t">            <span class="str">f'Rules count: {self.rules_count}\n'</span> <span class="op">+</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t120" href="#t120">120</a></span><span class="t">            <span class="str">f'Conditions per rule: {self.conditions_per_rule}\n'</span> <span class="op">+</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t121" href="#t121">121</a></span><span class="t">            <span class="str">f'Induced conditions per rule: {self.induced_conditions_per_rule}\n'</span> <span class="op">+</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t122" href="#t122">122</a></span><span class="t">            <span class="str">'\n'</span> <span class="op">+</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t123" href="#t123">123</a></span><span class="t">            <span class="str">f'Average rule coverage: {self.avg_rule_coverage}\n'</span> <span class="op">+</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t124" href="#t124">124</a></span><span class="t">            <span class="str">f'Average rule precision: {self.avg_rule_precision}\n'</span> <span class="op">+</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t125" href="#t125">125</a></span><span class="t">            <span class="str">f'Average rule quality: {self.avg_rule_quality}\n'</span> <span class="op">+</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t126" href="#t126">126</a></span><span class="t">            <span class="str">'\n'</span> <span class="op">+</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t127" href="#t127">127</a></span><span class="t">            <span class="str">f'pvalue: {self.pvalue}\n'</span> <span class="op">+</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t128" href="#t128">128</a></span><span class="t">            <span class="str">f'FDR pvalue: {self.FDR_pvalue}\n'</span> <span class="op">+</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t129" href="#t129">129</a></span><span class="t">            <span class="str">f'FWER pvalue: {self.FWER_pvalue}\n'</span> <span class="op">+</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t130" href="#t130">130</a></span><span class="t">            <span class="str">'\n'</span> <span class="op">+</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t131" href="#t131">131</a></span><span class="t">            <span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t132" href="#t132">132</a></span><span class="t">                <span class="str">f'Fraction {RuleSetStatistics.SIGNIFICANCE_LEVEL} '</span> <span class="op">+</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t133" href="#t133">133</a></span><span class="t">                <span class="str">f'significant: {self.fraction_significant}\n'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t134" href="#t134">134</a></span><span class="t">            <span class="op">)</span> <span class="op">+</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t135" href="#t135">135</a></span><span class="t">            <span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t136" href="#t136">136</a></span><span class="t">                <span class="str">f'Fraction {RuleSetStatistics.SIGNIFICANCE_LEVEL} '</span> <span class="op">+</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t137" href="#t137">137</a></span><span class="t">                <span class="str">f'FDR significant: {self.fraction_FDR_significant}\n'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t138" href="#t138">138</a></span><span class="t">            <span class="op">)</span> <span class="op">+</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t139" href="#t139">139</a></span><span class="t">            <span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t140" href="#t140">140</a></span><span class="t">                <span class="str">f'Fraction {RuleSetStatistics.SIGNIFICANCE_LEVEL} '</span> <span class="op">+</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t141" href="#t141">141</a></span><span class="t">                <span class="str">f'FWER significant: {self.fraction_FWER_significant}\n'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t142" href="#t142">142</a></span><span class="t">            <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t143" href="#t143">143</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t91" href="#t91">91</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">induced_conditions_per_rule</span> <span class="op">=</span> <span class="nam">ruleset</span><span class="op">.</span> <span class="xx">\</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t92" href="#t92">92</a></span><span class="t">            <span class="nam">calculate_induced_conditions_count</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t93" href="#t93">93</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t94" href="#t94">94</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">avg_rule_coverage</span> <span class="op">=</span> <span class="nam">ruleset</span><span class="op">.</span><span class="nam">calculate_avg_rule_coverage</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t95" href="#t95">95</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">avg_rule_precision</span> <span class="op">=</span> <span class="nam">ruleset</span><span class="op">.</span><span class="nam">calculate_avg_rule_precision</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t96" href="#t96">96</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">avg_rule_quality</span> <span class="op">=</span> <span class="nam">ruleset</span><span class="op">.</span><span class="nam">calculate_avg_rule_quality</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t97" href="#t97">97</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t98" href="#t98">98</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">pvalue</span> <span class="op">=</span> <span class="nam">ruleset</span><span class="op">.</span><span class="nam">calculate_significance</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t99" href="#t99">99</a></span><span class="t">            <span class="nam">RuleSetStatistics</span><span class="op">.</span><span class="nam">SIGNIFICANCE_LEVEL</span><span class="op">)</span><span class="op">[</span><span class="str">'p'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t100" href="#t100">100</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">FDR_pvalue</span> <span class="op">=</span> <span class="nam">ruleset</span><span class="op">.</span><span class="nam">calculate_significance_fdr</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t101" href="#t101">101</a></span><span class="t">            <span class="nam">RuleSetStatistics</span><span class="op">.</span><span class="nam">SIGNIFICANCE_LEVEL</span><span class="op">)</span><span class="op">[</span><span class="str">'p'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t102" href="#t102">102</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">FWER_pvalue</span> <span class="op">=</span> <span class="nam">ruleset</span><span class="op">.</span><span class="nam">calculate_significance_fwer</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t103" href="#t103">103</a></span><span class="t">            <span class="nam">RuleSetStatistics</span><span class="op">.</span><span class="nam">SIGNIFICANCE_LEVEL</span><span class="op">)</span><span class="op">[</span><span class="str">'p'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t104" href="#t104">104</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t105" href="#t105">105</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">fraction_significant</span> <span class="op">=</span> <span class="nam">ruleset</span><span class="op">.</span><span class="nam">calculate_significance</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t106" href="#t106">106</a></span><span class="t">            <span class="nam">RuleSetStatistics</span><span class="op">.</span><span class="nam">SIGNIFICANCE_LEVEL</span><span class="op">)</span><span class="op">[</span><span class="str">'fraction'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t107" href="#t107">107</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">fraction_FDR_significant</span> <span class="op">=</span> <span class="nam">ruleset</span><span class="op">.</span><span class="nam">calculate_significance_fdr</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t108" href="#t108">108</a></span><span class="t">            <span class="nam">RuleSetStatistics</span><span class="op">.</span><span class="nam">SIGNIFICANCE_LEVEL</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t109" href="#t109">109</a></span><span class="t">        <span class="op">)</span><span class="op">[</span><span class="str">'fraction'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t110" href="#t110">110</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">fraction_FWER_significant</span> <span class="op">=</span> <span class="nam">ruleset</span><span class="op">.</span><span class="nam">calculate_significance_fwer</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t111" href="#t111">111</a></span><span class="t">            <span class="nam">RuleSetStatistics</span><span class="op">.</span><span class="nam">SIGNIFICANCE_LEVEL</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t112" href="#t112">112</a></span><span class="t">        <span class="op">)</span><span class="op">[</span><span class="str">'fraction'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t113" href="#t113">113</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t114" href="#t114">114</a></span><span class="t">    <span class="key">def</span> <span class="nam">__str__</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t115" href="#t115">115</a></span><span class="t">        <span class="key">return</span> <span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t116" href="#t116">116</a></span><span class="t">            <span class="str">f'Time total [s]: {self.time_total_s}\n'</span> <span class="op">+</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t117" href="#t117">117</a></span><span class="t">            <span class="str">f'Time growing [s]: {self.time_growing_s}\n'</span> <span class="op">+</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t118" href="#t118">118</a></span><span class="t">            <span class="str">f'Time pruning [s]: {self.time_pruning_s}\n'</span> <span class="op">+</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t119" href="#t119">119</a></span><span class="t">            <span class="str">'\n'</span> <span class="op">+</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t120" href="#t120">120</a></span><span class="t">            <span class="str">f'Rules count: {self.rules_count}\n'</span> <span class="op">+</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t121" href="#t121">121</a></span><span class="t">            <span class="str">f'Conditions per rule: {self.conditions_per_rule}\n'</span> <span class="op">+</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t122" href="#t122">122</a></span><span class="t">            <span class="str">'Induced conditions per rule: '</span> <span class="op">+</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t123" href="#t123">123</a></span><span class="t">            <span class="str">f'{self.induced_conditions_per_rule}\n'</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t124" href="#t124">124</a></span><span class="t">            <span class="str">'\n'</span> <span class="op">+</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t125" href="#t125">125</a></span><span class="t">            <span class="str">f'Average rule coverage: {self.avg_rule_coverage}\n'</span> <span class="op">+</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t126" href="#t126">126</a></span><span class="t">            <span class="str">f'Average rule precision: {self.avg_rule_precision}\n'</span> <span class="op">+</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t127" href="#t127">127</a></span><span class="t">            <span class="str">f'Average rule quality: {self.avg_rule_quality}\n'</span> <span class="op">+</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t128" href="#t128">128</a></span><span class="t">            <span class="str">'\n'</span> <span class="op">+</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t129" href="#t129">129</a></span><span class="t">            <span class="str">f'pvalue: {self.pvalue}\n'</span> <span class="op">+</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t130" href="#t130">130</a></span><span class="t">            <span class="str">f'FDR pvalue: {self.FDR_pvalue}\n'</span> <span class="op">+</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t131" href="#t131">131</a></span><span class="t">            <span class="str">f'FWER pvalue: {self.FWER_pvalue}\n'</span> <span class="op">+</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t132" href="#t132">132</a></span><span class="t">            <span class="str">'\n'</span> <span class="op">+</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t133" href="#t133">133</a></span><span class="t">            <span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t134" href="#t134">134</a></span><span class="t">                <span class="str">f'Fraction {RuleSetStatistics.SIGNIFICANCE_LEVEL} '</span> <span class="op">+</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t135" href="#t135">135</a></span><span class="t">                <span class="str">f'significant: {self.fraction_significant}\n'</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t136" href="#t136">136</a></span><span class="t">            <span class="op">)</span> <span class="op">+</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t137" href="#t137">137</a></span><span class="t">            <span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t138" href="#t138">138</a></span><span class="t">                <span class="str">f'Fraction {RuleSetStatistics.SIGNIFICANCE_LEVEL} '</span> <span class="op">+</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t139" href="#t139">139</a></span><span class="t">                <span class="str">f'FDR significant: {self.fraction_FDR_significant}\n'</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t140" href="#t140">140</a></span><span class="t">            <span class="op">)</span> <span class="op">+</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t141" href="#t141">141</a></span><span class="t">            <span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t142" href="#t142">142</a></span><span class="t">                <span class="str">f'Fraction {RuleSetStatistics.SIGNIFICANCE_LEVEL} '</span> <span class="op">+</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t143" href="#t143">143</a></span><span class="t">                <span class="str">f'FWER significant: {self.fraction_FWER_significant}\n'</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t144" href="#t144">144</a></span><span class="t">            <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t145" href="#t145">145</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
 </main>
 <footer>
     <div class="content">
@@ -232,7 +234,7 @@ <h2>
             <a class="nav" href="z_a87f2a4bb6695d91_survival_py.html">&#xbb; next</a>
             &nbsp; &nbsp; &nbsp;
             <a class="nav" href="https://coverage.readthedocs.io/en/7.6.4">coverage.py v7.6.4</a>,
-            created at 2024-11-05 13:43 +0100
+            created at 2024-11-28 11:55 +0100
         </p>
     </div>
 </footer>
diff --git a/docs/reports/coverage/z_a87f2a4bb6695d91_survival_py.html b/docs/reports/coverage/z_a87f2a4bb6695d91_survival_py.html
index b1eddd9..58fff02 100644
--- a/docs/reports/coverage/z_a87f2a4bb6695d91_survival_py.html
+++ b/docs/reports/coverage/z_a87f2a4bb6695d91_survival_py.html
@@ -2,7 +2,7 @@
 <html lang="en">
 <head>
     <meta http-equiv="Content-Type" content="text/html; charset=utf-8">
-    <title>Coverage for rulekit\survival.py: 69%</title>
+    <title>Coverage for rulekit\survival.py: 80%</title>
     <link rel="icon" sizes="32x32" href="favicon_32_cb_58284776.png">
     <link rel="stylesheet" href="style_cb_718ce007.css" type="text/css">
     <script src="coverage_html_cb_497bf287.js" defer></script>
@@ -12,7 +12,7 @@
     <div class="content">
         <h1>
             <span class="text">Coverage for </span><b>rulekit\survival.py</b>:
-            <span class="pc_cov">69%</span>
+            <span class="pc_cov">80%</span>
         </h1>
         <aside id="help_panel_wrapper">
             <input id="help_panel_state" type="checkbox">
@@ -54,9 +54,9 @@ <h1>
             </div>
         </aside>
         <h2>
-            <span class="text">118 statements &nbsp;</span>
-            <button type="button" class="run button_toggle_run" value="run" data-shortcut="r" title="Toggle lines run">81<span class="text"> run</span></button>
-            <button type="button" class="mis show_mis button_toggle_mis" value="mis" data-shortcut="m" title="Toggle lines missing">37<span class="text"> missing</span></button>
+            <span class="text">122 statements &nbsp;</span>
+            <button type="button" class="run button_toggle_run" value="run" data-shortcut="r" title="Toggle lines run">98<span class="text"> run</span></button>
+            <button type="button" class="mis show_mis button_toggle_mis" value="mis" data-shortcut="m" title="Toggle lines missing">24<span class="text"> missing</span></button>
             <button type="button" class="exc show_exc button_toggle_exc" value="exc" data-shortcut="x" title="Toggle lines excluded">0<span class="text"> excluded</span></button>
         </h2>
         <p class="text">
@@ -65,7 +65,7 @@ <h2>
             <a id="nextFileLink" class="nav" href="z_a44f0ac069e85531___init___py.html">&#xbb; next</a>
             &nbsp; &nbsp; &nbsp;
             <a class="nav" href="https://coverage.readthedocs.io/en/7.6.4">coverage.py v7.6.4</a>,
-            created at 2024-11-08 14:43 +0100
+            created at 2024-11-28 12:23 +0100
         </p>
         <aside class="hidden">
             <button type="button" class="button_next_chunk" data-shortcut="j"></button>
@@ -94,15 +94,15 @@ <h2>
     <p class="run"><span class="n"><a id="t12" href="#t12">12</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">_helpers</span> <span class="key">import</span> <span class="nam">ExampleSetFactory</span><span class="op">,</span> <span class="nam">PredictionResultMapper</span>&nbsp;</span><span class="r"></span></p>
     <p class="run"><span class="n"><a id="t13" href="#t13">13</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">_operator</span> <span class="key">import</span> <span class="nam">BaseOperator</span><span class="op">,</span> <span class="nam">Data</span><span class="op">,</span> <span class="nam">ExpertKnowledgeOperator</span>&nbsp;</span><span class="r"></span></p>
     <p class="run"><span class="n"><a id="t14" href="#t14">14</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">_problem_types</span> <span class="key">import</span> <span class="nam">ProblemType</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t15" href="#t15">15</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">params</span> <span class="key">import</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">,</span> <span class="nam">ContrastSetModelParams</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t16" href="#t16">16</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">rules</span> <span class="key">import</span> <span class="nam">RuleSet</span><span class="op">,</span> <span class="nam">SurvivalRule</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t17" href="#t17">17</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t18" href="#t18">18</a></span><span class="t"><span class="nam">_DEFAULT_SURVIVAL_TIME_ATTR</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="str">'survival_time'</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t15" href="#t15">15</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">kaplan_meier</span> <span class="key">import</span> <span class="nam">KaplanMeierEstimator</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t16" href="#t16">16</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">params</span> <span class="key">import</span> <span class="op">(</span><span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">,</span> <span class="nam">ContrastSetModelParams</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t17" href="#t17">17</a></span><span class="t">                            <span class="nam">ExpertModelParams</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t18" href="#t18">18</a></span><span class="t"><span class="key">from</span> <span class="nam">rulekit</span><span class="op">.</span><span class="nam">rules</span> <span class="key">import</span> <span class="nam">RuleSet</span><span class="op">,</span> <span class="nam">SurvivalRule</span>&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t19" href="#t19">19</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t20" href="#t20">20</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t21" href="#t21">21</a></span><span class="t"><span class="key">class</span> <span class="nam">SurvivalModelsParams</span><span class="op">(</span><span class="nam">BaseModel</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t22" href="#t22">22</a></span><span class="t">    <span class="str">"""Model for validating survival models hyperparameters</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t23" href="#t23">23</a></span><span class="t"><span class="str">    """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t20" href="#t20">20</a></span><span class="t"><span class="nam">_DEFAULT_SURVIVAL_TIME_ATTR</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="str">'survival_time'</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t21" href="#t21">21</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t22" href="#t22">22</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t23" href="#t23">23</a></span><span class="t"><span class="key">class</span> <span class="nam">_SurvivalModelsParams</span><span class="op">(</span><span class="nam">BaseModel</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
     <p class="run"><span class="n"><a id="t24" href="#t24">24</a></span><span class="t">    <span class="nam">survival_time_attr</span><span class="op">:</span> <span class="nam">Optional</span><span class="op">[</span><span class="nam">str</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
     <p class="run"><span class="n"><a id="t25" href="#t25">25</a></span><span class="t">    <span class="nam">minsupp_new</span><span class="op">:</span> <span class="nam">Optional</span><span class="op">[</span><span class="nam">float</span><span class="op">]</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'minsupp_new'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
     <p class="run"><span class="n"><a id="t26" href="#t26">26</a></span><span class="t">    <span class="nam">max_growing</span><span class="op">:</span> <span class="nam">Optional</span><span class="op">[</span><span class="nam">float</span><span class="op">]</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'max_growing'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
@@ -112,548 +112,561 @@ <h2>
     <p class="run"><span class="n"><a id="t30" href="#t30">30</a></span><span class="t">    <span class="nam">select_best_candidate</span><span class="op">:</span> <span class="nam">Optional</span><span class="op">[</span><span class="nam">bool</span><span class="op">]</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'select_best_candidate'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
     <p class="run"><span class="n"><a id="t31" href="#t31">31</a></span><span class="t">    <span class="nam">complementary_conditions</span><span class="op">:</span> <span class="nam">Optional</span><span class="op">[</span><span class="nam">bool</span><span class="op">]</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'complementary_conditions'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t32" href="#t32">32</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t33" href="#t33">33</a></span><span class="t">    <span class="nam">extend_using_preferred</span><span class="op">:</span> <span class="nam">Optional</span><span class="op">[</span><span class="nam">bool</span><span class="op">]</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'extend_using_preferred'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t34" href="#t34">34</a></span><span class="t">    <span class="nam">extend_using_automatic</span><span class="op">:</span> <span class="nam">Optional</span><span class="op">[</span><span class="nam">bool</span><span class="op">]</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'extend_using_automatic'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t35" href="#t35">35</a></span><span class="t">    <span class="nam">induce_using_preferred</span><span class="op">:</span> <span class="nam">Optional</span><span class="op">[</span><span class="nam">bool</span><span class="op">]</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'induce_using_preferred'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t36" href="#t36">36</a></span><span class="t">    <span class="nam">induce_using_automatic</span><span class="op">:</span> <span class="nam">Optional</span><span class="op">[</span><span class="nam">bool</span><span class="op">]</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'induce_using_automatic'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t37" href="#t37">37</a></span><span class="t">    <span class="nam">consider_other_classes</span><span class="op">:</span> <span class="nam">Optional</span><span class="op">[</span><span class="nam">bool</span><span class="op">]</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'consider_other_classes'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t38" href="#t38">38</a></span><span class="t">    <span class="nam">preferred_conditions_per_rule</span><span class="op">:</span> <span class="nam">Optional</span><span class="op">[</span><span class="nam">int</span><span class="op">]</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'preferred_conditions_per_rule'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t39" href="#t39">39</a></span><span class="t">    <span class="nam">preferred_attributes_per_rule</span><span class="op">:</span> <span class="nam">Optional</span><span class="op">[</span><span class="nam">int</span><span class="op">]</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'preferred_attributes_per_rule'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t40" href="#t40">40</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t33" href="#t33">33</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t34" href="#t34">34</a></span><span class="t"><span class="key">class</span> <span class="nam">_SurvivalExpertModelParams</span><span class="op">(</span><span class="nam">_SurvivalModelsParams</span><span class="op">,</span> <span class="nam">ExpertModelParams</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t35" href="#t35">35</a></span><span class="t">    <span class="key">pass</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t36" href="#t36">36</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t37" href="#t37">37</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t38" href="#t38">38</a></span><span class="t"><span class="key">class</span> <span class="nam">_BaseSurvivalRulesModel</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t39" href="#t39">39</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t40" href="#t40">40</a></span><span class="t">    <span class="nam">model</span><span class="op">:</span> <span class="nam">RuleSet</span><span class="op">[</span><span class="nam">SurvivalRule</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t41" href="#t41">41</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t42" href="#t42">42</a></span><span class="t"><span class="key">class</span> <span class="nam">SurvivalRules</span><span class="op">(</span><span class="nam">BaseOperator</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t43" href="#t43">43</a></span><span class="t">    <span class="str">"""Survival model."""</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t42" href="#t42">42</a></span><span class="t">    <span class="key">def</span> <span class="nam">get_train_set_kaplan_meier</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">KaplanMeierEstimator</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t43" href="#t43">43</a></span><span class="t">        <span class="str">"""Returns train set KaplanMeier estimator</span>&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t44" href="#t44">44</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t45" href="#t45">45</a></span><span class="t">    <span class="nam">__params_class__</span> <span class="op">=</span> <span class="nam">SurvivalModelsParams</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t46" href="#t46">46</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t47" href="#t47">47</a></span><span class="t">    <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span>  <span class="com"># pylint: disable=super-init-not-called,too-many-arguments</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t48" href="#t48">48</a></span><span class="t">        <span class="nam">self</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t49" href="#t49">49</a></span><span class="t">        <span class="nam">survival_time_attr</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="key">None</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t50" href="#t50">50</a></span><span class="t">        <span class="nam">minsupp_new</span><span class="op">:</span> <span class="nam">int</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'minsupp_new'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t51" href="#t51">51</a></span><span class="t">        <span class="nam">max_growing</span><span class="op">:</span> <span class="nam">int</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'max_growing'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t52" href="#t52">52</a></span><span class="t">        <span class="nam">enable_pruning</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'enable_pruning'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t53" href="#t53">53</a></span><span class="t">        <span class="nam">ignore_missing</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'ignore_missing'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t54" href="#t54">54</a></span><span class="t">        <span class="nam">max_uncovered_fraction</span><span class="op">:</span> <span class="nam">float</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'max_uncovered_fraction'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t55" href="#t55">55</a></span><span class="t">        <span class="nam">select_best_candidate</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'select_best_candidate'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t56" href="#t56">56</a></span><span class="t">        <span class="nam">complementary_conditions</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'complementary_conditions'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t57" href="#t57">57</a></span><span class="t">        <span class="nam">max_rule_count</span><span class="op">:</span> <span class="nam">int</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'max_rule_count'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t58" href="#t58">58</a></span><span class="t">    <span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t59" href="#t59">59</a></span><span class="t">        <span class="str">"""</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t60" href="#t60">60</a></span><span class="t"><span class="str">        Parameters</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t61" href="#t61">61</a></span><span class="t"><span class="str">        ----------</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t62" href="#t62">62</a></span><span class="t"><span class="str">        survival_time_attr : str</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t63" href="#t63">63</a></span><span class="t"><span class="str">            name of column containing survival time data (use when data passed to model is padnas</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t64" href="#t64">64</a></span><span class="t"><span class="str">            dataframe).</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t65" href="#t65">65</a></span><span class="t"><span class="str">        minsupp_new : float = 5.0</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t66" href="#t66">66</a></span><span class="t"><span class="str">            a minimum number (or fraction, if value &lt; 1.0) of previously uncovered examples</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t67" href="#t67">67</a></span><span class="t"><span class="str">             to be covered by a new rule (positive examples for classification problems); default: 5,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t68" href="#t68">68</a></span><span class="t"><span class="str">        max_growing : int = 0.0</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t69" href="#t69">69</a></span><span class="t"><span class="str">            non-negative integer representing maximum number of conditions which can be added to</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t70" href="#t70">70</a></span><span class="t"><span class="str">            the rule in the growing phase  (use this parameter for large datasets if execution time</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t71" href="#t71">71</a></span><span class="t"><span class="str">            is prohibitive); 0 indicates no limit; default: 0,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t72" href="#t72">72</a></span><span class="t"><span class="str">        enable_pruning : bool = True</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t73" href="#t73">73</a></span><span class="t"><span class="str">            enable or disable pruning, default is True.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t74" href="#t74">74</a></span><span class="t"><span class="str">        ignore_missing : bool = False</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t75" href="#t75">75</a></span><span class="t"><span class="str">            boolean telling whether missing values should be ignored (by default, a missing value</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t76" href="#t76">76</a></span><span class="t"><span class="str">             of given attribute is always considered as not fulfilling the condition build upon that</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t77" href="#t77">77</a></span><span class="t"><span class="str">            attribute); default: False.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t78" href="#t78">78</a></span><span class="t"><span class="str">        max_uncovered_fraction : float = 0.0</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t79" href="#t79">79</a></span><span class="t"><span class="str">            Floating-point number from [0,1] interval representing maximum fraction of examples</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t80" href="#t80">80</a></span><span class="t"><span class="str">             that may remain uncovered by the rule set, default: 0.0.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t81" href="#t81">81</a></span><span class="t"><span class="str">        select_best_candidate : bool = False</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t82" href="#t82">82</a></span><span class="t"><span class="str">            Flag determining if best candidate should be selected from growing phase;</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t83" href="#t83">83</a></span><span class="t"><span class="str">             default: False.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t84" href="#t84">84</a></span><span class="t"><span class="str">        complementary_conditions : bool = False</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t85" href="#t85">85</a></span><span class="t"><span class="str">            If enabled, complementary conditions in the form a = !{value} for nominal attributes</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t86" href="#t86">86</a></span><span class="t"><span class="str">            are supported.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t87" href="#t87">87</a></span><span class="t"><span class="str">        max_rule_count : int = 0</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t88" href="#t88">88</a></span><span class="t"><span class="str">            Maximum number of rules to be generated (for classification data sets it applies</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t89" href="#t89">89</a></span><span class="t"><span class="str">             to a single class); 0 indicates no limit.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t90" href="#t90">90</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t91" href="#t91">91</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_params</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t92" href="#t92">92</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_rule_generator</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t93" href="#t93">93</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_configurator</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t94" href="#t94">94</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">set_params</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t95" href="#t95">95</a></span><span class="t">            <span class="nam">survival_time_attr</span><span class="op">=</span><span class="nam">survival_time_attr</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t96" href="#t96">96</a></span><span class="t">            <span class="nam">minsupp_new</span><span class="op">=</span><span class="nam">minsupp_new</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t97" href="#t97">97</a></span><span class="t">            <span class="nam">max_growing</span><span class="op">=</span><span class="nam">max_growing</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t98" href="#t98">98</a></span><span class="t">            <span class="nam">enable_pruning</span><span class="op">=</span><span class="nam">enable_pruning</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t99" href="#t99">99</a></span><span class="t">            <span class="nam">ignore_missing</span><span class="op">=</span><span class="nam">ignore_missing</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t100" href="#t100">100</a></span><span class="t">            <span class="nam">max_uncovered_fraction</span><span class="op">=</span><span class="nam">max_uncovered_fraction</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t101" href="#t101">101</a></span><span class="t">            <span class="nam">select_best_candidate</span><span class="op">=</span><span class="nam">select_best_candidate</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t102" href="#t102">102</a></span><span class="t">            <span class="nam">complementary_conditions</span><span class="op">=</span><span class="nam">complementary_conditions</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t103" href="#t103">103</a></span><span class="t">            <span class="nam">max_rule_count</span><span class="op">=</span><span class="nam">max_rule_count</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t104" href="#t104">104</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t105" href="#t105">105</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">model</span><span class="op">:</span> <span class="nam">RuleSet</span><span class="op">[</span><span class="nam">SurvivalRule</span><span class="op">]</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t106" href="#t106">106</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t107" href="#t107">107</a></span><span class="t">    <span class="key">def</span> <span class="nam">set_params</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t108" href="#t108">108</a></span><span class="t">        <span class="nam">self</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t109" href="#t109">109</a></span><span class="t">        <span class="op">**</span><span class="nam">kwargs</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t110" href="#t110">110</a></span><span class="t">    <span class="op">)</span> <span class="op">-></span> <span class="nam">object</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t111" href="#t111">111</a></span><span class="t">        <span class="str">"""Set models hyperparameters. Parameters are the same as in constructor."""</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t112" href="#t112">112</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">survival_time_attr</span> <span class="op">=</span> <span class="nam">kwargs</span><span class="op">.</span><span class="nam">get</span><span class="op">(</span><span class="str">'survival_time_attr'</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t113" href="#t113">113</a></span><span class="t">        <span class="key">return</span> <span class="nam">BaseOperator</span><span class="op">.</span><span class="nam">set_params</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="op">**</span><span class="nam">kwargs</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t114" href="#t114">114</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t115" href="#t115">115</a></span><span class="t">    <span class="op">@</span><span class="nam">staticmethod</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t116" href="#t116">116</a></span><span class="t">    <span class="key">def</span> <span class="nam">_append_survival_time_columns</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t117" href="#t117">117</a></span><span class="t">        <span class="nam">values</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t118" href="#t118">118</a></span><span class="t">        <span class="nam">survival_time</span><span class="op">:</span> <span class="nam">Union</span><span class="op">[</span><span class="nam">pd</span><span class="op">.</span><span class="nam">Series</span><span class="op">,</span> <span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span><span class="op">,</span> <span class="nam">list</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t119" href="#t119">119</a></span><span class="t">    <span class="op">)</span> <span class="op">-></span> <span class="nam">Optional</span><span class="op">[</span><span class="nam">str</span><span class="op">]</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t120" href="#t120">120</a></span><span class="t">        <span class="nam">survival_time_attr</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="nam">_DEFAULT_SURVIVAL_TIME_ATTR</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t121" href="#t121">121</a></span><span class="t">        <span class="key">if</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">values</span><span class="op">,</span> <span class="nam">pd</span><span class="op">.</span><span class="nam">Series</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t122" href="#t122">122</a></span><span class="t">            <span class="key">if</span> <span class="nam">survival_time</span><span class="op">.</span><span class="nam">name</span> <span class="key">is</span> <span class="key">None</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t123" href="#t123">123</a></span><span class="t">                <span class="nam">survival_time</span><span class="op">.</span><span class="nam">name</span> <span class="op">=</span> <span class="nam">survival_time_attr</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t124" href="#t124">124</a></span><span class="t">            <span class="key">else</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t125" href="#t125">125</a></span><span class="t">                <span class="nam">survival_time_attr</span> <span class="op">=</span> <span class="nam">survival_time</span><span class="op">.</span><span class="nam">name</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t126" href="#t126">126</a></span><span class="t">            <span class="nam">values</span><span class="op">[</span><span class="nam">survival_time</span><span class="op">.</span><span class="nam">name</span><span class="op">]</span> <span class="op">=</span> <span class="nam">survival_time</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t127" href="#t127">127</a></span><span class="t">        <span class="key">elif</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">values</span><span class="op">,</span> <span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t128" href="#t128">128</a></span><span class="t">            <span class="nam">np</span><span class="op">.</span><span class="nam">append</span><span class="op">(</span><span class="nam">values</span><span class="op">,</span> <span class="nam">survival_time</span><span class="op">,</span> <span class="nam">axis</span><span class="op">=</span><span class="num">1</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t129" href="#t129">129</a></span><span class="t">        <span class="key">elif</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">values</span><span class="op">,</span> <span class="nam">list</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t130" href="#t130">130</a></span><span class="t">            <span class="key">for</span> <span class="nam">index</span><span class="op">,</span> <span class="nam">row</span> <span class="key">in</span> <span class="nam">enumerate</span><span class="op">(</span><span class="nam">values</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t131" href="#t131">131</a></span><span class="t">                <span class="nam">row</span><span class="op">.</span><span class="nam">append</span><span class="op">(</span><span class="nam">survival_time</span><span class="op">[</span><span class="nam">index</span><span class="op">]</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t132" href="#t132">132</a></span><span class="t">        <span class="key">else</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t133" href="#t133">133</a></span><span class="t">            <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t134" href="#t134">134</a></span><span class="t">                <span class="str">'Data values must be instance of either pandas DataFrame, numpy array or list'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t135" href="#t135">135</a></span><span class="t">            <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t136" href="#t136">136</a></span><span class="t">        <span class="key">return</span> <span class="nam">survival_time_attr</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t137" href="#t137">137</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t138" href="#t138">138</a></span><span class="t">    <span class="key">def</span> <span class="nam">_prepare_survival_attribute</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">survival_time</span><span class="op">:</span> <span class="nam">Optional</span><span class="op">[</span><span class="nam">Data</span><span class="op">]</span><span class="op">,</span> <span class="nam">values</span><span class="op">:</span> <span class="nam">Data</span><span class="op">)</span> <span class="op">-></span> <span class="nam">str</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t139" href="#t139">139</a></span><span class="t">        <span class="key">if</span> <span class="nam">self</span><span class="op">.</span><span class="nam">survival_time_attr</span> <span class="key">is</span> <span class="key">None</span> <span class="key">and</span> <span class="nam">survival_time</span> <span class="key">is</span> <span class="key">None</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t140" href="#t140">140</a></span><span class="t">            <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t141" href="#t141">141</a></span><span class="t">                <span class="str">'No "survival_time" attribute name was specified. '</span> <span class="op">+</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t142" href="#t142">142</a></span><span class="t">                <span class="str">'Specify it using method set_params'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t143" href="#t143">143</a></span><span class="t">            <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t144" href="#t144">144</a></span><span class="t">        <span class="key">if</span> <span class="nam">survival_time</span> <span class="key">is</span> <span class="key">not</span> <span class="key">None</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t145" href="#t145">145</a></span><span class="t">            <span class="key">return</span> <span class="nam">SurvivalRules</span><span class="op">.</span><span class="nam">_append_survival_time_columns</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t146" href="#t146">146</a></span><span class="t">                <span class="nam">values</span><span class="op">,</span> <span class="nam">survival_time</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t147" href="#t147">147</a></span><span class="t">        <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">survival_time_attr</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t148" href="#t148">148</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t149" href="#t149">149</a></span><span class="t">    <span class="key">def</span> <span class="nam">fit</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">values</span><span class="op">:</span> <span class="nam">Data</span><span class="op">,</span> <span class="nam">labels</span><span class="op">:</span> <span class="nam">Data</span><span class="op">,</span> <span class="nam">survival_time</span><span class="op">:</span> <span class="nam">Data</span> <span class="op">=</span> <span class="key">None</span><span class="op">)</span> <span class="op">-></span> <span class="nam">SurvivalRules</span><span class="op">:</span>  <span class="com"># pylint: disable=arguments-differ</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t150" href="#t150">150</a></span><span class="t">        <span class="str">"""Train model on given dataset.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t151" href="#t151">151</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t152" href="#t152">152</a></span><span class="t"><span class="str">        Parameters</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t153" href="#t153">153</a></span><span class="t"><span class="str">        ----------</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t154" href="#t154">154</a></span><span class="t"><span class="str">        values : :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t155" href="#t155">155</a></span><span class="t"><span class="str">            attributes</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t156" href="#t156">156</a></span><span class="t"><span class="str">        labels : :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t157" href="#t157">157</a></span><span class="t"><span class="str">            survival status</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t158" href="#t158">158</a></span><span class="t"><span class="str">        survival_time: :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t159" href="#t159">159</a></span><span class="t"><span class="str">            data about survival time. Could be omitted when *survival_time_attr* parameter</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t160" href="#t160">160</a></span><span class="t"><span class="str">             was specified.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t161" href="#t161">161</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t162" href="#t162">162</a></span><span class="t"><span class="str">        Returns</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t163" href="#t163">163</a></span><span class="t"><span class="str">        -------</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t164" href="#t164">164</a></span><span class="t"><span class="str">        self : SurvivalRules</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t165" href="#t165">165</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t166" href="#t166">166</a></span><span class="t">        <span class="nam">survival_time_attribute</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_prepare_survival_attribute</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t167" href="#t167">167</a></span><span class="t">            <span class="nam">survival_time</span><span class="op">,</span> <span class="nam">values</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t168" href="#t168">168</a></span><span class="t">        <span class="nam">super</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">fit</span><span class="op">(</span><span class="nam">values</span><span class="op">,</span> <span class="nam">labels</span><span class="op">,</span> <span class="nam">survival_time_attribute</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t169" href="#t169">169</a></span><span class="t">        <span class="key">return</span> <span class="nam">self</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t170" href="#t170">170</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t171" href="#t171">171</a></span><span class="t">    <span class="key">def</span> <span class="nam">predict</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">values</span><span class="op">:</span> <span class="nam">Data</span><span class="op">)</span> <span class="op">-></span> <span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t172" href="#t172">172</a></span><span class="t">        <span class="str">"""Perform prediction and return estimated survival function for each example.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t45" href="#t45">45</a></span><span class="t"><span class="str">        Returns:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t46" href="#t46">46</a></span><span class="t"><span class="str">            KaplanMeierEstimator: estimator</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t47" href="#t47">47</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t48" href="#t48">48</a></span><span class="t">        <span class="key">return</span> <span class="nam">KaplanMeierEstimator</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t49" href="#t49">49</a></span><span class="t">            <span class="nam">self</span><span class="op">.</span><span class="nam">model</span><span class="op">.</span><span class="nam">_java_object</span><span class="op">.</span><span class="nam">getTrainingEstimator</span><span class="op">(</span><span class="op">)</span>  <span class="com"># pylint: disable=protected-access</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t50" href="#t50">50</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t51" href="#t51">51</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t52" href="#t52">52</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t53" href="#t53">53</a></span><span class="t"><span class="key">class</span> <span class="nam">SurvivalRules</span><span class="op">(</span><span class="nam">BaseOperator</span><span class="op">,</span> <span class="nam">_BaseSurvivalRulesModel</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t54" href="#t54">54</a></span><span class="t">    <span class="str">"""Survival model."""</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t55" href="#t55">55</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t56" href="#t56">56</a></span><span class="t">    <span class="nam">__params_class__</span> <span class="op">=</span> <span class="nam">_SurvivalModelsParams</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t57" href="#t57">57</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t58" href="#t58">58</a></span><span class="t">    <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span>  <span class="com"># pylint: disable=super-init-not-called,too-many-arguments</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t59" href="#t59">59</a></span><span class="t">        <span class="nam">self</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t60" href="#t60">60</a></span><span class="t">        <span class="nam">survival_time_attr</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="key">None</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t61" href="#t61">61</a></span><span class="t">        <span class="nam">minsupp_new</span><span class="op">:</span> <span class="nam">int</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'minsupp_new'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t62" href="#t62">62</a></span><span class="t">        <span class="nam">max_growing</span><span class="op">:</span> <span class="nam">int</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'max_growing'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t63" href="#t63">63</a></span><span class="t">        <span class="nam">enable_pruning</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'enable_pruning'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t64" href="#t64">64</a></span><span class="t">        <span class="nam">ignore_missing</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'ignore_missing'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t65" href="#t65">65</a></span><span class="t">        <span class="nam">max_uncovered_fraction</span><span class="op">:</span> <span class="nam">float</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'max_uncovered_fraction'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t66" href="#t66">66</a></span><span class="t">        <span class="nam">select_best_candidate</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'select_best_candidate'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t67" href="#t67">67</a></span><span class="t">        <span class="nam">complementary_conditions</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'complementary_conditions'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t68" href="#t68">68</a></span><span class="t">        <span class="nam">max_rule_count</span><span class="op">:</span> <span class="nam">int</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'max_rule_count'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t69" href="#t69">69</a></span><span class="t">    <span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t70" href="#t70">70</a></span><span class="t">        <span class="str">"""</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t71" href="#t71">71</a></span><span class="t"><span class="str">        Parameters</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t72" href="#t72">72</a></span><span class="t"><span class="str">        ----------</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t73" href="#t73">73</a></span><span class="t"><span class="str">        survival_time_attr : str</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t74" href="#t74">74</a></span><span class="t"><span class="str">            name of column containing survival time data (use when data passed to model is padnas</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t75" href="#t75">75</a></span><span class="t"><span class="str">            dataframe).</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t76" href="#t76">76</a></span><span class="t"><span class="str">        minsupp_new : float = 5.0</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t77" href="#t77">77</a></span><span class="t"><span class="str">            a minimum number (or fraction, if value &lt; 1.0) of previously uncovered examples</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t78" href="#t78">78</a></span><span class="t"><span class="str">             to be covered by a new rule (positive examples for classification problems); default: 5,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t79" href="#t79">79</a></span><span class="t"><span class="str">        max_growing : int = 0.0</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t80" href="#t80">80</a></span><span class="t"><span class="str">            non-negative integer representing maximum number of conditions which can be added to</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t81" href="#t81">81</a></span><span class="t"><span class="str">            the rule in the growing phase  (use this parameter for large datasets if execution time</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t82" href="#t82">82</a></span><span class="t"><span class="str">            is prohibitive); 0 indicates no limit; default: 0,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t83" href="#t83">83</a></span><span class="t"><span class="str">        enable_pruning : bool = True</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t84" href="#t84">84</a></span><span class="t"><span class="str">            enable or disable pruning, default is True.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t85" href="#t85">85</a></span><span class="t"><span class="str">        ignore_missing : bool = False</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t86" href="#t86">86</a></span><span class="t"><span class="str">            boolean telling whether missing values should be ignored (by default, a missing value</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t87" href="#t87">87</a></span><span class="t"><span class="str">             of given attribute is always considered as not fulfilling the condition build upon that</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t88" href="#t88">88</a></span><span class="t"><span class="str">            attribute); default: False.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t89" href="#t89">89</a></span><span class="t"><span class="str">        max_uncovered_fraction : float = 0.0</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t90" href="#t90">90</a></span><span class="t"><span class="str">            Floating-point number from [0,1] interval representing maximum fraction of examples</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t91" href="#t91">91</a></span><span class="t"><span class="str">             that may remain uncovered by the rule set, default: 0.0.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t92" href="#t92">92</a></span><span class="t"><span class="str">        select_best_candidate : bool = False</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t93" href="#t93">93</a></span><span class="t"><span class="str">            Flag determining if best candidate should be selected from growing phase;</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t94" href="#t94">94</a></span><span class="t"><span class="str">             default: False.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t95" href="#t95">95</a></span><span class="t"><span class="str">        complementary_conditions : bool = False</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t96" href="#t96">96</a></span><span class="t"><span class="str">            If enabled, complementary conditions in the form a = !{value} for nominal attributes</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t97" href="#t97">97</a></span><span class="t"><span class="str">            are supported.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t98" href="#t98">98</a></span><span class="t"><span class="str">        max_rule_count : int = 0</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t99" href="#t99">99</a></span><span class="t"><span class="str">            Maximum number of rules to be generated (for classification data sets it applies</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t100" href="#t100">100</a></span><span class="t"><span class="str">             to a single class); 0 indicates no limit.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t101" href="#t101">101</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t102" href="#t102">102</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_params</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t103" href="#t103">103</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_rule_generator</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t104" href="#t104">104</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_configurator</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t105" href="#t105">105</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_initialize_rulekit</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t106" href="#t106">106</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">set_params</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t107" href="#t107">107</a></span><span class="t">            <span class="nam">survival_time_attr</span><span class="op">=</span><span class="nam">survival_time_attr</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t108" href="#t108">108</a></span><span class="t">            <span class="nam">minsupp_new</span><span class="op">=</span><span class="nam">minsupp_new</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t109" href="#t109">109</a></span><span class="t">            <span class="nam">max_growing</span><span class="op">=</span><span class="nam">max_growing</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t110" href="#t110">110</a></span><span class="t">            <span class="nam">enable_pruning</span><span class="op">=</span><span class="nam">enable_pruning</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t111" href="#t111">111</a></span><span class="t">            <span class="nam">ignore_missing</span><span class="op">=</span><span class="nam">ignore_missing</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t112" href="#t112">112</a></span><span class="t">            <span class="nam">max_uncovered_fraction</span><span class="op">=</span><span class="nam">max_uncovered_fraction</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t113" href="#t113">113</a></span><span class="t">            <span class="nam">select_best_candidate</span><span class="op">=</span><span class="nam">select_best_candidate</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t114" href="#t114">114</a></span><span class="t">            <span class="nam">complementary_conditions</span><span class="op">=</span><span class="nam">complementary_conditions</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t115" href="#t115">115</a></span><span class="t">            <span class="nam">max_rule_count</span><span class="op">=</span><span class="nam">max_rule_count</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t116" href="#t116">116</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t117" href="#t117">117</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">model</span><span class="op">:</span> <span class="nam">RuleSet</span><span class="op">[</span><span class="nam">SurvivalRule</span><span class="op">]</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t118" href="#t118">118</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t119" href="#t119">119</a></span><span class="t">    <span class="key">def</span> <span class="nam">set_params</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t120" href="#t120">120</a></span><span class="t">        <span class="nam">self</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t121" href="#t121">121</a></span><span class="t">        <span class="op">**</span><span class="nam">kwargs</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t122" href="#t122">122</a></span><span class="t">    <span class="op">)</span> <span class="op">-></span> <span class="nam">object</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t123" href="#t123">123</a></span><span class="t">        <span class="str">"""Set models hyperparameters. Parameters are the same as in constructor."""</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t124" href="#t124">124</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">survival_time_attr</span> <span class="op">=</span> <span class="nam">kwargs</span><span class="op">.</span><span class="nam">get</span><span class="op">(</span><span class="str">'survival_time_attr'</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t125" href="#t125">125</a></span><span class="t">        <span class="key">return</span> <span class="nam">BaseOperator</span><span class="op">.</span><span class="nam">set_params</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="op">**</span><span class="nam">kwargs</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t126" href="#t126">126</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t127" href="#t127">127</a></span><span class="t">    <span class="op">@</span><span class="nam">staticmethod</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t128" href="#t128">128</a></span><span class="t">    <span class="key">def</span> <span class="nam">_append_survival_time_columns</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t129" href="#t129">129</a></span><span class="t">        <span class="nam">values</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t130" href="#t130">130</a></span><span class="t">        <span class="nam">survival_time</span><span class="op">:</span> <span class="nam">Union</span><span class="op">[</span><span class="nam">pd</span><span class="op">.</span><span class="nam">Series</span><span class="op">,</span> <span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span><span class="op">,</span> <span class="nam">list</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t131" href="#t131">131</a></span><span class="t">    <span class="op">)</span> <span class="op">-></span> <span class="nam">Optional</span><span class="op">[</span><span class="nam">str</span><span class="op">]</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t132" href="#t132">132</a></span><span class="t">        <span class="nam">survival_time_attr</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="nam">_DEFAULT_SURVIVAL_TIME_ATTR</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t133" href="#t133">133</a></span><span class="t">        <span class="key">if</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">survival_time</span><span class="op">,</span> <span class="nam">pd</span><span class="op">.</span><span class="nam">Series</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t134" href="#t134">134</a></span><span class="t">            <span class="key">if</span> <span class="nam">survival_time</span><span class="op">.</span><span class="nam">name</span> <span class="key">is</span> <span class="key">None</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t135" href="#t135">135</a></span><span class="t">                <span class="nam">survival_time</span><span class="op">.</span><span class="nam">name</span> <span class="op">=</span> <span class="nam">survival_time_attr</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t136" href="#t136">136</a></span><span class="t">            <span class="key">else</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t137" href="#t137">137</a></span><span class="t">                <span class="nam">survival_time_attr</span> <span class="op">=</span> <span class="nam">survival_time</span><span class="op">.</span><span class="nam">name</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t138" href="#t138">138</a></span><span class="t">            <span class="nam">values</span><span class="op">[</span><span class="nam">survival_time</span><span class="op">.</span><span class="nam">name</span><span class="op">]</span> <span class="op">=</span> <span class="nam">survival_time</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t139" href="#t139">139</a></span><span class="t">        <span class="key">elif</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">survival_time</span><span class="op">,</span> <span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t140" href="#t140">140</a></span><span class="t">            <span class="nam">np</span><span class="op">.</span><span class="nam">append</span><span class="op">(</span><span class="nam">values</span><span class="op">,</span> <span class="nam">survival_time</span><span class="op">,</span> <span class="nam">axis</span><span class="op">=</span><span class="num">1</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t141" href="#t141">141</a></span><span class="t">        <span class="key">elif</span> <span class="nam">isinstance</span><span class="op">(</span><span class="nam">survival_time</span><span class="op">,</span> <span class="nam">list</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t142" href="#t142">142</a></span><span class="t">            <span class="key">for</span> <span class="nam">index</span><span class="op">,</span> <span class="nam">row</span> <span class="key">in</span> <span class="nam">enumerate</span><span class="op">(</span><span class="nam">values</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t143" href="#t143">143</a></span><span class="t">                <span class="nam">row</span><span class="op">.</span><span class="nam">append</span><span class="op">(</span><span class="nam">survival_time</span><span class="op">[</span><span class="nam">index</span><span class="op">]</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t144" href="#t144">144</a></span><span class="t">        <span class="key">else</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t145" href="#t145">145</a></span><span class="t">            <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t146" href="#t146">146</a></span><span class="t">                <span class="str">'Data values must be instance of either pandas DataFrame, numpy array or list'</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t147" href="#t147">147</a></span><span class="t">            <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t148" href="#t148">148</a></span><span class="t">        <span class="key">return</span> <span class="nam">survival_time_attr</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t149" href="#t149">149</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t150" href="#t150">150</a></span><span class="t">    <span class="key">def</span> <span class="nam">_prepare_survival_attribute</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">survival_time</span><span class="op">:</span> <span class="nam">Optional</span><span class="op">[</span><span class="nam">Data</span><span class="op">]</span><span class="op">,</span> <span class="nam">values</span><span class="op">:</span> <span class="nam">Data</span><span class="op">)</span> <span class="op">-></span> <span class="nam">str</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t151" href="#t151">151</a></span><span class="t">        <span class="key">if</span> <span class="nam">self</span><span class="op">.</span><span class="nam">survival_time_attr</span> <span class="key">is</span> <span class="key">None</span> <span class="key">and</span> <span class="nam">survival_time</span> <span class="key">is</span> <span class="key">None</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t152" href="#t152">152</a></span><span class="t">            <span class="key">raise</span> <span class="nam">ValueError</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t153" href="#t153">153</a></span><span class="t">                <span class="str">'No "survival_time" attribute name was specified. '</span> <span class="op">+</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t154" href="#t154">154</a></span><span class="t">                <span class="str">'Specify it using method set_params'</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t155" href="#t155">155</a></span><span class="t">            <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t156" href="#t156">156</a></span><span class="t">        <span class="key">if</span> <span class="nam">survival_time</span> <span class="key">is</span> <span class="key">not</span> <span class="key">None</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t157" href="#t157">157</a></span><span class="t">            <span class="key">return</span> <span class="nam">SurvivalRules</span><span class="op">.</span><span class="nam">_append_survival_time_columns</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t158" href="#t158">158</a></span><span class="t">                <span class="nam">values</span><span class="op">,</span> <span class="nam">survival_time</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t159" href="#t159">159</a></span><span class="t">        <span class="key">return</span> <span class="nam">self</span><span class="op">.</span><span class="nam">survival_time_attr</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t160" href="#t160">160</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t161" href="#t161">161</a></span><span class="t">    <span class="key">def</span> <span class="nam">fit</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">values</span><span class="op">:</span> <span class="nam">Data</span><span class="op">,</span> <span class="nam">labels</span><span class="op">:</span> <span class="nam">Data</span><span class="op">,</span> <span class="nam">survival_time</span><span class="op">:</span> <span class="nam">Data</span> <span class="op">=</span> <span class="key">None</span><span class="op">)</span> <span class="op">-></span> <span class="nam">SurvivalRules</span><span class="op">:</span>  <span class="com"># pylint: disable=arguments-differ</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t162" href="#t162">162</a></span><span class="t">        <span class="str">"""Train model on given dataset.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t163" href="#t163">163</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t164" href="#t164">164</a></span><span class="t"><span class="str">        Parameters</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t165" href="#t165">165</a></span><span class="t"><span class="str">        ----------</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t166" href="#t166">166</a></span><span class="t"><span class="str">        values : :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t167" href="#t167">167</a></span><span class="t"><span class="str">            attributes</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t168" href="#t168">168</a></span><span class="t"><span class="str">        labels : :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t169" href="#t169">169</a></span><span class="t"><span class="str">            survival status</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t170" href="#t170">170</a></span><span class="t"><span class="str">        survival_time: :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t171" href="#t171">171</a></span><span class="t"><span class="str">            data about survival time. Could be omitted when *survival_time_attr* parameter</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t172" href="#t172">172</a></span><span class="t"><span class="str">             was specified.</span>&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t173" href="#t173">173</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t174" href="#t174">174</a></span><span class="t"><span class="str">        Parameters</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t175" href="#t175">175</a></span><span class="t"><span class="str">        ----------</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t176" href="#t176">176</a></span><span class="t"><span class="str">        values : :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t177" href="#t177">177</a></span><span class="t"><span class="str">            attributes</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t178" href="#t178">178</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t179" href="#t179">179</a></span><span class="t"><span class="str">        Returns</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t180" href="#t180">180</a></span><span class="t"><span class="str">        -------</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t181" href="#t181">181</a></span><span class="t"><span class="str">        result : np.ndarray</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t182" href="#t182">182</a></span><span class="t"><span class="str">            Each row represent single example from dataset and contains estimated survival function</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t183" href="#t183">183</a></span><span class="t"><span class="str">            for that example. Estimated survival function is returned as a dictionary containing</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t184" href="#t184">184</a></span><span class="t"><span class="str">             times and corresponding probabilities.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t185" href="#t185">185</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t186" href="#t186">186</a></span><span class="t">        <span class="key">return</span> <span class="nam">PredictionResultMapper</span><span class="op">.</span><span class="nam">map_survival</span><span class="op">(</span><span class="nam">super</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">predict</span><span class="op">(</span><span class="nam">values</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t187" href="#t187">187</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t188" href="#t188">188</a></span><span class="t">    <span class="key">def</span> <span class="nam">score</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">values</span><span class="op">:</span> <span class="nam">Data</span><span class="op">,</span> <span class="nam">labels</span><span class="op">:</span> <span class="nam">Data</span><span class="op">,</span> <span class="nam">survival_time</span><span class="op">:</span> <span class="nam">Data</span> <span class="op">=</span> <span class="key">None</span><span class="op">)</span> <span class="op">-></span> <span class="nam">float</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t189" href="#t189">189</a></span><span class="t">        <span class="str">"""Return the Integrated Brier Score on the given dataset and labels</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t190" href="#t190">190</a></span><span class="t"><span class="str">         (event status indicator).</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t191" href="#t191">191</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t192" href="#t192">192</a></span><span class="t"><span class="str">        Integrated Brier Score (IBS) - the Brier score (BS) represents the squared difference</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t193" href="#t193">193</a></span><span class="t"><span class="str">         between true event status at time T and predicted event status at that time;</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t194" href="#t194">194</a></span><span class="t"><span class="str">         the Integrated Brier score summarizes the prediction error over all observations and over</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t195" href="#t195">195</a></span><span class="t"><span class="str">         all times in a test set.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t196" href="#t196">196</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t197" href="#t197">197</a></span><span class="t"><span class="str">        Parameters</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t198" href="#t198">198</a></span><span class="t"><span class="str">        ----------</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t199" href="#t199">199</a></span><span class="t"><span class="str">        values : :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t200" href="#t200">200</a></span><span class="t"><span class="str">            attributes</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t201" href="#t201">201</a></span><span class="t"><span class="str">        labels : :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t202" href="#t202">202</a></span><span class="t"><span class="str">            survival status</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t203" href="#t203">203</a></span><span class="t"><span class="str">        survival_time: :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t204" href="#t204">204</a></span><span class="t"><span class="str">            data about survival time. Could be omitted when *survival_time_attr* parameter was</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t205" href="#t205">205</a></span><span class="t"><span class="str">            specified</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t206" href="#t206">206</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t207" href="#t207">207</a></span><span class="t"><span class="str">        Returns</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t208" href="#t208">208</a></span><span class="t"><span class="str">        -------</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t209" href="#t209">209</a></span><span class="t"><span class="str">        score : float</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t210" href="#t210">210</a></span><span class="t"><span class="str">            Integrated Brier Score of self.predict(values) wrt. labels.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t211" href="#t211">211</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t212" href="#t212">212</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t213" href="#t213">213</a></span><span class="t">        <span class="nam">survival_time_attribute</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_prepare_survival_attribute</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t214" href="#t214">214</a></span><span class="t">            <span class="nam">survival_time</span><span class="op">,</span> <span class="nam">values</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t215" href="#t215">215</a></span><span class="t">        <span class="nam">example_set</span> <span class="op">=</span> <span class="nam">ExampleSetFactory</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">_get_problem_type</span><span class="op">(</span><span class="op">)</span><span class="op">)</span><span class="op">.</span><span class="nam">make</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t216" href="#t216">216</a></span><span class="t">            <span class="nam">values</span><span class="op">,</span> <span class="nam">labels</span><span class="op">,</span> <span class="nam">survival_time_attribute</span><span class="op">=</span><span class="nam">survival_time_attribute</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t217" href="#t217">217</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t218" href="#t218">218</a></span><span class="t">        <span class="nam">predicted_example_set</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">model</span><span class="op">.</span><span class="nam">_java_object</span><span class="op">.</span><span class="nam">apply</span><span class="op">(</span>  <span class="com"># pylint: disable=protected-access</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t219" href="#t219">219</a></span><span class="t">            <span class="nam">example_set</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t220" href="#t220">220</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t221" href="#t221">221</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t222" href="#t222">222</a></span><span class="t">        <span class="nam">IntegratedBrierScore</span> <span class="op">=</span> <span class="nam">JClass</span><span class="op">(</span>  <span class="com"># pylint: disable=invalid-name</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t223" href="#t223">223</a></span><span class="t">            <span class="str">'adaa.analytics.rules.logic.performance.IntegratedBrierScore'</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t224" href="#t224">224</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t225" href="#t225">225</a></span><span class="t">        <span class="nam">integrated_brier_score</span> <span class="op">=</span> <span class="nam">IntegratedBrierScore</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t226" href="#t226">226</a></span><span class="t">        <span class="nam">ibs</span> <span class="op">=</span> <span class="nam">integrated_brier_score</span><span class="op">.</span><span class="nam">countExample</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t227" href="#t227">227</a></span><span class="t">            <span class="nam">predicted_example_set</span><span class="op">)</span><span class="op">.</span><span class="nam">getValue</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t228" href="#t228">228</a></span><span class="t">        <span class="key">return</span> <span class="nam">float</span><span class="op">(</span><span class="nam">ibs</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t174" href="#t174">174</a></span><span class="t"><span class="str">        Returns</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t175" href="#t175">175</a></span><span class="t"><span class="str">        -------</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t176" href="#t176">176</a></span><span class="t"><span class="str">        self : SurvivalRules</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t177" href="#t177">177</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t178" href="#t178">178</a></span><span class="t">        <span class="nam">survival_time_attribute</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_prepare_survival_attribute</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t179" href="#t179">179</a></span><span class="t">            <span class="nam">survival_time</span><span class="op">,</span> <span class="nam">values</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t180" href="#t180">180</a></span><span class="t">        <span class="nam">super</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">fit</span><span class="op">(</span><span class="nam">values</span><span class="op">,</span> <span class="nam">labels</span><span class="op">,</span> <span class="nam">survival_time_attribute</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t181" href="#t181">181</a></span><span class="t">        <span class="key">return</span> <span class="nam">self</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t182" href="#t182">182</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t183" href="#t183">183</a></span><span class="t">    <span class="key">def</span> <span class="nam">predict</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">values</span><span class="op">:</span> <span class="nam">Data</span><span class="op">)</span> <span class="op">-></span> <span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t184" href="#t184">184</a></span><span class="t">        <span class="str">"""Perform prediction and return estimated survival function for each example.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t185" href="#t185">185</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t186" href="#t186">186</a></span><span class="t"><span class="str">        Parameters</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t187" href="#t187">187</a></span><span class="t"><span class="str">        ----------</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t188" href="#t188">188</a></span><span class="t"><span class="str">        values : :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t189" href="#t189">189</a></span><span class="t"><span class="str">            attributes</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t190" href="#t190">190</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t191" href="#t191">191</a></span><span class="t"><span class="str">        Returns</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t192" href="#t192">192</a></span><span class="t"><span class="str">        -------</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t193" href="#t193">193</a></span><span class="t"><span class="str">        result : np.ndarray</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t194" href="#t194">194</a></span><span class="t"><span class="str">            Each row represent single example from dataset and contains estimated survival function</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t195" href="#t195">195</a></span><span class="t"><span class="str">            for that example. Estimated survival function is returned as a dictionary containing</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t196" href="#t196">196</a></span><span class="t"><span class="str">             times and corresponding probabilities.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t197" href="#t197">197</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t198" href="#t198">198</a></span><span class="t">        <span class="key">return</span> <span class="nam">PredictionResultMapper</span><span class="op">.</span><span class="nam">map_survival</span><span class="op">(</span><span class="nam">super</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">predict</span><span class="op">(</span><span class="nam">values</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t199" href="#t199">199</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t200" href="#t200">200</a></span><span class="t">    <span class="key">def</span> <span class="nam">score</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">values</span><span class="op">:</span> <span class="nam">Data</span><span class="op">,</span> <span class="nam">labels</span><span class="op">:</span> <span class="nam">Data</span><span class="op">,</span> <span class="nam">survival_time</span><span class="op">:</span> <span class="nam">Data</span> <span class="op">=</span> <span class="key">None</span><span class="op">)</span> <span class="op">-></span> <span class="nam">float</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t201" href="#t201">201</a></span><span class="t">        <span class="str">"""Return the Integrated Brier Score on the given dataset and labels</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t202" href="#t202">202</a></span><span class="t"><span class="str">         (event status indicator).</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t203" href="#t203">203</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t204" href="#t204">204</a></span><span class="t"><span class="str">        Integrated Brier Score (IBS) - the Brier score (BS) represents the squared difference</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t205" href="#t205">205</a></span><span class="t"><span class="str">         between true event status at time T and predicted event status at that time;</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t206" href="#t206">206</a></span><span class="t"><span class="str">         the Integrated Brier score summarizes the prediction error over all observations and over</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t207" href="#t207">207</a></span><span class="t"><span class="str">         all times in a test set.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t208" href="#t208">208</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t209" href="#t209">209</a></span><span class="t"><span class="str">        Parameters</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t210" href="#t210">210</a></span><span class="t"><span class="str">        ----------</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t211" href="#t211">211</a></span><span class="t"><span class="str">        values : :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t212" href="#t212">212</a></span><span class="t"><span class="str">            attributes</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t213" href="#t213">213</a></span><span class="t"><span class="str">        labels : :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t214" href="#t214">214</a></span><span class="t"><span class="str">            survival status</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t215" href="#t215">215</a></span><span class="t"><span class="str">        survival_time: :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t216" href="#t216">216</a></span><span class="t"><span class="str">            data about survival time. Could be omitted when *survival_time_attr* parameter was</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t217" href="#t217">217</a></span><span class="t"><span class="str">            specified</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t218" href="#t218">218</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t219" href="#t219">219</a></span><span class="t"><span class="str">        Returns</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t220" href="#t220">220</a></span><span class="t"><span class="str">        -------</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t221" href="#t221">221</a></span><span class="t"><span class="str">        score : float</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t222" href="#t222">222</a></span><span class="t"><span class="str">            Integrated Brier Score of self.predict(values) wrt. labels.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t223" href="#t223">223</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t224" href="#t224">224</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t225" href="#t225">225</a></span><span class="t">        <span class="nam">survival_time_attribute</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">_prepare_survival_attribute</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t226" href="#t226">226</a></span><span class="t">            <span class="nam">survival_time</span><span class="op">,</span> <span class="nam">values</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t227" href="#t227">227</a></span><span class="t">        <span class="nam">example_set</span> <span class="op">=</span> <span class="nam">ExampleSetFactory</span><span class="op">(</span><span class="nam">self</span><span class="op">.</span><span class="nam">_get_problem_type</span><span class="op">(</span><span class="op">)</span><span class="op">)</span><span class="op">.</span><span class="nam">make</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t228" href="#t228">228</a></span><span class="t">            <span class="nam">values</span><span class="op">,</span> <span class="nam">labels</span><span class="op">,</span> <span class="nam">survival_time_attribute</span><span class="op">=</span><span class="nam">survival_time_attribute</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t229" href="#t229">229</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t230" href="#t230">230</a></span><span class="t">    <span class="key">def</span> <span class="nam">_get_problem_type</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">ProblemType</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t231" href="#t231">231</a></span><span class="t">        <span class="key">return</span> <span class="nam">ProblemType</span><span class="op">.</span><span class="nam">SURVIVAL</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t232" href="#t232">232</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t230" href="#t230">230</a></span><span class="t">        <span class="nam">predicted_example_set</span> <span class="op">=</span> <span class="nam">self</span><span class="op">.</span><span class="nam">model</span><span class="op">.</span><span class="nam">_java_object</span><span class="op">.</span><span class="nam">apply</span><span class="op">(</span>  <span class="com"># pylint: disable=protected-access</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t231" href="#t231">231</a></span><span class="t">            <span class="nam">example_set</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t232" href="#t232">232</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t233" href="#t233">233</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t234" href="#t234">234</a></span><span class="t"><span class="key">class</span> <span class="nam">ExpertSurvivalRules</span><span class="op">(</span><span class="nam">ExpertKnowledgeOperator</span><span class="op">,</span> <span class="nam">SurvivalRules</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t235" href="#t235">235</a></span><span class="t">    <span class="str">"""Expert Survival model."""</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t236" href="#t236">236</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t237" href="#t237">237</a></span><span class="t">    <span class="nam">__params_class__</span> <span class="op">=</span> <span class="nam">SurvivalModelsParams</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t238" href="#t238">238</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t239" href="#t239">239</a></span><span class="t">    <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span>  <span class="com"># pylint: disable=super-init-not-called,too-many-arguments,too-many-locals</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t240" href="#t240">240</a></span><span class="t">        <span class="nam">self</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t241" href="#t241">241</a></span><span class="t">        <span class="nam">survival_time_attr</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="key">None</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t242" href="#t242">242</a></span><span class="t">        <span class="nam">minsupp_new</span><span class="op">:</span> <span class="nam">float</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'minsupp_new'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t243" href="#t243">243</a></span><span class="t">        <span class="nam">max_growing</span><span class="op">:</span> <span class="nam">int</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'max_growing'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t244" href="#t244">244</a></span><span class="t">        <span class="nam">enable_pruning</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'enable_pruning'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t245" href="#t245">245</a></span><span class="t">        <span class="nam">ignore_missing</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'ignore_missing'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t246" href="#t246">246</a></span><span class="t">        <span class="nam">max_uncovered_fraction</span><span class="op">:</span> <span class="nam">float</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'max_uncovered_fraction'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t247" href="#t247">247</a></span><span class="t">        <span class="nam">select_best_candidate</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'select_best_candidate'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t248" href="#t248">248</a></span><span class="t">        <span class="nam">complementary_conditions</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'complementary_conditions'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t249" href="#t249">249</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t250" href="#t250">250</a></span><span class="t">        <span class="nam">extend_using_preferred</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'extend_using_preferred'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t251" href="#t251">251</a></span><span class="t">        <span class="nam">extend_using_automatic</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'extend_using_automatic'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t252" href="#t252">252</a></span><span class="t">        <span class="nam">induce_using_preferred</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'induce_using_preferred'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t253" href="#t253">253</a></span><span class="t">        <span class="nam">induce_using_automatic</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'induce_using_automatic'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t254" href="#t254">254</a></span><span class="t">        <span class="nam">preferred_conditions_per_rule</span><span class="op">:</span> <span class="nam">int</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t255" href="#t255">255</a></span><span class="t">            <span class="str">'preferred_conditions_per_rule'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t256" href="#t256">256</a></span><span class="t">        <span class="nam">preferred_attributes_per_rule</span><span class="op">:</span> <span class="nam">int</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t257" href="#t257">257</a></span><span class="t">            <span class="str">'preferred_attributes_per_rule'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t258" href="#t258">258</a></span><span class="t">        <span class="nam">max_rule_count</span><span class="op">:</span> <span class="nam">int</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'max_rule_count'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t259" href="#t259">259</a></span><span class="t">    <span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t260" href="#t260">260</a></span><span class="t">        <span class="str">"""</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t261" href="#t261">261</a></span><span class="t"><span class="str">        Parameters</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t262" href="#t262">262</a></span><span class="t"><span class="str">        ----------</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t263" href="#t263">263</a></span><span class="t"><span class="str">        minsupp_new : float = 5.0</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t264" href="#t264">264</a></span><span class="t"><span class="str">            a minimum number (or fraction, if value &lt; 1.0) of previously uncovered examples</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t265" href="#t265">265</a></span><span class="t"><span class="str">             to be covered by a new rule (positive examples for classification problems); default: 5,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t266" href="#t266">266</a></span><span class="t"><span class="str">        survival_time_attr : str</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t267" href="#t267">267</a></span><span class="t"><span class="str">            name of column containing survival time data (use when data passed to model is pandas</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t268" href="#t268">268</a></span><span class="t"><span class="str">            dataframe).</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t269" href="#t269">269</a></span><span class="t"><span class="str">        max_growing : int = 0.0</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t270" href="#t270">270</a></span><span class="t"><span class="str">            non-negative integer representing maximum number of conditions which can be added to</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t271" href="#t271">271</a></span><span class="t"><span class="str">            the rule in the growing phase (use this parameter for large datasets if execution time</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t272" href="#t272">272</a></span><span class="t"><span class="str">            is prohibitive); 0 indicates no limit; default: 0,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t273" href="#t273">273</a></span><span class="t"><span class="str">        enable_pruning : bool = True</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t274" href="#t274">274</a></span><span class="t"><span class="str">            enable or disable pruning, default is True.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t275" href="#t275">275</a></span><span class="t"><span class="str">        ignore_missing : bool = False</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t276" href="#t276">276</a></span><span class="t"><span class="str">            boolean telling whether missing values should be ignored (by default, a missing value</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t277" href="#t277">277</a></span><span class="t"><span class="str">            of given attribute is always considered as not fulfilling the condition build upon that</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t278" href="#t278">278</a></span><span class="t"><span class="str">            attribute); default: False.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t279" href="#t279">279</a></span><span class="t"><span class="str">        max_uncovered_fraction : float = 0.0</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t280" href="#t280">280</a></span><span class="t"><span class="str">            Floating-point number from [0,1] interval representing maximum fraction of examples</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t281" href="#t281">281</a></span><span class="t"><span class="str">             that may remain uncovered by the rule set, default: 0.0.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t282" href="#t282">282</a></span><span class="t"><span class="str">        select_best_candidate : bool = False</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t283" href="#t283">283</a></span><span class="t"><span class="str">            Flag determining if best candidate should be selected from growing phase;</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t284" href="#t284">284</a></span><span class="t"><span class="str">             default: False.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t285" href="#t285">285</a></span><span class="t"><span class="str">        complementary_conditions : bool = False</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t286" href="#t286">286</a></span><span class="t"><span class="str">            If enabled, complementary conditions in the form a = !{value} for nominal attributes</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t287" href="#t287">287</a></span><span class="t"><span class="str">            are supported.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t288" href="#t288">288</a></span><span class="t"><span class="str">        max_rule_count : int = 0</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t289" href="#t289">289</a></span><span class="t"><span class="str">            Maximum number of rules to be generated (for classification data sets it applies</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t290" href="#t290">290</a></span><span class="t"><span class="str">             to a single class); 0 indicates no limit.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t291" href="#t291">291</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t292" href="#t292">292</a></span><span class="t"><span class="str">        extend_using_preferred : bool = False</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t293" href="#t293">293</a></span><span class="t"><span class="str">            boolean indicating whether initial rules should be extended with a use of preferred</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t294" href="#t294">294</a></span><span class="t"><span class="str">            conditions and attributes; default is False</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t295" href="#t295">295</a></span><span class="t"><span class="str">        extend_using_automatic : bool = False</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t296" href="#t296">296</a></span><span class="t"><span class="str">            boolean indicating whether initial rules should be extended with a use of automatic</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t297" href="#t297">297</a></span><span class="t"><span class="str">            conditions and attributes; default is False</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t298" href="#t298">298</a></span><span class="t"><span class="str">        induce_using_preferred : bool = False</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t299" href="#t299">299</a></span><span class="t"><span class="str">            boolean indicating whether new rules should be induced with a use of preferred</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t300" href="#t300">300</a></span><span class="t"><span class="str">             conditions and attributes; default is False</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t301" href="#t301">301</a></span><span class="t"><span class="str">        induce_using_automatic : bool = False</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t302" href="#t302">302</a></span><span class="t"><span class="str">            boolean indicating whether new rules should be induced with a use of automatic</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t303" href="#t303">303</a></span><span class="t"><span class="str">             conditions and attributes; default is False</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t304" href="#t304">304</a></span><span class="t"><span class="str">        preferred_conditions_per_rule : int = None</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t305" href="#t305">305</a></span><span class="t"><span class="str">            maximum number of preferred conditions per rule; default: unlimited,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t306" href="#t306">306</a></span><span class="t"><span class="str">        preferred_attributes_per_rule : int = None</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t307" href="#t307">307</a></span><span class="t"><span class="str">            maximum number of preferred attributes per rule; default: unlimited.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t308" href="#t308">308</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t309" href="#t309">309</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_params</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t310" href="#t310">310</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_rule_generator</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t311" href="#t311">311</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_configurator</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t312" href="#t312">312</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">set_params</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t313" href="#t313">313</a></span><span class="t">            <span class="nam">survival_time_attr</span><span class="op">=</span><span class="nam">survival_time_attr</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t314" href="#t314">314</a></span><span class="t">            <span class="nam">minsupp_new</span><span class="op">=</span><span class="nam">minsupp_new</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t315" href="#t315">315</a></span><span class="t">            <span class="nam">max_growing</span><span class="op">=</span><span class="nam">max_growing</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t316" href="#t316">316</a></span><span class="t">            <span class="nam">enable_pruning</span><span class="op">=</span><span class="nam">enable_pruning</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t317" href="#t317">317</a></span><span class="t">            <span class="nam">ignore_missing</span><span class="op">=</span><span class="nam">ignore_missing</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t318" href="#t318">318</a></span><span class="t">            <span class="nam">max_uncovered_fraction</span><span class="op">=</span><span class="nam">max_uncovered_fraction</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t319" href="#t319">319</a></span><span class="t">            <span class="nam">select_best_candidate</span><span class="op">=</span><span class="nam">select_best_candidate</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t320" href="#t320">320</a></span><span class="t">            <span class="nam">extend_using_preferred</span><span class="op">=</span><span class="nam">extend_using_preferred</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t321" href="#t321">321</a></span><span class="t">            <span class="nam">extend_using_automatic</span><span class="op">=</span><span class="nam">extend_using_automatic</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t322" href="#t322">322</a></span><span class="t">            <span class="nam">induce_using_preferred</span><span class="op">=</span><span class="nam">induce_using_preferred</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t323" href="#t323">323</a></span><span class="t">            <span class="nam">induce_using_automatic</span><span class="op">=</span><span class="nam">induce_using_automatic</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t324" href="#t324">324</a></span><span class="t">            <span class="nam">preferred_conditions_per_rule</span><span class="op">=</span><span class="nam">preferred_conditions_per_rule</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t325" href="#t325">325</a></span><span class="t">            <span class="nam">preferred_attributes_per_rule</span><span class="op">=</span><span class="nam">preferred_attributes_per_rule</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t326" href="#t326">326</a></span><span class="t">            <span class="nam">complementary_conditions</span><span class="op">=</span><span class="nam">complementary_conditions</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t327" href="#t327">327</a></span><span class="t">            <span class="nam">max_rule_count</span><span class="op">=</span><span class="nam">max_rule_count</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t328" href="#t328">328</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t329" href="#t329">329</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">model</span><span class="op">:</span> <span class="nam">RuleSet</span><span class="op">[</span><span class="nam">SurvivalRule</span><span class="op">]</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t330" href="#t330">330</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t331" href="#t331">331</a></span><span class="t">    <span class="key">def</span> <span class="nam">set_params</span><span class="op">(</span>  <span class="com"># pylint: disable=arguments-differ</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t332" href="#t332">332</a></span><span class="t">        <span class="nam">self</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t333" href="#t333">333</a></span><span class="t">        <span class="op">**</span><span class="nam">kwargs</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t334" href="#t334">334</a></span><span class="t">    <span class="op">)</span> <span class="op">-></span> <span class="nam">object</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t335" href="#t335">335</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">survival_time_attr</span> <span class="op">=</span> <span class="nam">kwargs</span><span class="op">[</span><span class="str">'survival_time_attr'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t336" href="#t336">336</a></span><span class="t">        <span class="key">return</span> <span class="nam">ExpertKnowledgeOperator</span><span class="op">.</span><span class="nam">set_params</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="op">**</span><span class="nam">kwargs</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t337" href="#t337">337</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t338" href="#t338">338</a></span><span class="t">    <span class="key">def</span> <span class="nam">fit</span><span class="op">(</span>  <span class="com"># pylint: disable=arguments-differ,too-many-arguments</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t339" href="#t339">339</a></span><span class="t">        <span class="nam">self</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t340" href="#t340">340</a></span><span class="t">        <span class="nam">values</span><span class="op">:</span> <span class="nam">Data</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t341" href="#t341">341</a></span><span class="t">        <span class="nam">labels</span><span class="op">:</span> <span class="nam">Data</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t342" href="#t342">342</a></span><span class="t">        <span class="nam">survival_time</span><span class="op">:</span> <span class="nam">Data</span> <span class="op">=</span> <span class="key">None</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t234" href="#t234">234</a></span><span class="t">        <span class="nam">IntegratedBrierScore</span> <span class="op">=</span> <span class="nam">JClass</span><span class="op">(</span>  <span class="com"># pylint: disable=invalid-name</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t235" href="#t235">235</a></span><span class="t">            <span class="str">'adaa.analytics.rules.logic.performance.IntegratedBrierScore'</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t236" href="#t236">236</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t237" href="#t237">237</a></span><span class="t">        <span class="nam">integrated_brier_score</span> <span class="op">=</span> <span class="nam">IntegratedBrierScore</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t238" href="#t238">238</a></span><span class="t">        <span class="nam">ibs</span> <span class="op">=</span> <span class="nam">integrated_brier_score</span><span class="op">.</span><span class="nam">countExample</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t239" href="#t239">239</a></span><span class="t">            <span class="nam">predicted_example_set</span><span class="op">)</span><span class="op">.</span><span class="nam">getValue</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t240" href="#t240">240</a></span><span class="t">        <span class="key">return</span> <span class="nam">float</span><span class="op">(</span><span class="nam">ibs</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t241" href="#t241">241</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t242" href="#t242">242</a></span><span class="t">    <span class="key">def</span> <span class="nam">_get_problem_type</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">ProblemType</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t243" href="#t243">243</a></span><span class="t">        <span class="key">return</span> <span class="nam">ProblemType</span><span class="op">.</span><span class="nam">SURVIVAL</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t244" href="#t244">244</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t245" href="#t245">245</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t246" href="#t246">246</a></span><span class="t"><span class="key">class</span> <span class="nam">ExpertSurvivalRules</span><span class="op">(</span><span class="nam">ExpertKnowledgeOperator</span><span class="op">,</span> <span class="nam">SurvivalRules</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t247" href="#t247">247</a></span><span class="t">    <span class="str">"""Expert Survival model."""</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t248" href="#t248">248</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t249" href="#t249">249</a></span><span class="t">    <span class="nam">__params_class__</span> <span class="op">=</span> <span class="nam">_SurvivalExpertModelParams</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t250" href="#t250">250</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t251" href="#t251">251</a></span><span class="t">    <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span>  <span class="com"># pylint: disable=super-init-not-called,too-many-arguments,too-many-locals</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t252" href="#t252">252</a></span><span class="t">        <span class="nam">self</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t253" href="#t253">253</a></span><span class="t">        <span class="nam">survival_time_attr</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="key">None</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t254" href="#t254">254</a></span><span class="t">        <span class="nam">minsupp_new</span><span class="op">:</span> <span class="nam">float</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'minsupp_new'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t255" href="#t255">255</a></span><span class="t">        <span class="nam">max_growing</span><span class="op">:</span> <span class="nam">int</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'max_growing'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t256" href="#t256">256</a></span><span class="t">        <span class="nam">enable_pruning</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'enable_pruning'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t257" href="#t257">257</a></span><span class="t">        <span class="nam">ignore_missing</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'ignore_missing'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t258" href="#t258">258</a></span><span class="t">        <span class="nam">max_uncovered_fraction</span><span class="op">:</span> <span class="nam">float</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'max_uncovered_fraction'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t259" href="#t259">259</a></span><span class="t">        <span class="nam">select_best_candidate</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'select_best_candidate'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t260" href="#t260">260</a></span><span class="t">        <span class="nam">complementary_conditions</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'complementary_conditions'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t261" href="#t261">261</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t262" href="#t262">262</a></span><span class="t">        <span class="nam">extend_using_preferred</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'extend_using_preferred'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t263" href="#t263">263</a></span><span class="t">        <span class="nam">extend_using_automatic</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'extend_using_automatic'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t264" href="#t264">264</a></span><span class="t">        <span class="nam">induce_using_preferred</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'induce_using_preferred'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t265" href="#t265">265</a></span><span class="t">        <span class="nam">induce_using_automatic</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'induce_using_automatic'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t266" href="#t266">266</a></span><span class="t">        <span class="nam">preferred_conditions_per_rule</span><span class="op">:</span> <span class="nam">int</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t267" href="#t267">267</a></span><span class="t">            <span class="str">'preferred_conditions_per_rule'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t268" href="#t268">268</a></span><span class="t">        <span class="nam">preferred_attributes_per_rule</span><span class="op">:</span> <span class="nam">int</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t269" href="#t269">269</a></span><span class="t">            <span class="str">'preferred_attributes_per_rule'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t270" href="#t270">270</a></span><span class="t">        <span class="nam">max_rule_count</span><span class="op">:</span> <span class="nam">int</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'max_rule_count'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t271" href="#t271">271</a></span><span class="t">    <span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t272" href="#t272">272</a></span><span class="t">        <span class="str">"""</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t273" href="#t273">273</a></span><span class="t"><span class="str">        Parameters</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t274" href="#t274">274</a></span><span class="t"><span class="str">        ----------</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t275" href="#t275">275</a></span><span class="t"><span class="str">        minsupp_new : float = 5.0</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t276" href="#t276">276</a></span><span class="t"><span class="str">            a minimum number (or fraction, if value &lt; 1.0) of previously uncovered examples</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t277" href="#t277">277</a></span><span class="t"><span class="str">             to be covered by a new rule (positive examples for classification problems); default: 5,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t278" href="#t278">278</a></span><span class="t"><span class="str">        survival_time_attr : str</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t279" href="#t279">279</a></span><span class="t"><span class="str">            name of column containing survival time data (use when data passed to model is pandas</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t280" href="#t280">280</a></span><span class="t"><span class="str">            dataframe).</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t281" href="#t281">281</a></span><span class="t"><span class="str">        max_growing : int = 0.0</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t282" href="#t282">282</a></span><span class="t"><span class="str">            non-negative integer representing maximum number of conditions which can be added to</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t283" href="#t283">283</a></span><span class="t"><span class="str">            the rule in the growing phase (use this parameter for large datasets if execution time</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t284" href="#t284">284</a></span><span class="t"><span class="str">            is prohibitive); 0 indicates no limit; default: 0,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t285" href="#t285">285</a></span><span class="t"><span class="str">        enable_pruning : bool = True</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t286" href="#t286">286</a></span><span class="t"><span class="str">            enable or disable pruning, default is True.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t287" href="#t287">287</a></span><span class="t"><span class="str">        ignore_missing : bool = False</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t288" href="#t288">288</a></span><span class="t"><span class="str">            boolean telling whether missing values should be ignored (by default, a missing value</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t289" href="#t289">289</a></span><span class="t"><span class="str">            of given attribute is always considered as not fulfilling the condition build upon that</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t290" href="#t290">290</a></span><span class="t"><span class="str">            attribute); default: False.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t291" href="#t291">291</a></span><span class="t"><span class="str">        max_uncovered_fraction : float = 0.0</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t292" href="#t292">292</a></span><span class="t"><span class="str">            Floating-point number from [0,1] interval representing maximum fraction of examples</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t293" href="#t293">293</a></span><span class="t"><span class="str">             that may remain uncovered by the rule set, default: 0.0.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t294" href="#t294">294</a></span><span class="t"><span class="str">        select_best_candidate : bool = False</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t295" href="#t295">295</a></span><span class="t"><span class="str">            Flag determining if best candidate should be selected from growing phase;</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t296" href="#t296">296</a></span><span class="t"><span class="str">             default: False.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t297" href="#t297">297</a></span><span class="t"><span class="str">        complementary_conditions : bool = False</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t298" href="#t298">298</a></span><span class="t"><span class="str">            If enabled, complementary conditions in the form a = !{value} for nominal attributes</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t299" href="#t299">299</a></span><span class="t"><span class="str">            are supported.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t300" href="#t300">300</a></span><span class="t"><span class="str">        max_rule_count : int = 0</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t301" href="#t301">301</a></span><span class="t"><span class="str">            Maximum number of rules to be generated (for classification data sets it applies</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t302" href="#t302">302</a></span><span class="t"><span class="str">             to a single class); 0 indicates no limit.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t303" href="#t303">303</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t304" href="#t304">304</a></span><span class="t"><span class="str">        extend_using_preferred : bool = False</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t305" href="#t305">305</a></span><span class="t"><span class="str">            boolean indicating whether initial rules should be extended with a use of preferred</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t306" href="#t306">306</a></span><span class="t"><span class="str">            conditions and attributes; default is False</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t307" href="#t307">307</a></span><span class="t"><span class="str">        extend_using_automatic : bool = False</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t308" href="#t308">308</a></span><span class="t"><span class="str">            boolean indicating whether initial rules should be extended with a use of automatic</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t309" href="#t309">309</a></span><span class="t"><span class="str">            conditions and attributes; default is False</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t310" href="#t310">310</a></span><span class="t"><span class="str">        induce_using_preferred : bool = False</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t311" href="#t311">311</a></span><span class="t"><span class="str">            boolean indicating whether new rules should be induced with a use of preferred</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t312" href="#t312">312</a></span><span class="t"><span class="str">             conditions and attributes; default is False</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t313" href="#t313">313</a></span><span class="t"><span class="str">        induce_using_automatic : bool = False</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t314" href="#t314">314</a></span><span class="t"><span class="str">            boolean indicating whether new rules should be induced with a use of automatic</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t315" href="#t315">315</a></span><span class="t"><span class="str">             conditions and attributes; default is False</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t316" href="#t316">316</a></span><span class="t"><span class="str">        preferred_conditions_per_rule : int = None</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t317" href="#t317">317</a></span><span class="t"><span class="str">            maximum number of preferred conditions per rule; default: unlimited,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t318" href="#t318">318</a></span><span class="t"><span class="str">        preferred_attributes_per_rule : int = None</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t319" href="#t319">319</a></span><span class="t"><span class="str">            maximum number of preferred attributes per rule; default: unlimited.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t320" href="#t320">320</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t321" href="#t321">321</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_params</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t322" href="#t322">322</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_rule_generator</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t323" href="#t323">323</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_configurator</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t324" href="#t324">324</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_initialize_rulekit</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t325" href="#t325">325</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">set_params</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t326" href="#t326">326</a></span><span class="t">            <span class="nam">survival_time_attr</span><span class="op">=</span><span class="nam">survival_time_attr</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t327" href="#t327">327</a></span><span class="t">            <span class="nam">minsupp_new</span><span class="op">=</span><span class="nam">minsupp_new</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t328" href="#t328">328</a></span><span class="t">            <span class="nam">max_growing</span><span class="op">=</span><span class="nam">max_growing</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t329" href="#t329">329</a></span><span class="t">            <span class="nam">enable_pruning</span><span class="op">=</span><span class="nam">enable_pruning</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t330" href="#t330">330</a></span><span class="t">            <span class="nam">ignore_missing</span><span class="op">=</span><span class="nam">ignore_missing</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t331" href="#t331">331</a></span><span class="t">            <span class="nam">max_uncovered_fraction</span><span class="op">=</span><span class="nam">max_uncovered_fraction</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t332" href="#t332">332</a></span><span class="t">            <span class="nam">select_best_candidate</span><span class="op">=</span><span class="nam">select_best_candidate</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t333" href="#t333">333</a></span><span class="t">            <span class="nam">extend_using_preferred</span><span class="op">=</span><span class="nam">extend_using_preferred</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t334" href="#t334">334</a></span><span class="t">            <span class="nam">extend_using_automatic</span><span class="op">=</span><span class="nam">extend_using_automatic</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t335" href="#t335">335</a></span><span class="t">            <span class="nam">induce_using_preferred</span><span class="op">=</span><span class="nam">induce_using_preferred</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t336" href="#t336">336</a></span><span class="t">            <span class="nam">induce_using_automatic</span><span class="op">=</span><span class="nam">induce_using_automatic</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t337" href="#t337">337</a></span><span class="t">            <span class="nam">preferred_conditions_per_rule</span><span class="op">=</span><span class="nam">preferred_conditions_per_rule</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t338" href="#t338">338</a></span><span class="t">            <span class="nam">preferred_attributes_per_rule</span><span class="op">=</span><span class="nam">preferred_attributes_per_rule</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t339" href="#t339">339</a></span><span class="t">            <span class="nam">complementary_conditions</span><span class="op">=</span><span class="nam">complementary_conditions</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t340" href="#t340">340</a></span><span class="t">            <span class="nam">max_rule_count</span><span class="op">=</span><span class="nam">max_rule_count</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t341" href="#t341">341</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t342" href="#t342">342</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">model</span><span class="op">:</span> <span class="nam">RuleSet</span><span class="op">[</span><span class="nam">SurvivalRule</span><span class="op">]</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t343" href="#t343">343</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t344" href="#t344">344</a></span><span class="t">        <span class="nam">expert_rules</span><span class="op">:</span> <span class="nam">list</span><span class="op">[</span><span class="nam">Union</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">tuple</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">str</span><span class="op">]</span><span class="op">]</span><span class="op">]</span> <span class="op">=</span> <span class="key">None</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t345" href="#t345">345</a></span><span class="t">        <span class="nam">expert_preferred_conditions</span><span class="op">:</span> <span class="nam">list</span><span class="op">[</span><span class="nam">Union</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">tuple</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">str</span><span class="op">]</span><span class="op">]</span><span class="op">]</span> <span class="op">=</span> <span class="key">None</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t346" href="#t346">346</a></span><span class="t">        <span class="nam">expert_forbidden_conditions</span><span class="op">:</span> <span class="nam">list</span><span class="op">[</span><span class="nam">Union</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">tuple</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">str</span><span class="op">]</span><span class="op">]</span><span class="op">]</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t347" href="#t347">347</a></span><span class="t">    <span class="op">)</span> <span class="op">-></span> <span class="nam">ExpertSurvivalRules</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t348" href="#t348">348</a></span><span class="t">        <span class="str">"""Train model on given dataset.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t349" href="#t349">349</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t350" href="#t350">350</a></span><span class="t"><span class="str">        Parameters</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t351" href="#t351">351</a></span><span class="t"><span class="str">        ----------</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t352" href="#t352">352</a></span><span class="t"><span class="str">        values : :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t353" href="#t353">353</a></span><span class="t"><span class="str">            attributes</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t354" href="#t354">354</a></span><span class="t"><span class="str">        labels : Data</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t355" href="#t355">355</a></span><span class="t"><span class="str">            survival status</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t356" href="#t356">356</a></span><span class="t"><span class="str">        survival_time: :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t357" href="#t357">357</a></span><span class="t"><span class="str">            data about survival time. Could be omitted when *survival_time_attr* parameter was</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t358" href="#t358">358</a></span><span class="t"><span class="str">            specified.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t359" href="#t359">359</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t360" href="#t360">360</a></span><span class="t"><span class="str">        expert_rules : List[Union[str, Tuple[str, str]]]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t361" href="#t361">361</a></span><span class="t"><span class="str">            set of initial rules, either passed as a list of strings representing rules or as list</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t362" href="#t362">362</a></span><span class="t"><span class="str">            of tuples where first</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t363" href="#t363">363</a></span><span class="t"><span class="str">            element is name of the rule and second one is rule string.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t364" href="#t364">364</a></span><span class="t"><span class="str">        expert_preferred_conditions : List[Union[str, Tuple[str, str]]]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t365" href="#t365">365</a></span><span class="t"><span class="str">            multiset of preferred conditions (used also for specifying preferred attributes by</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t366" href="#t366">366</a></span><span class="t"><span class="str">             using special value Any). Either passed as a list of strings representing rules or as</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t367" href="#t367">367</a></span><span class="t"><span class="str">            list of tuples where first element is name of the rule and second one is rule string.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t368" href="#t368">368</a></span><span class="t"><span class="str">        expert_forbidden_conditions : List[Union[str, Tuple[str, str]]]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t369" href="#t369">369</a></span><span class="t"><span class="str">            set of forbidden conditions (used also for specifying forbidden attributes by using</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t370" href="#t370">370</a></span><span class="t"><span class="str">             special valye Any). Either passed as a list of strings representing rules or as list</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t371" href="#t371">371</a></span><span class="t"><span class="str">            of tuples where first element is name of the rule and second one is rule string.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t344" href="#t344">344</a></span><span class="t">    <span class="key">def</span> <span class="nam">set_params</span><span class="op">(</span>  <span class="com"># pylint: disable=arguments-differ</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t345" href="#t345">345</a></span><span class="t">        <span class="nam">self</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t346" href="#t346">346</a></span><span class="t">        <span class="op">**</span><span class="nam">kwargs</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t347" href="#t347">347</a></span><span class="t">    <span class="op">)</span> <span class="op">-></span> <span class="nam">object</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t348" href="#t348">348</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">survival_time_attr</span> <span class="op">=</span> <span class="nam">kwargs</span><span class="op">[</span><span class="str">'survival_time_attr'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t349" href="#t349">349</a></span><span class="t">        <span class="key">return</span> <span class="nam">ExpertKnowledgeOperator</span><span class="op">.</span><span class="nam">set_params</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="op">**</span><span class="nam">kwargs</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t350" href="#t350">350</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t351" href="#t351">351</a></span><span class="t">    <span class="key">def</span> <span class="nam">fit</span><span class="op">(</span>  <span class="com"># pylint: disable=arguments-differ,too-many-arguments</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t352" href="#t352">352</a></span><span class="t">        <span class="nam">self</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t353" href="#t353">353</a></span><span class="t">        <span class="nam">values</span><span class="op">:</span> <span class="nam">Data</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t354" href="#t354">354</a></span><span class="t">        <span class="nam">labels</span><span class="op">:</span> <span class="nam">Data</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t355" href="#t355">355</a></span><span class="t">        <span class="nam">survival_time</span><span class="op">:</span> <span class="nam">Data</span> <span class="op">=</span> <span class="key">None</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t356" href="#t356">356</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t357" href="#t357">357</a></span><span class="t">        <span class="nam">expert_rules</span><span class="op">:</span> <span class="nam">list</span><span class="op">[</span><span class="nam">Union</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">tuple</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">str</span><span class="op">]</span><span class="op">]</span><span class="op">]</span> <span class="op">=</span> <span class="key">None</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t358" href="#t358">358</a></span><span class="t">        <span class="nam">expert_preferred_conditions</span><span class="op">:</span> <span class="nam">list</span><span class="op">[</span><span class="nam">Union</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">tuple</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">str</span><span class="op">]</span><span class="op">]</span><span class="op">]</span> <span class="op">=</span> <span class="key">None</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t359" href="#t359">359</a></span><span class="t">        <span class="nam">expert_forbidden_conditions</span><span class="op">:</span> <span class="nam">list</span><span class="op">[</span><span class="nam">Union</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">tuple</span><span class="op">[</span><span class="nam">str</span><span class="op">,</span> <span class="nam">str</span><span class="op">]</span><span class="op">]</span><span class="op">]</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t360" href="#t360">360</a></span><span class="t">    <span class="op">)</span> <span class="op">-></span> <span class="nam">ExpertSurvivalRules</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t361" href="#t361">361</a></span><span class="t">        <span class="str">"""Train model on given dataset.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t362" href="#t362">362</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t363" href="#t363">363</a></span><span class="t"><span class="str">        Parameters</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t364" href="#t364">364</a></span><span class="t"><span class="str">        ----------</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t365" href="#t365">365</a></span><span class="t"><span class="str">        values : :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t366" href="#t366">366</a></span><span class="t"><span class="str">            attributes</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t367" href="#t367">367</a></span><span class="t"><span class="str">        labels : Data</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t368" href="#t368">368</a></span><span class="t"><span class="str">            survival status</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t369" href="#t369">369</a></span><span class="t"><span class="str">        survival_time: :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t370" href="#t370">370</a></span><span class="t"><span class="str">            data about survival time. Could be omitted when *survival_time_attr* parameter was</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t371" href="#t371">371</a></span><span class="t"><span class="str">            specified.</span>&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t372" href="#t372">372</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t373" href="#t373">373</a></span><span class="t"><span class="str">        Returns</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t374" href="#t374">374</a></span><span class="t"><span class="str">        -------</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t375" href="#t375">375</a></span><span class="t"><span class="str">        self : ExpertSurvivalRules</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t376" href="#t376">376</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t377" href="#t377">377</a></span><span class="t">        <span class="nam">survival_time_attribute</span> <span class="op">=</span> <span class="nam">SurvivalRules</span><span class="op">.</span><span class="nam">_prepare_survival_attribute</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t378" href="#t378">378</a></span><span class="t">            <span class="nam">self</span><span class="op">,</span> <span class="nam">survival_time</span><span class="op">,</span> <span class="nam">values</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t379" href="#t379">379</a></span><span class="t">        <span class="key">return</span> <span class="nam">ExpertKnowledgeOperator</span><span class="op">.</span><span class="nam">fit</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t380" href="#t380">380</a></span><span class="t">            <span class="nam">self</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t381" href="#t381">381</a></span><span class="t">            <span class="nam">values</span><span class="op">=</span><span class="nam">values</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t382" href="#t382">382</a></span><span class="t">            <span class="nam">labels</span><span class="op">=</span><span class="nam">labels</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t383" href="#t383">383</a></span><span class="t">            <span class="nam">survival_time_attribute</span><span class="op">=</span><span class="nam">survival_time_attribute</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t384" href="#t384">384</a></span><span class="t">            <span class="nam">expert_rules</span><span class="op">=</span><span class="nam">expert_rules</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t385" href="#t385">385</a></span><span class="t">            <span class="nam">expert_preferred_conditions</span><span class="op">=</span><span class="nam">expert_preferred_conditions</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t386" href="#t386">386</a></span><span class="t">            <span class="nam">expert_forbidden_conditions</span><span class="op">=</span><span class="nam">expert_forbidden_conditions</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t387" href="#t387">387</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t388" href="#t388">388</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t389" href="#t389">389</a></span><span class="t">    <span class="key">def</span> <span class="nam">predict</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">values</span><span class="op">:</span> <span class="nam">Data</span><span class="op">)</span> <span class="op">-></span> <span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t390" href="#t390">390</a></span><span class="t">        <span class="key">return</span> <span class="nam">PredictionResultMapper</span><span class="op">.</span><span class="nam">map_survival</span><span class="op">(</span><span class="nam">ExpertKnowledgeOperator</span><span class="op">.</span><span class="nam">predict</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">values</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t391" href="#t391">391</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t392" href="#t392">392</a></span><span class="t">    <span class="key">def</span> <span class="nam">_get_problem_type</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">ProblemType</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t393" href="#t393">393</a></span><span class="t">        <span class="key">return</span> <span class="nam">ProblemType</span><span class="op">.</span><span class="nam">SURVIVAL</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t394" href="#t394">394</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t395" href="#t395">395</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t396" href="#t396">396</a></span><span class="t"><span class="key">class</span> <span class="nam">SurvivalContrastSetModelParams</span><span class="op">(</span><span class="nam">ContrastSetModelParams</span><span class="op">,</span> <span class="nam">SurvivalModelsParams</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t397" href="#t397">397</a></span><span class="t">    <span class="str">"""Model for validating survival contrast sets models hyperparameters</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t398" href="#t398">398</a></span><span class="t"><span class="str">     """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t399" href="#t399">399</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t400" href="#t400">400</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t401" href="#t401">401</a></span><span class="t"><span class="key">class</span> <span class="nam">ContrastSetSurvivalRules</span><span class="op">(</span><span class="nam">BaseOperator</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t402" href="#t402">402</a></span><span class="t">    <span class="str">"""Contrast set survival model."""</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t403" href="#t403">403</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t404" href="#t404">404</a></span><span class="t">    <span class="nam">__params_class__</span> <span class="op">=</span> <span class="nam">SurvivalContrastSetModelParams</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t405" href="#t405">405</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t406" href="#t406">406</a></span><span class="t">    <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span>  <span class="com"># pylint: disable=super-init-not-called,too-many-arguments</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t407" href="#t407">407</a></span><span class="t">        <span class="nam">self</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t408" href="#t408">408</a></span><span class="t">        <span class="nam">minsupp_all</span><span class="op">:</span> <span class="nam">Tuple</span><span class="op">[</span><span class="nam">float</span><span class="op">,</span> <span class="nam">float</span><span class="op">,</span> <span class="nam">float</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t409" href="#t409">409</a></span><span class="t">                           <span class="nam">float</span><span class="op">]</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'minsupp_all'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t410" href="#t410">410</a></span><span class="t">        <span class="nam">max_neg2pos</span><span class="op">:</span> <span class="nam">float</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'max_neg2pos'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t411" href="#t411">411</a></span><span class="t">        <span class="nam">max_passes_count</span><span class="op">:</span> <span class="nam">int</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'max_passes_count'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t412" href="#t412">412</a></span><span class="t">        <span class="nam">penalty_strength</span><span class="op">:</span> <span class="nam">float</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'penalty_strength'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t413" href="#t413">413</a></span><span class="t">        <span class="nam">penalty_saturation</span><span class="op">:</span> <span class="nam">float</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'penalty_saturation'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t414" href="#t414">414</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t415" href="#t415">415</a></span><span class="t">        <span class="nam">survival_time_attr</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="key">None</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t416" href="#t416">416</a></span><span class="t">        <span class="nam">minsupp_new</span><span class="op">:</span> <span class="nam">float</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'minsupp_new'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t417" href="#t417">417</a></span><span class="t">        <span class="nam">max_growing</span><span class="op">:</span> <span class="nam">int</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'max_growing'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t418" href="#t418">418</a></span><span class="t">        <span class="nam">enable_pruning</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'enable_pruning'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t419" href="#t419">419</a></span><span class="t">        <span class="nam">ignore_missing</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'ignore_missing'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t420" href="#t420">420</a></span><span class="t">        <span class="nam">max_uncovered_fraction</span><span class="op">:</span> <span class="nam">float</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'max_uncovered_fraction'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t421" href="#t421">421</a></span><span class="t">        <span class="nam">select_best_candidate</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'select_best_candidate'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t422" href="#t422">422</a></span><span class="t">        <span class="nam">complementary_conditions</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'complementary_conditions'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t423" href="#t423">423</a></span><span class="t">        <span class="nam">max_rule_count</span><span class="op">:</span> <span class="nam">int</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'max_rule_count'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t424" href="#t424">424</a></span><span class="t">    <span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t425" href="#t425">425</a></span><span class="t">        <span class="str">"""</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t426" href="#t426">426</a></span><span class="t"><span class="str">        Parameters</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t427" href="#t427">427</a></span><span class="t"><span class="str">        ----------</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t428" href="#t428">428</a></span><span class="t"><span class="str">        minsupp_all: Tuple[float, float, float, float]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t429" href="#t429">429</a></span><span class="t"><span class="str">            a minimum positive support of a contrast set (p/P). When multiple values are specified,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t430" href="#t430">430</a></span><span class="t"><span class="str">            a metainduction is performed; Default and recommended sequence is: 0.8, 0.5, 0.2, 0.1</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t431" href="#t431">431</a></span><span class="t"><span class="str">        max_neg2pos: float</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t432" href="#t432">432</a></span><span class="t"><span class="str">            a maximum ratio of negative to positive supports (nP/pN); Default is 0.5</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t433" href="#t433">433</a></span><span class="t"><span class="str">        max_passes_count: int</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t434" href="#t434">434</a></span><span class="t"><span class="str">            a maximum number of sequential covering passes for a single minsupp-all; Default is 5</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t435" href="#t435">435</a></span><span class="t"><span class="str">        penalty_strength: float</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t436" href="#t436">436</a></span><span class="t"><span class="str">            (s) - penalty strength; Default is 0.5</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t437" href="#t437">437</a></span><span class="t"><span class="str">        penalty_saturation: float</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t438" href="#t438">438</a></span><span class="t"><span class="str">            the value of p_new / P at which penalty reward saturates; Default is 0.2.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t439" href="#t439">439</a></span><span class="t"><span class="str">        survival_time_attr : str</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t440" href="#t440">440</a></span><span class="t"><span class="str">            name of column containing survival time data (use when data passed to model is pandas</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t441" href="#t441">441</a></span><span class="t"><span class="str">            dataframe).</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t442" href="#t442">442</a></span><span class="t"><span class="str">        minsupp_new : float = 5.0</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t443" href="#t443">443</a></span><span class="t"><span class="str">            a minimum number (or fraction, if value &lt; 1.0) of previously uncovered examples</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t444" href="#t444">444</a></span><span class="t"><span class="str">             to be covered by a new rule (positive examples for classification problems); default: 5,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t445" href="#t445">445</a></span><span class="t"><span class="str">        max_growing : int = 0.0</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t446" href="#t446">446</a></span><span class="t"><span class="str">            non-negative integer representing maximum number of conditions which can be added to</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t447" href="#t447">447</a></span><span class="t"><span class="str">             the rule in the growing phase (use this parameter for large datasets if execution time</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t448" href="#t448">448</a></span><span class="t"><span class="str">            is prohibitive); 0 indicates no limit; default: 0,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t449" href="#t449">449</a></span><span class="t"><span class="str">        enable_pruning : bool = True</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t450" href="#t450">450</a></span><span class="t"><span class="str">            enable or disable pruning, default is True.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t451" href="#t451">451</a></span><span class="t"><span class="str">        ignore_missing : bool = False</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t452" href="#t452">452</a></span><span class="t"><span class="str">            boolean telling whether missing values should be ignored (by default, a missing value</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t453" href="#t453">453</a></span><span class="t"><span class="str">             of given attribute is always considered as not fulfilling the condition build upon that</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t454" href="#t454">454</a></span><span class="t"><span class="str">            attribute); default: False.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t455" href="#t455">455</a></span><span class="t"><span class="str">        max_uncovered_fraction : float = 0.0</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t456" href="#t456">456</a></span><span class="t"><span class="str">            Floating-point number from [0,1] interval representing maximum fraction of examples</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t457" href="#t457">457</a></span><span class="t"><span class="str">             that may remain uncovered by the rule set, default: 0.0.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t458" href="#t458">458</a></span><span class="t"><span class="str">        select_best_candidate : bool = False</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t459" href="#t459">459</a></span><span class="t"><span class="str">            Flag determining if best candidate should be selected from growing phase;</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t460" href="#t460">460</a></span><span class="t"><span class="str">            default: False.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t461" href="#t461">461</a></span><span class="t"><span class="str">        complementary_conditions : bool = False</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t462" href="#t462">462</a></span><span class="t"><span class="str">            If enabled, complementary conditions in the form a = !{value} for nominal attributes</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t463" href="#t463">463</a></span><span class="t"><span class="str">            are supported.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t464" href="#t464">464</a></span><span class="t"><span class="str">        max_rule_count : int = 0</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t465" href="#t465">465</a></span><span class="t"><span class="str">            Maximum number of rules to be generated (for classification data sets it applies</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t466" href="#t466">466</a></span><span class="t"><span class="str">             to a single class); 0 indicates no limit.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t467" href="#t467">467</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t468" href="#t468">468</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_params</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t469" href="#t469">469</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_rule_generator</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t470" href="#t470">470</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_configurator</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t471" href="#t471">471</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">contrast_attribute</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t472" href="#t472">472</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">set_params</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t473" href="#t473">473</a></span><span class="t">            <span class="nam">minsupp_all</span><span class="op">=</span><span class="nam">minsupp_all</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t474" href="#t474">474</a></span><span class="t">            <span class="nam">max_neg2pos</span><span class="op">=</span><span class="nam">max_neg2pos</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t475" href="#t475">475</a></span><span class="t">            <span class="nam">max_passes_count</span><span class="op">=</span><span class="nam">max_passes_count</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t476" href="#t476">476</a></span><span class="t">            <span class="nam">penalty_strength</span><span class="op">=</span><span class="nam">penalty_strength</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t477" href="#t477">477</a></span><span class="t">            <span class="nam">penalty_saturation</span><span class="op">=</span><span class="nam">penalty_saturation</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t478" href="#t478">478</a></span><span class="t">            <span class="nam">survival_time_attr</span><span class="op">=</span><span class="nam">survival_time_attr</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t479" href="#t479">479</a></span><span class="t">            <span class="nam">minsupp_new</span><span class="op">=</span><span class="nam">minsupp_new</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t480" href="#t480">480</a></span><span class="t">            <span class="nam">max_growing</span><span class="op">=</span><span class="nam">max_growing</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t481" href="#t481">481</a></span><span class="t">            <span class="nam">enable_pruning</span><span class="op">=</span><span class="nam">enable_pruning</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t482" href="#t482">482</a></span><span class="t">            <span class="nam">ignore_missing</span><span class="op">=</span><span class="nam">ignore_missing</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t483" href="#t483">483</a></span><span class="t">            <span class="nam">max_uncovered_fraction</span><span class="op">=</span><span class="nam">max_uncovered_fraction</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t484" href="#t484">484</a></span><span class="t">            <span class="nam">select_best_candidate</span><span class="op">=</span><span class="nam">select_best_candidate</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t485" href="#t485">485</a></span><span class="t">            <span class="nam">complementary_conditions</span><span class="op">=</span><span class="nam">complementary_conditions</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t486" href="#t486">486</a></span><span class="t">            <span class="nam">max_rule_count</span><span class="op">=</span><span class="nam">max_rule_count</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t487" href="#t487">487</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t488" href="#t488">488</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">model</span><span class="op">:</span> <span class="nam">RuleSet</span><span class="op">[</span><span class="nam">SurvivalRule</span><span class="op">]</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t489" href="#t489">489</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t490" href="#t490">490</a></span><span class="t">    <span class="key">def</span> <span class="nam">set_params</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="op">**</span><span class="nam">kwargs</span><span class="op">)</span> <span class="op">-></span> <span class="nam">object</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t491" href="#t491">491</a></span><span class="t">        <span class="str">"""Set models hyperparameters. Parameters are the same as in constructor."""</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t492" href="#t492">492</a></span><span class="t">        <span class="com"># params validation</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t493" href="#t493">493</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">survival_time_attr</span> <span class="op">=</span> <span class="nam">kwargs</span><span class="op">[</span><span class="str">'survival_time_attr'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t494" href="#t494">494</a></span><span class="t">        <span class="key">return</span> <span class="nam">BaseOperator</span><span class="op">.</span><span class="nam">set_params</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="op">**</span><span class="nam">kwargs</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t495" href="#t495">495</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t496" href="#t496">496</a></span><span class="t">    <span class="key">def</span> <span class="nam">fit</span><span class="op">(</span>  <span class="com"># pylint: disable=arguments-renamed</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t497" href="#t497">497</a></span><span class="t">        <span class="nam">self</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t498" href="#t498">498</a></span><span class="t">        <span class="nam">values</span><span class="op">:</span> <span class="nam">Data</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t499" href="#t499">499</a></span><span class="t">        <span class="nam">labels</span><span class="op">:</span> <span class="nam">Data</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t500" href="#t500">500</a></span><span class="t">        <span class="nam">contrast_attribute</span><span class="op">:</span> <span class="nam">str</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t501" href="#t501">501</a></span><span class="t">        <span class="nam">survival_time</span><span class="op">:</span> <span class="nam">Data</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t502" href="#t502">502</a></span><span class="t">    <span class="op">)</span> <span class="op">-></span> <span class="nam">ContrastSetSurvivalRules</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t503" href="#t503">503</a></span><span class="t">        <span class="str">"""Train model on given dataset.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t504" href="#t504">504</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t505" href="#t505">505</a></span><span class="t"><span class="str">        Parameters</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t506" href="#t506">506</a></span><span class="t"><span class="str">        ----------</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t507" href="#t507">507</a></span><span class="t"><span class="str">        values : :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t508" href="#t508">508</a></span><span class="t"><span class="str">            attributes</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t509" href="#t509">509</a></span><span class="t"><span class="str">        labels : :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t510" href="#t510">510</a></span><span class="t"><span class="str">            survival status</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t511" href="#t511">511</a></span><span class="t"><span class="str">        contrast_attribute: str</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t512" href="#t512">512</a></span><span class="t"><span class="str">            group attribute</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t513" href="#t513">513</a></span><span class="t"><span class="str">        survival_time: :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t514" href="#t514">514</a></span><span class="t"><span class="str">            data about survival time. Could be omitted when *survival_time_attr* parameter</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t515" href="#t515">515</a></span><span class="t"><span class="str">             was specified.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t516" href="#t516">516</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t517" href="#t517">517</a></span><span class="t"><span class="str">        Returns</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t518" href="#t518">518</a></span><span class="t"><span class="str">        -------</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t519" href="#t519">519</a></span><span class="t"><span class="str">        self : ContrastSetSurvivalRules</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t520" href="#t520">520</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t521" href="#t521">521</a></span><span class="t">        <span class="nam">survival_time_attribute</span> <span class="op">=</span> <span class="nam">SurvivalRules</span><span class="op">.</span><span class="nam">_prepare_survival_attribute</span><span class="op">(</span>  <span class="com"># pylint: disable=protected-access</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t522" href="#t522">522</a></span><span class="t">            <span class="nam">self</span><span class="op">,</span> <span class="nam">survival_time</span><span class="op">,</span> <span class="nam">values</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t523" href="#t523">523</a></span><span class="t">        <span class="nam">super</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">fit</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t524" href="#t524">524</a></span><span class="t">            <span class="nam">values</span><span class="op">,</span> <span class="nam">labels</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t525" href="#t525">525</a></span><span class="t">            <span class="nam">survival_time_attribute</span><span class="op">=</span><span class="nam">survival_time_attribute</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t526" href="#t526">526</a></span><span class="t">            <span class="nam">contrast_attribute</span><span class="op">=</span><span class="nam">contrast_attribute</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t527" href="#t527">527</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">contrast_attribute</span> <span class="op">=</span> <span class="nam">contrast_attribute</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t528" href="#t528">528</a></span><span class="t">        <span class="key">return</span> <span class="nam">self</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t373" href="#t373">373</a></span><span class="t"><span class="str">        expert_rules : List[Union[str, Tuple[str, str]]]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t374" href="#t374">374</a></span><span class="t"><span class="str">            set of initial rules, either passed as a list of strings representing rules or as list</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t375" href="#t375">375</a></span><span class="t"><span class="str">            of tuples where first</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t376" href="#t376">376</a></span><span class="t"><span class="str">            element is name of the rule and second one is rule string.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t377" href="#t377">377</a></span><span class="t"><span class="str">        expert_preferred_conditions : List[Union[str, Tuple[str, str]]]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t378" href="#t378">378</a></span><span class="t"><span class="str">            multiset of preferred conditions (used also for specifying preferred attributes by</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t379" href="#t379">379</a></span><span class="t"><span class="str">             using special value Any). Either passed as a list of strings representing rules or as</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t380" href="#t380">380</a></span><span class="t"><span class="str">            list of tuples where first element is name of the rule and second one is rule string.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t381" href="#t381">381</a></span><span class="t"><span class="str">        expert_forbidden_conditions : List[Union[str, Tuple[str, str]]]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t382" href="#t382">382</a></span><span class="t"><span class="str">            set of forbidden conditions (used also for specifying forbidden attributes by using</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t383" href="#t383">383</a></span><span class="t"><span class="str">             special valye Any). Either passed as a list of strings representing rules or as list</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t384" href="#t384">384</a></span><span class="t"><span class="str">            of tuples where first element is name of the rule and second one is rule string.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t385" href="#t385">385</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t386" href="#t386">386</a></span><span class="t"><span class="str">        Returns</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t387" href="#t387">387</a></span><span class="t"><span class="str">        -------</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t388" href="#t388">388</a></span><span class="t"><span class="str">        self : ExpertSurvivalRules</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t389" href="#t389">389</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t390" href="#t390">390</a></span><span class="t">        <span class="nam">survival_time_attribute</span> <span class="op">=</span> <span class="nam">SurvivalRules</span><span class="op">.</span><span class="nam">_prepare_survival_attribute</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t391" href="#t391">391</a></span><span class="t">            <span class="nam">self</span><span class="op">,</span> <span class="nam">survival_time</span><span class="op">,</span> <span class="nam">values</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t392" href="#t392">392</a></span><span class="t">        <span class="key">return</span> <span class="nam">ExpertKnowledgeOperator</span><span class="op">.</span><span class="nam">fit</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t393" href="#t393">393</a></span><span class="t">            <span class="nam">self</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t394" href="#t394">394</a></span><span class="t">            <span class="nam">values</span><span class="op">=</span><span class="nam">values</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t395" href="#t395">395</a></span><span class="t">            <span class="nam">labels</span><span class="op">=</span><span class="nam">labels</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t396" href="#t396">396</a></span><span class="t">            <span class="nam">survival_time_attribute</span><span class="op">=</span><span class="nam">survival_time_attribute</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t397" href="#t397">397</a></span><span class="t">            <span class="nam">expert_rules</span><span class="op">=</span><span class="nam">expert_rules</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t398" href="#t398">398</a></span><span class="t">            <span class="nam">expert_preferred_conditions</span><span class="op">=</span><span class="nam">expert_preferred_conditions</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t399" href="#t399">399</a></span><span class="t">            <span class="nam">expert_forbidden_conditions</span><span class="op">=</span><span class="nam">expert_forbidden_conditions</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t400" href="#t400">400</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t401" href="#t401">401</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t402" href="#t402">402</a></span><span class="t">    <span class="key">def</span> <span class="nam">predict</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">values</span><span class="op">:</span> <span class="nam">Data</span><span class="op">)</span> <span class="op">-></span> <span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t403" href="#t403">403</a></span><span class="t">        <span class="key">return</span> <span class="nam">PredictionResultMapper</span><span class="op">.</span><span class="nam">map_survival</span><span class="op">(</span><span class="nam">ExpertKnowledgeOperator</span><span class="op">.</span><span class="nam">predict</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">values</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t404" href="#t404">404</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t405" href="#t405">405</a></span><span class="t">    <span class="key">def</span> <span class="nam">_get_problem_type</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">ProblemType</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t406" href="#t406">406</a></span><span class="t">        <span class="key">return</span> <span class="nam">ProblemType</span><span class="op">.</span><span class="nam">SURVIVAL</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t407" href="#t407">407</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t408" href="#t408">408</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t409" href="#t409">409</a></span><span class="t"><span class="key">class</span> <span class="nam">_SurvivalContrastSetModelParams</span><span class="op">(</span><span class="nam">ContrastSetModelParams</span><span class="op">,</span> <span class="nam">_SurvivalModelsParams</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t410" href="#t410">410</a></span><span class="t">    <span class="key">pass</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t411" href="#t411">411</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t412" href="#t412">412</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t413" href="#t413">413</a></span><span class="t"><span class="key">class</span> <span class="nam">ContrastSetSurvivalRules</span><span class="op">(</span><span class="nam">BaseOperator</span><span class="op">,</span> <span class="nam">_BaseSurvivalRulesModel</span><span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t414" href="#t414">414</a></span><span class="t">    <span class="str">"""Contrast set survival model."""</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t415" href="#t415">415</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t416" href="#t416">416</a></span><span class="t">    <span class="nam">__params_class__</span> <span class="op">=</span> <span class="nam">_SurvivalContrastSetModelParams</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t417" href="#t417">417</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t418" href="#t418">418</a></span><span class="t">    <span class="key">def</span> <span class="nam">__init__</span><span class="op">(</span>  <span class="com"># pylint: disable=super-init-not-called,too-many-arguments</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t419" href="#t419">419</a></span><span class="t">        <span class="nam">self</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t420" href="#t420">420</a></span><span class="t">        <span class="nam">minsupp_all</span><span class="op">:</span> <span class="nam">Tuple</span><span class="op">[</span><span class="nam">float</span><span class="op">,</span> <span class="nam">float</span><span class="op">,</span> <span class="nam">float</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t421" href="#t421">421</a></span><span class="t">                           <span class="nam">float</span><span class="op">]</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'minsupp_all'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t422" href="#t422">422</a></span><span class="t">        <span class="nam">max_neg2pos</span><span class="op">:</span> <span class="nam">float</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'max_neg2pos'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t423" href="#t423">423</a></span><span class="t">        <span class="nam">max_passes_count</span><span class="op">:</span> <span class="nam">int</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'max_passes_count'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t424" href="#t424">424</a></span><span class="t">        <span class="nam">penalty_strength</span><span class="op">:</span> <span class="nam">float</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'penalty_strength'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t425" href="#t425">425</a></span><span class="t">        <span class="nam">penalty_saturation</span><span class="op">:</span> <span class="nam">float</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'penalty_saturation'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t426" href="#t426">426</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t427" href="#t427">427</a></span><span class="t">        <span class="nam">survival_time_attr</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="key">None</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t428" href="#t428">428</a></span><span class="t">        <span class="nam">minsupp_new</span><span class="op">:</span> <span class="nam">float</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'minsupp_new'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t429" href="#t429">429</a></span><span class="t">        <span class="nam">max_growing</span><span class="op">:</span> <span class="nam">int</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'max_growing'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t430" href="#t430">430</a></span><span class="t">        <span class="nam">enable_pruning</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'enable_pruning'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t431" href="#t431">431</a></span><span class="t">        <span class="nam">ignore_missing</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'ignore_missing'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t432" href="#t432">432</a></span><span class="t">        <span class="nam">max_uncovered_fraction</span><span class="op">:</span> <span class="nam">float</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'max_uncovered_fraction'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t433" href="#t433">433</a></span><span class="t">        <span class="nam">select_best_candidate</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'select_best_candidate'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t434" href="#t434">434</a></span><span class="t">        <span class="nam">complementary_conditions</span><span class="op">:</span> <span class="nam">bool</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'complementary_conditions'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t435" href="#t435">435</a></span><span class="t">        <span class="nam">max_rule_count</span><span class="op">:</span> <span class="nam">int</span> <span class="op">=</span> <span class="nam">DEFAULT_PARAMS_VALUE</span><span class="op">[</span><span class="str">'max_rule_count'</span><span class="op">]</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t436" href="#t436">436</a></span><span class="t">    <span class="op">)</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t437" href="#t437">437</a></span><span class="t">        <span class="str">"""</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t438" href="#t438">438</a></span><span class="t"><span class="str">        Parameters</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t439" href="#t439">439</a></span><span class="t"><span class="str">        ----------</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t440" href="#t440">440</a></span><span class="t"><span class="str">        minsupp_all: Tuple[float, float, float, float]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t441" href="#t441">441</a></span><span class="t"><span class="str">            a minimum positive support of a contrast set (p/P). When multiple values are specified,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t442" href="#t442">442</a></span><span class="t"><span class="str">            a metainduction is performed; Default and recommended sequence is: 0.8, 0.5, 0.2, 0.1</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t443" href="#t443">443</a></span><span class="t"><span class="str">        max_neg2pos: float</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t444" href="#t444">444</a></span><span class="t"><span class="str">            a maximum ratio of negative to positive supports (nP/pN); Default is 0.5</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t445" href="#t445">445</a></span><span class="t"><span class="str">        max_passes_count: int</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t446" href="#t446">446</a></span><span class="t"><span class="str">            a maximum number of sequential covering passes for a single minsupp-all; Default is 5</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t447" href="#t447">447</a></span><span class="t"><span class="str">        penalty_strength: float</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t448" href="#t448">448</a></span><span class="t"><span class="str">            (s) - penalty strength; Default is 0.5</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t449" href="#t449">449</a></span><span class="t"><span class="str">        penalty_saturation: float</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t450" href="#t450">450</a></span><span class="t"><span class="str">            the value of p_new / P at which penalty reward saturates; Default is 0.2.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t451" href="#t451">451</a></span><span class="t"><span class="str">        survival_time_attr : str</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t452" href="#t452">452</a></span><span class="t"><span class="str">            name of column containing survival time data (use when data passed to model is pandas</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t453" href="#t453">453</a></span><span class="t"><span class="str">            dataframe).</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t454" href="#t454">454</a></span><span class="t"><span class="str">        minsupp_new : float = 5.0</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t455" href="#t455">455</a></span><span class="t"><span class="str">            a minimum number (or fraction, if value &lt; 1.0) of previously uncovered examples</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t456" href="#t456">456</a></span><span class="t"><span class="str">             to be covered by a new rule (positive examples for classification problems); default: 5,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t457" href="#t457">457</a></span><span class="t"><span class="str">        max_growing : int = 0.0</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t458" href="#t458">458</a></span><span class="t"><span class="str">            non-negative integer representing maximum number of conditions which can be added to</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t459" href="#t459">459</a></span><span class="t"><span class="str">             the rule in the growing phase (use this parameter for large datasets if execution time</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t460" href="#t460">460</a></span><span class="t"><span class="str">            is prohibitive); 0 indicates no limit; default: 0,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t461" href="#t461">461</a></span><span class="t"><span class="str">        enable_pruning : bool = True</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t462" href="#t462">462</a></span><span class="t"><span class="str">            enable or disable pruning, default is True.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t463" href="#t463">463</a></span><span class="t"><span class="str">        ignore_missing : bool = False</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t464" href="#t464">464</a></span><span class="t"><span class="str">            boolean telling whether missing values should be ignored (by default, a missing value</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t465" href="#t465">465</a></span><span class="t"><span class="str">             of given attribute is always considered as not fulfilling the condition build upon that</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t466" href="#t466">466</a></span><span class="t"><span class="str">            attribute); default: False.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t467" href="#t467">467</a></span><span class="t"><span class="str">        max_uncovered_fraction : float = 0.0</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t468" href="#t468">468</a></span><span class="t"><span class="str">            Floating-point number from [0,1] interval representing maximum fraction of examples</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t469" href="#t469">469</a></span><span class="t"><span class="str">             that may remain uncovered by the rule set, default: 0.0.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t470" href="#t470">470</a></span><span class="t"><span class="str">        select_best_candidate : bool = False</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t471" href="#t471">471</a></span><span class="t"><span class="str">            Flag determining if best candidate should be selected from growing phase;</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t472" href="#t472">472</a></span><span class="t"><span class="str">            default: False.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t473" href="#t473">473</a></span><span class="t"><span class="str">        complementary_conditions : bool = False</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t474" href="#t474">474</a></span><span class="t"><span class="str">            If enabled, complementary conditions in the form a = !{value} for nominal attributes</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t475" href="#t475">475</a></span><span class="t"><span class="str">            are supported.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t476" href="#t476">476</a></span><span class="t"><span class="str">        max_rule_count : int = 0</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t477" href="#t477">477</a></span><span class="t"><span class="str">            Maximum number of rules to be generated (for classification data sets it applies</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t478" href="#t478">478</a></span><span class="t"><span class="str">             to a single class); 0 indicates no limit.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t479" href="#t479">479</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t480" href="#t480">480</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_params</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t481" href="#t481">481</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_rule_generator</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t482" href="#t482">482</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_configurator</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t483" href="#t483">483</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">contrast_attribute</span><span class="op">:</span> <span class="nam">str</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t484" href="#t484">484</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">_initialize_rulekit</span><span class="op">(</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t485" href="#t485">485</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">set_params</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t486" href="#t486">486</a></span><span class="t">            <span class="nam">minsupp_all</span><span class="op">=</span><span class="nam">minsupp_all</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t487" href="#t487">487</a></span><span class="t">            <span class="nam">max_neg2pos</span><span class="op">=</span><span class="nam">max_neg2pos</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t488" href="#t488">488</a></span><span class="t">            <span class="nam">max_passes_count</span><span class="op">=</span><span class="nam">max_passes_count</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t489" href="#t489">489</a></span><span class="t">            <span class="nam">penalty_strength</span><span class="op">=</span><span class="nam">penalty_strength</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t490" href="#t490">490</a></span><span class="t">            <span class="nam">penalty_saturation</span><span class="op">=</span><span class="nam">penalty_saturation</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t491" href="#t491">491</a></span><span class="t">            <span class="nam">survival_time_attr</span><span class="op">=</span><span class="nam">survival_time_attr</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t492" href="#t492">492</a></span><span class="t">            <span class="nam">minsupp_new</span><span class="op">=</span><span class="nam">minsupp_new</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t493" href="#t493">493</a></span><span class="t">            <span class="nam">max_growing</span><span class="op">=</span><span class="nam">max_growing</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t494" href="#t494">494</a></span><span class="t">            <span class="nam">enable_pruning</span><span class="op">=</span><span class="nam">enable_pruning</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t495" href="#t495">495</a></span><span class="t">            <span class="nam">ignore_missing</span><span class="op">=</span><span class="nam">ignore_missing</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t496" href="#t496">496</a></span><span class="t">            <span class="nam">max_uncovered_fraction</span><span class="op">=</span><span class="nam">max_uncovered_fraction</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t497" href="#t497">497</a></span><span class="t">            <span class="nam">select_best_candidate</span><span class="op">=</span><span class="nam">select_best_candidate</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t498" href="#t498">498</a></span><span class="t">            <span class="nam">complementary_conditions</span><span class="op">=</span><span class="nam">complementary_conditions</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t499" href="#t499">499</a></span><span class="t">            <span class="nam">max_rule_count</span><span class="op">=</span><span class="nam">max_rule_count</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t500" href="#t500">500</a></span><span class="t">        <span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t501" href="#t501">501</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">model</span><span class="op">:</span> <span class="nam">RuleSet</span><span class="op">[</span><span class="nam">SurvivalRule</span><span class="op">]</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t502" href="#t502">502</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t503" href="#t503">503</a></span><span class="t">    <span class="key">def</span> <span class="nam">set_params</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="op">**</span><span class="nam">kwargs</span><span class="op">)</span> <span class="op">-></span> <span class="nam">object</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t504" href="#t504">504</a></span><span class="t">        <span class="str">"""Set models hyperparameters. Parameters are the same as in constructor."""</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t505" href="#t505">505</a></span><span class="t">        <span class="com"># params validation</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t506" href="#t506">506</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">survival_time_attr</span> <span class="op">=</span> <span class="nam">kwargs</span><span class="op">[</span><span class="str">'survival_time_attr'</span><span class="op">]</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t507" href="#t507">507</a></span><span class="t">        <span class="key">return</span> <span class="nam">BaseOperator</span><span class="op">.</span><span class="nam">set_params</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="op">**</span><span class="nam">kwargs</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t508" href="#t508">508</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t509" href="#t509">509</a></span><span class="t">    <span class="key">def</span> <span class="nam">fit</span><span class="op">(</span>  <span class="com"># pylint: disable=arguments-renamed</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t510" href="#t510">510</a></span><span class="t">        <span class="nam">self</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t511" href="#t511">511</a></span><span class="t">        <span class="nam">values</span><span class="op">:</span> <span class="nam">Data</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t512" href="#t512">512</a></span><span class="t">        <span class="nam">labels</span><span class="op">:</span> <span class="nam">Data</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t513" href="#t513">513</a></span><span class="t">        <span class="nam">contrast_attribute</span><span class="op">:</span> <span class="nam">str</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t514" href="#t514">514</a></span><span class="t">        <span class="nam">survival_time</span><span class="op">:</span> <span class="nam">Data</span> <span class="op">=</span> <span class="key">None</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t515" href="#t515">515</a></span><span class="t">    <span class="op">)</span> <span class="op">-></span> <span class="nam">ContrastSetSurvivalRules</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t516" href="#t516">516</a></span><span class="t">        <span class="str">"""Train model on given dataset.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t517" href="#t517">517</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t518" href="#t518">518</a></span><span class="t"><span class="str">        Parameters</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t519" href="#t519">519</a></span><span class="t"><span class="str">        ----------</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t520" href="#t520">520</a></span><span class="t"><span class="str">        values : :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t521" href="#t521">521</a></span><span class="t"><span class="str">            attributes</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t522" href="#t522">522</a></span><span class="t"><span class="str">        labels : :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t523" href="#t523">523</a></span><span class="t"><span class="str">            survival status</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t524" href="#t524">524</a></span><span class="t"><span class="str">        contrast_attribute: str</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t525" href="#t525">525</a></span><span class="t"><span class="str">            group attribute</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t526" href="#t526">526</a></span><span class="t"><span class="str">        survival_time: :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t527" href="#t527">527</a></span><span class="t"><span class="str">            data about survival time. Could be omitted when *survival_time_attr* parameter</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t528" href="#t528">528</a></span><span class="t"><span class="str">             was specified.</span>&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t529" href="#t529">529</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t530" href="#t530">530</a></span><span class="t">    <span class="key">def</span> <span class="nam">predict</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">values</span><span class="op">:</span> <span class="nam">Data</span><span class="op">)</span> <span class="op">-></span> <span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t531" href="#t531">531</a></span><span class="t">        <span class="str">"""Perform prediction and return estimated survival function for each example.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t532" href="#t532">532</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t533" href="#t533">533</a></span><span class="t"><span class="str">        Parameters</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t534" href="#t534">534</a></span><span class="t"><span class="str">        ----------</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t535" href="#t535">535</a></span><span class="t"><span class="str">        values : :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t536" href="#t536">536</a></span><span class="t"><span class="str">            attributes</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t537" href="#t537">537</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t538" href="#t538">538</a></span><span class="t"><span class="str">        Returns</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t539" href="#t539">539</a></span><span class="t"><span class="str">        -------</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t540" href="#t540">540</a></span><span class="t"><span class="str">        result : np.ndarray</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t541" href="#t541">541</a></span><span class="t"><span class="str">            Each row represent single example from dataset and contains estimated survival function</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t542" href="#t542">542</a></span><span class="t"><span class="str">            for that example. Estimated survival function is returned as a dictionary containing</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t543" href="#t543">543</a></span><span class="t"><span class="str">             times and corresponding probabilities.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t544" href="#t544">544</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t545" href="#t545">545</a></span><span class="t">        <span class="key">return</span> <span class="nam">PredictionResultMapper</span><span class="op">.</span><span class="nam">map_survival</span><span class="op">(</span><span class="nam">super</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">predict</span><span class="op">(</span><span class="nam">values</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t546" href="#t546">546</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t547" href="#t547">547</a></span><span class="t">    <span class="key">def</span> <span class="nam">score</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">values</span><span class="op">:</span> <span class="nam">Data</span><span class="op">,</span> <span class="nam">labels</span><span class="op">:</span> <span class="nam">Data</span><span class="op">,</span> <span class="nam">survival_time</span><span class="op">:</span> <span class="nam">Data</span> <span class="op">=</span> <span class="key">None</span><span class="op">)</span> <span class="op">-></span> <span class="nam">float</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t548" href="#t548">548</a></span><span class="t">        <span class="str">"""Return the Integrated Brier Score on the given dataset and</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t549" href="#t549">549</a></span><span class="t"><span class="str">         labels(event status indicator).</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t530" href="#t530">530</a></span><span class="t"><span class="str">        Returns</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t531" href="#t531">531</a></span><span class="t"><span class="str">        -------</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t532" href="#t532">532</a></span><span class="t"><span class="str">        self : ContrastSetSurvivalRules</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t533" href="#t533">533</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t534" href="#t534">534</a></span><span class="t">        <span class="nam">survival_time_attribute</span> <span class="op">=</span> <span class="nam">SurvivalRules</span><span class="op">.</span><span class="nam">_prepare_survival_attribute</span><span class="op">(</span>  <span class="com"># pylint: disable=protected-access</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t535" href="#t535">535</a></span><span class="t">            <span class="nam">self</span><span class="op">,</span> <span class="nam">survival_time</span><span class="op">,</span> <span class="nam">values</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t536" href="#t536">536</a></span><span class="t">        <span class="nam">super</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">fit</span><span class="op">(</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t537" href="#t537">537</a></span><span class="t">            <span class="nam">values</span><span class="op">,</span> <span class="nam">labels</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t538" href="#t538">538</a></span><span class="t">            <span class="nam">survival_time_attribute</span><span class="op">=</span><span class="nam">survival_time_attribute</span><span class="op">,</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t539" href="#t539">539</a></span><span class="t">            <span class="nam">contrast_attribute</span><span class="op">=</span><span class="nam">contrast_attribute</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t540" href="#t540">540</a></span><span class="t">        <span class="nam">self</span><span class="op">.</span><span class="nam">contrast_attribute</span> <span class="op">=</span> <span class="nam">contrast_attribute</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t541" href="#t541">541</a></span><span class="t">        <span class="key">return</span> <span class="nam">self</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t542" href="#t542">542</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t543" href="#t543">543</a></span><span class="t">    <span class="key">def</span> <span class="nam">predict</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">values</span><span class="op">:</span> <span class="nam">Data</span><span class="op">)</span> <span class="op">-></span> <span class="nam">np</span><span class="op">.</span><span class="nam">ndarray</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t544" href="#t544">544</a></span><span class="t">        <span class="str">"""Perform prediction and return estimated survival function for each example.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t545" href="#t545">545</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t546" href="#t546">546</a></span><span class="t"><span class="str">        Parameters</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t547" href="#t547">547</a></span><span class="t"><span class="str">        ----------</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t548" href="#t548">548</a></span><span class="t"><span class="str">        values : :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t549" href="#t549">549</a></span><span class="t"><span class="str">            attributes</span>&nbsp;</span><span class="r"></span></p>
     <p class="pln"><span class="n"><a id="t550" href="#t550">550</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t551" href="#t551">551</a></span><span class="t"><span class="str">        Integrated Brier Score (IBS) - the Brier score (BS) represents the squared difference</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t552" href="#t552">552</a></span><span class="t"><span class="str">        between true event status at time T and predicted event status at that time;</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t553" href="#t553">553</a></span><span class="t"><span class="str">         the Integrated Brier score summarizes the prediction error over all observations and</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t554" href="#t554">554</a></span><span class="t"><span class="str">         over all times in a test set.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t555" href="#t555">555</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t556" href="#t556">556</a></span><span class="t"><span class="str">        Parameters</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t557" href="#t557">557</a></span><span class="t"><span class="str">        ----------</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t558" href="#t558">558</a></span><span class="t"><span class="str">        values : :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t559" href="#t559">559</a></span><span class="t"><span class="str">            attributes</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t560" href="#t560">560</a></span><span class="t"><span class="str">        labels : :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t561" href="#t561">561</a></span><span class="t"><span class="str">            survival status</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t562" href="#t562">562</a></span><span class="t"><span class="str">        survival_time: :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t563" href="#t563">563</a></span><span class="t"><span class="str">            data about survival time. Could be omitted when *survival_time_attr* parameter was</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t564" href="#t564">564</a></span><span class="t"><span class="str">            specified</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t565" href="#t565">565</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t566" href="#t566">566</a></span><span class="t"><span class="str">        Returns</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t567" href="#t567">567</a></span><span class="t"><span class="str">        -------</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t568" href="#t568">568</a></span><span class="t"><span class="str">        score : float</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t569" href="#t569">569</a></span><span class="t"><span class="str">            Integrated Brier Score of self.predict(values) wrt. labels.</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t570" href="#t570">570</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t571" href="#t571">571</a></span><span class="t">        <span class="key">return</span> <span class="nam">SurvivalRules</span><span class="op">.</span><span class="nam">score</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">values</span><span class="op">,</span> <span class="nam">labels</span><span class="op">,</span> <span class="nam">survival_time</span><span class="op">=</span><span class="nam">survival_time</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
-    <p class="pln"><span class="n"><a id="t572" href="#t572">572</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
-    <p class="run"><span class="n"><a id="t573" href="#t573">573</a></span><span class="t">    <span class="key">def</span> <span class="nam">_get_problem_type</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">ProblemType</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
-    <p class="mis show_mis"><span class="n"><a id="t574" href="#t574">574</a></span><span class="t">        <span class="key">return</span> <span class="nam">ProblemType</span><span class="op">.</span><span class="nam">CONTRAST_SURVIVAL</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t551" href="#t551">551</a></span><span class="t"><span class="str">        Returns</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t552" href="#t552">552</a></span><span class="t"><span class="str">        -------</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t553" href="#t553">553</a></span><span class="t"><span class="str">        result : np.ndarray</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t554" href="#t554">554</a></span><span class="t"><span class="str">            Each row represent single example from dataset and contains estimated survival function</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t555" href="#t555">555</a></span><span class="t"><span class="str">            for that example. Estimated survival function is returned as a dictionary containing</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t556" href="#t556">556</a></span><span class="t"><span class="str">             times and corresponding probabilities.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t557" href="#t557">557</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t558" href="#t558">558</a></span><span class="t">        <span class="key">return</span> <span class="nam">PredictionResultMapper</span><span class="op">.</span><span class="nam">map_survival</span><span class="op">(</span><span class="nam">super</span><span class="op">(</span><span class="op">)</span><span class="op">.</span><span class="nam">predict</span><span class="op">(</span><span class="nam">values</span><span class="op">)</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t559" href="#t559">559</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t560" href="#t560">560</a></span><span class="t">    <span class="key">def</span> <span class="nam">score</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">values</span><span class="op">:</span> <span class="nam">Data</span><span class="op">,</span> <span class="nam">labels</span><span class="op">:</span> <span class="nam">Data</span><span class="op">,</span> <span class="nam">survival_time</span><span class="op">:</span> <span class="nam">Data</span> <span class="op">=</span> <span class="key">None</span><span class="op">)</span> <span class="op">-></span> <span class="nam">float</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t561" href="#t561">561</a></span><span class="t">        <span class="str">"""Return the Integrated Brier Score on the given dataset and</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t562" href="#t562">562</a></span><span class="t"><span class="str">         labels(event status indicator).</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t563" href="#t563">563</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t564" href="#t564">564</a></span><span class="t"><span class="str">        Integrated Brier Score (IBS) - the Brier score (BS) represents the squared difference</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t565" href="#t565">565</a></span><span class="t"><span class="str">        between true event status at time T and predicted event status at that time;</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t566" href="#t566">566</a></span><span class="t"><span class="str">         the Integrated Brier score summarizes the prediction error over all observations and</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t567" href="#t567">567</a></span><span class="t"><span class="str">         over all times in a test set.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t568" href="#t568">568</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t569" href="#t569">569</a></span><span class="t"><span class="str">        Parameters</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t570" href="#t570">570</a></span><span class="t"><span class="str">        ----------</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t571" href="#t571">571</a></span><span class="t"><span class="str">        values : :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t572" href="#t572">572</a></span><span class="t"><span class="str">            attributes</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t573" href="#t573">573</a></span><span class="t"><span class="str">        labels : :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t574" href="#t574">574</a></span><span class="t"><span class="str">            survival status</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t575" href="#t575">575</a></span><span class="t"><span class="str">        survival_time: :class:`rulekit.operator.Data`</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t576" href="#t576">576</a></span><span class="t"><span class="str">            data about survival time. Could be omitted when *survival_time_attr* parameter was</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t577" href="#t577">577</a></span><span class="t"><span class="str">            specified</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t578" href="#t578">578</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t579" href="#t579">579</a></span><span class="t"><span class="str">        Returns</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t580" href="#t580">580</a></span><span class="t"><span class="str">        -------</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t581" href="#t581">581</a></span><span class="t"><span class="str">        score : float</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t582" href="#t582">582</a></span><span class="t"><span class="str">            Integrated Brier Score of self.predict(values) wrt. labels.</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t583" href="#t583">583</a></span><span class="t"><span class="str">        """</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t584" href="#t584">584</a></span><span class="t">        <span class="key">return</span> <span class="nam">SurvivalRules</span><span class="op">.</span><span class="nam">score</span><span class="op">(</span><span class="nam">self</span><span class="op">,</span> <span class="nam">values</span><span class="op">,</span> <span class="nam">labels</span><span class="op">,</span> <span class="nam">survival_time</span><span class="op">=</span><span class="nam">survival_time</span><span class="op">)</span>&nbsp;</span><span class="r"></span></p>
+    <p class="pln"><span class="n"><a id="t585" href="#t585">585</a></span><span class="t">&nbsp;</span><span class="r"></span></p>
+    <p class="run"><span class="n"><a id="t586" href="#t586">586</a></span><span class="t">    <span class="key">def</span> <span class="nam">_get_problem_type</span><span class="op">(</span><span class="nam">self</span><span class="op">)</span> <span class="op">-></span> <span class="nam">ProblemType</span><span class="op">:</span>&nbsp;</span><span class="r"></span></p>
+    <p class="mis show_mis"><span class="n"><a id="t587" href="#t587">587</a></span><span class="t">        <span class="key">return</span> <span class="nam">ProblemType</span><span class="op">.</span><span class="nam">CONTRAST_SURVIVAL</span>&nbsp;</span><span class="r"></span></p>
 </main>
 <footer>
     <div class="content">
@@ -663,7 +676,7 @@ <h2>
             <a class="nav" href="z_a44f0ac069e85531___init___py.html">&#xbb; next</a>
             &nbsp; &nbsp; &nbsp;
             <a class="nav" href="https://coverage.readthedocs.io/en/7.6.4">coverage.py v7.6.4</a>,
-            created at 2024-11-08 14:43 +0100
+            created at 2024-11-28 12:23 +0100
         </p>
     </div>
 </footer>
diff --git a/docs/reports/flake8/flake8stats.txt b/docs/reports/flake8/flake8stats.txt
index 7d0b13e..366abe8 100644
--- a/docs/reports/flake8/flake8stats.txt
+++ b/docs/reports/flake8/flake8stats.txt
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 3     W291 trailing whitespace
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diff --git a/docs/reports/flake8/index.html b/docs/reports/flake8/index.html
index c4234db..4220f0a 100644
--- a/docs/reports/flake8/index.html
+++ b/docs/reports/flake8/index.html
@@ -9,89 +9,44 @@
       <div id="masthead" class="sev-2"></div>
       <div id="page">
           <h1>flake8 violations</h1>
-         <p id="versions">Generated on 2024-11-12 15:06
+         <p id="versions">Generated on 2024-11-28 13:34
             with Installed plugins: flake8-html: 0.4.3, mccabe: 0.7.0, pycodestyle: 2.12.1, pyflakes: 3.2.0
          </p>
          <ul id="index">
          
-         <li>
-            <a href="rulekit.classification.report.html">
-               <span class="count sev-2">
-                  126
-               </span>
-               rulekit\classification.py
-            </a>
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          <li>
             <a href="rulekit.survival.report.html">
                <span class="count sev-2">
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+                  3
                </span>
                rulekit\survival.py
             </a>
          </li>
          
          <li>
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-               <span class="count sev-2">
-                  78
-               </span>
-               rulekit\regression.py
-            </a>
-         </li>
-         
-         <li>
-            <a href="rulekit._helpers.report.html">
-               <span class="count sev-2">
-                  29
-               </span>
-               rulekit\_helpers.py
-            </a>
-         </li>
-         
-         <li>
-            <a href="rulekit.main.report.html">
-               <span class="count sev-2">
-                  18
-               </span>
-               rulekit\main.py
-            </a>
-         </li>
-         
-         <li>
-            <a href="rulekit.params.report.html">
-               <span class="count sev-2">
-                  17
-               </span>
-               rulekit\params.py
-            </a>
-         </li>
-         
-         <li>
-            <a href="rulekit._operator.report.html">
+            <a href="rulekit.events.report.html">
                <span class="count sev-2">
-                  15
+                  2
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-               rulekit\_operator.py
+               rulekit\events.py
             </a>
          </li>
          
          <li>
-            <a href="rulekit.rules.report.html">
+            <a href="rulekit.classification.report.html">
                <span class="count sev-2">
-                  11
+                  1
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-               rulekit\rules.py
+               rulekit\classification.py
             </a>
          </li>
          
          <li>
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+            <a href="rulekit.regression.report.html">
                <span class="count sev-2">
-                  2
+                  1
                </span>
-               rulekit\events.py
+               rulekit\regression.py
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diff --git a/docs/reports/flake8/rulekit._helpers.report.html b/docs/reports/flake8/rulekit._helpers.report.html
deleted file mode 100644
index 5e5b529..0000000
--- a/docs/reports/flake8/rulekit._helpers.report.html
+++ /dev/null
@@ -1,273 +0,0 @@
-<!DOCTYPE html>
-<html>
-   <head>
-      <title>flake8 violations: rulekit\_helpers.py</title>
-      <meta http-equiv="Content-Type" value="text/html; charset=UTF-8">
-      <link rel="stylesheet" href="styles.css">
-<script>
-function bindHandler(link) {
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-            </a></p>
-         <h1>
-            <a href="index.html">
-               <img src="back.svg" alt="&#x2B05;">
-               rulekit\_helpers.py
-            </a>
-         </h1>
-
-         <ul id="index">
-         
-         <li>
-            <a data-code="E501">
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-               
-               <a href="rulekit._helpers.source.html#l108">
-                  <tt><i>108</i>     <span class="k">def</span> <span class="nf">_configure_user_defined_measure_parameter</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">param_name</span><span class="p">:</span> <span class="nb">str</span><span class="p">,</span> <span class="n">param_value</span><span class="p">:</span> <span class="n">Any</span><span class="p">):</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (83 > 79 characters):</p>
-               
-               <a href="rulekit._helpers.source.html#l112">
-                  <tt><i>112</i>             <span class="s1">&#39;induction_measure&#39;</span><span class="p">:</span> <span class="bp">self</span><span class="o">.</span><span class="n">rule_generator</span><span class="o">.</span><span class="n">setUserMeasureInductionObject</span><span class="p">,</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (105 > 79 characters):</p>
-               
-               <a href="rulekit._helpers.source.html#l120">
-                  <tt><i>120</i>         <span class="k">if</span> <span class="nb">any</span><span class="p">([</span><span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">param_name</span><span class="p">)</span> <span class="o">==</span> <span class="n">Measures</span><span class="o">.</span><span class="n">LogRank</span> <span class="k">for</span> <span class="n">param_name</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">_MEASURES_PARAMETERS</span><span class="p">]):</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (87 > 79 characters):</p>
-               
-               <a href="rulekit._helpers.source.html#l130">
-                  <tt><i>130</i>     <span class="k">def</span> <span class="nf">_validate_rule_generator_parameters</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">python_parameters</span><span class="p">:</span> <span class="nb">dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">Any</span><span class="p">]):</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (87 > 79 characters):</p>
-               
-               <a href="rulekit._helpers.source.html#l131">
-                  <tt><i>131</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Validate whether operator parameters configuration is properly passed to the</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (84 > 79 characters):</p>
-               
-               <a href="rulekit._helpers.source.html#l135">
-                  <tt><i>135</i> <span class="sd">            python_parameters (dict[str, Any]): parameters values configured for the</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (88 > 79 characters):</p>
-               
-               <a href="rulekit._helpers.source.html#l140">
-                  <tt><i>140</i> <span class="sd">            RuleKitMisconfigurationException: If Java and Python parameters do not match</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (89 > 79 characters):</p>
-               
-               <a href="rulekit._helpers.source.html#l142">
-                  <tt><i>142</i>         <span class="k">def</span> <span class="nf">are_params_equal</span><span class="p">(</span><span class="n">java_params</span><span class="p">:</span> <span class="nb">dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">Any</span><span class="p">],</span> <span class="n">python_params</span><span class="p">:</span> <span class="nb">dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">Any</span><span class="p">]):</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (91 > 79 characters):</p>
-               
-               <a href="rulekit._helpers.source.html#l185">
-                  <tt><i>185</i>         <span class="n">logger_config</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">_RuleKitJavaLoggerConfig</span><span class="p">]</span> <span class="o">=</span> <span class="n">RuleKit</span><span class="o">.</span><span class="n">get_java_logger_config</span><span class="p">(</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (81 > 79 characters):</p>
-               
-               <a href="rulekit._helpers.source.html#l221">
-                  <tt><i>221</i> <span class="sd">            y (Union[pd.Series, np.ndarray], optional): Labels. Defaults to None.</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (85 > 79 characters):</p>
-               
-               <a href="rulekit._helpers.source.html#l222">
-                  <tt><i>222</i> <span class="sd">            survival_time_attribute (str, optional): Name of survival time attribute.</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (93 > 79 characters):</p>
-               
-               <a href="rulekit._helpers.source.html#l224">
-                  <tt><i>224</i> <span class="sd">            contrast_attribute (str, optional): Name of contrast attribute. Defaults to None.</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (89 > 79 characters):</p>
-               
-               <a href="rulekit._helpers.source.html#l259">
-                  <tt><i>259</i>                 <span class="s1">&#39;Supported types are: 1 dimensional numpy array or pandas Series object.&#39;</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (92 > 79 characters):</p>
-               
-               <a href="rulekit._helpers.source.html#l280">
-                  <tt><i>280</i>                 <span class="s1">&#39;Supported types are: 2 dimensional numpy array or pandas DataFrame object.&#39;</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (86 > 79 characters):</p>
-               
-               <a href="rulekit._helpers.source.html#l286">
-                  <tt><i>286</i>                 <span class="s1">&#39;X must be a 2 dimensional numpy array or pandas DataFrame object. &#39;</span> <span class="o">+</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (86 > 79 characters):</p>
-               
-               <a href="rulekit._helpers.source.html#l293">
-                  <tt><i>293</i>                 <span class="s1">&#39;y must be a 1 dimensional numpy array or pandas DataFrame object. &#39;</span> <span class="o">+</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (93 > 79 characters):</p>
-               
-               <a href="rulekit._helpers.source.html#l313">
-                  <tt><i>313</i>                     <span class="s1">&#39;adaa.analytics.rules.logic.representation.exampleset.ExampleSetFactory&#39;</span><span class="p">)</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (100 > 79 characters):</p>
-               
-               <a href="rulekit._helpers.source.html#l325">
-                  <tt><i>325</i>         <span class="c1"># training dataset must be wrapped in additional classes for rule induction to work properly</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (85 > 79 characters):</p>
-               
-               <a href="rulekit._helpers.source.html#l327">
-                  <tt><i>327</i>             <span class="s1">&#39;adaa.analytics.rules.logic.representation.exampleset.ExampleSetFactory&#39;</span><span class="p">)</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (81 > 79 characters):</p>
-               
-               <a href="rulekit._helpers.source.html#l363">
-                  <tt><i>363</i>             <span class="n">confidence_col</span><span class="p">:</span> <span class="n">JObject</span> <span class="o">=</span> <span class="n">PredictionResultMapper</span><span class="o">.</span><span class="n">_get_column_by_role</span><span class="p">(</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (80 > 79 characters):</p>
-               
-               <a href="rulekit._helpers.source.html#l365">
-                  <tt><i>365</i>                 <span class="sa">f</span><span class="s1">&#39;</span><span class="si">{</span><span class="n">PredictionResultMapper</span><span class="o">.</span><span class="n">CONFIDENCE_COLUMN_ROLE</span><span class="si">}</span><span class="s1">_</span><span class="si">{</span><span class="n">label_value</span><span class="si">}</span><span class="s1">&#39;</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (91 > 79 characters):</p>
-               
-               <a href="rulekit._helpers.source.html#l417">
-                  <tt><i>417</i>     <span class="k">def</span> <span class="nf">map_to_numerical</span><span class="p">(</span><span class="n">predicted_example_set</span><span class="p">:</span> <span class="n">JObject</span><span class="p">,</span> <span class="n">remap</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">True</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">:</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (85 > 79 characters):</p>
-               
-               <a href="rulekit._helpers.source.html#l430">
-                  <tt><i>430</i>         <span class="n">label_mapping</span> <span class="o">=</span> <span class="n">predicted_example_set</span><span class="o">.</span><span class="n">getAttributes</span><span class="p">()</span><span class="o">.</span><span class="n">getLabel</span><span class="p">()</span><span class="o">.</span><span class="n">getMapping</span><span class="p">()</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (95 > 79 characters):</p>
-               
-               <a href="rulekit._helpers.source.html#l450">
-                  <tt><i>450</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Maps survival models predictions to numpy array. Used as alternative to `map` method</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (82 > 79 characters):</p>
-               
-               <a href="rulekit._helpers.source.html#l481">
-                  <tt><i>481</i>     <span class="k">def</span> <span class="nf">_get_column_by_role</span><span class="p">(</span><span class="n">predicted_example_set</span><span class="p">:</span> <span class="n">JObject</span><span class="p">,</span> <span class="n">role</span><span class="p">:</span> <span class="nb">str</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">JObject</span><span class="p">:</span></tt>
-               </a>
-            </li>
-            </ul>
-         </li>
-         
-         </ul>
-      </div>
-   </body>
-</html>
\ No newline at end of file
diff --git a/docs/reports/flake8/rulekit._helpers.source.html b/docs/reports/flake8/rulekit._helpers.source.html
deleted file mode 100644
index 670b84d..0000000
--- a/docs/reports/flake8/rulekit._helpers.source.html
+++ /dev/null
@@ -1,1835 +0,0 @@
-<!DOCTYPE html>
-<html>
-   <head>
-      <title>rulekit\_helpers.py - flake8 annotated source</title>
-      <meta http-equiv="Content-Type" value="text/html; charset=UTF-8">
-      <link rel="stylesheet" href="styles.css">
-   </head>
-   <body>
-      <div id="masthead" class="sev-2"></div>
-      <div id="page">
-         <h1>
-            <a href="rulekit._helpers.report.html">
-               <img src="back.svg" alt="&#x2B05;">
-               rulekit\_helpers.py source
-            </a>
-         </h1>
-
-         <div id="doc">
-            <div id="l1"
-               class="code sev- "><tt><i>1</i> <span class="sd">&quot;&quot;&quot;Contains helper functions and classes</span></tt>
-            </div>
-            <div id="l2"
-               class="code sev- "><tt><i>2</i> <span class="sd">&quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l3"
-               class="code sev- "><tt><i>3</i> <span class="kn">import</span> <span class="nn">io</span></tt>
-            </div>
-            <div id="l4"
-               class="code sev- "><tt><i>4</i> <span class="kn">import</span> <span class="nn">json</span></tt>
-            </div>
-            <div id="l5"
-               class="code sev- "><tt><i>5</i> <span class="kn">from</span> <span class="nn">typing</span> <span class="kn">import</span> <span class="n">Any</span></tt>
-            </div>
-            <div id="l6"
-               class="code sev- "><tt><i>6</i> <span class="kn">from</span> <span class="nn">typing</span> <span class="kn">import</span> <span class="n">Callable</span></tt>
-            </div>
-            <div id="l7"
-               class="code sev- "><tt><i>7</i> <span class="kn">from</span> <span class="nn">typing</span> <span class="kn">import</span> <span class="n">Optional</span></tt>
-            </div>
-            <div id="l8"
-               class="code sev- "><tt><i>8</i> <span class="kn">from</span> <span class="nn">typing</span> <span class="kn">import</span> <span class="n">Union</span></tt>
-            </div>
-            <div id="l9"
-               class="code sev- "><tt><i>9</i> &nbsp;</tt>
-            </div>
-            <div id="l10"
-               class="code sev- "><tt><i>10</i> <span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span></tt>
-            </div>
-            <div id="l11"
-               class="code sev- "><tt><i>11</i> <span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span></tt>
-            </div>
-            <div id="l12"
-               class="code sev- "><tt><i>12</i> <span class="kn">from</span> <span class="nn">jpype</span> <span class="kn">import</span> <span class="n">JArray</span></tt>
-            </div>
-            <div id="l13"
-               class="code sev- "><tt><i>13</i> <span class="kn">from</span> <span class="nn">jpype</span> <span class="kn">import</span> <span class="n">java</span></tt>
-            </div>
-            <div id="l14"
-               class="code sev- "><tt><i>14</i> <span class="kn">from</span> <span class="nn">jpype</span> <span class="kn">import</span> <span class="n">JClass</span></tt>
-            </div>
-            <div id="l15"
-               class="code sev- "><tt><i>15</i> <span class="kn">from</span> <span class="nn">jpype</span> <span class="kn">import</span> <span class="n">JObject</span></tt>
-            </div>
-            <div id="l16"
-               class="code sev- "><tt><i>16</i> <span class="kn">from</span> <span class="nn">jpype.pickle</span> <span class="kn">import</span> <span class="n">JPickler</span></tt>
-            </div>
-            <div id="l17"
-               class="code sev- "><tt><i>17</i> <span class="kn">from</span> <span class="nn">jpype.pickle</span> <span class="kn">import</span> <span class="n">JUnpickler</span></tt>
-            </div>
-            <div id="l18"
-               class="code sev- "><tt><i>18</i> &nbsp;</tt>
-            </div>
-            <div id="l19"
-               class="code sev- "><tt><i>19</i> <span class="kn">from</span> <span class="nn">rulekit._logging</span> <span class="kn">import</span> <span class="n">_RuleKitJavaLoggerConfig</span></tt>
-            </div>
-            <div id="l20"
-               class="code sev- "><tt><i>20</i> <span class="kn">from</span> <span class="nn">rulekit._problem_types</span> <span class="kn">import</span> <span class="n">ProblemType</span></tt>
-            </div>
-            <div id="l21"
-               class="code sev- "><tt><i>21</i> <span class="kn">from</span> <span class="nn">rulekit.exceptions</span> <span class="kn">import</span> <span class="n">RuleKitMisconfigurationException</span></tt>
-            </div>
-            <div id="l22"
-               class="code sev- "><tt><i>22</i> <span class="kn">from</span> <span class="nn">rulekit.main</span> <span class="kn">import</span> <span class="n">RuleKit</span></tt>
-            </div>
-            <div id="l23"
-               class="code sev- "><tt><i>23</i> <span class="kn">from</span> <span class="nn">rulekit.params</span> <span class="kn">import</span> <span class="n">Measures</span></tt>
-            </div>
-            <div id="l24"
-               class="code sev- "><tt><i>24</i> <span class="kn">from</span> <span class="nn">rulekit.rules</span> <span class="kn">import</span> <span class="n">BaseRule</span></tt>
-            </div>
-            <div id="l25"
-               class="code sev- "><tt><i>25</i> &nbsp;</tt>
-            </div>
-            <div id="l26"
-               class="code sev- "><tt><i>26</i> &nbsp;</tt>
-            </div>
-            <div id="l27"
-               class="code sev- "><tt><i>27</i> <span class="k">def</span> <span class="nf">get_rule_generator</span><span class="p">(</span><span class="n">expert</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Any</span><span class="p">:</span></tt>
-            </div>
-            <div id="l28"
-               class="code sev- "><tt><i>28</i> <span class="w">    </span><span class="sd">&quot;&quot;&quot;Factory for Java RuleGenerator class object</span></tt>
-            </div>
-            <div id="l29"
-               class="code sev- "><tt><i>29</i> &nbsp;</tt>
-            </div>
-            <div id="l30"
-               class="code sev- "><tt><i>30</i> <span class="sd">    Args:</span></tt>
-            </div>
-            <div id="l31"
-               class="code sev- "><tt><i>31</i> <span class="sd">        expert (bool, optional): Whether expert induction is enables.</span></tt>
-            </div>
-            <div id="l32"
-               class="code sev- "><tt><i>32</i> <span class="sd">         Defaults to False.</span></tt>
-            </div>
-            <div id="l33"
-               class="code sev- "><tt><i>33</i> &nbsp;</tt>
-            </div>
-            <div id="l34"
-               class="code sev- "><tt><i>34</i> <span class="sd">    Returns:</span></tt>
-            </div>
-            <div id="l35"
-               class="code sev- "><tt><i>35</i> <span class="sd">        Any: RuleGenerator instance</span></tt>
-            </div>
-            <div id="l36"
-               class="code sev- "><tt><i>36</i> <span class="sd">    &quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l37"
-               class="code sev- "><tt><i>37</i>     <span class="n">RuleGenerator</span> <span class="o">=</span> <span class="n">JClass</span><span class="p">(</span>  <span class="c1"># pylint: disable=invalid-name</span></tt>
-            </div>
-            <div id="l38"
-               class="code sev- "><tt><i>38</i>         <span class="s1">&#39;adaa.analytics.rules.logic.rulegenerator.RuleGenerator&#39;</span></tt>
-            </div>
-            <div id="l39"
-               class="code sev- "><tt><i>39</i>     <span class="p">)</span></tt>
-            </div>
-            <div id="l40"
-               class="code sev- "><tt><i>40</i>     <span class="n">rule_generator</span> <span class="o">=</span> <span class="n">RuleGenerator</span><span class="p">(</span><span class="n">expert</span><span class="p">)</span></tt>
-            </div>
-            <div id="l41"
-               class="code sev- "><tt><i>41</i>     <span class="k">return</span> <span class="n">rule_generator</span></tt>
-            </div>
-            <div id="l42"
-               class="code sev- "><tt><i>42</i> &nbsp;</tt>
-            </div>
-            <div id="l43"
-               class="code sev- "><tt><i>43</i> &nbsp;</tt>
-            </div>
-            <div id="l44"
-               class="code sev- "><tt><i>44</i> <span class="k">class</span> <span class="nc">RuleGeneratorConfigurator</span><span class="p">:</span></tt>
-            </div>
-            <div id="l45"
-               class="code sev- "><tt><i>45</i> <span class="w">    </span><span class="sd">&quot;&quot;&quot;Class for configuring rule induction parameters</span></tt>
-            </div>
-            <div id="l46"
-               class="code sev- "><tt><i>46</i> <span class="sd">    &quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l47"
-               class="code sev- "><tt><i>47</i> &nbsp;</tt>
-            </div>
-            <div id="l48"
-               class="code sev- "><tt><i>48</i>     <span class="n">_MEASURES_PARAMETERS</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="nb">str</span><span class="p">]</span> <span class="o">=</span> <span class="p">[</span></tt>
-            </div>
-            <div id="l49"
-               class="code sev- "><tt><i>49</i>         <span class="s1">&#39;induction_measure&#39;</span><span class="p">,</span> <span class="s1">&#39;pruning_measure&#39;</span><span class="p">,</span> <span class="s1">&#39;voting_measure&#39;</span><span class="p">,</span></tt>
-            </div>
-            <div id="l50"
-               class="code sev- "><tt><i>50</i>     <span class="p">]</span></tt>
-            </div>
-            <div id="l51"
-               class="code sev- "><tt><i>51</i>     <span class="n">_USER_DEFINED_MEASURE_VALUE</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="s1">&#39;UserDefined&#39;</span></tt>
-            </div>
-            <div id="l52"
-               class="code sev- "><tt><i>52</i> &nbsp;</tt>
-            </div>
-            <div id="l53"
-               class="code sev- "><tt><i>53</i>     <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">rule_generator</span><span class="p">):</span></tt>
-            </div>
-            <div id="l54"
-               class="code sev- "><tt><i>54</i>         <span class="bp">self</span><span class="o">.</span><span class="n">rule_generator</span> <span class="o">=</span> <span class="n">rule_generator</span></tt>
-            </div>
-            <div id="l55"
-               class="code sev- "><tt><i>55</i>         <span class="bp">self</span><span class="o">.</span><span class="n">LogRank</span> <span class="o">=</span> <span class="kc">None</span>  <span class="c1"># pylint: disable=invalid-name</span></tt>
-            </div>
-            <div id="l56"
-               class="code sev- "><tt><i>56</i> &nbsp;</tt>
-            </div>
-            <div id="l57"
-               class="code sev- "><tt><i>57</i>     <span class="k">def</span> <span class="nf">configure</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">params</span><span class="p">:</span> <span class="nb">dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">Any</span><span class="p">])</span> <span class="o">-&gt;</span> <span class="n">Any</span><span class="p">:</span></tt>
-            </div>
-            <div id="l58"
-               class="code sev- "><tt><i>58</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Configures RuleGenerator instance with given induction parameters</span></tt>
-            </div>
-            <div id="l59"
-               class="code sev- "><tt><i>59</i> &nbsp;</tt>
-            </div>
-            <div id="l60"
-               class="code sev- "><tt><i>60</i> <span class="sd">        Returns:</span></tt>
-            </div>
-            <div id="l61"
-               class="code sev- "><tt><i>61</i> <span class="sd">            Any: configured RuleGenerator instance</span></tt>
-            </div>
-            <div id="l62"
-               class="code sev- "><tt><i>62</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l63"
-               class="code sev- "><tt><i>63</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_configure_rule_generator</span><span class="p">(</span><span class="o">**</span><span class="n">params</span><span class="p">)</span></tt>
-            </div>
-            <div id="l64"
-               class="code sev- "><tt><i>64</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_validate_rule_generator_parameters</span><span class="p">(</span><span class="o">**</span><span class="n">params</span><span class="p">)</span></tt>
-            </div>
-            <div id="l65"
-               class="code sev- "><tt><i>65</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_configure_java_logging</span><span class="p">()</span></tt>
-            </div>
-            <div id="l66"
-               class="code sev- "><tt><i>66</i>         <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">rule_generator</span></tt>
-            </div>
-            <div id="l67"
-               class="code sev- "><tt><i>67</i> &nbsp;</tt>
-            </div>
-            <div id="l68"
-               class="code sev- "><tt><i>68</i>     <span class="k">def</span> <span class="nf">_configure_expert_parameter</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">param_name</span><span class="p">:</span> <span class="nb">str</span><span class="p">,</span> <span class="n">param_value</span><span class="p">:</span> <span class="n">Any</span><span class="p">):</span></tt>
-            </div>
-            <div id="l69"
-               class="code sev- "><tt><i>69</i>         <span class="k">if</span> <span class="n">param_value</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span></tt>
-            </div>
-            <div id="l70"
-               class="code sev- "><tt><i>70</i>             <span class="k">return</span></tt>
-            </div>
-            <div id="l71"
-               class="code sev- "><tt><i>71</i>         <span class="n">rules_list</span> <span class="o">=</span> <span class="n">java</span><span class="o">.</span><span class="n">util</span><span class="o">.</span><span class="n">ArrayList</span><span class="p">()</span></tt>
-            </div>
-            <div id="l72"
-               class="code sev- "><tt><i>72</i>         <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">param_value</span><span class="p">,</span> <span class="nb">list</span><span class="p">)</span> <span class="ow">and</span> <span class="nb">len</span><span class="p">(</span><span class="n">param_value</span><span class="p">)</span> <span class="o">&gt;</span> <span class="mi">0</span><span class="p">:</span></tt>
-            </div>
-            <div id="l73"
-               class="code sev- "><tt><i>73</i>             <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">param_value</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="nb">str</span><span class="p">):</span></tt>
-            </div>
-            <div id="l74"
-               class="code sev- "><tt><i>74</i>                 <span class="k">for</span> <span class="n">index</span><span class="p">,</span> <span class="n">rule</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">param_value</span><span class="p">):</span></tt>
-            </div>
-            <div id="l75"
-               class="code sev- "><tt><i>75</i>                     <span class="n">rule_name</span> <span class="o">=</span> <span class="sa">f</span><span class="s1">&#39;</span><span class="si">{</span><span class="n">param_name</span><span class="p">[:</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span><span class="si">}</span><span class="s1">-</span><span class="si">{</span><span class="n">index</span><span class="si">}</span><span class="s1">&#39;</span></tt>
-            </div>
-            <div id="l76"
-               class="code sev- "><tt><i>76</i>                     <span class="n">rules_list</span><span class="o">.</span><span class="n">add</span><span class="p">(</span></tt>
-            </div>
-            <div id="l77"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (82 > 79 characters)</li>
-               
-               </ul><tt><i>77</i>                         <span class="n">JObject</span><span class="p">([</span><span class="n">rule_name</span><span class="p">,</span> <span class="n">rule</span><span class="p">],</span> <span class="n">JArray</span><span class="p">(</span><span class="s1">&#39;java.lang.String&#39;</span><span class="p">,</span> <span class="mi">1</span><span class="p">)))</span></tt>
-            </div>
-            <div id="l78"
-               class="code sev- "><tt><i>78</i>             <span class="k">elif</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">param_value</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">BaseRule</span><span class="p">):</span></tt>
-            </div>
-            <div id="l79"
-               class="code sev- "><tt><i>79</i>                 <span class="k">for</span> <span class="n">index</span><span class="p">,</span> <span class="n">rule</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">param_value</span><span class="p">):</span></tt>
-            </div>
-            <div id="l80"
-               class="code sev- "><tt><i>80</i>                     <span class="n">rule_name</span> <span class="o">=</span> <span class="sa">f</span><span class="s1">&#39;</span><span class="si">{</span><span class="n">param_name</span><span class="p">[:</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span><span class="si">}</span><span class="s1">-</span><span class="si">{</span><span class="n">index</span><span class="si">}</span><span class="s1">&#39;</span></tt>
-            </div>
-            <div id="l81"
-               class="code sev- "><tt><i>81</i>                     <span class="n">rules_list</span><span class="o">.</span><span class="n">add</span><span class="p">(</span></tt>
-            </div>
-            <div id="l82"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (87 > 79 characters)</li>
-               
-               </ul><tt><i>82</i>                         <span class="n">JObject</span><span class="p">([</span><span class="n">rule_name</span><span class="p">,</span> <span class="nb">str</span><span class="p">(</span><span class="n">rule</span><span class="p">)],</span> <span class="n">JArray</span><span class="p">(</span><span class="s1">&#39;java.lang.String&#39;</span><span class="p">,</span> <span class="mi">1</span><span class="p">)))</span></tt>
-            </div>
-            <div id="l83"
-               class="code sev- "><tt><i>83</i>             <span class="k">elif</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">param_value</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="nb">tuple</span><span class="p">):</span></tt>
-            </div>
-            <div id="l84"
-               class="code sev- "><tt><i>84</i>                 <span class="k">for</span> <span class="n">index</span><span class="p">,</span> <span class="n">rule</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">param_value</span><span class="p">):</span></tt>
-            </div>
-            <div id="l85"
-               class="code sev- "><tt><i>85</i>                     <span class="n">rules_list</span><span class="o">.</span><span class="n">add</span><span class="p">(</span></tt>
-            </div>
-            <div id="l86"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (83 > 79 characters)</li>
-               
-               </ul><tt><i>86</i>                         <span class="n">JObject</span><span class="p">([</span><span class="n">rule</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">rule</span><span class="p">[</span><span class="mi">1</span><span class="p">]],</span> <span class="n">JArray</span><span class="p">(</span><span class="s1">&#39;java.lang.String&#39;</span><span class="p">,</span> <span class="mi">1</span><span class="p">)))</span></tt>
-            </div>
-            <div id="l87"
-               class="code sev- "><tt><i>87</i>         <span class="bp">self</span><span class="o">.</span><span class="n">rule_generator</span><span class="o">.</span><span class="n">setListParameter</span><span class="p">(</span><span class="n">param_name</span><span class="p">,</span> <span class="n">rules_list</span><span class="p">)</span></tt>
-            </div>
-            <div id="l88"
-               class="code sev- "><tt><i>88</i> &nbsp;</tt>
-            </div>
-            <div id="l89"
-               class="code sev- "><tt><i>89</i>     <span class="k">def</span> <span class="nf">_configure_simple_parameter</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">param_name</span><span class="p">:</span> <span class="nb">str</span><span class="p">,</span> <span class="n">param_value</span><span class="p">:</span> <span class="n">Any</span><span class="p">):</span></tt>
-            </div>
-            <div id="l90"
-               class="code sev- "><tt><i>90</i>         <span class="k">if</span> <span class="n">param_value</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span></tt>
-            </div>
-            <div id="l91"
-               class="code sev- "><tt><i>91</i>             <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">param_value</span><span class="p">,</span> <span class="nb">bool</span><span class="p">):</span></tt>
-            </div>
-            <div id="l92"
-               class="code sev- "><tt><i>92</i>                 <span class="n">param_value</span> <span class="o">=</span> <span class="p">(</span><span class="nb">str</span><span class="p">(</span><span class="n">param_value</span><span class="p">))</span><span class="o">.</span><span class="n">lower</span><span class="p">()</span></tt>
-            </div>
-            <div id="l93"
-               class="code sev- "><tt><i>93</i>             <span class="k">elif</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">param_value</span><span class="p">,</span> <span class="nb">tuple</span><span class="p">):</span></tt>
-            </div>
-            <div id="l94"
-               class="code sev- "><tt><i>94</i>                 <span class="n">param_value</span> <span class="o">=</span> <span class="s1">&#39; &#39;</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="nb">list</span><span class="p">(</span><span class="nb">map</span><span class="p">(</span><span class="nb">str</span><span class="p">,</span> <span class="n">param_value</span><span class="p">)))</span></tt>
-            </div>
-            <div id="l95"
-               class="code sev- "><tt><i>95</i>             <span class="k">elif</span> <span class="ow">not</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">param_value</span><span class="p">,</span> <span class="nb">str</span><span class="p">):</span></tt>
-            </div>
-            <div id="l96"
-               class="code sev- "><tt><i>96</i>                 <span class="n">param_value</span> <span class="o">=</span> <span class="nb">str</span><span class="p">(</span><span class="n">param_value</span><span class="p">)</span></tt>
-            </div>
-            <div id="l97"
-               class="code sev- "><tt><i>97</i>             <span class="bp">self</span><span class="o">.</span><span class="n">rule_generator</span><span class="o">.</span><span class="n">setParameter</span><span class="p">(</span><span class="n">param_name</span><span class="p">,</span> <span class="n">param_value</span><span class="p">)</span></tt>
-            </div>
-            <div id="l98"
-               class="code sev- "><tt><i>98</i> &nbsp;</tt>
-            </div>
-            <div id="l99"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (95 > 79 characters)</li>
-               
-               </ul><tt><i>99</i>     <span class="k">def</span> <span class="nf">_configure_measure_parameter</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">param_name</span><span class="p">:</span> <span class="nb">str</span><span class="p">,</span> <span class="n">param_value</span><span class="p">:</span> <span class="n">Union</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">Measures</span><span class="p">]):</span></tt>
-            </div>
-            <div id="l100"
-               class="code sev- "><tt><i>100</i>         <span class="k">if</span> <span class="n">param_value</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span></tt>
-            </div>
-            <div id="l101"
-               class="code sev- "><tt><i>101</i>             <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">param_value</span><span class="p">,</span> <span class="n">Measures</span><span class="p">):</span></tt>
-            </div>
-            <div id="l102"
-               class="code sev- "><tt><i>102</i>                 <span class="bp">self</span><span class="o">.</span><span class="n">rule_generator</span><span class="o">.</span><span class="n">setParameter</span><span class="p">(</span></tt>
-            </div>
-            <div id="l103"
-               class="code sev- "><tt><i>103</i>                     <span class="n">param_name</span><span class="p">,</span> <span class="n">param_value</span><span class="o">.</span><span class="n">value</span><span class="p">)</span></tt>
-            </div>
-            <div id="l104"
-               class="code sev- "><tt><i>104</i>             <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">param_value</span><span class="p">,</span> <span class="n">Callable</span><span class="p">):</span></tt>
-            </div>
-            <div id="l105"
-               class="code sev- "><tt><i>105</i>                 <span class="bp">self</span><span class="o">.</span><span class="n">_configure_user_defined_measure_parameter</span><span class="p">(</span></tt>
-            </div>
-            <div id="l106"
-               class="code sev- "><tt><i>106</i>                     <span class="n">param_name</span><span class="p">,</span> <span class="n">param_value</span><span class="p">)</span></tt>
-            </div>
-            <div id="l107"
-               class="code sev- "><tt><i>107</i> &nbsp;</tt>
-            </div>
-            <div id="l108"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (91 > 79 characters)</li>
-               
-               </ul><tt><i>108</i>     <span class="k">def</span> <span class="nf">_configure_user_defined_measure_parameter</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">param_name</span><span class="p">:</span> <span class="nb">str</span><span class="p">,</span> <span class="n">param_value</span><span class="p">:</span> <span class="n">Any</span><span class="p">):</span></tt>
-            </div>
-            <div id="l109"
-               class="code sev- "><tt><i>109</i>         <span class="kn">from</span> <span class="nn">rulekit.params</span> <span class="kn">import</span> <span class="n">_user_defined_measure_factory</span></tt>
-            </div>
-            <div id="l110"
-               class="code sev- "><tt><i>110</i>         <span class="n">user_defined_measure</span> <span class="o">=</span> <span class="n">_user_defined_measure_factory</span><span class="p">(</span><span class="n">param_value</span><span class="p">)</span></tt>
-            </div>
-            <div id="l111"
-               class="code sev- "><tt><i>111</i>         <span class="p">{</span></tt>
-            </div>
-            <div id="l112"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (83 > 79 characters)</li>
-               
-               </ul><tt><i>112</i>             <span class="s1">&#39;induction_measure&#39;</span><span class="p">:</span> <span class="bp">self</span><span class="o">.</span><span class="n">rule_generator</span><span class="o">.</span><span class="n">setUserMeasureInductionObject</span><span class="p">,</span></tt>
-            </div>
-            <div id="l113"
-               class="code sev- "><tt><i>113</i>             <span class="s1">&#39;pruning_measure&#39;</span><span class="p">:</span> <span class="bp">self</span><span class="o">.</span><span class="n">rule_generator</span><span class="o">.</span><span class="n">setUserMeasurePurningObject</span><span class="p">,</span></tt>
-            </div>
-            <div id="l114"
-               class="code sev- "><tt><i>114</i>             <span class="s1">&#39;voting_measure&#39;</span><span class="p">:</span> <span class="bp">self</span><span class="o">.</span><span class="n">rule_generator</span><span class="o">.</span><span class="n">setUserMeasureVotingObject</span><span class="p">,</span></tt>
-            </div>
-            <div id="l115"
-               class="code sev- "><tt><i>115</i>         <span class="p">}[</span><span class="n">param_name</span><span class="p">](</span><span class="n">user_defined_measure</span><span class="p">)</span></tt>
-            </div>
-            <div id="l116"
-               class="code sev- "><tt><i>116</i>         <span class="bp">self</span><span class="o">.</span><span class="n">rule_generator</span><span class="o">.</span><span class="n">setParameter</span><span class="p">(</span></tt>
-            </div>
-            <div id="l117"
-               class="code sev- "><tt><i>117</i>             <span class="n">param_name</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">_USER_DEFINED_MEASURE_VALUE</span><span class="p">)</span></tt>
-            </div>
-            <div id="l118"
-               class="code sev- "><tt><i>118</i> &nbsp;</tt>
-            </div>
-            <div id="l119"
-               class="code sev- "><tt><i>119</i>     <span class="k">def</span> <span class="nf">_configure_rule_generator</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">:</span> <span class="nb">dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">Any</span><span class="p">]):</span></tt>
-            </div>
-            <div id="l120"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (105 > 79 characters)</li>
-               
-               </ul><tt><i>120</i>         <span class="k">if</span> <span class="nb">any</span><span class="p">([</span><span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">param_name</span><span class="p">)</span> <span class="o">==</span> <span class="n">Measures</span><span class="o">.</span><span class="n">LogRank</span> <span class="k">for</span> <span class="n">param_name</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">_MEASURES_PARAMETERS</span><span class="p">]):</span></tt>
-            </div>
-            <div id="l121"
-               class="code sev- "><tt><i>121</i>             <span class="bp">self</span><span class="o">.</span><span class="n">LogRank</span> <span class="o">=</span> <span class="n">JClass</span><span class="p">(</span><span class="s1">&#39;adaa.analytics.rules.logic.quality.LogRank&#39;</span><span class="p">)</span></tt>
-            </div>
-            <div id="l122"
-               class="code sev- "><tt><i>122</i>         <span class="k">for</span> <span class="n">measure_param_name</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">_MEASURES_PARAMETERS</span><span class="p">:</span></tt>
-            </div>
-            <div id="l123"
-               class="code sev- "><tt><i>123</i>             <span class="n">measure_param_value</span><span class="p">:</span> <span class="n">Measures</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">pop</span><span class="p">(</span></tt>
-            </div>
-            <div id="l124"
-               class="code sev- "><tt><i>124</i>                 <span class="n">measure_param_name</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span></tt>
-            </div>
-            <div id="l125"
-               class="code sev- "><tt><i>125</i>             <span class="bp">self</span><span class="o">.</span><span class="n">_configure_measure_parameter</span><span class="p">(</span></tt>
-            </div>
-            <div id="l126"
-               class="code sev- "><tt><i>126</i>                 <span class="n">measure_param_name</span><span class="p">,</span> <span class="n">measure_param_value</span><span class="p">)</span></tt>
-            </div>
-            <div id="l127"
-               class="code sev- "><tt><i>127</i>         <span class="k">for</span> <span class="n">param_name</span><span class="p">,</span> <span class="n">param_value</span> <span class="ow">in</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">items</span><span class="p">():</span></tt>
-            </div>
-            <div id="l128"
-               class="code sev- "><tt><i>128</i>             <span class="bp">self</span><span class="o">.</span><span class="n">_configure_simple_parameter</span><span class="p">(</span><span class="n">param_name</span><span class="p">,</span> <span class="n">param_value</span><span class="p">)</span></tt>
-            </div>
-            <div id="l129"
-               class="code sev- "><tt><i>129</i> &nbsp;</tt>
-            </div>
-            <div id="l130"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (87 > 79 characters)</li>
-               
-               </ul><tt><i>130</i>     <span class="k">def</span> <span class="nf">_validate_rule_generator_parameters</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">python_parameters</span><span class="p">:</span> <span class="nb">dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">Any</span><span class="p">]):</span></tt>
-            </div>
-            <div id="l131"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (87 > 79 characters)</li>
-               
-               </ul><tt><i>131</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Validate whether operator parameters configuration is properly passed to the</span></tt>
-            </div>
-            <div id="l132"
-               class="code sev- "><tt><i>132</i> <span class="sd">        java RuleGenerator class. Otherwise, it raises an error.</span></tt>
-            </div>
-            <div id="l133"
-               class="code sev- "><tt><i>133</i> &nbsp;</tt>
-            </div>
-            <div id="l134"
-               class="code sev- "><tt><i>134</i> <span class="sd">        Args:</span></tt>
-            </div>
-            <div id="l135"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (84 > 79 characters)</li>
-               
-               </ul><tt><i>135</i> <span class="sd">            python_parameters (dict[str, Any]): parameters values configured for the</span></tt>
-            </div>
-            <div id="l136"
-               class="code sev- "><tt><i>136</i> <span class="sd">                operator in Python</span></tt>
-            </div>
-            <div id="l137"
-               class="code sev- "><tt><i>137</i> &nbsp;</tt>
-            </div>
-            <div id="l138"
-               class="code sev- "><tt><i>138</i> <span class="sd">        Raises:</span></tt>
-            </div>
-            <div id="l139"
-               class="code sev- "><tt><i>139</i> <span class="sd">            ValueError: If failed to retrieve RuleGenerator parameters JSON</span></tt>
-            </div>
-            <div id="l140"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (88 > 79 characters)</li>
-               
-               </ul><tt><i>140</i> <span class="sd">            RuleKitMisconfigurationException: If Java and Python parameters do not match</span></tt>
-            </div>
-            <div id="l141"
-               class="code sev- "><tt><i>141</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l142"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (89 > 79 characters)</li>
-               
-               </ul><tt><i>142</i>         <span class="k">def</span> <span class="nf">are_params_equal</span><span class="p">(</span><span class="n">java_params</span><span class="p">:</span> <span class="nb">dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">Any</span><span class="p">],</span> <span class="n">python_params</span><span class="p">:</span> <span class="nb">dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">Any</span><span class="p">]):</span></tt>
-            </div>
-            <div id="l143"
-               class="code sev- "><tt><i>143</i>             <span class="k">if</span> <span class="n">java_params</span><span class="o">.</span><span class="n">keys</span><span class="p">()</span> <span class="o">!=</span> <span class="n">python_params</span><span class="o">.</span><span class="n">keys</span><span class="p">():</span></tt>
-            </div>
-            <div id="l144"
-               class="code sev- "><tt><i>144</i>                 <span class="k">return</span> <span class="kc">False</span></tt>
-            </div>
-            <div id="l145"
-               class="code sev- "><tt><i>145</i>             <span class="k">for</span> <span class="n">key</span> <span class="ow">in</span> <span class="n">java_params</span><span class="o">.</span><span class="n">keys</span><span class="p">():</span></tt>
-            </div>
-            <div id="l146"
-               class="code sev- "><tt><i>146</i>                 <span class="n">skip_check</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">python_params</span><span class="p">[</span><span class="n">key</span><span class="p">],</span> <span class="n">Callable</span><span class="p">)</span></tt>
-            </div>
-            <div id="l147"
-               class="code sev- "><tt><i>147</i>                 <span class="k">if</span> <span class="n">java_params</span><span class="p">[</span><span class="n">key</span><span class="p">]</span> <span class="o">!=</span> <span class="n">python_params</span><span class="p">[</span><span class="n">key</span><span class="p">]</span> <span class="ow">and</span> <span class="ow">not</span> <span class="n">skip_check</span><span class="p">:</span></tt>
-            </div>
-            <div id="l148"
-               class="code sev- "><tt><i>148</i>                     <span class="k">return</span> <span class="kc">False</span></tt>
-            </div>
-            <div id="l149"
-               class="code sev- "><tt><i>149</i>             <span class="k">return</span> <span class="kc">True</span></tt>
-            </div>
-            <div id="l150"
-               class="code sev- "><tt><i>150</i> &nbsp;</tt>
-            </div>
-            <div id="l151"
-               class="code sev- "><tt><i>151</i>         <span class="n">python_parameters</span> <span class="o">=</span> <span class="nb">dict</span><span class="p">(</span><span class="n">python_parameters</span><span class="p">)</span></tt>
-            </div>
-            <div id="l152"
-               class="code sev- "><tt><i>152</i>         <span class="k">for</span> <span class="n">param_name</span><span class="p">,</span> <span class="n">param_value</span> <span class="ow">in</span> <span class="n">python_parameters</span><span class="o">.</span><span class="n">items</span><span class="p">():</span></tt>
-            </div>
-            <div id="l153"
-               class="code sev- "><tt><i>153</i>             <span class="c1"># convert measures to strings values for comparison</span></tt>
-            </div>
-            <div id="l154"
-               class="code sev- "><tt><i>154</i>             <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">param_value</span><span class="p">,</span> <span class="n">Measures</span><span class="p">):</span></tt>
-            </div>
-            <div id="l155"
-               class="code sev- "><tt><i>155</i>                 <span class="n">python_parameters</span><span class="p">[</span><span class="n">param_name</span><span class="p">]</span> <span class="o">=</span> <span class="n">param_value</span><span class="o">.</span><span class="n">value</span></tt>
-            </div>
-            <div id="l156"
-               class="code sev- "><tt><i>156</i>             <span class="c1"># convert booleans to lowercase strings for comparison</span></tt>
-            </div>
-            <div id="l157"
-               class="code sev- "><tt><i>157</i>             <span class="k">elif</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">param_value</span><span class="p">,</span> <span class="nb">bool</span><span class="p">):</span></tt>
-            </div>
-            <div id="l158"
-               class="code sev- "><tt><i>158</i>                 <span class="n">python_parameters</span><span class="p">[</span><span class="n">param_name</span><span class="p">]</span> <span class="o">=</span> <span class="nb">str</span><span class="p">(</span><span class="n">param_value</span><span class="p">)</span><span class="o">.</span><span class="n">lower</span><span class="p">()</span></tt>
-            </div>
-            <div id="l159"
-               class="code sev- "><tt><i>159</i>             <span class="c1"># normalize tuples to strings for comparison</span></tt>
-            </div>
-            <div id="l160"
-               class="code sev- "><tt><i>160</i>             <span class="k">elif</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">param_value</span><span class="p">,</span> <span class="nb">tuple</span><span class="p">):</span></tt>
-            </div>
-            <div id="l161"
-               class="code sev- "><tt><i>161</i>                 <span class="n">value</span> <span class="o">=</span> <span class="s1">&#39; &#39;</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="nb">list</span><span class="p">(</span><span class="nb">map</span><span class="p">(</span><span class="nb">str</span><span class="p">,</span> <span class="n">param_value</span><span class="p">)))</span></tt>
-            </div>
-            <div id="l162"
-               class="code sev- "><tt><i>162</i>                 <span class="n">python_parameters</span><span class="p">[</span><span class="n">param_name</span><span class="p">]</span> <span class="o">=</span> <span class="n">value</span></tt>
-            </div>
-            <div id="l163"
-               class="code sev- "><tt><i>163</i>             <span class="c1"># convert numbers to strings for comparison</span></tt>
-            </div>
-            <div id="l164"
-               class="code sev- "><tt><i>164</i>             <span class="k">elif</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">param_value</span><span class="p">,</span> <span class="p">(</span><span class="nb">int</span><span class="p">,</span> <span class="nb">float</span><span class="p">)):</span></tt>
-            </div>
-            <div id="l165"
-               class="code sev- "><tt><i>165</i>                 <span class="n">python_parameters</span><span class="p">[</span><span class="n">param_name</span><span class="p">]</span> <span class="o">=</span> <span class="nb">str</span><span class="p">(</span><span class="n">param_value</span><span class="p">)</span></tt>
-            </div>
-            <div id="l166"
-               class="code sev- "><tt><i>166</i>         <span class="n">java_params_json</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="nb">str</span><span class="p">(</span></tt>
-            </div>
-            <div id="l167"
-               class="code sev- "><tt><i>167</i>             <span class="bp">self</span><span class="o">.</span><span class="n">rule_generator</span><span class="o">.</span><span class="n">getParamsAsJsonString</span><span class="p">())</span></tt>
-            </div>
-            <div id="l168"
-               class="code sev- "><tt><i>168</i>         <span class="k">try</span><span class="p">:</span></tt>
-            </div>
-            <div id="l169"
-               class="code sev- "><tt><i>169</i>             <span class="n">java_params</span><span class="p">:</span> <span class="nb">dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">Any</span><span class="p">]</span> <span class="o">=</span> <span class="n">json</span><span class="o">.</span><span class="n">loads</span><span class="p">(</span><span class="n">java_params_json</span><span class="p">)</span></tt>
-            </div>
-            <div id="l170"
-               class="code sev- "><tt><i>170</i>         <span class="k">except</span> <span class="n">json</span><span class="o">.</span><span class="n">JSONDecodeError</span> <span class="k">as</span> <span class="n">error</span><span class="p">:</span></tt>
-            </div>
-            <div id="l171"
-               class="code sev- "><tt><i>171</i>             <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span></tt>
-            </div>
-            <div id="l172"
-               class="code sev- "><tt><i>172</i>                 <span class="s1">&#39;Failed to decode RuleGenerator parameters JSON&#39;</span><span class="p">)</span> <span class="kn">from</span> <span class="nn">error</span></tt>
-            </div>
-            <div id="l173"
-               class="code sev- "><tt><i>173</i>         <span class="c1"># select only values that are used by Python wrapper</span></tt>
-            </div>
-            <div id="l174"
-               class="code sev- "><tt><i>174</i>         <span class="n">java_params</span> <span class="o">=</span> <span class="p">{</span></tt>
-            </div>
-            <div id="l175"
-               class="code sev- "><tt><i>175</i>             <span class="n">param_name</span><span class="p">:</span> <span class="nb">str</span><span class="p">(</span><span class="n">java_params</span><span class="p">[</span><span class="n">param_name</span><span class="p">])</span></tt>
-            </div>
-            <div id="l176"
-               class="code sev- "><tt><i>176</i>             <span class="k">for</span> <span class="n">param_name</span> <span class="ow">in</span> <span class="n">python_parameters</span><span class="o">.</span><span class="n">keys</span><span class="p">()</span></tt>
-            </div>
-            <div id="l177"
-               class="code sev- "><tt><i>177</i>         <span class="p">}</span></tt>
-            </div>
-            <div id="l178"
-               class="code sev- "><tt><i>178</i>         <span class="k">if</span> <span class="ow">not</span> <span class="n">are_params_equal</span><span class="p">(</span><span class="n">java_params</span><span class="p">,</span> <span class="n">python_parameters</span><span class="p">):</span></tt>
-            </div>
-            <div id="l179"
-               class="code sev- "><tt><i>179</i>             <span class="k">raise</span> <span class="n">RuleKitMisconfigurationException</span><span class="p">(</span></tt>
-            </div>
-            <div id="l180"
-               class="code sev- "><tt><i>180</i>                 <span class="n">java_parameters</span><span class="o">=</span><span class="n">java_params</span><span class="p">,</span></tt>
-            </div>
-            <div id="l181"
-               class="code sev- "><tt><i>181</i>                 <span class="n">python_parameters</span><span class="o">=</span><span class="n">python_parameters</span></tt>
-            </div>
-            <div id="l182"
-               class="code sev- "><tt><i>182</i>             <span class="p">)</span></tt>
-            </div>
-            <div id="l183"
-               class="code sev- "><tt><i>183</i> &nbsp;</tt>
-            </div>
-            <div id="l184"
-               class="code sev- "><tt><i>184</i>     <span class="k">def</span> <span class="nf">_configure_java_logging</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span></tt>
-            </div>
-            <div id="l185"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (91 > 79 characters)</li>
-               
-               </ul><tt><i>185</i>         <span class="n">logger_config</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">_RuleKitJavaLoggerConfig</span><span class="p">]</span> <span class="o">=</span> <span class="n">RuleKit</span><span class="o">.</span><span class="n">get_java_logger_config</span><span class="p">(</span></tt>
-            </div>
-            <div id="l186"
-               class="code sev- "><tt><i>186</i>         <span class="p">)</span></tt>
-            </div>
-            <div id="l187"
-               class="code sev- "><tt><i>187</i>         <span class="k">if</span> <span class="n">logger_config</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span></tt>
-            </div>
-            <div id="l188"
-               class="code sev- "><tt><i>188</i>             <span class="k">return</span></tt>
-            </div>
-            <div id="l189"
-               class="code sev- "><tt><i>189</i>         <span class="bp">self</span><span class="o">.</span><span class="n">rule_generator</span><span class="o">.</span><span class="n">configureLogger</span><span class="p">(</span></tt>
-            </div>
-            <div id="l190"
-               class="code sev- "><tt><i>190</i>             <span class="n">logger_config</span><span class="o">.</span><span class="n">log_file_path</span><span class="p">,</span></tt>
-            </div>
-            <div id="l191"
-               class="code sev- "><tt><i>191</i>             <span class="n">logger_config</span><span class="o">.</span><span class="n">verbosity_level</span></tt>
-            </div>
-            <div id="l192"
-               class="code sev- "><tt><i>192</i>         <span class="p">)</span></tt>
-            </div>
-            <div id="l193"
-               class="code sev- "><tt><i>193</i> &nbsp;</tt>
-            </div>
-            <div id="l194"
-               class="code sev- "><tt><i>194</i> &nbsp;</tt>
-            </div>
-            <div id="l195"
-               class="code sev- "><tt><i>195</i> <span class="k">class</span> <span class="nc">ExampleSetFactory</span><span class="p">():</span></tt>
-            </div>
-            <div id="l196"
-               class="code sev- "><tt><i>196</i> <span class="w">    </span><span class="sd">&quot;&quot;&quot; Creates ExampleSet object from given data&quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l197"
-               class="code sev- "><tt><i>197</i> &nbsp;</tt>
-            </div>
-            <div id="l198"
-               class="code sev- "><tt><i>198</i>     <span class="n">DEFAULT_LABEL_ATTRIBUTE_NAME</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="s1">&#39;label&#39;</span></tt>
-            </div>
-            <div id="l199"
-               class="code sev- "><tt><i>199</i>     <span class="n">AUTOMATIC_ATTRIBUTES_NAMES_PREFIX</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="s1">&#39;att&#39;</span></tt>
-            </div>
-            <div id="l200"
-               class="code sev- "><tt><i>200</i> &nbsp;</tt>
-            </div>
-            <div id="l201"
-               class="code sev- "><tt><i>201</i>     <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">problem_type</span><span class="p">:</span> <span class="n">ProblemType</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="kc">None</span><span class="p">:</span></tt>
-            </div>
-            <div id="l202"
-               class="code sev- "><tt><i>202</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_problem_type</span><span class="p">:</span> <span class="n">ProblemType</span> <span class="o">=</span> <span class="n">problem_type</span></tt>
-            </div>
-            <div id="l203"
-               class="code sev- "><tt><i>203</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_attributes_names</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="nb">str</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span></tt>
-            </div>
-            <div id="l204"
-               class="code sev- "><tt><i>204</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_label_name</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="kc">None</span></tt>
-            </div>
-            <div id="l205"
-               class="code sev- "><tt><i>205</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_survival_time_attribute</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="kc">None</span></tt>
-            </div>
-            <div id="l206"
-               class="code sev- "><tt><i>206</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_contrast_attribute</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="kc">None</span></tt>
-            </div>
-            <div id="l207"
-               class="code sev- "><tt><i>207</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_X</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span> <span class="o">=</span> <span class="kc">None</span></tt>
-            </div>
-            <div id="l208"
-               class="code sev- "><tt><i>208</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_y</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span> <span class="o">=</span> <span class="kc">None</span></tt>
-            </div>
-            <div id="l209"
-               class="code sev- "><tt><i>209</i> &nbsp;</tt>
-            </div>
-            <div id="l210"
-               class="code sev- "><tt><i>210</i>     <span class="k">def</span> <span class="nf">make</span><span class="p">(</span></tt>
-            </div>
-            <div id="l211"
-               class="code sev- "><tt><i>211</i>         <span class="bp">self</span><span class="p">,</span></tt>
-            </div>
-            <div id="l212"
-               class="code sev- "><tt><i>212</i>         <span class="n">X</span><span class="p">:</span> <span class="n">Union</span><span class="p">[</span><span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">],</span></tt>
-            </div>
-            <div id="l213"
-               class="code sev- "><tt><i>213</i>         <span class="n">y</span><span class="p">:</span> <span class="n">Union</span><span class="p">[</span><span class="n">pd</span><span class="o">.</span><span class="n">Series</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span></tt>
-            </div>
-            <div id="l214"
-               class="code sev- "><tt><i>214</i>         <span class="n">survival_time_attribute</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span></tt>
-            </div>
-            <div id="l215"
-               class="code sev- "><tt><i>215</i>         <span class="n">contrast_attribute</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span></tt>
-            </div>
-            <div id="l216"
-               class="code sev- "><tt><i>216</i>     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">JObject</span><span class="p">:</span></tt>
-            </div>
-            <div id="l217"
-               class="code sev- "><tt><i>217</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Creates ExampleSet object from given data</span></tt>
-            </div>
-            <div id="l218"
-               class="code sev- "><tt><i>218</i> &nbsp;</tt>
-            </div>
-            <div id="l219"
-               class="code sev- "><tt><i>219</i> <span class="sd">        Args:</span></tt>
-            </div>
-            <div id="l220"
-               class="code sev- "><tt><i>220</i> <span class="sd">            X (Union[pd.DataFrame, np.ndarray]): Data</span></tt>
-            </div>
-            <div id="l221"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (81 > 79 characters)</li>
-               
-               </ul><tt><i>221</i> <span class="sd">            y (Union[pd.Series, np.ndarray], optional): Labels. Defaults to None.</span></tt>
-            </div>
-            <div id="l222"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (85 > 79 characters)</li>
-               
-               </ul><tt><i>222</i> <span class="sd">            survival_time_attribute (str, optional): Name of survival time attribute.</span></tt>
-            </div>
-            <div id="l223"
-               class="code sev- "><tt><i>223</i> <span class="sd">             Defaults to None.</span></tt>
-            </div>
-            <div id="l224"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (93 > 79 characters)</li>
-               
-               </ul><tt><i>224</i> <span class="sd">            contrast_attribute (str, optional): Name of contrast attribute. Defaults to None.</span></tt>
-            </div>
-            <div id="l225"
-               class="code sev- "><tt><i>225</i> &nbsp;</tt>
-            </div>
-            <div id="l226"
-               class="code sev- "><tt><i>226</i> <span class="sd">        Returns:</span></tt>
-            </div>
-            <div id="l227"
-               class="code sev- "><tt><i>227</i> <span class="sd">            JObject: ExampleSet object</span></tt>
-            </div>
-            <div id="l228"
-               class="code sev- "><tt><i>228</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l229"
-               class="code sev- "><tt><i>229</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_attributes_names</span> <span class="o">=</span> <span class="p">[]</span></tt>
-            </div>
-            <div id="l230"
-               class="code sev- "><tt><i>230</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_survival_time_attribute</span> <span class="o">=</span> <span class="n">survival_time_attribute</span></tt>
-            </div>
-            <div id="l231"
-               class="code sev- "><tt><i>231</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_contrast_attribute</span> <span class="o">=</span> <span class="n">contrast_attribute</span></tt>
-            </div>
-            <div id="l232"
-               class="code sev- "><tt><i>232</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_sanitize_X</span><span class="p">(</span><span class="n">X</span><span class="p">)</span></tt>
-            </div>
-            <div id="l233"
-               class="code sev- "><tt><i>233</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_sanitize_y</span><span class="p">(</span><span class="n">y</span><span class="p">)</span></tt>
-            </div>
-            <div id="l234"
-               class="code sev- "><tt><i>234</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_validate_X</span><span class="p">()</span></tt>
-            </div>
-            <div id="l235"
-               class="code sev- "><tt><i>235</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_validate_y</span><span class="p">()</span></tt>
-            </div>
-            <div id="l236"
-               class="code sev- "><tt><i>236</i>         <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_create_example_set</span><span class="p">()</span></tt>
-            </div>
-            <div id="l237"
-               class="code sev- "><tt><i>237</i> &nbsp;</tt>
-            </div>
-            <div id="l238"
-               class="code sev- "><tt><i>238</i>     <span class="k">def</span> <span class="nf">_sanitize_y</span><span class="p">(</span></tt>
-            </div>
-            <div id="l239"
-               class="code sev- "><tt><i>239</i>         <span class="bp">self</span><span class="p">,</span></tt>
-            </div>
-            <div id="l240"
-               class="code sev- "><tt><i>240</i>         <span class="n">y</span><span class="p">:</span> <span class="n">Union</span><span class="p">[</span><span class="n">pd</span><span class="o">.</span><span class="n">Series</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">,</span> <span class="nb">list</span><span class="p">]</span></tt>
-            </div>
-            <div id="l241"
-               class="code sev- "><tt><i>241</i>     <span class="p">):</span></tt>
-            </div>
-            <div id="l242"
-               class="code sev- "><tt><i>242</i>         <span class="k">if</span> <span class="n">y</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span></tt>
-            </div>
-            <div id="l243"
-               class="code sev- "><tt><i>243</i>             <span class="k">return</span></tt>
-            </div>
-            <div id="l244"
-               class="code sev- "><tt><i>244</i>         <span class="k">elif</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">y</span><span class="p">,</span> <span class="n">pd</span><span class="o">.</span><span class="n">Series</span><span class="p">):</span></tt>
-            </div>
-            <div id="l245"
-               class="code sev- "><tt><i>245</i>             <span class="bp">self</span><span class="o">.</span><span class="n">_label_name</span> <span class="o">=</span> <span class="n">y</span><span class="o">.</span><span class="n">name</span></tt>
-            </div>
-            <div id="l246"
-               class="code sev- "><tt><i>246</i>             <span class="bp">self</span><span class="o">.</span><span class="n">_attributes_names</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_label_name</span><span class="p">)</span></tt>
-            </div>
-            <div id="l247"
-               class="code sev- "><tt><i>247</i>             <span class="bp">self</span><span class="o">.</span><span class="n">_y</span> <span class="o">=</span> <span class="n">y</span><span class="o">.</span><span class="n">to_numpy</span><span class="p">()</span></tt>
-            </div>
-            <div id="l248"
-               class="code sev- "><tt><i>248</i>         <span class="k">elif</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">y</span><span class="p">,</span> <span class="nb">list</span><span class="p">):</span></tt>
-            </div>
-            <div id="l249"
-               class="code sev- "><tt><i>249</i>             <span class="bp">self</span><span class="o">.</span><span class="n">_label_name</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">DEFAULT_LABEL_ATTRIBUTE_NAME</span></tt>
-            </div>
-            <div id="l250"
-               class="code sev- "><tt><i>250</i>             <span class="bp">self</span><span class="o">.</span><span class="n">_attributes_names</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_label_name</span><span class="p">)</span></tt>
-            </div>
-            <div id="l251"
-               class="code sev- "><tt><i>251</i>             <span class="bp">self</span><span class="o">.</span><span class="n">_y</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">y</span><span class="p">)</span></tt>
-            </div>
-            <div id="l252"
-               class="code sev- "><tt><i>252</i>         <span class="k">elif</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">y</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">):</span></tt>
-            </div>
-            <div id="l253"
-               class="code sev- "><tt><i>253</i>             <span class="bp">self</span><span class="o">.</span><span class="n">_label_name</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">DEFAULT_LABEL_ATTRIBUTE_NAME</span></tt>
-            </div>
-            <div id="l254"
-               class="code sev- "><tt><i>254</i>             <span class="bp">self</span><span class="o">.</span><span class="n">_attributes_names</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_label_name</span><span class="p">)</span></tt>
-            </div>
-            <div id="l255"
-               class="code sev- "><tt><i>255</i>             <span class="bp">self</span><span class="o">.</span><span class="n">_y</span> <span class="o">=</span> <span class="n">y</span></tt>
-            </div>
-            <div id="l256"
-               class="code sev- "><tt><i>256</i>         <span class="k">else</span><span class="p">:</span></tt>
-            </div>
-            <div id="l257"
-               class="code sev- "><tt><i>257</i>             <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span></tt>
-            </div>
-            <div id="l258"
-               class="code sev- "><tt><i>258</i>                 <span class="sa">f</span><span class="s1">&#39;Invalid y type: </span><span class="si">{</span><span class="nb">str</span><span class="p">(</span><span class="nb">type</span><span class="p">(</span><span class="n">y</span><span class="p">))</span><span class="si">}</span><span class="s1">. &#39;</span> <span class="o">+</span></tt>
-            </div>
-            <div id="l259"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (89 > 79 characters)</li>
-               
-               </ul><tt><i>259</i>                 <span class="s1">&#39;Supported types are: 1 dimensional numpy array or pandas Series object.&#39;</span></tt>
-            </div>
-            <div id="l260"
-               class="code sev- "><tt><i>260</i>             <span class="p">)</span></tt>
-            </div>
-            <div id="l261"
-               class="code sev- "><tt><i>261</i> &nbsp;</tt>
-            </div>
-            <div id="l262"
-               class="code sev- "><tt><i>262</i>     <span class="k">def</span> <span class="nf">_sanitize_X</span><span class="p">(</span></tt>
-            </div>
-            <div id="l263"
-               class="code sev- "><tt><i>263</i>         <span class="bp">self</span><span class="p">,</span></tt>
-            </div>
-            <div id="l264"
-               class="code sev- "><tt><i>264</i>         <span class="n">X</span><span class="p">:</span> <span class="n">Union</span><span class="p">[</span><span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">],</span></tt>
-            </div>
-            <div id="l265"
-               class="code sev- "><tt><i>265</i>     <span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">tuple</span><span class="p">[</span><span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">]:</span></tt>
-            </div>
-            <div id="l266"
-               class="code sev- "><tt><i>266</i>         <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">X</span><span class="p">,</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">):</span></tt>
-            </div>
-            <div id="l267"
-               class="code sev- "><tt><i>267</i>             <span class="bp">self</span><span class="o">.</span><span class="n">_attributes_names</span> <span class="o">=</span> <span class="n">X</span><span class="o">.</span><span class="n">columns</span><span class="o">.</span><span class="n">tolist</span><span class="p">()</span></tt>
-            </div>
-            <div id="l268"
-               class="code sev- "><tt><i>268</i>             <span class="c1"># replace nan values with None</span></tt>
-            </div>
-            <div id="l269"
-               class="code sev- "><tt><i>269</i>             <span class="n">X</span> <span class="o">=</span> <span class="n">X</span><span class="o">.</span><span class="n">where</span><span class="p">(</span><span class="n">pd</span><span class="o">.</span><span class="n">notnull</span><span class="p">(</span><span class="n">X</span><span class="p">),</span> <span class="kc">None</span><span class="p">)</span></tt>
-            </div>
-            <div id="l270"
-               class="code sev- "><tt><i>270</i>             <span class="bp">self</span><span class="o">.</span><span class="n">_X</span> <span class="o">=</span> <span class="n">X</span><span class="o">.</span><span class="n">to_numpy</span><span class="p">()</span></tt>
-            </div>
-            <div id="l271"
-               class="code sev- "><tt><i>271</i>         <span class="k">elif</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">X</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">):</span></tt>
-            </div>
-            <div id="l272"
-               class="code sev- "><tt><i>272</i>             <span class="bp">self</span><span class="o">.</span><span class="n">_attributes_names</span> <span class="o">=</span> <span class="p">[</span></tt>
-            </div>
-            <div id="l273"
-               class="code sev- "><tt><i>273</i>                 <span class="sa">f</span><span class="s1">&#39;</span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">AUTOMATIC_ATTRIBUTES_NAMES_PREFIX</span><span class="si">}{</span><span class="n">index</span><span class="w"> </span><span class="o">+</span><span class="w"> </span><span class="mi">1</span><span class="si">}</span><span class="s1">&#39;</span></tt>
-            </div>
-            <div id="l274"
-               class="code sev- "><tt><i>274</i>                 <span class="k">for</span> <span class="n">index</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">X</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">1</span><span class="p">])</span></tt>
-            </div>
-            <div id="l275"
-               class="code sev- "><tt><i>275</i>             <span class="p">]</span></tt>
-            </div>
-            <div id="l276"
-               class="code sev- "><tt><i>276</i>             <span class="bp">self</span><span class="o">.</span><span class="n">_X</span> <span class="o">=</span> <span class="n">X</span></tt>
-            </div>
-            <div id="l277"
-               class="code sev- "><tt><i>277</i>         <span class="k">else</span><span class="p">:</span></tt>
-            </div>
-            <div id="l278"
-               class="code sev- "><tt><i>278</i>             <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span></tt>
-            </div>
-            <div id="l279"
-               class="code sev- "><tt><i>279</i>                 <span class="sa">f</span><span class="s1">&#39;Invalid X type: </span><span class="si">{</span><span class="nb">str</span><span class="p">(</span><span class="nb">type</span><span class="p">(</span><span class="n">X</span><span class="p">))</span><span class="si">}</span><span class="s1">. &#39;</span> <span class="o">+</span></tt>
-            </div>
-            <div id="l280"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (92 > 79 characters)</li>
-               
-               </ul><tt><i>280</i>                 <span class="s1">&#39;Supported types are: 2 dimensional numpy array or pandas DataFrame object.&#39;</span></tt>
-            </div>
-            <div id="l281"
-               class="code sev- "><tt><i>281</i>             <span class="p">)</span></tt>
-            </div>
-            <div id="l282"
-               class="code sev- "><tt><i>282</i> &nbsp;</tt>
-            </div>
-            <div id="l283"
-               class="code sev- "><tt><i>283</i>     <span class="k">def</span> <span class="nf">_validate_X</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span></tt>
-            </div>
-            <div id="l284"
-               class="code sev- "><tt><i>284</i>         <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_X</span><span class="o">.</span><span class="n">shape</span><span class="p">)</span> <span class="o">!=</span> <span class="mi">2</span><span class="p">:</span></tt>
-            </div>
-            <div id="l285"
-               class="code sev- "><tt><i>285</i>             <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span></tt>
-            </div>
-            <div id="l286"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (86 > 79 characters)</li>
-               
-               </ul><tt><i>286</i>                 <span class="s1">&#39;X must be a 2 dimensional numpy array or pandas DataFrame object. &#39;</span> <span class="o">+</span></tt>
-            </div>
-            <div id="l287"
-               class="code sev- "><tt><i>287</i>                 <span class="sa">f</span><span class="s1">&#39;Its current shape is: </span><span class="si">{</span><span class="nb">str</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_X</span><span class="o">.</span><span class="n">shape</span><span class="p">)</span><span class="si">}</span><span class="s1">&#39;</span></tt>
-            </div>
-            <div id="l288"
-               class="code sev- "><tt><i>288</i>             <span class="p">)</span></tt>
-            </div>
-            <div id="l289"
-               class="code sev- "><tt><i>289</i> &nbsp;</tt>
-            </div>
-            <div id="l290"
-               class="code sev- "><tt><i>290</i>     <span class="k">def</span> <span class="nf">_validate_y</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span></tt>
-            </div>
-            <div id="l291"
-               class="code sev- "><tt><i>291</i>         <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">_y</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span> <span class="ow">and</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_y</span><span class="o">.</span><span class="n">shape</span><span class="p">)</span> <span class="o">!=</span> <span class="mi">1</span><span class="p">:</span></tt>
-            </div>
-            <div id="l292"
-               class="code sev- "><tt><i>292</i>             <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span></tt>
-            </div>
-            <div id="l293"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (86 > 79 characters)</li>
-               
-               </ul><tt><i>293</i>                 <span class="s1">&#39;y must be a 1 dimensional numpy array or pandas DataFrame object. &#39;</span> <span class="o">+</span></tt>
-            </div>
-            <div id="l294"
-               class="code sev- "><tt><i>294</i>                 <span class="sa">f</span><span class="s1">&#39;Its current shape is: </span><span class="si">{</span><span class="nb">str</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_y</span><span class="o">.</span><span class="n">shape</span><span class="p">)</span><span class="si">}</span><span class="s1">&#39;</span></tt>
-            </div>
-            <div id="l295"
-               class="code sev- "><tt><i>295</i>             <span class="p">)</span></tt>
-            </div>
-            <div id="l296"
-               class="code sev- "><tt><i>296</i> &nbsp;</tt>
-            </div>
-            <div id="l297"
-               class="code sev- "><tt><i>297</i>     <span class="k">def</span> <span class="nf">_create_example_set</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">JObject</span><span class="p">:</span></tt>
-            </div>
-            <div id="l298"
-               class="code sev- "><tt><i>298</i>         <span class="n">data</span><span class="p">:</span> <span class="n">JObject</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_prepare_data</span><span class="p">()</span></tt>
-            </div>
-            <div id="l299"
-               class="code sev- "><tt><i>299</i>         <span class="n">args</span><span class="p">:</span> <span class="nb">list</span> <span class="o">=</span> <span class="p">[</span></tt>
-            </div>
-            <div id="l300"
-               class="code sev- "><tt><i>300</i>             <span class="n">data</span><span class="p">,</span></tt>
-            </div>
-            <div id="l301"
-               class="code sev- "><tt><i>301</i>             <span class="bp">self</span><span class="o">.</span><span class="n">_attributes_names</span><span class="p">,</span></tt>
-            </div>
-            <div id="l302"
-               class="code sev- "><tt><i>302</i>             <span class="bp">self</span><span class="o">.</span><span class="n">_label_name</span><span class="p">,</span></tt>
-            </div>
-            <div id="l303"
-               class="code sev- "><tt><i>303</i>             <span class="bp">self</span><span class="o">.</span><span class="n">_survival_time_attribute</span><span class="p">,</span></tt>
-            </div>
-            <div id="l304"
-               class="code sev- "><tt><i>304</i>             <span class="bp">self</span><span class="o">.</span><span class="n">_contrast_attribute</span></tt>
-            </div>
-            <div id="l305"
-               class="code sev- "><tt><i>305</i>         <span class="p">]</span></tt>
-            </div>
-            <div id="l306"
-               class="code sev- "><tt><i>306</i>         <span class="n">DataTable</span> <span class="o">=</span> <span class="n">JClass</span><span class="p">(</span>  <span class="c1"># pylint: disable=invalid-name</span></tt>
-            </div>
-            <div id="l307"
-               class="code sev- "><tt><i>307</i>             <span class="s1">&#39;adaa.analytics.rules.data.DataTable&#39;</span></tt>
-            </div>
-            <div id="l308"
-               class="code sev- "><tt><i>308</i>         <span class="p">)</span></tt>
-            </div>
-            <div id="l309"
-               class="code sev- "><tt><i>309</i>         <span class="k">try</span><span class="p">:</span></tt>
-            </div>
-            <div id="l310"
-               class="code sev- "><tt><i>310</i>             <span class="n">table</span> <span class="o">=</span> <span class="n">DataTable</span><span class="p">(</span><span class="o">*</span><span class="n">args</span><span class="p">)</span></tt>
-            </div>
-            <div id="l311"
-               class="code sev- "><tt><i>311</i>             <span class="k">if</span> <span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_y</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">):</span></tt>
-            </div>
-            <div id="l312"
-               class="code sev- "><tt><i>312</i>                 <span class="n">ExampleSetFactory</span> <span class="o">=</span> <span class="n">JClass</span><span class="p">(</span></tt>
-            </div>
-            <div id="l313"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (93 > 79 characters)</li>
-               
-               </ul><tt><i>313</i>                     <span class="s1">&#39;adaa.analytics.rules.logic.representation.exampleset.ExampleSetFactory&#39;</span><span class="p">)</span></tt>
-            </div>
-            <div id="l314"
-               class="code sev- "><tt><i>314</i>                 <span class="n">factory</span> <span class="o">=</span> <span class="n">ExampleSetFactory</span><span class="p">(</span><span class="mi">2</span><span class="p">)</span></tt>
-            </div>
-            <div id="l315"
-               class="code sev- "><tt><i>315</i>                 <span class="n">example_set</span> <span class="o">=</span> <span class="n">factory</span><span class="o">.</span><span class="n">create</span><span class="p">(</span><span class="n">table</span><span class="p">)</span></tt>
-            </div>
-            <div id="l316"
-               class="code sev- "><tt><i>316</i>                 <span class="k">return</span> <span class="n">example_set</span></tt>
-            </div>
-            <div id="l317"
-               class="code sev- "><tt><i>317</i>             <span class="k">else</span><span class="p">:</span></tt>
-            </div>
-            <div id="l318"
-               class="code sev- "><tt><i>318</i>                 <span class="k">return</span> <span class="n">table</span></tt>
-            </div>
-            <div id="l319"
-               class="code sev- "><tt><i>319</i>         <span class="k">except</span> <span class="ne">Exception</span> <span class="k">as</span> <span class="n">error</span><span class="p">:</span></tt>
-            </div>
-            <div id="l320"
-               class="code sev- "><tt><i>320</i>             <span class="kn">from</span> <span class="nn">rulekit.exceptions</span> <span class="kn">import</span> <span class="n">RuleKitJavaException</span></tt>
-            </div>
-            <div id="l321"
-               class="code sev- "><tt><i>321</i>             <span class="n">RuleKitJavaException</span><span class="p">(</span><span class="n">error</span><span class="p">)</span><span class="o">.</span><span class="n">print_java_stack_trace</span><span class="p">()</span></tt>
-            </div>
-            <div id="l322"
-               class="code sev- "><tt><i>322</i>             <span class="k">raise</span> <span class="n">error</span></tt>
-            </div>
-            <div id="l323"
-               class="code sev- "><tt><i>323</i> &nbsp;</tt>
-            </div>
-            <div id="l324"
-               class="code sev- "><tt><i>324</i>     <span class="k">def</span> <span class="nf">_wrap_training_example_set</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">example_set</span><span class="p">:</span> <span class="n">JObject</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">JObject</span><span class="p">:</span></tt>
-            </div>
-            <div id="l325"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (100 > 79 characters)</li>
-               
-               </ul><tt><i>325</i>         <span class="c1"># training dataset must be wrapped in additional classes for rule induction to work properly</span></tt>
-            </div>
-            <div id="l326"
-               class="code sev- "><tt><i>326</i>         <span class="n">ExampleSetFactory</span> <span class="o">=</span> <span class="n">JClass</span><span class="p">(</span></tt>
-            </div>
-            <div id="l327"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (85 > 79 characters)</li>
-               
-               </ul><tt><i>327</i>             <span class="s1">&#39;adaa.analytics.rules.logic.representation.exampleset.ExampleSetFactory&#39;</span><span class="p">)</span></tt>
-            </div>
-            <div id="l328"
-               class="code sev- "><tt><i>328</i>         <span class="n">factory</span><span class="p">:</span> <span class="n">JObject</span> <span class="o">=</span> <span class="n">ExampleSetFactory</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_problem_type</span><span class="o">.</span><span class="n">value</span><span class="p">)</span></tt>
-            </div>
-            <div id="l329"
-               class="code sev- "><tt><i>329</i>         <span class="k">return</span> <span class="n">factory</span><span class="o">.</span><span class="n">create</span><span class="p">(</span><span class="n">example_set</span><span class="p">)</span></tt>
-            </div>
-            <div id="l330"
-               class="code sev- "><tt><i>330</i> &nbsp;</tt>
-            </div>
-            <div id="l331"
-               class="code sev- "><tt><i>331</i>     <span class="k">def</span> <span class="nf">_prepare_data</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">JObject</span><span class="p">:</span></tt>
-            </div>
-            <div id="l332"
-               class="code sev- "><tt><i>332</i>         <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">_y</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span></tt>
-            </div>
-            <div id="l333"
-               class="code sev- "><tt><i>333</i>             <span class="n">data</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_X</span></tt>
-            </div>
-            <div id="l334"
-               class="code sev- "><tt><i>334</i>         <span class="k">else</span><span class="p">:</span></tt>
-            </div>
-            <div id="l335"
-               class="code sev- "><tt><i>335</i>             <span class="n">data</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">hstack</span><span class="p">((</span><span class="bp">self</span><span class="o">.</span><span class="n">_X</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="nb">object</span><span class="p">),</span> <span class="bp">self</span><span class="o">.</span><span class="n">_y</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">)))</span></tt>
-            </div>
-            <div id="l336"
-               class="code sev- "><tt><i>336</i>         <span class="n">java_data</span> <span class="o">=</span> <span class="n">JObject</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">JArray</span><span class="p">(</span><span class="s1">&#39;java.lang.Object&#39;</span><span class="p">,</span> <span class="mi">2</span><span class="p">))</span></tt>
-            </div>
-            <div id="l337"
-               class="code sev- "><tt><i>337</i>         <span class="k">return</span> <span class="n">java_data</span></tt>
-            </div>
-            <div id="l338"
-               class="code sev- "><tt><i>338</i> &nbsp;</tt>
-            </div>
-            <div id="l339"
-               class="code sev- "><tt><i>339</i> &nbsp;</tt>
-            </div>
-            <div id="l340"
-               class="code sev- "><tt><i>340</i> <span class="k">class</span> <span class="nc">PredictionResultMapper</span><span class="p">:</span></tt>
-            </div>
-            <div id="l341"
-               class="code sev- "><tt><i>341</i> <span class="w">    </span><span class="sd">&quot;&quot;&quot;Maps prediction results to numpy array</span></tt>
-            </div>
-            <div id="l342"
-               class="code sev- "><tt><i>342</i> <span class="sd">    &quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l343"
-               class="code sev- "><tt><i>343</i> &nbsp;</tt>
-            </div>
-            <div id="l344"
-               class="code sev- "><tt><i>344</i>     <span class="n">PREDICTION_COLUMN_ROLE</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="s1">&#39;prediction&#39;</span></tt>
-            </div>
-            <div id="l345"
-               class="code sev- "><tt><i>345</i>     <span class="n">CONFIDENCE_COLUMN_ROLE</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="s1">&#39;confidence&#39;</span></tt>
-            </div>
-            <div id="l346"
-               class="code sev- "><tt><i>346</i> &nbsp;</tt>
-            </div>
-            <div id="l347"
-               class="code sev- "><tt><i>347</i>     <span class="nd">@staticmethod</span></tt>
-            </div>
-            <div id="l348"
-               class="code sev- "><tt><i>348</i>     <span class="k">def</span> <span class="nf">map_confidence</span><span class="p">(</span></tt>
-            </div>
-            <div id="l349"
-               class="code sev- "><tt><i>349</i>         <span class="n">predicted_example_set</span><span class="p">,</span></tt>
-            </div>
-            <div id="l350"
-               class="code sev- "><tt><i>350</i>         <span class="n">label_unique_values</span><span class="p">:</span> <span class="nb">list</span></tt>
-            </div>
-            <div id="l351"
-               class="code sev- "><tt><i>351</i>     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">:</span></tt>
-            </div>
-            <div id="l352"
-               class="code sev- "><tt><i>352</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Maps models confidence values to numpy array</span></tt>
-            </div>
-            <div id="l353"
-               class="code sev- "><tt><i>353</i> &nbsp;</tt>
-            </div>
-            <div id="l354"
-               class="code sev- "><tt><i>354</i> <span class="sd">        Args:</span></tt>
-            </div>
-            <div id="l355"
-               class="code sev- "><tt><i>355</i> <span class="sd">            predicted_example_set (_type_): predicted ExampleSet instance</span></tt>
-            </div>
-            <div id="l356"
-               class="code sev- "><tt><i>356</i> <span class="sd">            label_unique_values (list): unique labels values</span></tt>
-            </div>
-            <div id="l357"
-               class="code sev- "><tt><i>357</i> &nbsp;</tt>
-            </div>
-            <div id="l358"
-               class="code sev- "><tt><i>358</i> <span class="sd">        Returns:</span></tt>
-            </div>
-            <div id="l359"
-               class="code sev- "><tt><i>359</i> <span class="sd">            np.ndarray: numpy array with mapped confidence values</span></tt>
-            </div>
-            <div id="l360"
-               class="code sev- "><tt><i>360</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l361"
-               class="code sev- "><tt><i>361</i>         <span class="n">confidence_matrix</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="nb">list</span><span class="p">[</span><span class="nb">float</span><span class="p">]]</span> <span class="o">=</span> <span class="p">[]</span></tt>
-            </div>
-            <div id="l362"
-               class="code sev- "><tt><i>362</i>         <span class="k">for</span> <span class="n">label_value</span> <span class="ow">in</span> <span class="n">label_unique_values</span><span class="p">:</span></tt>
-            </div>
-            <div id="l363"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (81 > 79 characters)</li>
-               
-               </ul><tt><i>363</i>             <span class="n">confidence_col</span><span class="p">:</span> <span class="n">JObject</span> <span class="o">=</span> <span class="n">PredictionResultMapper</span><span class="o">.</span><span class="n">_get_column_by_role</span><span class="p">(</span></tt>
-            </div>
-            <div id="l364"
-               class="code sev- "><tt><i>364</i>                 <span class="n">predicted_example_set</span><span class="p">,</span></tt>
-            </div>
-            <div id="l365"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (80 > 79 characters)</li>
-               
-               </ul><tt><i>365</i>                 <span class="sa">f</span><span class="s1">&#39;</span><span class="si">{</span><span class="n">PredictionResultMapper</span><span class="o">.</span><span class="n">CONFIDENCE_COLUMN_ROLE</span><span class="si">}</span><span class="s1">_</span><span class="si">{</span><span class="n">label_value</span><span class="si">}</span><span class="s1">&#39;</span></tt>
-            </div>
-            <div id="l366"
-               class="code sev- "><tt><i>366</i>             <span class="p">)</span></tt>
-            </div>
-            <div id="l367"
-               class="code sev- "><tt><i>367</i> &nbsp;</tt>
-            </div>
-            <div id="l368"
-               class="code sev- "><tt><i>368</i>             <span class="n">confidence_values</span> <span class="o">=</span> <span class="p">[</span></tt>
-            </div>
-            <div id="l369"
-               class="code sev- "><tt><i>369</i>                 <span class="nb">float</span><span class="p">(</span><span class="n">predicted_example_set</span><span class="o">.</span><span class="n">getExample</span><span class="p">(</span></tt>
-            </div>
-            <div id="l370"
-               class="code sev- "><tt><i>370</i>                     <span class="n">i</span><span class="p">)</span><span class="o">.</span><span class="n">getValue</span><span class="p">(</span><span class="n">confidence_col</span><span class="p">))</span></tt>
-            </div>
-            <div id="l371"
-               class="code sev- "><tt><i>371</i>                 <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">predicted_example_set</span><span class="o">.</span><span class="n">size</span><span class="p">())</span></tt>
-            </div>
-            <div id="l372"
-               class="code sev- "><tt><i>372</i>             <span class="p">]</span></tt>
-            </div>
-            <div id="l373"
-               class="code sev- "><tt><i>373</i> &nbsp;</tt>
-            </div>
-            <div id="l374"
-               class="code sev- "><tt><i>374</i>             <span class="n">confidence_matrix</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">confidence_values</span><span class="p">)</span></tt>
-            </div>
-            <div id="l375"
-               class="code sev- "><tt><i>375</i>         <span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">confidence_matrix</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="nb">float</span><span class="p">)</span><span class="o">.</span><span class="n">T</span></tt>
-            </div>
-            <div id="l376"
-               class="code sev- "><tt><i>376</i> &nbsp;</tt>
-            </div>
-            <div id="l377"
-               class="code sev- "><tt><i>377</i>     <span class="nd">@staticmethod</span></tt>
-            </div>
-            <div id="l378"
-               class="code sev- "><tt><i>378</i>     <span class="k">def</span> <span class="nf">map</span><span class="p">(</span><span class="n">predicted_example_set</span><span class="p">:</span> <span class="n">JObject</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">:</span></tt>
-            </div>
-            <div id="l379"
-               class="code sev- "><tt><i>379</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Maps models predictions to numpy array</span></tt>
-            </div>
-            <div id="l380"
-               class="code sev- "><tt><i>380</i> &nbsp;</tt>
-            </div>
-            <div id="l381"
-               class="code sev- "><tt><i>381</i> <span class="sd">        Args:</span></tt>
-            </div>
-            <div id="l382"
-               class="code sev- "><tt><i>382</i> <span class="sd">            predicted_example_set (_type_): ExampleSet with predictions</span></tt>
-            </div>
-            <div id="l383"
-               class="code sev- "><tt><i>383</i> &nbsp;</tt>
-            </div>
-            <div id="l384"
-               class="code sev- "><tt><i>384</i> <span class="sd">        Returns:</span></tt>
-            </div>
-            <div id="l385"
-               class="code sev- "><tt><i>385</i> <span class="sd">            np.ndarray: numpy array containing predictions</span></tt>
-            </div>
-            <div id="l386"
-               class="code sev- "><tt><i>386</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l387"
-               class="code sev- "><tt><i>387</i>         <span class="n">prediction_col</span><span class="p">:</span> <span class="n">JObject</span> <span class="o">=</span> <span class="n">PredictionResultMapper</span><span class="o">.</span><span class="n">_get_column_by_role</span><span class="p">(</span></tt>
-            </div>
-            <div id="l388"
-               class="code sev- "><tt><i>388</i>             <span class="n">predicted_example_set</span><span class="p">,</span></tt>
-            </div>
-            <div id="l389"
-               class="code sev- "><tt><i>389</i>             <span class="n">PredictionResultMapper</span><span class="o">.</span><span class="n">PREDICTION_COLUMN_ROLE</span></tt>
-            </div>
-            <div id="l390"
-               class="code sev- "><tt><i>390</i>         <span class="p">)</span></tt>
-            </div>
-            <div id="l391"
-               class="code sev- "><tt><i>391</i>         <span class="k">if</span> <span class="n">prediction_col</span><span class="o">.</span><span class="n">isNominal</span><span class="p">():</span></tt>
-            </div>
-            <div id="l392"
-               class="code sev- "><tt><i>392</i>             <span class="k">return</span> <span class="n">PredictionResultMapper</span><span class="o">.</span><span class="n">map_to_nominal</span><span class="p">(</span><span class="n">predicted_example_set</span><span class="p">)</span></tt>
-            </div>
-            <div id="l393"
-               class="code sev- "><tt><i>393</i>         <span class="k">return</span> <span class="n">PredictionResultMapper</span><span class="o">.</span><span class="n">map_to_numerical</span><span class="p">(</span><span class="n">predicted_example_set</span><span class="p">)</span></tt>
-            </div>
-            <div id="l394"
-               class="code sev- "><tt><i>394</i> &nbsp;</tt>
-            </div>
-            <div id="l395"
-               class="code sev- "><tt><i>395</i>     <span class="nd">@staticmethod</span></tt>
-            </div>
-            <div id="l396"
-               class="code sev- "><tt><i>396</i>     <span class="k">def</span> <span class="nf">map_to_nominal</span><span class="p">(</span><span class="n">predicted_example_set</span><span class="p">:</span> <span class="n">JObject</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">:</span></tt>
-            </div>
-            <div id="l397"
-               class="code sev- "><tt><i>397</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Maps models predictions to nominal numpy array of strings</span></tt>
-            </div>
-            <div id="l398"
-               class="code sev- "><tt><i>398</i> &nbsp;</tt>
-            </div>
-            <div id="l399"
-               class="code sev- "><tt><i>399</i> <span class="sd">        Args:</span></tt>
-            </div>
-            <div id="l400"
-               class="code sev- "><tt><i>400</i> <span class="sd">            predicted_example_set (_type_): ExampleSet with predictions</span></tt>
-            </div>
-            <div id="l401"
-               class="code sev- "><tt><i>401</i> &nbsp;</tt>
-            </div>
-            <div id="l402"
-               class="code sev- "><tt><i>402</i> <span class="sd">        Returns:</span></tt>
-            </div>
-            <div id="l403"
-               class="code sev- "><tt><i>403</i> <span class="sd">            np.ndarray: numpy array containing predictions</span></tt>
-            </div>
-            <div id="l404"
-               class="code sev- "><tt><i>404</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l405"
-               class="code sev- "><tt><i>405</i>         <span class="n">prediction_col</span><span class="p">:</span> <span class="n">JObject</span> <span class="o">=</span> <span class="n">PredictionResultMapper</span><span class="o">.</span><span class="n">_get_column_by_role</span><span class="p">(</span></tt>
-            </div>
-            <div id="l406"
-               class="code sev- "><tt><i>406</i>             <span class="n">predicted_example_set</span><span class="p">,</span></tt>
-            </div>
-            <div id="l407"
-               class="code sev- "><tt><i>407</i>             <span class="n">PredictionResultMapper</span><span class="o">.</span><span class="n">PREDICTION_COLUMN_ROLE</span></tt>
-            </div>
-            <div id="l408"
-               class="code sev- "><tt><i>408</i>         <span class="p">)</span></tt>
-            </div>
-            <div id="l409"
-               class="code sev- "><tt><i>409</i> &nbsp;</tt>
-            </div>
-            <div id="l410"
-               class="code sev- "><tt><i>410</i>         <span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span></tt>
-            </div>
-            <div id="l411"
-               class="code sev- "><tt><i>411</i>             <span class="nb">str</span><span class="p">(</span><span class="n">predicted_example_set</span><span class="o">.</span><span class="n">getExample</span><span class="p">(</span></tt>
-            </div>
-            <div id="l412"
-               class="code sev- "><tt><i>412</i>                 <span class="n">i</span><span class="p">)</span><span class="o">.</span><span class="n">getNominalValue</span><span class="p">(</span><span class="n">prediction_col</span><span class="p">))</span></tt>
-            </div>
-            <div id="l413"
-               class="code sev- "><tt><i>413</i>             <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">predicted_example_set</span><span class="o">.</span><span class="n">size</span><span class="p">())</span></tt>
-            </div>
-            <div id="l414"
-               class="code sev- "><tt><i>414</i>         <span class="p">],</span> <span class="n">dtype</span><span class="o">=</span><span class="nb">str</span><span class="p">)</span></tt>
-            </div>
-            <div id="l415"
-               class="code sev- "><tt><i>415</i> &nbsp;</tt>
-            </div>
-            <div id="l416"
-               class="code sev- "><tt><i>416</i>     <span class="nd">@staticmethod</span></tt>
-            </div>
-            <div id="l417"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (91 > 79 characters)</li>
-               
-               </ul><tt><i>417</i>     <span class="k">def</span> <span class="nf">map_to_numerical</span><span class="p">(</span><span class="n">predicted_example_set</span><span class="p">:</span> <span class="n">JObject</span><span class="p">,</span> <span class="n">remap</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">True</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">:</span></tt>
-            </div>
-            <div id="l418"
-               class="code sev- "><tt><i>418</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Maps models predictions to numerical numpy array</span></tt>
-            </div>
-            <div id="l419"
-               class="code sev- "><tt><i>419</i> &nbsp;</tt>
-            </div>
-            <div id="l420"
-               class="code sev- "><tt><i>420</i> <span class="sd">        Args:</span></tt>
-            </div>
-            <div id="l421"
-               class="code sev- "><tt><i>421</i> <span class="sd">            predicted_example_set (_type_): ExampleSet with predictions</span></tt>
-            </div>
-            <div id="l422"
-               class="code sev- "><tt><i>422</i> &nbsp;</tt>
-            </div>
-            <div id="l423"
-               class="code sev- "><tt><i>423</i> <span class="sd">        Returns:</span></tt>
-            </div>
-            <div id="l424"
-               class="code sev- "><tt><i>424</i> <span class="sd">            np.ndarray: numpy array containing predictions</span></tt>
-            </div>
-            <div id="l425"
-               class="code sev- "><tt><i>425</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l426"
-               class="code sev- "><tt><i>426</i>         <span class="n">prediction_col</span><span class="p">:</span> <span class="n">JObject</span> <span class="o">=</span> <span class="n">PredictionResultMapper</span><span class="o">.</span><span class="n">_get_column_by_role</span><span class="p">(</span></tt>
-            </div>
-            <div id="l427"
-               class="code sev- "><tt><i>427</i>             <span class="n">predicted_example_set</span><span class="p">,</span></tt>
-            </div>
-            <div id="l428"
-               class="code sev- "><tt><i>428</i>             <span class="n">PredictionResultMapper</span><span class="o">.</span><span class="n">PREDICTION_COLUMN_ROLE</span></tt>
-            </div>
-            <div id="l429"
-               class="code sev- "><tt><i>429</i>         <span class="p">)</span></tt>
-            </div>
-            <div id="l430"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (85 > 79 characters)</li>
-               
-               </ul><tt><i>430</i>         <span class="n">label_mapping</span> <span class="o">=</span> <span class="n">predicted_example_set</span><span class="o">.</span><span class="n">getAttributes</span><span class="p">()</span><span class="o">.</span><span class="n">getLabel</span><span class="p">()</span><span class="o">.</span><span class="n">getMapping</span><span class="p">()</span></tt>
-            </div>
-            <div id="l431"
-               class="code sev- "><tt><i>431</i>         <span class="k">if</span> <span class="n">remap</span><span class="p">:</span></tt>
-            </div>
-            <div id="l432"
-               class="code sev- "><tt><i>432</i>             <span class="n">predictions</span><span class="p">:</span> <span class="nb">list</span> <span class="o">=</span> <span class="p">[</span></tt>
-            </div>
-            <div id="l433"
-               class="code sev- "><tt><i>433</i>                 <span class="n">label_mapping</span><span class="o">.</span><span class="n">mapIndex</span><span class="p">(</span><span class="nb">int</span><span class="p">(</span></tt>
-            </div>
-            <div id="l434"
-               class="code sev- "><tt><i>434</i>                     <span class="n">predicted_example_set</span><span class="o">.</span><span class="n">getExample</span><span class="p">(</span></tt>
-            </div>
-            <div id="l435"
-               class="code sev- "><tt><i>435</i>                         <span class="n">i</span><span class="p">)</span><span class="o">.</span><span class="n">getValue</span><span class="p">(</span><span class="n">prediction_col</span><span class="p">)</span></tt>
-            </div>
-            <div id="l436"
-               class="code sev- "><tt><i>436</i>                 <span class="p">))</span></tt>
-            </div>
-            <div id="l437"
-               class="code sev- "><tt><i>437</i>                 <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">predicted_example_set</span><span class="o">.</span><span class="n">size</span><span class="p">())</span></tt>
-            </div>
-            <div id="l438"
-               class="code sev- "><tt><i>438</i>             <span class="p">]</span></tt>
-            </div>
-            <div id="l439"
-               class="code sev- "><tt><i>439</i>             <span class="n">predictions</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="nb">map</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">:</span> <span class="nb">float</span><span class="p">(</span><span class="nb">str</span><span class="p">(</span><span class="n">x</span><span class="p">)),</span> <span class="n">predictions</span><span class="p">))</span></tt>
-            </div>
-            <div id="l440"
-               class="code sev- "><tt><i>440</i>             <span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">predictions</span><span class="p">)</span></tt>
-            </div>
-            <div id="l441"
-               class="code sev- "><tt><i>441</i>         <span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span></tt>
-            </div>
-            <div id="l442"
-               class="code sev- "><tt><i>442</i>             <span class="nb">float</span><span class="p">(</span></tt>
-            </div>
-            <div id="l443"
-               class="code sev- "><tt><i>443</i>                 <span class="n">predicted_example_set</span><span class="o">.</span><span class="n">getExample</span><span class="p">(</span><span class="n">i</span><span class="p">)</span><span class="o">.</span><span class="n">getValue</span><span class="p">(</span><span class="n">prediction_col</span><span class="p">)</span></tt>
-            </div>
-            <div id="l444"
-               class="code sev- "><tt><i>444</i>             <span class="p">)</span></tt>
-            </div>
-            <div id="l445"
-               class="code sev- "><tt><i>445</i>             <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">predicted_example_set</span><span class="o">.</span><span class="n">size</span><span class="p">())</span></tt>
-            </div>
-            <div id="l446"
-               class="code sev- "><tt><i>446</i>         <span class="p">])</span></tt>
-            </div>
-            <div id="l447"
-               class="code sev- "><tt><i>447</i> &nbsp;</tt>
-            </div>
-            <div id="l448"
-               class="code sev- "><tt><i>448</i>     <span class="nd">@staticmethod</span></tt>
-            </div>
-            <div id="l449"
-               class="code sev- "><tt><i>449</i>     <span class="k">def</span> <span class="nf">map_survival</span><span class="p">(</span><span class="n">predicted_example_set</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">:</span></tt>
-            </div>
-            <div id="l450"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (95 > 79 characters)</li>
-               
-               </ul><tt><i>450</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Maps survival models predictions to numpy array. Used as alternative to `map` method</span></tt>
-            </div>
-            <div id="l451"
-               class="code sev- "><tt><i>451</i> <span class="sd">        used in survival analysis</span></tt>
-            </div>
-            <div id="l452"
-               class="code sev- "><tt><i>452</i> &nbsp;</tt>
-            </div>
-            <div id="l453"
-               class="code sev- "><tt><i>453</i> <span class="sd">        Args:</span></tt>
-            </div>
-            <div id="l454"
-               class="code sev- "><tt><i>454</i> <span class="sd">            predicted_example_set (_type_): ExampleSet with predictions</span></tt>
-            </div>
-            <div id="l455"
-               class="code sev- "><tt><i>455</i> &nbsp;</tt>
-            </div>
-            <div id="l456"
-               class="code sev- "><tt><i>456</i> <span class="sd">        Returns:</span></tt>
-            </div>
-            <div id="l457"
-               class="code sev- "><tt><i>457</i> <span class="sd">            np.ndarray: numpy array containing predictions</span></tt>
-            </div>
-            <div id="l458"
-               class="code sev- "><tt><i>458</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l459"
-               class="code sev- "><tt><i>459</i>         <span class="n">estimators</span> <span class="o">=</span> <span class="p">[]</span></tt>
-            </div>
-            <div id="l460"
-               class="code sev- "><tt><i>460</i>         <span class="n">attribute</span> <span class="o">=</span> <span class="n">predicted_example_set</span><span class="o">.</span><span class="n">getAttributes</span><span class="p">()</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">&quot;estimator&quot;</span><span class="p">)</span></tt>
-            </div>
-            <div id="l461"
-               class="code sev- "><tt><i>461</i>         <span class="n">example_set_iterator</span> <span class="o">=</span> <span class="n">predicted_example_set</span><span class="o">.</span><span class="n">iterator</span><span class="p">()</span></tt>
-            </div>
-            <div id="l462"
-               class="code sev- "><tt><i>462</i>         <span class="k">while</span> <span class="n">example_set_iterator</span><span class="o">.</span><span class="n">hasNext</span><span class="p">():</span></tt>
-            </div>
-            <div id="l463"
-               class="code sev- "><tt><i>463</i>             <span class="n">example</span> <span class="o">=</span> <span class="n">example_set_iterator</span><span class="o">.</span><span class="n">next</span><span class="p">()</span></tt>
-            </div>
-            <div id="l464"
-               class="code sev- "><tt><i>464</i>             <span class="n">example_estimator</span> <span class="o">=</span> <span class="nb">str</span><span class="p">(</span><span class="n">example</span><span class="o">.</span><span class="n">getValueAsString</span><span class="p">(</span><span class="n">attribute</span><span class="p">))</span></tt>
-            </div>
-            <div id="l465"
-               class="code sev- "><tt><i>465</i>             <span class="n">example_estimator</span> <span class="o">=</span> <span class="n">example_estimator</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="s2">&quot; &quot;</span><span class="p">)</span></tt>
-            </div>
-            <div id="l466"
-               class="code sev- "><tt><i>466</i>             <span class="n">_</span><span class="p">,</span> <span class="n">example_estimator</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">=</span> <span class="n">example_estimator</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">split</span><span class="p">(</span></tt>
-            </div>
-            <div id="l467"
-               class="code sev- "><tt><i>467</i>                 <span class="s2">&quot;:&quot;</span><span class="p">)</span></tt>
-            </div>
-            <div id="l468"
-               class="code sev- "><tt><i>468</i>             <span class="n">times</span> <span class="o">=</span> <span class="p">[</span></tt>
-            </div>
-            <div id="l469"
-               class="code sev- "><tt><i>469</i>                 <span class="nb">float</span><span class="p">(</span><span class="n">example_estimator</span><span class="p">[</span><span class="n">i</span><span class="p">])</span></tt>
-            </div>
-            <div id="l470"
-               class="code sev- "><tt><i>470</i>                 <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">example_estimator</span><span class="p">)</span> <span class="o">-</span> <span class="mi">1</span><span class="p">)</span> <span class="k">if</span> <span class="n">i</span> <span class="o">%</span> <span class="mi">2</span> <span class="o">==</span> <span class="mi">0</span></tt>
-            </div>
-            <div id="l471"
-               class="code sev- "><tt><i>471</i>             <span class="p">]</span></tt>
-            </div>
-            <div id="l472"
-               class="code sev- "><tt><i>472</i>             <span class="n">probabilities</span> <span class="o">=</span> <span class="p">[</span></tt>
-            </div>
-            <div id="l473"
-               class="code sev- "><tt><i>473</i>                 <span class="nb">float</span><span class="p">(</span><span class="n">example_estimator</span><span class="p">[</span><span class="n">i</span><span class="p">])</span></tt>
-            </div>
-            <div id="l474"
-               class="code sev- "><tt><i>474</i>                 <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">example_estimator</span><span class="p">))</span> <span class="k">if</span> <span class="n">i</span> <span class="o">%</span> <span class="mi">2</span> <span class="o">!=</span> <span class="mi">0</span></tt>
-            </div>
-            <div id="l475"
-               class="code sev- "><tt><i>475</i>             <span class="p">]</span></tt>
-            </div>
-            <div id="l476"
-               class="code sev- "><tt><i>476</i>             <span class="n">estimator</span> <span class="o">=</span> <span class="p">{</span><span class="s1">&#39;times&#39;</span><span class="p">:</span> <span class="n">times</span><span class="p">,</span> <span class="s1">&#39;probabilities&#39;</span><span class="p">:</span> <span class="n">probabilities</span><span class="p">}</span></tt>
-            </div>
-            <div id="l477"
-               class="code sev- "><tt><i>477</i>             <span class="n">estimators</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">estimator</span><span class="p">)</span></tt>
-            </div>
-            <div id="l478"
-               class="code sev- "><tt><i>478</i>         <span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">estimators</span><span class="p">)</span></tt>
-            </div>
-            <div id="l479"
-               class="code sev- "><tt><i>479</i> &nbsp;</tt>
-            </div>
-            <div id="l480"
-               class="code sev- "><tt><i>480</i>     <span class="nd">@staticmethod</span></tt>
-            </div>
-            <div id="l481"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (82 > 79 characters)</li>
-               
-               </ul><tt><i>481</i>     <span class="k">def</span> <span class="nf">_get_column_by_role</span><span class="p">(</span><span class="n">predicted_example_set</span><span class="p">:</span> <span class="n">JObject</span><span class="p">,</span> <span class="n">role</span><span class="p">:</span> <span class="nb">str</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">JObject</span><span class="p">:</span></tt>
-            </div>
-            <div id="l482"
-               class="code sev- "><tt><i>482</i>         <span class="k">return</span> <span class="n">predicted_example_set</span><span class="o">.</span><span class="n">getAttributes</span><span class="p">()</span><span class="o">.</span><span class="n">getColumnByRole</span><span class="p">(</span><span class="n">role</span><span class="p">)</span></tt>
-            </div>
-            <div id="l483"
-               class="code sev- "><tt><i>483</i> &nbsp;</tt>
-            </div>
-            <div id="l484"
-               class="code sev- "><tt><i>484</i> &nbsp;</tt>
-            </div>
-            <div id="l485"
-               class="code sev- "><tt><i>485</i> <span class="k">class</span> <span class="nc">ModelSerializer</span><span class="p">:</span></tt>
-            </div>
-            <div id="l486"
-               class="code sev- "><tt><i>486</i> <span class="w">    </span><span class="sd">&quot;&quot;&quot;Class for serializing models</span></tt>
-            </div>
-            <div id="l487"
-               class="code sev- "><tt><i>487</i> <span class="sd">    &quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l488"
-               class="code sev- "><tt><i>488</i> &nbsp;</tt>
-            </div>
-            <div id="l489"
-               class="code sev- "><tt><i>489</i>     <span class="nd">@staticmethod</span></tt>
-            </div>
-            <div id="l490"
-               class="code sev- "><tt><i>490</i>     <span class="k">def</span> <span class="nf">serialize</span><span class="p">(</span><span class="n">real_model</span><span class="p">:</span> <span class="nb">object</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">bytes</span><span class="p">:</span></tt>
-            </div>
-            <div id="l491"
-               class="code sev- "><tt><i>491</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Serialize Java ruleset object.</span></tt>
-            </div>
-            <div id="l492"
-               class="code sev- "><tt><i>492</i> &nbsp;</tt>
-            </div>
-            <div id="l493"
-               class="code sev- "><tt><i>493</i> <span class="sd">        Args:</span></tt>
-            </div>
-            <div id="l494"
-               class="code sev- "><tt><i>494</i> <span class="sd">            real_model (object): Java ruleset object</span></tt>
-            </div>
-            <div id="l495"
-               class="code sev- "><tt><i>495</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l496"
-               class="code sev- "><tt><i>496</i>         <span class="n">in_memory_file</span> <span class="o">=</span> <span class="n">io</span><span class="o">.</span><span class="n">BytesIO</span><span class="p">()</span></tt>
-            </div>
-            <div id="l497"
-               class="code sev- "><tt><i>497</i>         <span class="n">JPickler</span><span class="p">(</span><span class="n">in_memory_file</span><span class="p">)</span><span class="o">.</span><span class="n">dump</span><span class="p">(</span><span class="n">real_model</span><span class="p">)</span></tt>
-            </div>
-            <div id="l498"
-               class="code sev- "><tt><i>498</i>         <span class="n">serialized_bytes</span> <span class="o">=</span> <span class="n">in_memory_file</span><span class="o">.</span><span class="n">getvalue</span><span class="p">()</span></tt>
-            </div>
-            <div id="l499"
-               class="code sev- "><tt><i>499</i>         <span class="n">in_memory_file</span><span class="o">.</span><span class="n">close</span><span class="p">()</span></tt>
-            </div>
-            <div id="l500"
-               class="code sev- "><tt><i>500</i>         <span class="k">return</span> <span class="n">serialized_bytes</span></tt>
-            </div>
-            <div id="l501"
-               class="code sev- "><tt><i>501</i> &nbsp;</tt>
-            </div>
-            <div id="l502"
-               class="code sev- "><tt><i>502</i>     <span class="nd">@staticmethod</span></tt>
-            </div>
-            <div id="l503"
-               class="code sev- "><tt><i>503</i>     <span class="k">def</span> <span class="nf">deserialize</span><span class="p">(</span><span class="n">serialized_bytes</span><span class="p">:</span> <span class="nb">bytes</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">object</span><span class="p">:</span></tt>
-            </div>
-            <div id="l504"
-               class="code sev- "><tt><i>504</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Deserialize Java ruleset object from bytes.</span></tt>
-            </div>
-            <div id="l505"
-               class="code sev- "><tt><i>505</i> &nbsp;</tt>
-            </div>
-            <div id="l506"
-               class="code sev- "><tt><i>506</i> <span class="sd">        Args:</span></tt>
-            </div>
-            <div id="l507"
-               class="code sev- "><tt><i>507</i> <span class="sd">            serialized_bytes (bytes): serialized bytes</span></tt>
-            </div>
-            <div id="l508"
-               class="code sev- "><tt><i>508</i> &nbsp;</tt>
-            </div>
-            <div id="l509"
-               class="code sev- "><tt><i>509</i> <span class="sd">        Returns:</span></tt>
-            </div>
-            <div id="l510"
-               class="code sev- "><tt><i>510</i> <span class="sd">            object: deserialized Java ruleset object</span></tt>
-            </div>
-            <div id="l511"
-               class="code sev- "><tt><i>511</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l512"
-               class="code sev- "><tt><i>512</i>         <span class="k">if</span> <span class="ow">not</span> <span class="n">RuleKit</span><span class="o">.</span><span class="n">initialized</span><span class="p">:</span></tt>
-            </div>
-            <div id="l513"
-               class="code sev- "><tt><i>513</i>             <span class="n">RuleKit</span><span class="o">.</span><span class="n">init</span><span class="p">()</span></tt>
-            </div>
-            <div id="l514"
-               class="code sev- "><tt><i>514</i>         <span class="n">in_memory_file</span> <span class="o">=</span> <span class="n">io</span><span class="o">.</span><span class="n">BytesIO</span><span class="p">(</span><span class="n">serialized_bytes</span><span class="p">)</span></tt>
-            </div>
-            <div id="l515"
-               class="code sev- "><tt><i>515</i>         <span class="n">model</span> <span class="o">=</span> <span class="n">JUnpickler</span><span class="p">(</span><span class="n">in_memory_file</span><span class="p">)</span><span class="o">.</span><span class="n">load</span><span class="p">()</span></tt>
-            </div>
-            <div id="l516"
-               class="code sev- "><tt><i>516</i>         <span class="n">in_memory_file</span><span class="o">.</span><span class="n">close</span><span class="p">()</span></tt>
-            </div>
-            <div id="l517"
-               class="code sev- "><tt><i>517</i>         <span class="k">return</span> <span class="n">model</span></tt>
-            </div>
-            
-         </div>
-      </div>
-   </body>
-</html>
\ No newline at end of file
diff --git a/docs/reports/flake8/rulekit._operator.report.html b/docs/reports/flake8/rulekit._operator.report.html
deleted file mode 100644
index 9c3db6c..0000000
--- a/docs/reports/flake8/rulekit._operator.report.html
+++ /dev/null
@@ -1,186 +0,0 @@
-<!DOCTYPE html>
-<html>
-   <head>
-      <title>flake8 violations: rulekit\_operator.py</title>
-      <meta http-equiv="Content-Type" value="text/html; charset=UTF-8">
-      <link rel="stylesheet" href="styles.css">
-<script>
-function bindHandler(link) {
-   var code = link.getAttribute('data-code');
-   var key = location.pathname + '#' + code;
-
-   var ul = link.parentNode.querySelector('.details');
-   if (sessionStorage[key] != 'open') {
-      ul.style.display = 'none';
-   }
-   link.addEventListener('click', function (event) {
-      if (!ul.style.display || ul.style.display == 'none') {
-         ul.style.display = 'block';
-         sessionStorage[key] = 'open';
-      } else {
-         ul.style.display = 'none';
-         sessionStorage[key] = 'closed';
-      }
-   });
-}
-
-window.addEventListener('DOMContentLoaded', function () {
-   var links = document.querySelectorAll('#index > li > a');
-   for (var i = 0; i < links.length; i++) {
-      bindHandler(links[i]);
-   }
-});
-</script>
-   </head>
-   <body>
-      <div id="masthead" class="sev-2"></div>
-      <div id="page">
-         <p id="srclink">
-            <a title="View full annotated source"
-               href="rulekit._operator.source.html">
-               <img src="file.svg" alt="&#x2261;">
-            </a></p>
-         <h1>
-            <a href="index.html">
-               <img src="back.svg" alt="&#x2B05;">
-               rulekit\_operator.py
-            </a>
-         </h1>
-
-         <ul id="index">
-         
-         <li>
-            <a data-code="E501">
-               <span class="count sev-2">
-                  14
-               </span>
-               <strong>E501:</strong> line too long (89 > 79 characters)
-               
-                  (and 9 similar)
-               
-            </a>
-            <ul class="details">
-            <li>
-               
-               <p>Line too long (89 > 79 characters):</p>
-               
-               <a href="rulekit._operator.source.html#l57">
-                  <tt><i>57</i>         <span class="n">contrast_attribute_instance</span> <span class="o">=</span> <span class="n">example_set</span><span class="o">.</span><span class="n">getAttributes</span><span class="p">()</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">contrast_attribute</span><span class="p">)</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (96 > 79 characters):</p>
-               
-               <a href="rulekit._operator.source.html#l83">
-                  <tt><i>83</i>     <span class="k">def</span> <span class="nf">predict</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">:</span> <span class="n">Data</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">:</span>  <span class="c1"># pylint: disable=missing-function-docstring</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (93 > 79 characters):</p>
-               
-               <a href="rulekit._operator.source.html#l88">
-                  <tt><i>88</i>         <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">model</span><span class="o">.</span><span class="n">_java_object</span><span class="o">.</span><span class="n">apply</span><span class="p">(</span><span class="n">example_set</span><span class="p">)</span>  <span class="c1"># pylint: disable=protected-access</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (97 > 79 characters):</p>
-               
-               <a href="rulekit._operator.source.html#l90">
-                  <tt><i>90</i>     <span class="k">def</span> <span class="nf">get_params</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">deep</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">True</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">Any</span><span class="p">]:</span>  <span class="c1"># pylint: disable=unused-argument</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (84 > 79 characters):</p>
-               
-               <a href="rulekit._operator.source.html#l105">
-                  <tt><i>105</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Set models hyperparameters. Parameters are the same as in constructor.&quot;&quot;&quot;</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (82 > 79 characters):</p>
-               
-               <a href="rulekit._operator.source.html#l107">
-                  <tt><i>107</i>         <span class="n">params</span><span class="p">:</span> <span class="n">BaseModel</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">__params_class__</span><span class="p">(</span>  <span class="c1"># pylint: disable=not-callable</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (99 > 79 characters):</p>
-               
-               <a href="rulekit._operator.source.html#l140">
-                  <tt><i>140</i> <span class="sd">            Each row of the matrix represent single example from dataset and every column represent</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (93 > 79 characters):</p>
-               
-               <a href="rulekit._operator.source.html#l141">
-                  <tt><i>141</i> <span class="sd">            on rule from rule set. Value 1 in the matrix cell means that rule covered certain</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (81 > 79 characters):</p>
-               
-               <a href="rulekit._operator.source.html#l239">
-                  <tt><i>239</i>         <span class="n">expert_preferred_conditions</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">list</span><span class="p">[</span><span class="n">Union</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">BaseRule</span><span class="p">]]]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (80 > 79 characters):</p>
-               
-               <a href="rulekit._operator.source.html#l240">
-                  <tt><i>240</i>         <span class="n">expert_forbidden_conditions</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">list</span><span class="p">[</span><span class="n">Union</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">BaseRule</span><span class="p">]]]</span> <span class="o">=</span> <span class="kc">None</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (85 > 79 characters):</p>
-               
-               <a href="rulekit._operator.source.html#l250">
-                  <tt><i>250</i>         <span class="n">configurator</span><span class="o">.</span><span class="n">_configure_simple_parameter</span><span class="p">(</span>  <span class="c1"># pylint: disable=protected-access</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (85 > 79 characters):</p>
-               
-               <a href="rulekit._operator.source.html#l252">
-                  <tt><i>252</i>         <span class="n">configurator</span><span class="o">.</span><span class="n">_configure_expert_parameter</span><span class="p">(</span>  <span class="c1"># pylint: disable=protected-access</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (85 > 79 characters):</p>
-               
-               <a href="rulekit._operator.source.html#l256">
-                  <tt><i>256</i>         <span class="n">configurator</span><span class="o">.</span><span class="n">_configure_expert_parameter</span><span class="p">(</span>  <span class="c1"># pylint: disable=protected-access</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (85 > 79 characters):</p>
-               
-               <a href="rulekit._operator.source.html#l260">
-                  <tt><i>260</i>         <span class="n">configurator</span><span class="o">.</span><span class="n">_configure_expert_parameter</span><span class="p">(</span>  <span class="c1"># pylint: disable=protected-access</span></tt>
-               </a>
-            </li>
-            </ul>
-         </li>
-         
-         <li>
-            <a data-code="E713">
-               <span class="count sev-2">
-                  1
-               </span>
-               <strong>E713:</strong> test for membership should be 'not in'
-               
-            </a>
-            <ul class="details">
-            <li>
-               
-               <a href="rulekit._operator.source.html#l154">
-                  <tt><i>154</i>                 <span class="mi">0</span> <span class="k">if</span> <span class="n">item</span> <span class="ow">is</span> <span class="kc">None</span> <span class="ow">or</span> <span class="ow">not</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">item</span> <span class="k">else</span> <span class="mi">1</span></tt>
-               </a>
-            </li>
-            </ul>
-         </li>
-         
-         </ul>
-      </div>
-   </body>
-</html>
\ No newline at end of file
diff --git a/docs/reports/flake8/rulekit._operator.source.html b/docs/reports/flake8/rulekit._operator.source.html
deleted file mode 100644
index bc4a4fa..0000000
--- a/docs/reports/flake8/rulekit._operator.source.html
+++ /dev/null
@@ -1,983 +0,0 @@
-<!DOCTYPE html>
-<html>
-   <head>
-      <title>rulekit\_operator.py - flake8 annotated source</title>
-      <meta http-equiv="Content-Type" value="text/html; charset=UTF-8">
-      <link rel="stylesheet" href="styles.css">
-   </head>
-   <body>
-      <div id="masthead" class="sev-2"></div>
-      <div id="page">
-         <h1>
-            <a href="rulekit._operator.report.html">
-               <img src="back.svg" alt="&#x2B05;">
-               rulekit\_operator.py source
-            </a>
-         </h1>
-
-         <div id="doc">
-            <div id="l1"
-               class="code sev- "><tt><i>1</i> <span class="sd">&quot;&quot;&quot;Contains base classes for rule induction operators</span></tt>
-            </div>
-            <div id="l2"
-               class="code sev- "><tt><i>2</i> <span class="sd">&quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l3"
-               class="code sev- "><tt><i>3</i> <span class="kn">from</span> <span class="nn">__future__</span> <span class="kn">import</span> <span class="n">annotations</span></tt>
-            </div>
-            <div id="l4"
-               class="code sev- "><tt><i>4</i> &nbsp;</tt>
-            </div>
-            <div id="l5"
-               class="code sev- "><tt><i>5</i> <span class="kn">from</span> <span class="nn">abc</span> <span class="kn">import</span> <span class="n">ABC</span></tt>
-            </div>
-            <div id="l6"
-               class="code sev- "><tt><i>6</i> <span class="kn">from</span> <span class="nn">abc</span> <span class="kn">import</span> <span class="n">abstractmethod</span></tt>
-            </div>
-            <div id="l7"
-               class="code sev- "><tt><i>7</i> <span class="kn">from</span> <span class="nn">typing</span> <span class="kn">import</span> <span class="n">Any</span></tt>
-            </div>
-            <div id="l8"
-               class="code sev- "><tt><i>8</i> <span class="kn">from</span> <span class="nn">typing</span> <span class="kn">import</span> <span class="n">Optional</span></tt>
-            </div>
-            <div id="l9"
-               class="code sev- "><tt><i>9</i> <span class="kn">from</span> <span class="nn">typing</span> <span class="kn">import</span> <span class="n">Union</span></tt>
-            </div>
-            <div id="l10"
-               class="code sev- "><tt><i>10</i> &nbsp;</tt>
-            </div>
-            <div id="l11"
-               class="code sev- "><tt><i>11</i> <span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span></tt>
-            </div>
-            <div id="l12"
-               class="code sev- "><tt><i>12</i> <span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span></tt>
-            </div>
-            <div id="l13"
-               class="code sev- "><tt><i>13</i> <span class="kn">from</span> <span class="nn">pydantic</span> <span class="kn">import</span> <span class="n">BaseModel</span></tt>
-            </div>
-            <div id="l14"
-               class="code sev- "><tt><i>14</i> &nbsp;</tt>
-            </div>
-            <div id="l15"
-               class="code sev- "><tt><i>15</i> <span class="kn">from</span> <span class="nn">rulekit._helpers</span> <span class="kn">import</span> <span class="n">ExampleSetFactory</span></tt>
-            </div>
-            <div id="l16"
-               class="code sev- "><tt><i>16</i> <span class="kn">from</span> <span class="nn">rulekit._helpers</span> <span class="kn">import</span> <span class="n">get_rule_generator</span></tt>
-            </div>
-            <div id="l17"
-               class="code sev- "><tt><i>17</i> <span class="kn">from</span> <span class="nn">rulekit._helpers</span> <span class="kn">import</span> <span class="n">ModelSerializer</span></tt>
-            </div>
-            <div id="l18"
-               class="code sev- "><tt><i>18</i> <span class="kn">from</span> <span class="nn">rulekit._helpers</span> <span class="kn">import</span> <span class="n">PredictionResultMapper</span></tt>
-            </div>
-            <div id="l19"
-               class="code sev- "><tt><i>19</i> <span class="kn">from</span> <span class="nn">rulekit._helpers</span> <span class="kn">import</span> <span class="n">RuleGeneratorConfigurator</span></tt>
-            </div>
-            <div id="l20"
-               class="code sev- "><tt><i>20</i> <span class="kn">from</span> <span class="nn">rulekit._problem_types</span> <span class="kn">import</span> <span class="n">ProblemType</span></tt>
-            </div>
-            <div id="l21"
-               class="code sev- "><tt><i>21</i> <span class="kn">from</span> <span class="nn">rulekit.events</span> <span class="kn">import</span> <span class="n">_command_listener_factory</span></tt>
-            </div>
-            <div id="l22"
-               class="code sev- "><tt><i>22</i> <span class="kn">from</span> <span class="nn">rulekit.events</span> <span class="kn">import</span> <span class="n">RuleInductionProgressListener</span></tt>
-            </div>
-            <div id="l23"
-               class="code sev- "><tt><i>23</i> <span class="kn">from</span> <span class="nn">rulekit.main</span> <span class="kn">import</span> <span class="n">RuleKit</span></tt>
-            </div>
-            <div id="l24"
-               class="code sev- "><tt><i>24</i> <span class="kn">from</span> <span class="nn">rulekit.rules</span> <span class="kn">import</span> <span class="n">BaseRule</span></tt>
-            </div>
-            <div id="l25"
-               class="code sev- "><tt><i>25</i> <span class="kn">from</span> <span class="nn">rulekit.rules</span> <span class="kn">import</span> <span class="n">RuleSet</span></tt>
-            </div>
-            <div id="l26"
-               class="code sev- "><tt><i>26</i> &nbsp;</tt>
-            </div>
-            <div id="l27"
-               class="code sev- "><tt><i>27</i> <span class="n">Data</span> <span class="o">=</span> <span class="n">Union</span><span class="p">[</span><span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">,</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">,</span> <span class="nb">list</span><span class="p">]</span></tt>
-            </div>
-            <div id="l28"
-               class="code sev- "><tt><i>28</i> &nbsp;</tt>
-            </div>
-            <div id="l29"
-               class="code sev- "><tt><i>29</i> &nbsp;</tt>
-            </div>
-            <div id="l30"
-               class="code sev- "><tt><i>30</i> <span class="k">class</span> <span class="nc">BaseOperator</span><span class="p">(</span><span class="n">ABC</span><span class="p">):</span></tt>
-            </div>
-            <div id="l31"
-               class="code sev- "><tt><i>31</i> <span class="w">    </span><span class="sd">&quot;&quot;&quot;Base class for rule induction operator</span></tt>
-            </div>
-            <div id="l32"
-               class="code sev- "><tt><i>32</i> <span class="sd">    &quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l33"
-               class="code sev- "><tt><i>33</i> &nbsp;</tt>
-            </div>
-            <div id="l34"
-               class="code sev- "><tt><i>34</i>     <span class="n">__params_class__</span><span class="p">:</span> <span class="nb">type</span> <span class="o">=</span> <span class="kc">None</span></tt>
-            </div>
-            <div id="l35"
-               class="code sev- "><tt><i>35</i> &nbsp;</tt>
-            </div>
-            <div id="l36"
-               class="code sev- "><tt><i>36</i>     <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span></tt>
-            </div>
-            <div id="l37"
-               class="code sev- "><tt><i>37</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_initialize_rulekit</span><span class="p">()</span></tt>
-            </div>
-            <div id="l38"
-               class="code sev- "><tt><i>38</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_params</span> <span class="o">=</span> <span class="kc">None</span></tt>
-            </div>
-            <div id="l39"
-               class="code sev- "><tt><i>39</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_rule_generator</span> <span class="o">=</span> <span class="kc">None</span></tt>
-            </div>
-            <div id="l40"
-               class="code sev- "><tt><i>40</i>         <span class="bp">self</span><span class="o">.</span><span class="n">set_params</span><span class="p">(</span><span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></tt>
-            </div>
-            <div id="l41"
-               class="code sev- "><tt><i>41</i>         <span class="bp">self</span><span class="o">.</span><span class="n">model</span><span class="p">:</span> <span class="n">RuleSet</span><span class="p">[</span><span class="n">BaseRule</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span></tt>
-            </div>
-            <div id="l42"
-               class="code sev- "><tt><i>42</i> &nbsp;</tt>
-            </div>
-            <div id="l43"
-               class="code sev- "><tt><i>43</i>     <span class="k">def</span> <span class="nf">_initialize_rulekit</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span></tt>
-            </div>
-            <div id="l44"
-               class="code sev- "><tt><i>44</i>         <span class="k">if</span> <span class="ow">not</span> <span class="n">RuleKit</span><span class="o">.</span><span class="n">initialized</span><span class="p">:</span></tt>
-            </div>
-            <div id="l45"
-               class="code sev- "><tt><i>45</i>             <span class="n">RuleKit</span><span class="o">.</span><span class="n">init</span><span class="p">()</span></tt>
-            </div>
-            <div id="l46"
-               class="code sev- "><tt><i>46</i> &nbsp;</tt>
-            </div>
-            <div id="l47"
-               class="code sev- "><tt><i>47</i>     <span class="k">def</span> <span class="nf">_map_result</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">predicted_example_set</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">:</span></tt>
-            </div>
-            <div id="l48"
-               class="code sev- "><tt><i>48</i>         <span class="k">return</span> <span class="n">PredictionResultMapper</span><span class="o">.</span><span class="n">map</span><span class="p">(</span><span class="n">predicted_example_set</span><span class="p">)</span></tt>
-            </div>
-            <div id="l49"
-               class="code sev- "><tt><i>49</i> &nbsp;</tt>
-            </div>
-            <div id="l50"
-               class="code sev- "><tt><i>50</i>     <span class="k">def</span> <span class="nf">_validate_contrast_attribute</span><span class="p">(</span></tt>
-            </div>
-            <div id="l51"
-               class="code sev- "><tt><i>51</i>         <span class="bp">self</span><span class="p">,</span></tt>
-            </div>
-            <div id="l52"
-               class="code sev- "><tt><i>52</i>         <span class="n">example_set</span><span class="p">,</span></tt>
-            </div>
-            <div id="l53"
-               class="code sev- "><tt><i>53</i>         <span class="n">contrast_attribute</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">str</span><span class="p">]</span></tt>
-            </div>
-            <div id="l54"
-               class="code sev- "><tt><i>54</i>     <span class="p">)</span> <span class="o">-&gt;</span> <span class="kc">None</span><span class="p">:</span></tt>
-            </div>
-            <div id="l55"
-               class="code sev- "><tt><i>55</i>         <span class="k">if</span> <span class="n">contrast_attribute</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span></tt>
-            </div>
-            <div id="l56"
-               class="code sev- "><tt><i>56</i>             <span class="k">return</span></tt>
-            </div>
-            <div id="l57"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (89 > 79 characters)</li>
-               
-               </ul><tt><i>57</i>         <span class="n">contrast_attribute_instance</span> <span class="o">=</span> <span class="n">example_set</span><span class="o">.</span><span class="n">getAttributes</span><span class="p">()</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">contrast_attribute</span><span class="p">)</span></tt>
-            </div>
-            <div id="l58"
-               class="code sev- "><tt><i>58</i>         <span class="k">if</span> <span class="n">contrast_attribute_instance</span><span class="o">.</span><span class="n">isNumerical</span><span class="p">():</span></tt>
-            </div>
-            <div id="l59"
-               class="code sev- "><tt><i>59</i>             <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span></tt>
-            </div>
-            <div id="l60"
-               class="code sev- "><tt><i>60</i>                 <span class="s1">&#39;Contrast set attributes must be a nominal attribute while &#39;</span> <span class="o">+</span></tt>
-            </div>
-            <div id="l61"
-               class="code sev- "><tt><i>61</i>                 <span class="sa">f</span><span class="s1">&#39;&quot;</span><span class="si">{</span><span class="n">contrast_attribute</span><span class="si">}</span><span class="s1">&quot; is a numerical one.&#39;</span></tt>
-            </div>
-            <div id="l62"
-               class="code sev- "><tt><i>62</i>             <span class="p">)</span></tt>
-            </div>
-            <div id="l63"
-               class="code sev- "><tt><i>63</i> &nbsp;</tt>
-            </div>
-            <div id="l64"
-               class="code sev- "><tt><i>64</i>     <span class="k">def</span> <span class="nf">fit</span><span class="p">(</span>  <span class="c1"># pylint: disable=missing-function-docstring</span></tt>
-            </div>
-            <div id="l65"
-               class="code sev- "><tt><i>65</i>         <span class="bp">self</span><span class="p">,</span></tt>
-            </div>
-            <div id="l66"
-               class="code sev- "><tt><i>66</i>         <span class="n">values</span><span class="p">:</span> <span class="n">Data</span><span class="p">,</span></tt>
-            </div>
-            <div id="l67"
-               class="code sev- "><tt><i>67</i>         <span class="n">labels</span><span class="p">:</span> <span class="n">Data</span><span class="p">,</span></tt>
-            </div>
-            <div id="l68"
-               class="code sev- "><tt><i>68</i>         <span class="n">survival_time_attribute</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span></tt>
-            </div>
-            <div id="l69"
-               class="code sev- "><tt><i>69</i>         <span class="n">contrast_attribute</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span></tt>
-            </div>
-            <div id="l70"
-               class="code sev- "><tt><i>70</i>     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">BaseOperator</span><span class="p">:</span></tt>
-            </div>
-            <div id="l71"
-               class="code sev- "><tt><i>71</i>         <span class="n">example_set</span> <span class="o">=</span> <span class="n">ExampleSetFactory</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_get_problem_type</span><span class="p">())</span><span class="o">.</span><span class="n">make</span><span class="p">(</span></tt>
-            </div>
-            <div id="l72"
-               class="code sev- "><tt><i>72</i>             <span class="n">values</span><span class="p">,</span></tt>
-            </div>
-            <div id="l73"
-               class="code sev- "><tt><i>73</i>             <span class="n">labels</span><span class="p">,</span></tt>
-            </div>
-            <div id="l74"
-               class="code sev- "><tt><i>74</i>             <span class="n">survival_time_attribute</span><span class="o">=</span><span class="n">survival_time_attribute</span><span class="p">,</span></tt>
-            </div>
-            <div id="l75"
-               class="code sev- "><tt><i>75</i>             <span class="n">contrast_attribute</span><span class="o">=</span><span class="n">contrast_attribute</span></tt>
-            </div>
-            <div id="l76"
-               class="code sev- "><tt><i>76</i>         <span class="p">)</span></tt>
-            </div>
-            <div id="l77"
-               class="code sev- "><tt><i>77</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_validate_contrast_attribute</span><span class="p">(</span><span class="n">example_set</span><span class="p">,</span> <span class="n">contrast_attribute</span><span class="p">)</span></tt>
-            </div>
-            <div id="l78"
-               class="code sev- "><tt><i>78</i> &nbsp;</tt>
-            </div>
-            <div id="l79"
-               class="code sev- "><tt><i>79</i>         <span class="n">java_model</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_rule_generator</span><span class="o">.</span><span class="n">learn</span><span class="p">(</span><span class="n">example_set</span><span class="p">)</span></tt>
-            </div>
-            <div id="l80"
-               class="code sev- "><tt><i>80</i>         <span class="bp">self</span><span class="o">.</span><span class="n">model</span> <span class="o">=</span> <span class="n">RuleSet</span><span class="p">[</span><span class="n">BaseRule</span><span class="p">](</span><span class="n">java_model</span><span class="p">)</span></tt>
-            </div>
-            <div id="l81"
-               class="code sev- "><tt><i>81</i>         <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">model</span></tt>
-            </div>
-            <div id="l82"
-               class="code sev- "><tt><i>82</i> &nbsp;</tt>
-            </div>
-            <div id="l83"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (96 > 79 characters)</li>
-               
-               </ul><tt><i>83</i>     <span class="k">def</span> <span class="nf">predict</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">:</span> <span class="n">Data</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">:</span>  <span class="c1"># pylint: disable=missing-function-docstring</span></tt>
-            </div>
-            <div id="l84"
-               class="code sev- "><tt><i>84</i>         <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">model</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span></tt>
-            </div>
-            <div id="l85"
-               class="code sev- "><tt><i>85</i>             <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span></tt>
-            </div>
-            <div id="l86"
-               class="code sev- "><tt><i>86</i>                 <span class="s1">&#39;&quot;fit&quot; method must be called before calling this method&#39;</span><span class="p">)</span></tt>
-            </div>
-            <div id="l87"
-               class="code sev- "><tt><i>87</i>         <span class="n">example_set</span> <span class="o">=</span> <span class="n">ExampleSetFactory</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_get_problem_type</span><span class="p">())</span><span class="o">.</span><span class="n">make</span><span class="p">(</span><span class="n">values</span><span class="p">)</span></tt>
-            </div>
-            <div id="l88"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (93 > 79 characters)</li>
-               
-               </ul><tt><i>88</i>         <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">model</span><span class="o">.</span><span class="n">_java_object</span><span class="o">.</span><span class="n">apply</span><span class="p">(</span><span class="n">example_set</span><span class="p">)</span>  <span class="c1"># pylint: disable=protected-access</span></tt>
-            </div>
-            <div id="l89"
-               class="code sev- "><tt><i>89</i> &nbsp;</tt>
-            </div>
-            <div id="l90"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (97 > 79 characters)</li>
-               
-               </ul><tt><i>90</i>     <span class="k">def</span> <span class="nf">get_params</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">deep</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">True</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">Any</span><span class="p">]:</span>  <span class="c1"># pylint: disable=unused-argument</span></tt>
-            </div>
-            <div id="l91"
-               class="code sev- "><tt><i>91</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l92"
-               class="code sev- "><tt><i>92</i> <span class="sd">        Parameters</span></tt>
-            </div>
-            <div id="l93"
-               class="code sev- "><tt><i>93</i> <span class="sd">        ----------</span></tt>
-            </div>
-            <div id="l94"
-               class="code sev- "><tt><i>94</i> <span class="sd">        deep : :class:`rulekit.operator.Data`</span></tt>
-            </div>
-            <div id="l95"
-               class="code sev- "><tt><i>95</i> <span class="sd">            Parameter for scikit-learn compatibility. Not used.</span></tt>
-            </div>
-            <div id="l96"
-               class="code sev- "><tt><i>96</i> &nbsp;</tt>
-            </div>
-            <div id="l97"
-               class="code sev- "><tt><i>97</i> <span class="sd">        Returns</span></tt>
-            </div>
-            <div id="l98"
-               class="code sev- "><tt><i>98</i> <span class="sd">        -------</span></tt>
-            </div>
-            <div id="l99"
-               class="code sev- "><tt><i>99</i> <span class="sd">        hyperparameters : np.ndarray</span></tt>
-            </div>
-            <div id="l100"
-               class="code sev- "><tt><i>100</i> <span class="sd">            Dictionary containing model hyperparameters.</span></tt>
-            </div>
-            <div id="l101"
-               class="code sev- "><tt><i>101</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l102"
-               class="code sev- "><tt><i>102</i>         <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_params</span></tt>
-            </div>
-            <div id="l103"
-               class="code sev- "><tt><i>103</i> &nbsp;</tt>
-            </div>
-            <div id="l104"
-               class="code sev- "><tt><i>104</i>     <span class="k">def</span> <span class="nf">set_params</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">object</span><span class="p">:</span></tt>
-            </div>
-            <div id="l105"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (84 > 79 characters)</li>
-               
-               </ul><tt><i>105</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Set models hyperparameters. Parameters are the same as in constructor.&quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l106"
-               class="code sev- "><tt><i>106</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_rule_generator</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_get_rule_generator</span><span class="p">()</span></tt>
-            </div>
-            <div id="l107"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (82 > 79 characters)</li>
-               
-               </ul><tt><i>107</i>         <span class="n">params</span><span class="p">:</span> <span class="n">BaseModel</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">__params_class__</span><span class="p">(</span>  <span class="c1"># pylint: disable=not-callable</span></tt>
-            </div>
-            <div id="l108"
-               class="code sev- "><tt><i>108</i>             <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></tt>
-            </div>
-            <div id="l109"
-               class="code sev- "><tt><i>109</i>         <span class="n">params_dict</span><span class="p">:</span> <span class="nb">dict</span> <span class="o">=</span> <span class="n">params</span><span class="o">.</span><span class="n">model_dump</span><span class="p">()</span></tt>
-            </div>
-            <div id="l110"
-               class="code sev- "><tt><i>110</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_params</span> <span class="o">=</span> <span class="p">{</span></tt>
-            </div>
-            <div id="l111"
-               class="code sev- "><tt><i>111</i>             <span class="n">key</span><span class="p">:</span> <span class="n">value</span> <span class="k">for</span> <span class="n">key</span><span class="p">,</span> <span class="n">value</span> <span class="ow">in</span> <span class="n">params_dict</span><span class="o">.</span><span class="n">items</span><span class="p">()</span></tt>
-            </div>
-            <div id="l112"
-               class="code sev- "><tt><i>112</i>             <span class="k">if</span> <span class="n">value</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span></tt>
-            </div>
-            <div id="l113"
-               class="code sev- "><tt><i>113</i>         <span class="p">}</span></tt>
-            </div>
-            <div id="l114"
-               class="code sev- "><tt><i>114</i>         <span class="n">configurator</span> <span class="o">=</span> <span class="n">RuleGeneratorConfigurator</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_rule_generator</span><span class="p">)</span></tt>
-            </div>
-            <div id="l115"
-               class="code sev- "><tt><i>115</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_rule_generator</span> <span class="o">=</span> <span class="n">configurator</span><span class="o">.</span><span class="n">configure</span><span class="p">(</span><span class="o">**</span><span class="n">params_dict</span><span class="p">)</span></tt>
-            </div>
-            <div id="l116"
-               class="code sev- "><tt><i>116</i>         <span class="k">return</span> <span class="bp">self</span></tt>
-            </div>
-            <div id="l117"
-               class="code sev- "><tt><i>117</i> &nbsp;</tt>
-            </div>
-            <div id="l118"
-               class="code sev- "><tt><i>118</i>     <span class="k">def</span> <span class="nf">get_metadata_routing</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="kc">None</span><span class="p">:</span></tt>
-            </div>
-            <div id="l119"
-               class="code sev- "><tt><i>119</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l120"
-               class="code sev- "><tt><i>120</i> <span class="sd">        .. warning:: Scikit-learn metadata routing is not supported yet.</span></tt>
-            </div>
-            <div id="l121"
-               class="code sev- "><tt><i>121</i> &nbsp;</tt>
-            </div>
-            <div id="l122"
-               class="code sev- "><tt><i>122</i> <span class="sd">        Raises:</span></tt>
-            </div>
-            <div id="l123"
-               class="code sev- "><tt><i>123</i> <span class="sd">            NotImplementedError: _description_</span></tt>
-            </div>
-            <div id="l124"
-               class="code sev- "><tt><i>124</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l125"
-               class="code sev- "><tt><i>125</i>         <span class="k">raise</span> <span class="ne">NotImplementedError</span><span class="p">(</span></tt>
-            </div>
-            <div id="l126"
-               class="code sev- "><tt><i>126</i>             <span class="s1">&#39;Scikit-learn metadata routing is not supported yet.&#39;</span></tt>
-            </div>
-            <div id="l127"
-               class="code sev- "><tt><i>127</i>         <span class="p">)</span></tt>
-            </div>
-            <div id="l128"
-               class="code sev- "><tt><i>128</i> &nbsp;</tt>
-            </div>
-            <div id="l129"
-               class="code sev- "><tt><i>129</i>     <span class="k">def</span> <span class="nf">get_coverage_matrix</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">:</span> <span class="n">Data</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">:</span></tt>
-            </div>
-            <div id="l130"
-               class="code sev- "><tt><i>130</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Calculates coverage matrix for ruleset.</span></tt>
-            </div>
-            <div id="l131"
-               class="code sev- "><tt><i>131</i> &nbsp;</tt>
-            </div>
-            <div id="l132"
-               class="code sev- "><tt><i>132</i> <span class="sd">        Parameters</span></tt>
-            </div>
-            <div id="l133"
-               class="code sev- "><tt><i>133</i> <span class="sd">        ----------</span></tt>
-            </div>
-            <div id="l134"
-               class="code sev- "><tt><i>134</i> <span class="sd">        values : :class:`rulekit.operator.Data`</span></tt>
-            </div>
-            <div id="l135"
-               class="code sev- "><tt><i>135</i> <span class="sd">            dataset</span></tt>
-            </div>
-            <div id="l136"
-               class="code sev- "><tt><i>136</i> &nbsp;</tt>
-            </div>
-            <div id="l137"
-               class="code sev- "><tt><i>137</i> <span class="sd">        Returns</span></tt>
-            </div>
-            <div id="l138"
-               class="code sev- "><tt><i>138</i> <span class="sd">        -------</span></tt>
-            </div>
-            <div id="l139"
-               class="code sev- "><tt><i>139</i> <span class="sd">        coverage_matrix : np.ndarray</span></tt>
-            </div>
-            <div id="l140"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (99 > 79 characters)</li>
-               
-               </ul><tt><i>140</i> <span class="sd">            Each row of the matrix represent single example from dataset and every column represent</span></tt>
-            </div>
-            <div id="l141"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (93 > 79 characters)</li>
-               
-               </ul><tt><i>141</i> <span class="sd">            on rule from rule set. Value 1 in the matrix cell means that rule covered certain</span></tt>
-            </div>
-            <div id="l142"
-               class="code sev- "><tt><i>142</i> <span class="sd">             example, value 0 means that it doesn&#39;t.</span></tt>
-            </div>
-            <div id="l143"
-               class="code sev- "><tt><i>143</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l144"
-               class="code sev- "><tt><i>144</i>         <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">model</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span></tt>
-            </div>
-            <div id="l145"
-               class="code sev- "><tt><i>145</i>             <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span></tt>
-            </div>
-            <div id="l146"
-               class="code sev- "><tt><i>146</i>                 <span class="s1">&#39;&quot;fit&quot; method must be called before calling this method&#39;</span><span class="p">)</span></tt>
-            </div>
-            <div id="l147"
-               class="code sev- "><tt><i>147</i>         <span class="n">example_set</span> <span class="o">=</span> <span class="n">ExampleSetFactory</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_get_problem_type</span><span class="p">())</span><span class="o">.</span><span class="n">make</span><span class="p">(</span><span class="n">values</span><span class="p">)</span></tt>
-            </div>
-            <div id="l148"
-               class="code sev- "><tt><i>148</i>         <span class="n">covering_info</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">model</span><span class="o">.</span><span class="n">covering</span><span class="p">(</span><span class="n">example_set</span><span class="p">)</span></tt>
-            </div>
-            <div id="l149"
-               class="code sev- "><tt><i>149</i>         <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">values</span><span class="p">,</span> <span class="p">(</span><span class="n">pd</span><span class="o">.</span><span class="n">Series</span><span class="p">,</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">)):</span></tt>
-            </div>
-            <div id="l150"
-               class="code sev- "><tt><i>150</i>             <span class="n">values</span> <span class="o">=</span> <span class="n">values</span><span class="o">.</span><span class="n">to_numpy</span><span class="p">()</span></tt>
-            </div>
-            <div id="l151"
-               class="code sev- "><tt><i>151</i>         <span class="n">result</span> <span class="o">=</span> <span class="p">[]</span></tt>
-            </div>
-            <div id="l152"
-               class="code sev- "><tt><i>152</i>         <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">values</span><span class="p">)):</span></tt>
-            </div>
-            <div id="l153"
-               class="code sev- "><tt><i>153</i>             <span class="n">row_result</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="nb">int</span><span class="p">]</span> <span class="o">=</span> <span class="p">[</span></tt>
-            </div>
-            <div id="l154"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E713
-                     </span>
-                     Test for membership should be 'not in'</li>
-               
-               </ul><tt><i>154</i>                 <span class="mi">0</span> <span class="k">if</span> <span class="n">item</span> <span class="ow">is</span> <span class="kc">None</span> <span class="ow">or</span> <span class="ow">not</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">item</span> <span class="k">else</span> <span class="mi">1</span></tt>
-            </div>
-            <div id="l155"
-               class="code sev- "><tt><i>155</i>                 <span class="k">for</span> <span class="n">item</span> <span class="ow">in</span> <span class="n">covering_info</span></tt>
-            </div>
-            <div id="l156"
-               class="code sev- "><tt><i>156</i>             <span class="p">]</span></tt>
-            </div>
-            <div id="l157"
-               class="code sev- "><tt><i>157</i>             <span class="n">result</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">row_result</span><span class="p">))</span></tt>
-            </div>
-            <div id="l158"
-               class="code sev- "><tt><i>158</i>         <span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">result</span><span class="p">)</span></tt>
-            </div>
-            <div id="l159"
-               class="code sev- "><tt><i>159</i> &nbsp;</tt>
-            </div>
-            <div id="l160"
-               class="code sev- "><tt><i>160</i>     <span class="k">def</span> <span class="nf">add_event_listener</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">listener</span><span class="p">:</span> <span class="n">RuleInductionProgressListener</span><span class="p">):</span></tt>
-            </div>
-            <div id="l161"
-               class="code sev- "><tt><i>161</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Add event listener object to the operator which allows to monitor</span></tt>
-            </div>
-            <div id="l162"
-               class="code sev- "><tt><i>162</i> <span class="sd">         rule induction progress.</span></tt>
-            </div>
-            <div id="l163"
-               class="code sev- "><tt><i>163</i> &nbsp;</tt>
-            </div>
-            <div id="l164"
-               class="code sev- "><tt><i>164</i> <span class="sd">        Example:</span></tt>
-            </div>
-            <div id="l165"
-               class="code sev- "><tt><i>165</i> <span class="sd">            &gt;&gt;&gt; from rulekit.events import RuleInductionProgressListener</span></tt>
-            </div>
-            <div id="l166"
-               class="code sev- "><tt><i>166</i> <span class="sd">            &gt;&gt;&gt; from rulekit.classification import RuleClassifier</span></tt>
-            </div>
-            <div id="l167"
-               class="code sev- "><tt><i>167</i> <span class="sd">            &gt;&gt;&gt;</span></tt>
-            </div>
-            <div id="l168"
-               class="code sev- "><tt><i>168</i> <span class="sd">            &gt;&gt;&gt; class MyEventListener(RuleInductionProgressListener):</span></tt>
-            </div>
-            <div id="l169"
-               class="code sev- "><tt><i>169</i> <span class="sd">            &gt;&gt;&gt;     def on_new_rule(self, rule):</span></tt>
-            </div>
-            <div id="l170"
-               class="code sev- "><tt><i>170</i> <span class="sd">            &gt;&gt;&gt;         print(&#39;Do something with new rule&#39;, rule)</span></tt>
-            </div>
-            <div id="l171"
-               class="code sev- "><tt><i>171</i> <span class="sd">            &gt;&gt;&gt;</span></tt>
-            </div>
-            <div id="l172"
-               class="code sev- "><tt><i>172</i> <span class="sd">            &gt;&gt;&gt; operator = RuleClassifier()</span></tt>
-            </div>
-            <div id="l173"
-               class="code sev- "><tt><i>173</i> <span class="sd">            &gt;&gt;&gt; operator.add_event_listener(MyEventListener())</span></tt>
-            </div>
-            <div id="l174"
-               class="code sev- "><tt><i>174</i> &nbsp;</tt>
-            </div>
-            <div id="l175"
-               class="code sev- "><tt><i>175</i> <span class="sd">        Args:</span></tt>
-            </div>
-            <div id="l176"
-               class="code sev- "><tt><i>176</i> <span class="sd">            listener (RuleInductionProgressListener): listener object</span></tt>
-            </div>
-            <div id="l177"
-               class="code sev- "><tt><i>177</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l178"
-               class="code sev- "><tt><i>178</i>         <span class="n">command_listener</span> <span class="o">=</span> <span class="n">_command_listener_factory</span><span class="p">(</span><span class="n">listener</span><span class="p">)</span></tt>
-            </div>
-            <div id="l179"
-               class="code sev- "><tt><i>179</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_rule_generator</span><span class="o">.</span><span class="n">addOperatorListener</span><span class="p">(</span><span class="n">command_listener</span><span class="p">)</span></tt>
-            </div>
-            <div id="l180"
-               class="code sev- "><tt><i>180</i> &nbsp;</tt>
-            </div>
-            <div id="l181"
-               class="code sev- "><tt><i>181</i>     <span class="k">def</span> <span class="nf">__getstate__</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">dict</span><span class="p">:</span></tt>
-            </div>
-            <div id="l182"
-               class="code sev- "><tt><i>182</i>         <span class="n">state</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="vm">__dict__</span><span class="o">.</span><span class="n">copy</span><span class="p">()</span></tt>
-            </div>
-            <div id="l183"
-               class="code sev- "><tt><i>183</i>         <span class="n">state</span><span class="o">.</span><span class="n">pop</span><span class="p">(</span><span class="s1">&#39;_rule_generator&#39;</span><span class="p">)</span></tt>
-            </div>
-            <div id="l184"
-               class="code sev- "><tt><i>184</i>         <span class="k">return</span> <span class="p">{</span></tt>
-            </div>
-            <div id="l185"
-               class="code sev- "><tt><i>185</i>             <span class="s1">&#39;_params&#39;</span><span class="p">:</span> <span class="bp">self</span><span class="o">.</span><span class="n">_params</span><span class="p">,</span></tt>
-            </div>
-            <div id="l186"
-               class="code sev- "><tt><i>186</i>             <span class="s1">&#39;model&#39;</span><span class="p">:</span> <span class="n">ModelSerializer</span><span class="o">.</span><span class="n">serialize</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">model</span><span class="p">)</span></tt>
-            </div>
-            <div id="l187"
-               class="code sev- "><tt><i>187</i>         <span class="p">}</span></tt>
-            </div>
-            <div id="l188"
-               class="code sev- "><tt><i>188</i> &nbsp;</tt>
-            </div>
-            <div id="l189"
-               class="code sev- "><tt><i>189</i>     <span class="k">def</span> <span class="nf">__setstate__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">state</span><span class="p">:</span> <span class="nb">dict</span><span class="p">):</span></tt>
-            </div>
-            <div id="l190"
-               class="code sev- "><tt><i>190</i>         <span class="bp">self</span><span class="o">.</span><span class="n">model</span> <span class="o">=</span> <span class="n">ModelSerializer</span><span class="o">.</span><span class="n">deserialize</span><span class="p">(</span><span class="n">state</span><span class="p">[</span><span class="s1">&#39;model&#39;</span><span class="p">])</span></tt>
-            </div>
-            <div id="l191"
-               class="code sev- "><tt><i>191</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_rule_generator</span> <span class="o">=</span> <span class="n">get_rule_generator</span><span class="p">()</span></tt>
-            </div>
-            <div id="l192"
-               class="code sev- "><tt><i>192</i>         <span class="bp">self</span><span class="o">.</span><span class="n">set_params</span><span class="p">(</span><span class="o">**</span><span class="n">state</span><span class="p">[</span><span class="s1">&#39;_params&#39;</span><span class="p">])</span></tt>
-            </div>
-            <div id="l193"
-               class="code sev- "><tt><i>193</i> &nbsp;</tt>
-            </div>
-            <div id="l194"
-               class="code sev- "><tt><i>194</i>     <span class="k">def</span> <span class="nf">_get_rule_generator</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">RuleGeneratorConfigurator</span><span class="p">:</span></tt>
-            </div>
-            <div id="l195"
-               class="code sev- "><tt><i>195</i>         <span class="k">return</span> <span class="n">get_rule_generator</span><span class="p">()</span></tt>
-            </div>
-            <div id="l196"
-               class="code sev- "><tt><i>196</i> &nbsp;</tt>
-            </div>
-            <div id="l197"
-               class="code sev- "><tt><i>197</i>     <span class="nd">@abstractmethod</span></tt>
-            </div>
-            <div id="l198"
-               class="code sev- "><tt><i>198</i>     <span class="k">def</span> <span class="nf">_get_problem_type</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ProblemType</span><span class="p">:</span></tt>
-            </div>
-            <div id="l199"
-               class="code sev- "><tt><i>199</i>         <span class="k">pass</span></tt>
-            </div>
-            <div id="l200"
-               class="code sev- "><tt><i>200</i> &nbsp;</tt>
-            </div>
-            <div id="l201"
-               class="code sev- "><tt><i>201</i> &nbsp;</tt>
-            </div>
-            <div id="l202"
-               class="code sev- "><tt><i>202</i> <span class="k">class</span> <span class="nc">ExpertKnowledgeOperator</span><span class="p">(</span><span class="n">BaseOperator</span><span class="p">,</span> <span class="n">ABC</span><span class="p">):</span></tt>
-            </div>
-            <div id="l203"
-               class="code sev- "><tt><i>203</i> <span class="w">    </span><span class="sd">&quot;&quot;&quot;Base class for expert rule induction operator</span></tt>
-            </div>
-            <div id="l204"
-               class="code sev- "><tt><i>204</i> <span class="sd">    &quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l205"
-               class="code sev- "><tt><i>205</i> &nbsp;</tt>
-            </div>
-            <div id="l206"
-               class="code sev- "><tt><i>206</i>     <span class="k">def</span> <span class="nf">fit</span><span class="p">(</span>  <span class="c1"># pylint: disable=missing-function-docstring,too-many-arguments</span></tt>
-            </div>
-            <div id="l207"
-               class="code sev- "><tt><i>207</i>         <span class="bp">self</span><span class="p">,</span></tt>
-            </div>
-            <div id="l208"
-               class="code sev- "><tt><i>208</i>         <span class="n">values</span><span class="p">:</span> <span class="n">Data</span><span class="p">,</span></tt>
-            </div>
-            <div id="l209"
-               class="code sev- "><tt><i>209</i>         <span class="n">labels</span><span class="p">:</span> <span class="n">Data</span><span class="p">,</span></tt>
-            </div>
-            <div id="l210"
-               class="code sev- "><tt><i>210</i>         <span class="n">survival_time_attribute</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span></tt>
-            </div>
-            <div id="l211"
-               class="code sev- "><tt><i>211</i>         <span class="n">contrast_attribute</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span></tt>
-            </div>
-            <div id="l212"
-               class="code sev- "><tt><i>212</i> &nbsp;</tt>
-            </div>
-            <div id="l213"
-               class="code sev- "><tt><i>213</i>         <span class="n">expert_rules</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="n">Union</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">BaseRule</span><span class="p">]]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span></tt>
-            </div>
-            <div id="l214"
-               class="code sev- "><tt><i>214</i>         <span class="n">expert_preferred_conditions</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="n">Union</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">BaseRule</span><span class="p">]]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span></tt>
-            </div>
-            <div id="l215"
-               class="code sev- "><tt><i>215</i>         <span class="n">expert_forbidden_conditions</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="n">Union</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">BaseRule</span><span class="p">]]</span> <span class="o">=</span> <span class="kc">None</span></tt>
-            </div>
-            <div id="l216"
-               class="code sev- "><tt><i>216</i>     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ExpertKnowledgeOperator</span><span class="p">:</span></tt>
-            </div>
-            <div id="l217"
-               class="code sev- "><tt><i>217</i>         <span class="n">example_set</span> <span class="o">=</span> <span class="n">ExampleSetFactory</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_get_problem_type</span><span class="p">())</span><span class="o">.</span><span class="n">make</span><span class="p">(</span></tt>
-            </div>
-            <div id="l218"
-               class="code sev- "><tt><i>218</i>             <span class="n">values</span><span class="p">,</span></tt>
-            </div>
-            <div id="l219"
-               class="code sev- "><tt><i>219</i>             <span class="n">labels</span><span class="p">,</span></tt>
-            </div>
-            <div id="l220"
-               class="code sev- "><tt><i>220</i>             <span class="n">survival_time_attribute</span><span class="o">=</span><span class="n">survival_time_attribute</span><span class="p">,</span></tt>
-            </div>
-            <div id="l221"
-               class="code sev- "><tt><i>221</i>             <span class="n">contrast_attribute</span><span class="o">=</span><span class="n">contrast_attribute</span></tt>
-            </div>
-            <div id="l222"
-               class="code sev- "><tt><i>222</i>         <span class="p">)</span></tt>
-            </div>
-            <div id="l223"
-               class="code sev- "><tt><i>223</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_validate_contrast_attribute</span><span class="p">(</span><span class="n">example_set</span><span class="p">,</span> <span class="n">contrast_attribute</span><span class="p">)</span></tt>
-            </div>
-            <div id="l224"
-               class="code sev- "><tt><i>224</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_configure_expert_parameters</span><span class="p">(</span></tt>
-            </div>
-            <div id="l225"
-               class="code sev- "><tt><i>225</i>             <span class="n">expert_rules</span><span class="p">,</span></tt>
-            </div>
-            <div id="l226"
-               class="code sev- "><tt><i>226</i>             <span class="n">expert_preferred_conditions</span><span class="p">,</span></tt>
-            </div>
-            <div id="l227"
-               class="code sev- "><tt><i>227</i>             <span class="n">expert_forbidden_conditions</span><span class="p">,</span></tt>
-            </div>
-            <div id="l228"
-               class="code sev- "><tt><i>228</i>         <span class="p">)</span></tt>
-            </div>
-            <div id="l229"
-               class="code sev- "><tt><i>229</i>         <span class="n">java_model</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_rule_generator</span><span class="o">.</span><span class="n">learn</span><span class="p">(</span><span class="n">example_set</span><span class="p">)</span></tt>
-            </div>
-            <div id="l230"
-               class="code sev- "><tt><i>230</i>         <span class="bp">self</span><span class="o">.</span><span class="n">model</span> <span class="o">=</span> <span class="n">RuleSet</span><span class="p">(</span><span class="n">java_model</span><span class="p">)</span></tt>
-            </div>
-            <div id="l231"
-               class="code sev- "><tt><i>231</i>         <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">model</span></tt>
-            </div>
-            <div id="l232"
-               class="code sev- "><tt><i>232</i> &nbsp;</tt>
-            </div>
-            <div id="l233"
-               class="code sev- "><tt><i>233</i>     <span class="k">def</span> <span class="nf">_get_rule_generator</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">RuleGeneratorConfigurator</span><span class="p">:</span></tt>
-            </div>
-            <div id="l234"
-               class="code sev- "><tt><i>234</i>         <span class="k">return</span> <span class="n">get_rule_generator</span><span class="p">(</span><span class="n">expert</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span></tt>
-            </div>
-            <div id="l235"
-               class="code sev- "><tt><i>235</i> &nbsp;</tt>
-            </div>
-            <div id="l236"
-               class="code sev- "><tt><i>236</i>     <span class="k">def</span> <span class="nf">_configure_expert_parameters</span><span class="p">(</span></tt>
-            </div>
-            <div id="l237"
-               class="code sev- "><tt><i>237</i>         <span class="bp">self</span><span class="p">,</span></tt>
-            </div>
-            <div id="l238"
-               class="code sev- "><tt><i>238</i>         <span class="n">expert_rules</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">list</span><span class="p">[</span><span class="n">Union</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">BaseRule</span><span class="p">]]]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span></tt>
-            </div>
-            <div id="l239"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (81 > 79 characters)</li>
-               
-               </ul><tt><i>239</i>         <span class="n">expert_preferred_conditions</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">list</span><span class="p">[</span><span class="n">Union</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">BaseRule</span><span class="p">]]]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span></tt>
-            </div>
-            <div id="l240"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (80 > 79 characters)</li>
-               
-               </ul><tt><i>240</i>         <span class="n">expert_forbidden_conditions</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">list</span><span class="p">[</span><span class="n">Union</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">BaseRule</span><span class="p">]]]</span> <span class="o">=</span> <span class="kc">None</span></tt>
-            </div>
-            <div id="l241"
-               class="code sev- "><tt><i>241</i>     <span class="p">)</span> <span class="o">-&gt;</span> <span class="kc">None</span><span class="p">:</span></tt>
-            </div>
-            <div id="l242"
-               class="code sev- "><tt><i>242</i>         <span class="k">if</span> <span class="n">expert_rules</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span></tt>
-            </div>
-            <div id="l243"
-               class="code sev- "><tt><i>243</i>             <span class="n">expert_rules</span> <span class="o">=</span> <span class="p">[]</span></tt>
-            </div>
-            <div id="l244"
-               class="code sev- "><tt><i>244</i>         <span class="k">if</span> <span class="n">expert_preferred_conditions</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span></tt>
-            </div>
-            <div id="l245"
-               class="code sev- "><tt><i>245</i>             <span class="n">expert_preferred_conditions</span> <span class="o">=</span> <span class="p">[]</span></tt>
-            </div>
-            <div id="l246"
-               class="code sev- "><tt><i>246</i>         <span class="k">if</span> <span class="n">expert_forbidden_conditions</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span></tt>
-            </div>
-            <div id="l247"
-               class="code sev- "><tt><i>247</i>             <span class="n">expert_forbidden_conditions</span> <span class="o">=</span> <span class="p">[]</span></tt>
-            </div>
-            <div id="l248"
-               class="code sev- "><tt><i>248</i> &nbsp;</tt>
-            </div>
-            <div id="l249"
-               class="code sev- "><tt><i>249</i>         <span class="n">configurator</span> <span class="o">=</span> <span class="n">RuleGeneratorConfigurator</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_rule_generator</span><span class="p">)</span></tt>
-            </div>
-            <div id="l250"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (85 > 79 characters)</li>
-               
-               </ul><tt><i>250</i>         <span class="n">configurator</span><span class="o">.</span><span class="n">_configure_simple_parameter</span><span class="p">(</span>  <span class="c1"># pylint: disable=protected-access</span></tt>
-            </div>
-            <div id="l251"
-               class="code sev- "><tt><i>251</i>             <span class="s1">&#39;use_expert&#39;</span><span class="p">,</span> <span class="kc">True</span><span class="p">)</span></tt>
-            </div>
-            <div id="l252"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (85 > 79 characters)</li>
-               
-               </ul><tt><i>252</i>         <span class="n">configurator</span><span class="o">.</span><span class="n">_configure_expert_parameter</span><span class="p">(</span>  <span class="c1"># pylint: disable=protected-access</span></tt>
-            </div>
-            <div id="l253"
-               class="code sev- "><tt><i>253</i>             <span class="s1">&#39;expert_preferred_conditions&#39;</span><span class="p">,</span></tt>
-            </div>
-            <div id="l254"
-               class="code sev- "><tt><i>254</i>             <span class="bp">self</span><span class="o">.</span><span class="n">_sanitize_expert_parameter</span><span class="p">(</span><span class="n">expert_preferred_conditions</span><span class="p">)</span></tt>
-            </div>
-            <div id="l255"
-               class="code sev- "><tt><i>255</i>         <span class="p">)</span></tt>
-            </div>
-            <div id="l256"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (85 > 79 characters)</li>
-               
-               </ul><tt><i>256</i>         <span class="n">configurator</span><span class="o">.</span><span class="n">_configure_expert_parameter</span><span class="p">(</span>  <span class="c1"># pylint: disable=protected-access</span></tt>
-            </div>
-            <div id="l257"
-               class="code sev- "><tt><i>257</i>             <span class="s1">&#39;expert_forbidden_conditions&#39;</span><span class="p">,</span></tt>
-            </div>
-            <div id="l258"
-               class="code sev- "><tt><i>258</i>             <span class="bp">self</span><span class="o">.</span><span class="n">_sanitize_expert_parameter</span><span class="p">(</span><span class="n">expert_forbidden_conditions</span><span class="p">)</span></tt>
-            </div>
-            <div id="l259"
-               class="code sev- "><tt><i>259</i>         <span class="p">)</span></tt>
-            </div>
-            <div id="l260"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (85 > 79 characters)</li>
-               
-               </ul><tt><i>260</i>         <span class="n">configurator</span><span class="o">.</span><span class="n">_configure_expert_parameter</span><span class="p">(</span>  <span class="c1"># pylint: disable=protected-access</span></tt>
-            </div>
-            <div id="l261"
-               class="code sev- "><tt><i>261</i>             <span class="s1">&#39;expert_rules&#39;</span><span class="p">,</span></tt>
-            </div>
-            <div id="l262"
-               class="code sev- "><tt><i>262</i>             <span class="bp">self</span><span class="o">.</span><span class="n">_sanitize_expert_parameter</span><span class="p">(</span><span class="n">expert_rules</span><span class="p">)</span></tt>
-            </div>
-            <div id="l263"
-               class="code sev- "><tt><i>263</i>         <span class="p">)</span></tt>
-            </div>
-            <div id="l264"
-               class="code sev- "><tt><i>264</i> &nbsp;</tt>
-            </div>
-            <div id="l265"
-               class="code sev- "><tt><i>265</i>     <span class="k">def</span> <span class="nf">_sanitize_expert_parameter</span><span class="p">(</span></tt>
-            </div>
-            <div id="l266"
-               class="code sev- "><tt><i>266</i>         <span class="bp">self</span><span class="p">,</span></tt>
-            </div>
-            <div id="l267"
-               class="code sev- "><tt><i>267</i>         <span class="n">expert_parameter</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">list</span><span class="p">[</span><span class="nb">tuple</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="nb">str</span><span class="p">]]]</span></tt>
-            </div>
-            <div id="l268"
-               class="code sev- "><tt><i>268</i>     <span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">list</span><span class="p">[</span><span class="nb">tuple</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="nb">str</span><span class="p">]]:</span></tt>
-            </div>
-            <div id="l269"
-               class="code sev- "><tt><i>269</i>         <span class="k">if</span> <span class="n">expert_parameter</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span></tt>
-            </div>
-            <div id="l270"
-               class="code sev- "><tt><i>270</i>             <span class="k">return</span> <span class="kc">None</span></tt>
-            </div>
-            <div id="l271"
-               class="code sev- "><tt><i>271</i>         <span class="n">sanitized_parameter</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="nb">tuple</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="nb">str</span><span class="p">]]</span> <span class="o">=</span> <span class="p">[]</span></tt>
-            </div>
-            <div id="l272"
-               class="code sev- "><tt><i>272</i>         <span class="k">for</span> <span class="n">item</span> <span class="ow">in</span> <span class="n">expert_parameter</span><span class="p">:</span></tt>
-            </div>
-            <div id="l273"
-               class="code sev- "><tt><i>273</i>             <span class="n">item_id</span><span class="p">,</span> <span class="n">item_value</span> <span class="o">=</span> <span class="n">item</span></tt>
-            </div>
-            <div id="l274"
-               class="code sev- "><tt><i>274</i>             <span class="n">sanitized_parameter</span><span class="o">.</span><span class="n">append</span><span class="p">((</span><span class="n">item_id</span><span class="p">,</span> <span class="n">item_value</span><span class="p">))</span></tt>
-            </div>
-            <div id="l275"
-               class="code sev- "><tt><i>275</i>         <span class="k">return</span> <span class="n">sanitized_parameter</span></tt>
-            </div>
-            
-         </div>
-      </div>
-   </body>
-</html>
\ No newline at end of file
diff --git a/docs/reports/flake8/rulekit.classification.report.html b/docs/reports/flake8/rulekit.classification.report.html
index d0d2615..1e43a1a 100644
--- a/docs/reports/flake8/rulekit.classification.report.html
+++ b/docs/reports/flake8/rulekit.classification.report.html
@@ -52,895 +52,16 @@ <h1>
          <li>
             <a data-code="E501">
                <span class="count sev-2">
-                  126
+                  1
                </span>
-               <strong>E501:</strong> line too long (87 > 79 characters)
-               
-                  (and 20 similar)
+               <strong>E501:</strong> line too long (92 > 88 characters)
                
             </a>
             <ul class="details">
             <li>
                
-               <p>Line too long (87 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l43">
-                  <tt><i>43</i>     <span class="n">control_apriori_precision</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;control_apriori_precision&#39;</span><span class="p">]</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (80 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l45">
-                  <tt><i>45</i>     <span class="n">approximate_bins_count</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;approximate_bins_count&#39;</span><span class="p">]</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (91 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l56">
-                  <tt><i>56</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_ClassificationRulesPerformance</span><span class="p">:</span> <span class="n">JClass</span> <span class="o">=</span> <span class="kc">None</span>  <span class="c1"># pylint: disable=invalid-name</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (95 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l57">
-                  <tt><i>57</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_NegativeVotingConflictsPerformance</span><span class="p">:</span> <span class="n">JClass</span> <span class="o">=</span> <span class="kc">None</span>  <span class="c1"># pylint: disable=invalid-name</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (86 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l67">
-                  <tt><i>67</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_ClassificationRulesPerformance</span> <span class="o">=</span> <span class="n">JClass</span><span class="p">(</span>  <span class="c1"># pylint: disable=invalid-name</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (83 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l68">
-                  <tt><i>68</i>             <span class="s1">&#39;adaa.analytics.rules.logic.performance.ClassificationRulesPerformance&#39;</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (89 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l71">
-                  <tt><i>71</i>     <span class="k">def</span> <span class="nf">_calculate_metric</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">example_set</span><span class="p">:</span> <span class="n">JObject</span><span class="p">,</span> <span class="n">metric_type</span><span class="p">:</span> <span class="n">MetricTypes</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">float</span><span class="p">:</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (92 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l77">
-                  <tt><i>77</i>     <span class="k">def</span> <span class="nf">_calculate_prediction_metrics</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">example_set</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ClassificationPredictionMetrics</span><span class="p">:</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (80 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l96">
-                  <tt><i>96</i>         <span class="n">induction_measure</span><span class="p">:</span> <span class="n">Measures</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;induction_measure&#39;</span><span class="p">],</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (87 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l103">
-                  <tt><i>103</i>         <span class="n">max_uncovered_fraction</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;max_uncovered_fraction&#39;</span><span class="p">],</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (84 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l104">
-                  <tt><i>104</i>         <span class="n">select_best_candidate</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;select_best_candidate&#39;</span><span class="p">],</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (90 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l105">
-                  <tt><i>105</i>         <span class="n">complementary_conditions</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;complementary_conditions&#39;</span><span class="p">],</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (92 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l106">
-                  <tt><i>106</i>         <span class="n">control_apriori_precision</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;control_apriori_precision&#39;</span><span class="p">],</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (84 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l108">
-                  <tt><i>108</i>         <span class="n">approximate_induction</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;approximate_induction&#39;</span><span class="p">],</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (85 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l109">
-                  <tt><i>109</i>         <span class="n">approximate_bins_count</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;approximate_bins_count&#39;</span><span class="p">],</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (91 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l115">
-                  <tt><i>115</i> <span class="sd">            a minimum number (or fraction, if value &lt; 1.0) of previously uncovered examples</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (89 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l116">
-                  <tt><i>116</i> <span class="sd">             to be covered by a new rule (positive examples for classification problems);</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (87 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l118">
-                  <tt><i>118</i> <span class="sd">        induction_measure : :class:`rulekit.params.Measures` = :class:`rulekit.params.\</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (84 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l123">
-                  <tt><i>123</i> <span class="sd">            measure used during pruning. Could be user defined (string), for example</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (93 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l129">
-                  <tt><i>129</i> <span class="sd">            non-negative integer representing maximum number of conditions which can be added</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (96 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l130">
-                  <tt><i>130</i> <span class="sd">            to the rule in the growing phase (use this parameter for large datasets if execution</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (97 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l135">
-                  <tt><i>135</i> <span class="sd">            boolean telling whether missing values should be ignored (by default, a missing value</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (95 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l136">
-                  <tt><i>136</i> <span class="sd">            of given attribute is always cconsidered as not fulfilling the condition build upon</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (95 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l139">
-                  <tt><i>139</i> <span class="sd">            Floating-point number from [0,1] interval representing maximum fraction of examples</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (94 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l142">
-                  <tt><i>142</i> <span class="sd">            Flag determining if best candidate should be selected from growing phase; default:</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (96 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l145">
-                  <tt><i>145</i> <span class="sd">            If enabled, complementary conditions in the form a = !{value} for nominal attributes</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (92 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l148">
-                  <tt><i>148</i> <span class="sd">            When inducing classification rules, verify if candidate precision is higher than</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (92 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l151">
-                  <tt><i>151</i> <span class="sd">            Maximum number of rules to be generated (for classification data sets it applies</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (92 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l154">
-                  <tt><i>154</i> <span class="sd">            Use an approximate induction heuristic which does not check all possible splits;</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (93 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l155">
-                  <tt><i>155</i> <span class="sd">            note: this is an experimental feature and currently works only for classification</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (91 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l158">
-                  <tt><i>158</i> <span class="sd">            maximum number of bins for an attribute evaluated in the approximate induction.</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (96 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l202">
-                  <tt><i>202</i>         <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">label_unique_values</span><span class="p">)</span> <span class="o">&gt;</span> <span class="mi">0</span> <span class="ow">and</span> <span class="nb">isinstance</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">label_unique_values</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="nb">bytes</span><span class="p">):</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (80 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l216">
-                  <tt><i>216</i>                 <span class="p">(</span><span class="nb">isinstance</span><span class="p">(</span><span class="n">labels</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">)</span> <span class="ow">and</span> <span class="n">labels</span><span class="o">.</span><span class="n">dtype</span><span class="o">.</span><span class="n">name</span> <span class="o">==</span> <span class="s1">&#39;bool&#39;</span><span class="p">)</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (100 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l224">
-                  <tt><i>224</i>     <span class="k">def</span> <span class="nf">fit</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">:</span> <span class="n">Data</span><span class="p">,</span> <span class="n">labels</span><span class="p">:</span> <span class="n">Data</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">RuleClassifier</span><span class="p">:</span>  <span class="c1"># pylint: disable=arguments-differ</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (96 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l255">
-                  <tt><i>255</i> <span class="sd">            Optional flag. If set to *True* method will calculate some additional model metrics.</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (94 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l262">
-                  <tt><i>262</i> <span class="sd">            tuple[np.ndarray, :class:`rulekit.classification.ClassificationPredictionMetrics`]</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (93 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l264">
-                  <tt><i>264</i> <span class="sd">        If *return_metrics* flag wasn&#39;t set it will return just prediction, otherwise a tuple</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (90 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l265">
-                  <tt><i>265</i> <span class="sd">        will be returned with first element being prediction and second one being metrics.</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (80 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l270">
-                  <tt><i>270</i>             <span class="n">metrics_values</span><span class="p">:</span> <span class="nb">dict</span> <span class="o">=</span> <span class="n">BaseClassifier</span><span class="o">.</span><span class="n">_calculate_prediction_metrics</span><span class="p">(</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (96 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l288">
-                  <tt><i>288</i> <span class="sd">            Optional flag. If set to *True* method will calculate some additional model metrics.</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (94 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l296">
-                  <tt><i>296</i> <span class="sd">            tuple[np.ndarray, :class:`rulekit.classification.ClassificationPredictionMetrics`]</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (95 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l298">
-                  <tt><i>298</i> <span class="sd">        If *return_metrics* flag wasn&#39;t set it will return just probabilities matrix, otherwise</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (98 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l299">
-                  <tt><i>299</i> <span class="sd">        a tuple will be returned with first element being prediction and second one being metrics.</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (80 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l304">
-                  <tt><i>304</i>             <span class="n">metrics_values</span><span class="p">:</span> <span class="nb">dict</span> <span class="o">=</span> <span class="n">BaseClassifier</span><span class="o">.</span><span class="n">_calculate_prediction_metrics</span><span class="p">(</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (80 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l351">
-                  <tt><i>351</i>         <span class="n">induction_measure</span><span class="p">:</span> <span class="n">Measures</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;induction_measure&#39;</span><span class="p">],</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (87 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l358">
-                  <tt><i>358</i>         <span class="n">max_uncovered_fraction</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;max_uncovered_fraction&#39;</span><span class="p">],</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (84 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l359">
-                  <tt><i>359</i>         <span class="n">select_best_candidate</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;select_best_candidate&#39;</span><span class="p">],</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (90 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l360">
-                  <tt><i>360</i>         <span class="n">complementary_conditions</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;complementary_conditions&#39;</span><span class="p">],</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (92 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l361">
-                  <tt><i>361</i>         <span class="n">control_apriori_precision</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;control_apriori_precision&#39;</span><span class="p">],</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (84 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l363">
-                  <tt><i>363</i>         <span class="n">approximate_induction</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;approximate_induction&#39;</span><span class="p">],</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (85 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l364">
-                  <tt><i>364</i>         <span class="n">approximate_bins_count</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;approximate_bins_count&#39;</span><span class="p">],</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (86 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l366">
-                  <tt><i>366</i>         <span class="n">extend_using_preferred</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;extend_using_preferred&#39;</span><span class="p">],</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (86 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l367">
-                  <tt><i>367</i>         <span class="n">extend_using_automatic</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;extend_using_automatic&#39;</span><span class="p">],</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (86 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l368">
-                  <tt><i>368</i>         <span class="n">induce_using_preferred</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;induce_using_preferred&#39;</span><span class="p">],</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (86 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l369">
-                  <tt><i>369</i>         <span class="n">induce_using_automatic</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;induce_using_automatic&#39;</span><span class="p">],</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (86 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l370">
-                  <tt><i>370</i>         <span class="n">consider_other_classes</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;consider_other_classes&#39;</span><span class="p">],</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (87 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l380">
-                  <tt><i>380</i> <span class="sd">        a minimum number (or fraction, if value &lt; 1.0) of previously uncovered examples</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (84 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l381">
-                  <tt><i>381</i> <span class="sd">        to be covered by a new rule (positive examples for classification problems);</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (84 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l389">
-                  <tt><i>389</i> <span class="sd">            measure used during pruning. Could be user defined (string), for example</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (96 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l395">
-                  <tt><i>395</i> <span class="sd">            non-negative integer representing maximum number of conditions which can be added to</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (98 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l396">
-                  <tt><i>396</i> <span class="sd">            the rule in the growing phase (use this parameter for large datasets if execution time</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (97 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l401">
-                  <tt><i>401</i> <span class="sd">            boolean telling whether missing values should be ignored (by default, a missing value</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (94 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l402">
-                  <tt><i>402</i> <span class="sd">            of given attribute is always considered as not fulfilling the condition build upon</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (95 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l405">
-                  <tt><i>405</i> <span class="sd">            Floating-point number from [0,1] interval representing maximum fraction of examples</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (94 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l408">
-                  <tt><i>408</i> <span class="sd">            Flag determining if best candidate should be selected from growing phase; default:</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (96 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l411">
-                  <tt><i>411</i> <span class="sd">            If enabled, complementary conditions in the form a = !{value} for nominal attributes</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (92 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l414">
-                  <tt><i>414</i> <span class="sd">            When inducing classification rules, verify if candidate precision is higher than</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (92 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l417">
-                  <tt><i>417</i> <span class="sd">            Maximum number of rules to be generated (for classification data sets it applies</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (92 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l420">
-                  <tt><i>420</i> <span class="sd">            Use an approximate induction heuristic which does not check all possible splits;</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (93 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l421">
-                  <tt><i>421</i> <span class="sd">            note: this is an experimental feature and currently works only for classification</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (91 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l424">
-                  <tt><i>424</i> <span class="sd">            maximum number of bins for an attribute evaluated in the approximate induction.</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (95 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l427">
-                  <tt><i>427</i> <span class="sd">            boolean indicating whether initial rules should be extended with a use of preferred</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (95 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l430">
-                  <tt><i>430</i> <span class="sd">            boolean indicating whether initial rules should be extended with a use of automatic</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (90 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l433">
-                  <tt><i>433</i> <span class="sd">            boolean indicating whether new rules should be induced with a use of preferred</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (90 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l436">
-                  <tt><i>436</i> <span class="sd">            boolean indicating whether new rules should be induced with a use of automatic</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (94 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l439">
-                  <tt><i>439</i> <span class="sd">            boolean indicating whether automatic induction should be performed for classes for</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (97 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l440">
-                  <tt><i>440</i> <span class="sd">              which no user&#39;s knowledge has been defined (classification only); default is False.</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (80 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l442">
-                  <tt><i>442</i> <span class="sd">            maximum number of preferred conditions per rule; default: unlimited,</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (80 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l444">
-                  <tt><i>444</i> <span class="sd">            maximum number of preferred attributes per rule; default: unlimited.</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (98 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l509">
-                  <tt><i>509</i> <span class="sd">            set of initial rules, either passed as a list of strings representing rules or as list</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (92 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l510">
-                  <tt><i>510</i> <span class="sd">            of tuples where first element is name of the rule and second one is rule string.</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (94 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l512">
-                  <tt><i>512</i> <span class="sd">            multiset of preferred conditions (used also for specifying preferred attributes by</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (97 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l513">
-                  <tt><i>513</i> <span class="sd">            using special value Any). Either passed as a list of strings representing rules or as</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (97 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l514">
-                  <tt><i>514</i> <span class="sd">            list of tuples where first element is name of the rule and second one is rule string.</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (95 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l516">
-                  <tt><i>516</i> <span class="sd">            set of forbidden conditions (used also for specifying forbidden attributes by using</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (97 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l517">
-                  <tt><i>517</i> <span class="sd">             special valye Any). Either passed as a list of strings representing rules or as list</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (92 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l518">
-                  <tt><i>518</i> <span class="sd">            of tuples where first element is name of the rule and second one is rule string.</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (80 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l577">
-                  <tt><i>577</i>         <span class="n">induction_measure</span><span class="p">:</span> <span class="n">Measures</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;induction_measure&#39;</span><span class="p">],</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (87 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l584">
-                  <tt><i>584</i>         <span class="n">max_uncovered_fraction</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;max_uncovered_fraction&#39;</span><span class="p">],</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (84 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l585">
-                  <tt><i>585</i>         <span class="n">select_best_candidate</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;select_best_candidate&#39;</span><span class="p">],</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (90 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l586">
-                  <tt><i>586</i>         <span class="n">complementary_conditions</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;complementary_conditions&#39;</span><span class="p">],</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (92 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l587">
-                  <tt><i>587</i>         <span class="n">control_apriori_precision</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;control_apriori_precision&#39;</span><span class="p">],</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (84 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l589">
-                  <tt><i>589</i>         <span class="n">approximate_induction</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;approximate_induction&#39;</span><span class="p">],</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (85 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l590">
-                  <tt><i>590</i>         <span class="n">approximate_bins_count</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;approximate_bins_count&#39;</span><span class="p">],</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (99 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l596">
-                  <tt><i>596</i> <span class="sd">            a minimum positive support of a contrast set (p/P). When multiple values are specified,</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (97 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l597">
-                  <tt><i>597</i> <span class="sd">            a metainduction is performed; Default and recommended sequence is: 0.8, 0.5, 0.2, 0.1</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (84 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l599">
-                  <tt><i>599</i> <span class="sd">            a maximum ratio of negative to positive supports (nP/pN); Default is 0.5</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (97 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l601">
-                  <tt><i>601</i> <span class="sd">            a maximum number of sequential covering passes for a single minsupp-all; Default is 5</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (85 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l605">
-                  <tt><i>605</i> <span class="sd">            the value of p_new / P at which penalty reward saturates; Default is 0.2.</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (91 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l607">
-                  <tt><i>607</i> <span class="sd">            a minimum number (or fraction, if value &lt; 1.0) of previously uncovered examples</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (101 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l608">
-                  <tt><i>608</i> <span class="sd">             to be covered by a new rule (positive examples for classification problems); default: 5,</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (84 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l614">
-                  <tt><i>614</i> <span class="sd">            measure used during pruning. Could be user defined (string), for example</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (96 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l620">
-                  <tt><i>620</i> <span class="sd">            non-negative integer representing maximum number of conditions which can be added to</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (98 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l621">
-                  <tt><i>621</i> <span class="sd">            the rule in the growing phase (use this parameter for large datasets if execution time</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (97 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l626">
-                  <tt><i>626</i> <span class="sd">            boolean telling whether missing values should be ignored (by default, a missing value</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (94 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l627">
-                  <tt><i>627</i> <span class="sd">            of given attribute is always considered as not fulfilling the condition build upon</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (95 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l630">
-                  <tt><i>630</i> <span class="sd">            Floating-point number from [0,1] interval representing maximum fraction of examples</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (85 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l633">
-                  <tt><i>633</i> <span class="sd">            Flag determining if best candidate should be selected from growing phase;</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (96 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l636">
-                  <tt><i>636</i> <span class="sd">            If enabled, complementary conditions in the form a = !{value} for nominal attributes</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (92 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l639">
-                  <tt><i>639</i> <span class="sd">            When inducing classification rules, verify if candidate precision is higher than</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (92 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l642">
-                  <tt><i>642</i> <span class="sd">            Maximum number of rules to be generated (for classification data sets it applies</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (92 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l645">
-                  <tt><i>645</i> <span class="sd">            Use an approximate induction heuristic which does not check all possible splits;</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (93 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l646">
-                  <tt><i>646</i> <span class="sd">            note: this is an experimental feature and currently works only for classification</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (91 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l649">
-                  <tt><i>649</i> <span class="sd">            maximum number of bins for an attribute evaluated in the approximate induction.</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (96 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l694">
-                  <tt><i>694</i>         <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">label_unique_values</span><span class="p">)</span> <span class="o">&gt;</span> <span class="mi">0</span> <span class="ow">and</span> <span class="nb">isinstance</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">label_unique_values</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="nb">bytes</span><span class="p">):</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (136 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l698">
-                  <tt><i>698</i>     <span class="k">def</span> <span class="nf">fit</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">:</span> <span class="n">Data</span><span class="p">,</span> <span class="n">labels</span><span class="p">:</span> <span class="n">Data</span><span class="p">,</span> <span class="n">contrast_attribute</span><span class="p">:</span> <span class="nb">str</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ContrastSetRuleClassifier</span><span class="p">:</span>  <span class="c1"># pylint: disable=arguments-differ</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (84 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l713">
-                  <tt><i>713</i>         <span class="n">RuleClassifier</span><span class="o">.</span><span class="n">_get_unique_label_values</span><span class="p">(</span>  <span class="c1"># pylint: disable=protected-access</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (92 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l716">
-                  <tt><i>716</i>         <span class="n">RuleClassifier</span><span class="o">.</span><span class="n">_prepare_labels</span><span class="p">(</span>  <span class="c1"># pylint: disable=protected-access,protected-access</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (96 > 79 characters):</p>
-               
                <a href="rulekit.classification.source.html#l739">
-                  <tt><i>739</i> <span class="sd">            Optional flag. If set to *True* method will calculate some additional model metrics.</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (118 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l744">
-                  <tt><i>744</i> <span class="sd">        result : Union[np.ndarray, tuple[np.ndarray, :class:`rulekit.classification.ClassificationPredictionMetrics`]]</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (97 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l745">
-                  <tt><i>745</i> <span class="sd">            If *return_metrics* flag wasn&#39;t set it will return just prediction, otherwise a tuple</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (94 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l746">
-                  <tt><i>746</i> <span class="sd">            will be returned with first element being prediction and second one being metrics.</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (96 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l763">
-                  <tt><i>763</i> <span class="sd">            Optional flag. If set to *True* method will calculate some additional model metrics.</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (96 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l770">
-                  <tt><i>770</i> <span class="sd">            tuple[np.ndarray, :class:`rulekit.classification.ClassificationPredictionMetrics`] \</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (97 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l772">
-                  <tt><i>772</i> <span class="sd">        If *return_metrics* flag wasn&#39;t set it will return just probabilities matrix, otherwise \</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (91 > 79 characters):</p>
-               
-               <a href="rulekit.classification.source.html#l773">
-                  <tt><i>773</i> <span class="sd">        a tuple will be returned with first element being prediction and second one being \</span></tt>
+                  <tt><i>739</i>         <span class="n">RuleClassifier</span><span class="o">.</span><span class="n">_prepare_labels</span><span class="p">(</span>  <span class="c1"># pylint: disable=protected-access,protected-access</span></tt>
                </a>
             </li>
             </ul>
diff --git a/docs/reports/flake8/rulekit.classification.source.html b/docs/reports/flake8/rulekit.classification.source.html
index c3a80ad..5b87383 100644
--- a/docs/reports/flake8/rulekit.classification.source.html
+++ b/docs/reports/flake8/rulekit.classification.source.html
@@ -23,3274 +23,2212 @@ <h1>
                class="code sev- "><tt><i>2</i> <span class="sd">&quot;&quot;&quot;</span></tt>
             </div>
             <div id="l3"
-               class="code sev- "><tt><i>3</i> <span class="kn">from</span> <span class="nn">__future__</span> <span class="kn">import</span> <span class="n">annotations</span></tt>
+               class="code sev- "><tt><i>3</i> &nbsp;</tt>
             </div>
             <div id="l4"
-               class="code sev- "><tt><i>4</i> &nbsp;</tt>
+               class="code sev- "><tt><i>4</i> <span class="kn">from</span> <span class="nn">__future__</span> <span class="kn">import</span> <span class="n">annotations</span></tt>
             </div>
             <div id="l5"
-               class="code sev- "><tt><i>5</i> <span class="kn">from</span> <span class="nn">enum</span> <span class="kn">import</span> <span class="n">Enum</span></tt>
+               class="code sev- "><tt><i>5</i> &nbsp;</tt>
             </div>
             <div id="l6"
-               class="code sev- "><tt><i>6</i> <span class="kn">from</span> <span class="nn">numbers</span> <span class="kn">import</span> <span class="n">Number</span></tt>
+               class="code sev- "><tt><i>6</i> <span class="kn">from</span> <span class="nn">enum</span> <span class="kn">import</span> <span class="n">Enum</span></tt>
             </div>
             <div id="l7"
-               class="code sev- "><tt><i>7</i> <span class="kn">from</span> <span class="nn">typing</span> <span class="kn">import</span> <span class="n">Tuple</span></tt>
+               class="code sev- "><tt><i>7</i> <span class="kn">from</span> <span class="nn">numbers</span> <span class="kn">import</span> <span class="n">Number</span></tt>
             </div>
             <div id="l8"
-               class="code sev- "><tt><i>8</i> <span class="kn">from</span> <span class="nn">typing</span> <span class="kn">import</span> <span class="n">TypedDict</span></tt>
+               class="code sev- "><tt><i>8</i> <span class="kn">from</span> <span class="nn">typing</span> <span class="kn">import</span> <span class="n">Tuple</span><span class="p">,</span> <span class="n">TypedDict</span><span class="p">,</span> <span class="n">Union</span></tt>
             </div>
             <div id="l9"
-               class="code sev- "><tt><i>9</i> <span class="kn">from</span> <span class="nn">typing</span> <span class="kn">import</span> <span class="n">Union</span></tt>
+               class="code sev- "><tt><i>9</i> &nbsp;</tt>
             </div>
             <div id="l10"
-               class="code sev- "><tt><i>10</i> &nbsp;</tt>
+               class="code sev- "><tt><i>10</i> <span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span></tt>
             </div>
             <div id="l11"
-               class="code sev- "><tt><i>11</i> <span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span></tt>
+               class="code sev- "><tt><i>11</i> <span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span></tt>
             </div>
             <div id="l12"
-               class="code sev- "><tt><i>12</i> <span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span></tt>
+               class="code sev- "><tt><i>12</i> <span class="kn">from</span> <span class="nn">jpype</span> <span class="kn">import</span> <span class="n">JClass</span><span class="p">,</span> <span class="n">JObject</span></tt>
             </div>
             <div id="l13"
-               class="code sev- "><tt><i>13</i> <span class="kn">from</span> <span class="nn">jpype</span> <span class="kn">import</span> <span class="n">JClass</span></tt>
+               class="code sev- "><tt><i>13</i> <span class="kn">from</span> <span class="nn">sklearn</span> <span class="kn">import</span> <span class="n">metrics</span></tt>
             </div>
             <div id="l14"
-               class="code sev- "><tt><i>14</i> <span class="kn">from</span> <span class="nn">jpype</span> <span class="kn">import</span> <span class="n">JObject</span></tt>
+               class="code sev- "><tt><i>14</i> &nbsp;</tt>
             </div>
             <div id="l15"
-               class="code sev- "><tt><i>15</i> <span class="kn">from</span> <span class="nn">sklearn</span> <span class="kn">import</span> <span class="n">metrics</span></tt>
+               class="code sev- "><tt><i>15</i> <span class="kn">from</span> <span class="nn">rulekit._helpers</span> <span class="kn">import</span> <span class="n">PredictionResultMapper</span></tt>
             </div>
             <div id="l16"
-               class="code sev- "><tt><i>16</i> &nbsp;</tt>
+               class="code sev- "><tt><i>16</i> <span class="kn">from</span> <span class="nn">rulekit._operator</span> <span class="kn">import</span> <span class="n">BaseOperator</span><span class="p">,</span> <span class="n">Data</span><span class="p">,</span> <span class="n">ExpertKnowledgeOperator</span></tt>
             </div>
             <div id="l17"
-               class="code sev- "><tt><i>17</i> <span class="kn">from</span> <span class="nn">rulekit._helpers</span> <span class="kn">import</span> <span class="n">PredictionResultMapper</span></tt>
+               class="code sev- "><tt><i>17</i> <span class="kn">from</span> <span class="nn">rulekit._problem_types</span> <span class="kn">import</span> <span class="n">ProblemType</span></tt>
             </div>
             <div id="l18"
-               class="code sev- "><tt><i>18</i> <span class="kn">from</span> <span class="nn">rulekit._operator</span> <span class="kn">import</span> <span class="n">BaseOperator</span></tt>
+               class="code sev- "><tt><i>18</i> <span class="kn">from</span> <span class="nn">rulekit.params</span> <span class="kn">import</span> <span class="p">(</span><span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">,</span> <span class="n">ContrastSetModelParams</span><span class="p">,</span></tt>
             </div>
             <div id="l19"
-               class="code sev- "><tt><i>19</i> <span class="kn">from</span> <span class="nn">rulekit._operator</span> <span class="kn">import</span> <span class="n">Data</span></tt>
+               class="code sev- "><tt><i>19</i>                             <span class="n">ExpertModelParams</span><span class="p">,</span> <span class="n">Measures</span><span class="p">,</span> <span class="n">ModelsParams</span><span class="p">)</span></tt>
             </div>
             <div id="l20"
-               class="code sev- "><tt><i>20</i> <span class="kn">from</span> <span class="nn">rulekit._operator</span> <span class="kn">import</span> <span class="n">ExpertKnowledgeOperator</span></tt>
+               class="code sev- "><tt><i>20</i> <span class="kn">from</span> <span class="nn">rulekit.rules</span> <span class="kn">import</span> <span class="n">ClassificationRule</span><span class="p">,</span> <span class="n">RuleSet</span></tt>
             </div>
             <div id="l21"
-               class="code sev- "><tt><i>21</i> <span class="kn">from</span> <span class="nn">rulekit._problem_types</span> <span class="kn">import</span> <span class="n">ProblemType</span></tt>
+               class="code sev- "><tt><i>21</i> &nbsp;</tt>
             </div>
             <div id="l22"
-               class="code sev- "><tt><i>22</i> <span class="kn">from</span> <span class="nn">rulekit.params</span> <span class="kn">import</span> <span class="n">ContrastSetModelParams</span></tt>
+               class="code sev- "><tt><i>22</i> &nbsp;</tt>
             </div>
             <div id="l23"
-               class="code sev- "><tt><i>23</i> <span class="kn">from</span> <span class="nn">rulekit.params</span> <span class="kn">import</span> <span class="n">DEFAULT_PARAMS_VALUE</span></tt>
+               class="code sev- "><tt><i>23</i> <span class="k">class</span> <span class="nc">ClassificationPredictionMetrics</span><span class="p">(</span><span class="n">TypedDict</span><span class="p">):</span></tt>
             </div>
             <div id="l24"
-               class="code sev- "><tt><i>24</i> <span class="kn">from</span> <span class="nn">rulekit.params</span> <span class="kn">import</span> <span class="n">ExpertModelParams</span></tt>
+               class="code sev- "><tt><i>24</i> <span class="w">    </span><span class="sd">&quot;&quot;&quot;Stores additional metrics for classification prediction.</span></tt>
             </div>
             <div id="l25"
-               class="code sev- "><tt><i>25</i> <span class="kn">from</span> <span class="nn">rulekit.params</span> <span class="kn">import</span> <span class="n">Measures</span></tt>
+               class="code sev- "><tt><i>25</i> &nbsp;</tt>
             </div>
             <div id="l26"
-               class="code sev- "><tt><i>26</i> <span class="kn">from</span> <span class="nn">rulekit.params</span> <span class="kn">import</span> <span class="n">ModelsParams</span></tt>
+               class="code sev- "><tt><i>26</i> <span class="sd">    Fields:</span></tt>
             </div>
             <div id="l27"
-               class="code sev- "><tt><i>27</i> <span class="kn">from</span> <span class="nn">rulekit.rules</span> <span class="kn">import</span> <span class="n">ClassificationRule</span></tt>
+               class="code sev- "><tt><i>27</i> <span class="sd">        * rules_per_example (float): Average number of rules per example.</span></tt>
             </div>
             <div id="l28"
-               class="code sev- "><tt><i>28</i> <span class="kn">from</span> <span class="nn">rulekit.rules</span> <span class="kn">import</span> <span class="n">RuleSet</span></tt>
+               class="code sev- "><tt><i>28</i> <span class="sd">        * voting_conflicts (_type_): Number of voting conflicts.</span></tt>
             </div>
             <div id="l29"
-               class="code sev- "><tt><i>29</i> &nbsp;</tt>
+               class="code sev- "><tt><i>29</i> <span class="sd">    &quot;&quot;&quot;</span></tt>
             </div>
             <div id="l30"
                class="code sev- "><tt><i>30</i> &nbsp;</tt>
             </div>
             <div id="l31"
-               class="code sev- "><tt><i>31</i> <span class="k">class</span> <span class="nc">ClassificationPredictionMetrics</span><span class="p">(</span><span class="n">TypedDict</span><span class="p">):</span></tt>
+               class="code sev- "><tt><i>31</i>     <span class="n">rules_per_example</span><span class="p">:</span> <span class="nb">float</span></tt>
             </div>
             <div id="l32"
-               class="code sev- "><tt><i>32</i> <span class="w">    </span><span class="sd">&quot;&quot;&quot;Stores additional metrics for classification prediction.</span></tt>
+               class="code sev- "><tt><i>32</i>     <span class="n">voting_conflicts</span><span class="p">:</span> <span class="nb">float</span></tt>
             </div>
             <div id="l33"
                class="code sev- "><tt><i>33</i> &nbsp;</tt>
             </div>
             <div id="l34"
-               class="code sev- "><tt><i>34</i> <span class="sd">    Fields:</span></tt>
+               class="code sev- "><tt><i>34</i> &nbsp;</tt>
             </div>
             <div id="l35"
-               class="code sev- "><tt><i>35</i> <span class="sd">        * rules_per_example (float): Average number of rules per example.</span></tt>
+               class="code sev- "><tt><i>35</i> <span class="k">class</span> <span class="nc">_ClassificationParams</span><span class="p">(</span><span class="n">ModelsParams</span><span class="p">):</span></tt>
             </div>
             <div id="l36"
-               class="code sev- "><tt><i>36</i> <span class="sd">        * voting_conflicts (_type_): Number of voting conflicts.</span></tt>
+               class="code sev- "><tt><i>36</i>     <span class="n">control_apriori_precision</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;control_apriori_precision&quot;</span><span class="p">]</span></tt>
             </div>
             <div id="l37"
-               class="code sev- "><tt><i>37</i> <span class="sd">    &quot;&quot;&quot;</span></tt>
+               class="code sev- "><tt><i>37</i>     <span class="n">approximate_induction</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;approximate_induction&quot;</span><span class="p">]</span></tt>
             </div>
             <div id="l38"
-               class="code sev- "><tt><i>38</i>     <span class="n">rules_per_example</span><span class="p">:</span> <span class="nb">float</span></tt>
+               class="code sev- "><tt><i>38</i>     <span class="n">approximate_bins_count</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;approximate_bins_count&quot;</span><span class="p">]</span></tt>
             </div>
             <div id="l39"
-               class="code sev- "><tt><i>39</i>     <span class="n">voting_conflicts</span><span class="p">:</span> <span class="nb">float</span></tt>
+               class="code sev- "><tt><i>39</i> &nbsp;</tt>
             </div>
             <div id="l40"
                class="code sev- "><tt><i>40</i> &nbsp;</tt>
             </div>
             <div id="l41"
-               class="code sev- "><tt><i>41</i> &nbsp;</tt>
+               class="code sev- "><tt><i>41</i> <span class="k">class</span> <span class="nc">_ClassificationExpertParams</span><span class="p">(</span><span class="n">_ClassificationParams</span><span class="p">,</span> <span class="n">ExpertModelParams</span><span class="p">):</span></tt>
             </div>
             <div id="l42"
-               class="code sev- "><tt><i>42</i> <span class="k">class</span> <span class="nc">_ClassificationParams</span><span class="p">(</span><span class="n">ModelsParams</span><span class="p">):</span></tt>
+               class="code sev- "><tt><i>42</i>     <span class="k">pass</span></tt>
             </div>
             <div id="l43"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (87 > 79 characters)</li>
-               
-               </ul><tt><i>43</i>     <span class="n">control_apriori_precision</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;control_apriori_precision&#39;</span><span class="p">]</span></tt>
+               class="code sev- "><tt><i>43</i> &nbsp;</tt>
             </div>
             <div id="l44"
-               class="code sev- "><tt><i>44</i>     <span class="n">approximate_induction</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;approximate_induction&#39;</span><span class="p">]</span></tt>
+               class="code sev- "><tt><i>44</i> &nbsp;</tt>
             </div>
             <div id="l45"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (80 > 79 characters)</li>
-               
-               </ul><tt><i>45</i>     <span class="n">approximate_bins_count</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;approximate_bins_count&#39;</span><span class="p">]</span></tt>
+               class="code sev- "><tt><i>45</i> <span class="k">class</span> <span class="nc">BaseClassifier</span><span class="p">:</span></tt>
             </div>
             <div id="l46"
-               class="code sev- "><tt><i>46</i> &nbsp;</tt>
+               class="code sev- "><tt><i>46</i> <span class="w">    </span><span class="sd">&quot;&quot;&quot;:meta private:&quot;&quot;&quot;</span></tt>
             </div>
             <div id="l47"
                class="code sev- "><tt><i>47</i> &nbsp;</tt>
             </div>
             <div id="l48"
-               class="code sev- "><tt><i>48</i> <span class="k">class</span> <span class="nc">_ClassificationExpertParams</span><span class="p">(</span><span class="n">_ClassificationParams</span><span class="p">,</span> <span class="n">ExpertModelParams</span><span class="p">):</span></tt>
+               class="code sev- "><tt><i>48</i>     <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span></tt>
             </div>
             <div id="l49"
-               class="code sev- "><tt><i>49</i>     <span class="k">pass</span></tt>
+               class="code sev- "><tt><i>49</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_ClassificationRulesPerformance</span><span class="p">:</span> <span class="n">JClass</span> <span class="o">=</span> <span class="p">(</span></tt>
             </div>
             <div id="l50"
-               class="code sev- "><tt><i>50</i> &nbsp;</tt>
+               class="code sev- "><tt><i>50</i>             <span class="kc">None</span>  <span class="c1"># pylint: disable=invalid-name</span></tt>
             </div>
             <div id="l51"
-               class="code sev- "><tt><i>51</i> &nbsp;</tt>
+               class="code sev- "><tt><i>51</i>         <span class="p">)</span></tt>
             </div>
             <div id="l52"
-               class="code sev- "><tt><i>52</i> <span class="k">class</span> <span class="nc">BaseClassifier</span><span class="p">:</span></tt>
+               class="code sev- "><tt><i>52</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_NegativeVotingConflictsPerformance</span><span class="p">:</span> <span class="n">JClass</span> <span class="o">=</span> <span class="p">(</span></tt>
             </div>
             <div id="l53"
-               class="code sev- "><tt><i>53</i> <span class="w">    </span><span class="sd">&quot;&quot;&quot;:meta private:&quot;&quot;&quot;</span></tt>
+               class="code sev- "><tt><i>53</i>             <span class="kc">None</span>  <span class="c1"># pylint: disable=invalid-name</span></tt>
             </div>
             <div id="l54"
-               class="code sev- "><tt><i>54</i> &nbsp;</tt>
+               class="code sev- "><tt><i>54</i>         <span class="p">)</span></tt>
             </div>
             <div id="l55"
-               class="code sev- "><tt><i>55</i>     <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span></tt>
+               class="code sev- "><tt><i>55</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_init_classification_rule_performance_classes</span><span class="p">()</span></tt>
             </div>
             <div id="l56"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (91 > 79 characters)</li>
-               
-               </ul><tt><i>56</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_ClassificationRulesPerformance</span><span class="p">:</span> <span class="n">JClass</span> <span class="o">=</span> <span class="kc">None</span>  <span class="c1"># pylint: disable=invalid-name</span></tt>
+               class="code sev- "><tt><i>56</i> &nbsp;</tt>
             </div>
             <div id="l57"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (95 > 79 characters)</li>
-               
-               </ul><tt><i>57</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_NegativeVotingConflictsPerformance</span><span class="p">:</span> <span class="n">JClass</span> <span class="o">=</span> <span class="kc">None</span>  <span class="c1"># pylint: disable=invalid-name</span></tt>
+               class="code sev- "><tt><i>57</i>     <span class="k">class</span> <span class="nc">MetricTypes</span><span class="p">(</span><span class="n">Enum</span><span class="p">):</span></tt>
             </div>
             <div id="l58"
-               class="code sev- "><tt><i>58</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_init_classification_rule_performance_classes</span><span class="p">()</span></tt>
+               class="code sev- "><tt><i>58</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;:meta private:&quot;&quot;&quot;</span></tt>
             </div>
             <div id="l59"
                class="code sev- "><tt><i>59</i> &nbsp;</tt>
             </div>
             <div id="l60"
-               class="code sev- "><tt><i>60</i>     <span class="k">class</span> <span class="nc">MetricTypes</span><span class="p">(</span><span class="n">Enum</span><span class="p">):</span></tt>
+               class="code sev- "><tt><i>60</i>         <span class="n">RulesPerExample</span> <span class="o">=</span> <span class="mi">1</span>  <span class="c1"># pylint: disable=invalid-name</span></tt>
             </div>
             <div id="l61"
-               class="code sev- "><tt><i>61</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;:meta private:&quot;&quot;&quot;</span></tt>
+               class="code sev- "><tt><i>61</i>         <span class="n">VotingConflicts</span> <span class="o">=</span> <span class="mi">2</span>  <span class="c1"># pylint: disable=invalid-name</span></tt>
             </div>
             <div id="l62"
-               class="code sev- "><tt><i>62</i>         <span class="n">RulesPerExample</span> <span class="o">=</span> <span class="mi">1</span>  <span class="c1"># pylint: disable=invalid-name</span></tt>
+               class="code sev- "><tt><i>62</i>         <span class="n">NegativeVotingConflicts</span> <span class="o">=</span> <span class="mi">3</span>  <span class="c1"># pylint: disable=invalid-name</span></tt>
             </div>
             <div id="l63"
-               class="code sev- "><tt><i>63</i>         <span class="n">VotingConflicts</span> <span class="o">=</span> <span class="mi">2</span>  <span class="c1"># pylint: disable=invalid-name</span></tt>
+               class="code sev- "><tt><i>63</i> &nbsp;</tt>
             </div>
             <div id="l64"
-               class="code sev- "><tt><i>64</i>         <span class="n">NegativeVotingConflicts</span> <span class="o">=</span> <span class="mi">3</span>  <span class="c1"># pylint: disable=invalid-name</span></tt>
+               class="code sev- "><tt><i>64</i>     <span class="k">def</span> <span class="nf">_init_classification_rule_performance_classes</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span></tt>
             </div>
             <div id="l65"
-               class="code sev- "><tt><i>65</i> &nbsp;</tt>
+               class="code sev- "><tt><i>65</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_ClassificationRulesPerformance</span> <span class="o">=</span> <span class="n">JClass</span><span class="p">(</span>  <span class="c1"># pylint: disable=invalid-name</span></tt>
             </div>
             <div id="l66"
-               class="code sev- "><tt><i>66</i>     <span class="k">def</span> <span class="nf">_init_classification_rule_performance_classes</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span></tt>
+               class="code sev- "><tt><i>66</i>             <span class="s2">&quot;adaa.analytics.rules.logic.performance.ClassificationRulesPerformance&quot;</span></tt>
             </div>
             <div id="l67"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (86 > 79 characters)</li>
-               
-               </ul><tt><i>67</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_ClassificationRulesPerformance</span> <span class="o">=</span> <span class="n">JClass</span><span class="p">(</span>  <span class="c1"># pylint: disable=invalid-name</span></tt>
+               class="code sev- "><tt><i>67</i>         <span class="p">)</span></tt>
             </div>
             <div id="l68"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (83 > 79 characters)</li>
-               
-               </ul><tt><i>68</i>             <span class="s1">&#39;adaa.analytics.rules.logic.performance.ClassificationRulesPerformance&#39;</span></tt>
+               class="code sev- "><tt><i>68</i> &nbsp;</tt>
             </div>
             <div id="l69"
-               class="code sev- "><tt><i>69</i>         <span class="p">)</span></tt>
+               class="code sev- "><tt><i>69</i>     <span class="k">def</span> <span class="nf">_calculate_metric</span><span class="p">(</span></tt>
             </div>
             <div id="l70"
-               class="code sev- "><tt><i>70</i> &nbsp;</tt>
+               class="code sev- "><tt><i>70</i>         <span class="bp">self</span><span class="p">,</span> <span class="n">example_set</span><span class="p">:</span> <span class="n">JObject</span><span class="p">,</span> <span class="n">metric_type</span><span class="p">:</span> <span class="n">MetricTypes</span></tt>
             </div>
             <div id="l71"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (89 > 79 characters)</li>
-               
-               </ul><tt><i>71</i>     <span class="k">def</span> <span class="nf">_calculate_metric</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">example_set</span><span class="p">:</span> <span class="n">JObject</span><span class="p">,</span> <span class="n">metric_type</span><span class="p">:</span> <span class="n">MetricTypes</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">float</span><span class="p">:</span></tt>
+               class="code sev- "><tt><i>71</i>     <span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">float</span><span class="p">:</span></tt>
             </div>
             <div id="l72"
-               class="code sev- "><tt><i>72</i>         <span class="n">metric</span><span class="p">:</span> <span class="n">JObject</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_ClassificationRulesPerformance</span><span class="p">(</span></tt>
+               class="code sev- "><tt><i>72</i>         <span class="n">metric</span><span class="p">:</span> <span class="n">JObject</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_ClassificationRulesPerformance</span><span class="p">(</span><span class="n">metric_type</span><span class="o">.</span><span class="n">value</span><span class="p">)</span></tt>
             </div>
             <div id="l73"
-               class="code sev- "><tt><i>73</i>             <span class="n">metric_type</span><span class="o">.</span><span class="n">value</span><span class="p">)</span></tt>
+               class="code sev- "><tt><i>73</i>         <span class="n">metric_value</span> <span class="o">=</span> <span class="nb">float</span><span class="p">(</span><span class="n">metric</span><span class="o">.</span><span class="n">countExample</span><span class="p">(</span><span class="n">example_set</span><span class="p">)</span><span class="o">.</span><span class="n">getValue</span><span class="p">())</span></tt>
             </div>
             <div id="l74"
-               class="code sev- "><tt><i>74</i>         <span class="n">metric_value</span> <span class="o">=</span> <span class="nb">float</span><span class="p">(</span><span class="n">metric</span><span class="o">.</span><span class="n">countExample</span><span class="p">(</span><span class="n">example_set</span><span class="p">)</span><span class="o">.</span><span class="n">getValue</span><span class="p">())</span></tt>
+               class="code sev- "><tt><i>74</i>         <span class="k">return</span> <span class="n">metric_value</span></tt>
             </div>
             <div id="l75"
-               class="code sev- "><tt><i>75</i>         <span class="k">return</span> <span class="n">metric_value</span></tt>
+               class="code sev- "><tt><i>75</i> &nbsp;</tt>
             </div>
             <div id="l76"
-               class="code sev- "><tt><i>76</i> &nbsp;</tt>
+               class="code sev- "><tt><i>76</i>     <span class="k">def</span> <span class="nf">_calculate_prediction_metrics</span><span class="p">(</span></tt>
             </div>
             <div id="l77"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (92 > 79 characters)</li>
-               
-               </ul><tt><i>77</i>     <span class="k">def</span> <span class="nf">_calculate_prediction_metrics</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">example_set</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ClassificationPredictionMetrics</span><span class="p">:</span></tt>
+               class="code sev- "><tt><i>77</i>         <span class="bp">self</span><span class="p">,</span> <span class="n">example_set</span></tt>
             </div>
             <div id="l78"
-               class="code sev- "><tt><i>78</i>         <span class="k">return</span> <span class="n">ClassificationPredictionMetrics</span><span class="p">(</span></tt>
+               class="code sev- "><tt><i>78</i>     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ClassificationPredictionMetrics</span><span class="p">:</span></tt>
             </div>
             <div id="l79"
-               class="code sev- "><tt><i>79</i>             <span class="n">rules_per_example</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">_calculate_metric</span><span class="p">(</span></tt>
+               class="code sev- "><tt><i>79</i>         <span class="k">return</span> <span class="n">ClassificationPredictionMetrics</span><span class="p">(</span></tt>
             </div>
             <div id="l80"
-               class="code sev- "><tt><i>80</i>                 <span class="n">example_set</span><span class="p">,</span> <span class="n">BaseClassifier</span><span class="o">.</span><span class="n">MetricTypes</span><span class="o">.</span><span class="n">RulesPerExample</span></tt>
+               class="code sev- "><tt><i>80</i>             <span class="n">rules_per_example</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">_calculate_metric</span><span class="p">(</span></tt>
             </div>
             <div id="l81"
-               class="code sev- "><tt><i>81</i>             <span class="p">),</span></tt>
+               class="code sev- "><tt><i>81</i>                 <span class="n">example_set</span><span class="p">,</span> <span class="n">BaseClassifier</span><span class="o">.</span><span class="n">MetricTypes</span><span class="o">.</span><span class="n">RulesPerExample</span></tt>
             </div>
             <div id="l82"
-               class="code sev- "><tt><i>82</i>             <span class="n">voting_conflicts</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">_calculate_metric</span><span class="p">(</span></tt>
+               class="code sev- "><tt><i>82</i>             <span class="p">),</span></tt>
             </div>
             <div id="l83"
-               class="code sev- "><tt><i>83</i>                 <span class="n">example_set</span><span class="p">,</span> <span class="n">BaseClassifier</span><span class="o">.</span><span class="n">MetricTypes</span><span class="o">.</span><span class="n">VotingConflicts</span></tt>
+               class="code sev- "><tt><i>83</i>             <span class="n">voting_conflicts</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">_calculate_metric</span><span class="p">(</span></tt>
             </div>
             <div id="l84"
-               class="code sev- "><tt><i>84</i>             <span class="p">),</span></tt>
+               class="code sev- "><tt><i>84</i>                 <span class="n">example_set</span><span class="p">,</span> <span class="n">BaseClassifier</span><span class="o">.</span><span class="n">MetricTypes</span><span class="o">.</span><span class="n">VotingConflicts</span></tt>
             </div>
             <div id="l85"
-               class="code sev- "><tt><i>85</i>         <span class="p">)</span></tt>
+               class="code sev- "><tt><i>85</i>             <span class="p">),</span></tt>
             </div>
             <div id="l86"
-               class="code sev- "><tt><i>86</i> &nbsp;</tt>
+               class="code sev- "><tt><i>86</i>         <span class="p">)</span></tt>
             </div>
             <div id="l87"
                class="code sev- "><tt><i>87</i> &nbsp;</tt>
             </div>
             <div id="l88"
-               class="code sev- "><tt><i>88</i> <span class="k">class</span> <span class="nc">RuleClassifier</span><span class="p">(</span><span class="n">BaseOperator</span><span class="p">,</span> <span class="n">BaseClassifier</span><span class="p">):</span></tt>
+               class="code sev- "><tt><i>88</i> &nbsp;</tt>
             </div>
             <div id="l89"
-               class="code sev- "><tt><i>89</i> <span class="w">    </span><span class="sd">&quot;&quot;&quot;Classification model.&quot;&quot;&quot;</span></tt>
+               class="code sev- "><tt><i>89</i> <span class="k">class</span> <span class="nc">RuleClassifier</span><span class="p">(</span><span class="n">BaseOperator</span><span class="p">,</span> <span class="n">BaseClassifier</span><span class="p">):</span></tt>
             </div>
             <div id="l90"
-               class="code sev- "><tt><i>90</i> &nbsp;</tt>
+               class="code sev- "><tt><i>90</i> <span class="w">    </span><span class="sd">&quot;&quot;&quot;Classification model.&quot;&quot;&quot;</span></tt>
             </div>
             <div id="l91"
-               class="code sev- "><tt><i>91</i>     <span class="n">__params_class__</span> <span class="o">=</span> <span class="n">_ClassificationParams</span></tt>
+               class="code sev- "><tt><i>91</i> &nbsp;</tt>
             </div>
             <div id="l92"
-               class="code sev- "><tt><i>92</i> &nbsp;</tt>
+               class="code sev- "><tt><i>92</i>     <span class="n">__params_class__</span> <span class="o">=</span> <span class="n">_ClassificationParams</span></tt>
             </div>
             <div id="l93"
-               class="code sev- "><tt><i>93</i>     <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span>  <span class="c1"># pylint: disable=too-many-arguments,too-many-locals</span></tt>
+               class="code sev- "><tt><i>93</i> &nbsp;</tt>
             </div>
             <div id="l94"
-               class="code sev- "><tt><i>94</i>         <span class="bp">self</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>94</i>     <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span>  <span class="c1"># pylint: disable=too-many-arguments,too-many-locals</span></tt>
             </div>
             <div id="l95"
-               class="code sev- "><tt><i>95</i>         <span class="n">minsupp_new</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;minsupp_new&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>95</i>         <span class="bp">self</span><span class="p">,</span></tt>
             </div>
             <div id="l96"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (80 > 79 characters)</li>
-               
-               </ul><tt><i>96</i>         <span class="n">induction_measure</span><span class="p">:</span> <span class="n">Measures</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;induction_measure&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>96</i>         <span class="n">minsupp_new</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;minsupp_new&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l97"
-               class="code sev- "><tt><i>97</i>         <span class="n">pruning_measure</span><span class="p">:</span> <span class="n">Union</span><span class="p">[</span><span class="n">Measures</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>97</i>         <span class="n">induction_measure</span><span class="p">:</span> <span class="n">Measures</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;induction_measure&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l98"
-               class="code sev- "><tt><i>98</i>                                <span class="nb">str</span><span class="p">]</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;pruning_measure&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>98</i>         <span class="n">pruning_measure</span><span class="p">:</span> <span class="n">Union</span><span class="p">[</span><span class="n">Measures</span><span class="p">,</span> <span class="nb">str</span><span class="p">]</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;pruning_measure&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l99"
-               class="code sev- "><tt><i>99</i>         <span class="n">voting_measure</span><span class="p">:</span> <span class="n">Measures</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;voting_measure&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>99</i>         <span class="n">voting_measure</span><span class="p">:</span> <span class="n">Measures</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;voting_measure&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l100"
-               class="code sev- "><tt><i>100</i>         <span class="n">max_growing</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;max_growing&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>100</i>         <span class="n">max_growing</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;max_growing&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l101"
-               class="code sev- "><tt><i>101</i>         <span class="n">enable_pruning</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;enable_pruning&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>101</i>         <span class="n">enable_pruning</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;enable_pruning&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l102"
-               class="code sev- "><tt><i>102</i>         <span class="n">ignore_missing</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;ignore_missing&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>102</i>         <span class="n">ignore_missing</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;ignore_missing&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l103"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (87 > 79 characters)</li>
-               
-               </ul><tt><i>103</i>         <span class="n">max_uncovered_fraction</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;max_uncovered_fraction&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>103</i>         <span class="n">max_uncovered_fraction</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;max_uncovered_fraction&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l104"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (84 > 79 characters)</li>
-               
-               </ul><tt><i>104</i>         <span class="n">select_best_candidate</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;select_best_candidate&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>104</i>         <span class="n">select_best_candidate</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;select_best_candidate&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l105"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (90 > 79 characters)</li>
-               
-               </ul><tt><i>105</i>         <span class="n">complementary_conditions</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;complementary_conditions&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>105</i>         <span class="n">complementary_conditions</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span></tt>
             </div>
             <div id="l106"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (92 > 79 characters)</li>
-               
-               </ul><tt><i>106</i>         <span class="n">control_apriori_precision</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;control_apriori_precision&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>106</i>             <span class="s2">&quot;complementary_conditions&quot;</span></tt>
             </div>
             <div id="l107"
-               class="code sev- "><tt><i>107</i>         <span class="n">max_rule_count</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;max_rule_count&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>107</i>         <span class="p">],</span></tt>
             </div>
             <div id="l108"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (84 > 79 characters)</li>
-               
-               </ul><tt><i>108</i>         <span class="n">approximate_induction</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;approximate_induction&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>108</i>         <span class="n">control_apriori_precision</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span></tt>
             </div>
             <div id="l109"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (85 > 79 characters)</li>
-               
-               </ul><tt><i>109</i>         <span class="n">approximate_bins_count</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;approximate_bins_count&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>109</i>             <span class="s2">&quot;control_apriori_precision&quot;</span></tt>
             </div>
             <div id="l110"
-               class="code sev- "><tt><i>110</i>     <span class="p">):</span></tt>
+               class="code sev- "><tt><i>110</i>         <span class="p">],</span></tt>
             </div>
             <div id="l111"
-               class="code sev- "><tt><i>111</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;</span></tt>
+               class="code sev- "><tt><i>111</i>         <span class="n">max_rule_count</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;max_rule_count&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l112"
-               class="code sev- "><tt><i>112</i> <span class="sd">        Parameters</span></tt>
+               class="code sev- "><tt><i>112</i>         <span class="n">approximate_induction</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;approximate_induction&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l113"
-               class="code sev- "><tt><i>113</i> <span class="sd">        ----------</span></tt>
+               class="code sev- "><tt><i>113</i>         <span class="n">approximate_bins_count</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;approximate_bins_count&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l114"
-               class="code sev- "><tt><i>114</i> <span class="sd">        minsupp_new : float = 5.0</span></tt>
+               class="code sev- "><tt><i>114</i>     <span class="p">):</span></tt>
             </div>
             <div id="l115"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (91 > 79 characters)</li>
-               
-               </ul><tt><i>115</i> <span class="sd">            a minimum number (or fraction, if value &lt; 1.0) of previously uncovered examples</span></tt>
+               class="code sev- "><tt><i>115</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;</span></tt>
             </div>
             <div id="l116"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (89 > 79 characters)</li>
-               
-               </ul><tt><i>116</i> <span class="sd">             to be covered by a new rule (positive examples for classification problems);</span></tt>
+               class="code sev- "><tt><i>116</i> <span class="sd">        Parameters</span></tt>
             </div>
             <div id="l117"
-               class="code sev- "><tt><i>117</i> <span class="sd">             default: 5,</span></tt>
+               class="code sev- "><tt><i>117</i> <span class="sd">        ----------</span></tt>
             </div>
             <div id="l118"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (87 > 79 characters)</li>
-               
-               </ul><tt><i>118</i> <span class="sd">        induction_measure : :class:`rulekit.params.Measures` = :class:`rulekit.params.\</span></tt>
+               class="code sev- "><tt><i>118</i> <span class="sd">        minsupp_new : float = 5.0</span></tt>
             </div>
             <div id="l119"
-               class="code sev- "><tt><i>119</i> <span class="sd">            Measures.Correlation`</span></tt>
+               class="code sev- "><tt><i>119</i> <span class="sd">            a minimum number (or fraction, if value &lt; 1.0) of previously uncovered</span></tt>
             </div>
             <div id="l120"
-               class="code sev- "><tt><i>120</i> <span class="sd">            measure used during induction; default measure is correlation</span></tt>
+               class="code sev- "><tt><i>120</i> <span class="sd">            examples to be covered by a new rule (positive examples for classification</span></tt>
             </div>
             <div id="l121"
-               class="code sev- "><tt><i>121</i> <span class="sd">        pruning_measure : Union[:class:`rulekit.params.Measures`, str] = \</span></tt>
+               class="code sev- "><tt><i>121</i> <span class="sd">            problems); default: 5,</span></tt>
             </div>
             <div id="l122"
-               class="code sev- "><tt><i>122</i> <span class="sd">            :class:`rulekit.params.Measures.Correlation`</span></tt>
+               class="code sev- "><tt><i>122</i> <span class="sd">        induction_measure : :class:`rulekit.params.Measures` = :class:`rulekit.params.\</span></tt>
             </div>
             <div id="l123"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (84 > 79 characters)</li>
-               
-               </ul><tt><i>123</i> <span class="sd">            measure used during pruning. Could be user defined (string), for example</span></tt>
+               class="code sev- "><tt><i>123</i> <span class="sd">            Measures.Correlation`</span></tt>
             </div>
             <div id="l124"
-               class="code sev- "><tt><i>124</i> <span class="sd">             :code:`2 * p / n`; default measure is correlation</span></tt>
+               class="code sev- "><tt><i>124</i> <span class="sd">            measure used during induction; default measure is correlation</span></tt>
             </div>
             <div id="l125"
-               class="code sev- "><tt><i>125</i> <span class="sd">        voting_measure : :class:`rulekit.params.Measures` = \</span></tt>
+               class="code sev- "><tt><i>125</i> <span class="sd">        pruning_measure : Union[:class:`rulekit.params.Measures`, str] = \</span></tt>
             </div>
             <div id="l126"
                class="code sev- "><tt><i>126</i> <span class="sd">            :class:`rulekit.params.Measures.Correlation`</span></tt>
             </div>
             <div id="l127"
-               class="code sev- "><tt><i>127</i> <span class="sd">            measure used during voting; default measure is correlation</span></tt>
+               class="code sev- "><tt><i>127</i> <span class="sd">            measure used during pruning. Could be user defined (string), for example</span></tt>
             </div>
             <div id="l128"
-               class="code sev- "><tt><i>128</i> <span class="sd">        max_growing : int = 0.0</span></tt>
+               class="code sev- "><tt><i>128</i> <span class="sd">             :code:`2 * p / n`; default measure is correlation</span></tt>
             </div>
             <div id="l129"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (93 > 79 characters)</li>
-               
-               </ul><tt><i>129</i> <span class="sd">            non-negative integer representing maximum number of conditions which can be added</span></tt>
+               class="code sev- "><tt><i>129</i> <span class="sd">        voting_measure : :class:`rulekit.params.Measures` = \</span></tt>
             </div>
             <div id="l130"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (96 > 79 characters)</li>
-               
-               </ul><tt><i>130</i> <span class="sd">            to the rule in the growing phase (use this parameter for large datasets if execution</span></tt>
+               class="code sev- "><tt><i>130</i> <span class="sd">            :class:`rulekit.params.Measures.Correlation`</span></tt>
             </div>
             <div id="l131"
-               class="code sev- "><tt><i>131</i> <span class="sd">            time is prohibitive); 0 indicates no limit; default: 0,</span></tt>
+               class="code sev- "><tt><i>131</i> <span class="sd">            measure used during voting; default measure is correlation</span></tt>
             </div>
             <div id="l132"
-               class="code sev- "><tt><i>132</i> <span class="sd">        enable_pruning : bool = True</span></tt>
+               class="code sev- "><tt><i>132</i> <span class="sd">        max_growing : int = 0.0</span></tt>
             </div>
             <div id="l133"
-               class="code sev- "><tt><i>133</i> <span class="sd">            enable or disable pruning, default is True.</span></tt>
+               class="code sev- "><tt><i>133</i> <span class="sd">            non-negative integer representing maximum number of conditions which can be</span></tt>
             </div>
             <div id="l134"
-               class="code sev- "><tt><i>134</i> <span class="sd">        ignore_missing : bool = False</span></tt>
+               class="code sev- "><tt><i>134</i> <span class="sd">            added to the rule in the growing phase (use this parameter for large</span></tt>
             </div>
             <div id="l135"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (97 > 79 characters)</li>
-               
-               </ul><tt><i>135</i> <span class="sd">            boolean telling whether missing values should be ignored (by default, a missing value</span></tt>
+               class="code sev- "><tt><i>135</i> <span class="sd">            datasets if execution time is prohibitive); 0 indicates no limit; default: 0</span></tt>
             </div>
             <div id="l136"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (95 > 79 characters)</li>
-               
-               </ul><tt><i>136</i> <span class="sd">            of given attribute is always cconsidered as not fulfilling the condition build upon</span></tt>
+               class="code sev- "><tt><i>136</i> <span class="sd">        enable_pruning : bool = True</span></tt>
             </div>
             <div id="l137"
-               class="code sev- "><tt><i>137</i> <span class="sd">             that attribute); default: False.</span></tt>
+               class="code sev- "><tt><i>137</i> <span class="sd">            enable or disable pruning, default is True.</span></tt>
             </div>
             <div id="l138"
-               class="code sev- "><tt><i>138</i> <span class="sd">        max_uncovered_fraction : float = 0.0</span></tt>
+               class="code sev- "><tt><i>138</i> <span class="sd">        ignore_missing : bool = False</span></tt>
             </div>
             <div id="l139"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (95 > 79 characters)</li>
-               
-               </ul><tt><i>139</i> <span class="sd">            Floating-point number from [0,1] interval representing maximum fraction of examples</span></tt>
+               class="code sev- "><tt><i>139</i> <span class="sd">            boolean telling whether missing values should be ignored (by default, a</span></tt>
             </div>
             <div id="l140"
-               class="code sev- "><tt><i>140</i> <span class="sd">            that may remain uncovered by the rule set, default: 0.0.</span></tt>
+               class="code sev- "><tt><i>140</i> <span class="sd">            missing valueof given attribute is always cconsidered as not fulfilling the</span></tt>
             </div>
             <div id="l141"
-               class="code sev- "><tt><i>141</i> <span class="sd">        select_best_candidate : bool = False</span></tt>
+               class="code sev- "><tt><i>141</i> <span class="sd">            condition build upon that attribute); default: False.</span></tt>
             </div>
             <div id="l142"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (94 > 79 characters)</li>
-               
-               </ul><tt><i>142</i> <span class="sd">            Flag determining if best candidate should be selected from growing phase; default:</span></tt>
+               class="code sev- "><tt><i>142</i> <span class="sd">        max_uncovered_fraction : float = 0.0</span></tt>
             </div>
             <div id="l143"
-               class="code sev- "><tt><i>143</i> <span class="sd">            False.</span></tt>
+               class="code sev- "><tt><i>143</i> <span class="sd">            Floating-point number from [0,1] interval representing maximum fraction of</span></tt>
             </div>
             <div id="l144"
-               class="code sev- "><tt><i>144</i> <span class="sd">        complementary_conditions : bool = False</span></tt>
+               class="code sev- "><tt><i>144</i> <span class="sd">            examples that may remain uncovered by the rule set, default: 0.0.</span></tt>
             </div>
             <div id="l145"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (96 > 79 characters)</li>
-               
-               </ul><tt><i>145</i> <span class="sd">            If enabled, complementary conditions in the form a = !{value} for nominal attributes</span></tt>
+               class="code sev- "><tt><i>145</i> <span class="sd">        select_best_candidate : bool = False</span></tt>
             </div>
             <div id="l146"
-               class="code sev- "><tt><i>146</i> <span class="sd">            are supported.</span></tt>
+               class="code sev- "><tt><i>146</i> <span class="sd">            Flag determining if best candidate should be selected from growing phase;</span></tt>
             </div>
             <div id="l147"
-               class="code sev- "><tt><i>147</i> <span class="sd">        control_apriori_precision : bool = True</span></tt>
+               class="code sev- "><tt><i>147</i> <span class="sd">            default: False.</span></tt>
             </div>
             <div id="l148"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (92 > 79 characters)</li>
-               
-               </ul><tt><i>148</i> <span class="sd">            When inducing classification rules, verify if candidate precision is higher than</span></tt>
+               class="code sev- "><tt><i>148</i> <span class="sd">        complementary_conditions : bool = False</span></tt>
             </div>
             <div id="l149"
-               class="code sev- "><tt><i>149</i> <span class="sd">             apriori precision of the investigated class.</span></tt>
+               class="code sev- "><tt><i>149</i> <span class="sd">            If enabled, complementary conditions in the form a = !{value} for nominal</span></tt>
             </div>
             <div id="l150"
-               class="code sev- "><tt><i>150</i> <span class="sd">        max_rule_count : int = 0</span></tt>
+               class="code sev- "><tt><i>150</i> <span class="sd">            attributes are supported.</span></tt>
             </div>
             <div id="l151"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (92 > 79 characters)</li>
-               
-               </ul><tt><i>151</i> <span class="sd">            Maximum number of rules to be generated (for classification data sets it applies</span></tt>
+               class="code sev- "><tt><i>151</i> <span class="sd">        control_apriori_precision : bool = True</span></tt>
             </div>
             <div id="l152"
-               class="code sev- "><tt><i>152</i> <span class="sd">             to a single class); 0 indicates no limit.</span></tt>
+               class="code sev- "><tt><i>152</i> <span class="sd">            When inducing classification rules, verify if candidate precision is higher</span></tt>
             </div>
             <div id="l153"
-               class="code sev- "><tt><i>153</i> <span class="sd">        approximate_induction: bool = False</span></tt>
+               class="code sev- "><tt><i>153</i> <span class="sd">            than apriori precision of the investigated class.</span></tt>
             </div>
             <div id="l154"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (92 > 79 characters)</li>
-               
-               </ul><tt><i>154</i> <span class="sd">            Use an approximate induction heuristic which does not check all possible splits;</span></tt>
+               class="code sev- "><tt><i>154</i> <span class="sd">        max_rule_count : int = 0</span></tt>
             </div>
             <div id="l155"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (93 > 79 characters)</li>
-               
-               </ul><tt><i>155</i> <span class="sd">            note: this is an experimental feature and currently works only for classification</span></tt>
+               class="code sev- "><tt><i>155</i> <span class="sd">            Maximum number of rules to be generated (for classification data sets it</span></tt>
             </div>
             <div id="l156"
-               class="code sev- "><tt><i>156</i> <span class="sd">            data sets, results may change in future;</span></tt>
+               class="code sev- "><tt><i>156</i> <span class="sd">            applies to a single class); 0 indicates no limit.</span></tt>
             </div>
             <div id="l157"
-               class="code sev- "><tt><i>157</i> <span class="sd">        approximate_bins_count: int = 100</span></tt>
+               class="code sev- "><tt><i>157</i> <span class="sd">        approximate_induction: bool = False</span></tt>
             </div>
             <div id="l158"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (91 > 79 characters)</li>
-               
-               </ul><tt><i>158</i> <span class="sd">            maximum number of bins for an attribute evaluated in the approximate induction.</span></tt>
+               class="code sev- "><tt><i>158</i> <span class="sd">            Use an approximate induction heuristic which does not check all possible</span></tt>
             </div>
             <div id="l159"
-               class="code sev- "><tt><i>159</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
+               class="code sev- "><tt><i>159</i> <span class="sd">            splits; note: this is an experimental feature and currently works only for</span></tt>
             </div>
             <div id="l160"
-               class="code sev- "><tt><i>160</i>         <span class="n">BaseOperator</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span></tt>
+               class="code sev- "><tt><i>160</i> <span class="sd">            classification data sets, results may change in future;</span></tt>
             </div>
             <div id="l161"
-               class="code sev- "><tt><i>161</i>             <span class="bp">self</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>161</i> <span class="sd">        approximate_bins_count: int = 100</span></tt>
             </div>
             <div id="l162"
-               class="code sev- "><tt><i>162</i>             <span class="n">minsupp_new</span><span class="o">=</span><span class="n">minsupp_new</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>162</i> <span class="sd">            maximum number of bins for an attribute evaluated in the approximate</span></tt>
             </div>
             <div id="l163"
-               class="code sev- "><tt><i>163</i>             <span class="n">induction_measure</span><span class="o">=</span><span class="n">induction_measure</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>163</i> <span class="sd">            induction.</span></tt>
             </div>
             <div id="l164"
-               class="code sev- "><tt><i>164</i>             <span class="n">pruning_measure</span><span class="o">=</span><span class="n">pruning_measure</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>164</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
             </div>
             <div id="l165"
-               class="code sev- "><tt><i>165</i>             <span class="n">voting_measure</span><span class="o">=</span><span class="n">voting_measure</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>165</i>         <span class="n">BaseOperator</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span></tt>
             </div>
             <div id="l166"
-               class="code sev- "><tt><i>166</i>             <span class="n">max_growing</span><span class="o">=</span><span class="n">max_growing</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>166</i>             <span class="bp">self</span><span class="p">,</span></tt>
             </div>
             <div id="l167"
-               class="code sev- "><tt><i>167</i>             <span class="n">enable_pruning</span><span class="o">=</span><span class="n">enable_pruning</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>167</i>             <span class="n">minsupp_new</span><span class="o">=</span><span class="n">minsupp_new</span><span class="p">,</span></tt>
             </div>
             <div id="l168"
-               class="code sev- "><tt><i>168</i>             <span class="n">ignore_missing</span><span class="o">=</span><span class="n">ignore_missing</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>168</i>             <span class="n">induction_measure</span><span class="o">=</span><span class="n">induction_measure</span><span class="p">,</span></tt>
             </div>
             <div id="l169"
-               class="code sev- "><tt><i>169</i>             <span class="n">max_uncovered_fraction</span><span class="o">=</span><span class="n">max_uncovered_fraction</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>169</i>             <span class="n">pruning_measure</span><span class="o">=</span><span class="n">pruning_measure</span><span class="p">,</span></tt>
             </div>
             <div id="l170"
-               class="code sev- "><tt><i>170</i>             <span class="n">select_best_candidate</span><span class="o">=</span><span class="n">select_best_candidate</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>170</i>             <span class="n">voting_measure</span><span class="o">=</span><span class="n">voting_measure</span><span class="p">,</span></tt>
             </div>
             <div id="l171"
-               class="code sev- "><tt><i>171</i>             <span class="n">complementary_conditions</span><span class="o">=</span><span class="n">complementary_conditions</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>171</i>             <span class="n">max_growing</span><span class="o">=</span><span class="n">max_growing</span><span class="p">,</span></tt>
             </div>
             <div id="l172"
-               class="code sev- "><tt><i>172</i>             <span class="n">control_apriori_precision</span><span class="o">=</span><span class="n">control_apriori_precision</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>172</i>             <span class="n">enable_pruning</span><span class="o">=</span><span class="n">enable_pruning</span><span class="p">,</span></tt>
             </div>
             <div id="l173"
-               class="code sev- "><tt><i>173</i>             <span class="n">max_rule_count</span><span class="o">=</span><span class="n">max_rule_count</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>173</i>             <span class="n">ignore_missing</span><span class="o">=</span><span class="n">ignore_missing</span><span class="p">,</span></tt>
             </div>
             <div id="l174"
-               class="code sev- "><tt><i>174</i>             <span class="n">approximate_induction</span><span class="o">=</span><span class="n">approximate_induction</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>174</i>             <span class="n">max_uncovered_fraction</span><span class="o">=</span><span class="n">max_uncovered_fraction</span><span class="p">,</span></tt>
             </div>
             <div id="l175"
-               class="code sev- "><tt><i>175</i>             <span class="n">approximate_bins_count</span><span class="o">=</span><span class="n">approximate_bins_count</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>175</i>             <span class="n">select_best_candidate</span><span class="o">=</span><span class="n">select_best_candidate</span><span class="p">,</span></tt>
             </div>
             <div id="l176"
-               class="code sev- "><tt><i>176</i>         <span class="p">)</span></tt>
+               class="code sev- "><tt><i>176</i>             <span class="n">complementary_conditions</span><span class="o">=</span><span class="n">complementary_conditions</span><span class="p">,</span></tt>
             </div>
             <div id="l177"
-               class="code sev- "><tt><i>177</i>         <span class="n">BaseClassifier</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span></tt>
+               class="code sev- "><tt><i>177</i>             <span class="n">control_apriori_precision</span><span class="o">=</span><span class="n">control_apriori_precision</span><span class="p">,</span></tt>
             </div>
             <div id="l178"
-               class="code sev- "><tt><i>178</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_remap_to_numeric</span> <span class="o">=</span> <span class="kc">False</span></tt>
+               class="code sev- "><tt><i>178</i>             <span class="n">max_rule_count</span><span class="o">=</span><span class="n">max_rule_count</span><span class="p">,</span></tt>
             </div>
             <div id="l179"
-               class="code sev- "><tt><i>179</i>         <span class="bp">self</span><span class="o">.</span><span class="n">label_unique_values</span> <span class="o">=</span> <span class="p">[]</span></tt>
+               class="code sev- "><tt><i>179</i>             <span class="n">approximate_induction</span><span class="o">=</span><span class="n">approximate_induction</span><span class="p">,</span></tt>
             </div>
             <div id="l180"
-               class="code sev- "><tt><i>180</i>         <span class="bp">self</span><span class="o">.</span><span class="n">model</span><span class="p">:</span> <span class="n">RuleSet</span><span class="p">[</span><span class="n">ClassificationRule</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span></tt>
+               class="code sev- "><tt><i>180</i>             <span class="n">approximate_bins_count</span><span class="o">=</span><span class="n">approximate_bins_count</span><span class="p">,</span></tt>
             </div>
             <div id="l181"
-               class="code sev- "><tt><i>181</i> &nbsp;</tt>
+               class="code sev- "><tt><i>181</i>         <span class="p">)</span></tt>
             </div>
             <div id="l182"
-               class="code sev- "><tt><i>182</i>     <span class="k">def</span> <span class="nf">_map_result</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">predicted_example_set</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">:</span></tt>
+               class="code sev- "><tt><i>182</i>         <span class="n">BaseClassifier</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span></tt>
             </div>
             <div id="l183"
-               class="code sev- "><tt><i>183</i>         <span class="n">prediction</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span></tt>
+               class="code sev- "><tt><i>183</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_remap_to_numeric</span> <span class="o">=</span> <span class="kc">False</span></tt>
             </div>
             <div id="l184"
-               class="code sev- "><tt><i>184</i>         <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">_remap_to_numeric</span><span class="p">:</span></tt>
+               class="code sev- "><tt><i>184</i>         <span class="bp">self</span><span class="o">.</span><span class="n">label_unique_values</span> <span class="o">=</span> <span class="p">[]</span></tt>
             </div>
             <div id="l185"
-               class="code sev- "><tt><i>185</i>             <span class="n">prediction</span> <span class="o">=</span> <span class="n">PredictionResultMapper</span><span class="o">.</span><span class="n">map_to_numerical</span><span class="p">(</span></tt>
+               class="code sev- "><tt><i>185</i>         <span class="bp">self</span><span class="o">.</span><span class="n">model</span><span class="p">:</span> <span class="n">RuleSet</span><span class="p">[</span><span class="n">ClassificationRule</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span></tt>
             </div>
             <div id="l186"
-               class="code sev- "><tt><i>186</i>                 <span class="n">predicted_example_set</span><span class="p">)</span></tt>
+               class="code sev- "><tt><i>186</i> &nbsp;</tt>
             </div>
             <div id="l187"
-               class="code sev- "><tt><i>187</i>         <span class="k">else</span><span class="p">:</span></tt>
+               class="code sev- "><tt><i>187</i>     <span class="k">def</span> <span class="nf">_map_result</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">predicted_example_set</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">:</span></tt>
             </div>
             <div id="l188"
-               class="code sev- "><tt><i>188</i>             <span class="n">prediction</span> <span class="o">=</span> <span class="n">PredictionResultMapper</span><span class="o">.</span><span class="n">map_to_nominal</span><span class="p">(</span></tt>
+               class="code sev- "><tt><i>188</i>         <span class="n">prediction</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span></tt>
             </div>
             <div id="l189"
-               class="code sev- "><tt><i>189</i>                 <span class="n">predicted_example_set</span><span class="p">)</span></tt>
+               class="code sev- "><tt><i>189</i>         <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">_remap_to_numeric</span><span class="p">:</span></tt>
             </div>
             <div id="l190"
-               class="code sev- "><tt><i>190</i>         <span class="k">return</span> <span class="n">prediction</span></tt>
+               class="code sev- "><tt><i>190</i>             <span class="n">prediction</span> <span class="o">=</span> <span class="n">PredictionResultMapper</span><span class="o">.</span><span class="n">map_to_numerical</span><span class="p">(</span><span class="n">predicted_example_set</span><span class="p">)</span></tt>
             </div>
             <div id="l191"
-               class="code sev- "><tt><i>191</i> &nbsp;</tt>
+               class="code sev- "><tt><i>191</i>         <span class="k">else</span><span class="p">:</span></tt>
             </div>
             <div id="l192"
-               class="code sev- "><tt><i>192</i>     <span class="k">def</span> <span class="nf">_map_confidence</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">predicted_example_set</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">:</span></tt>
+               class="code sev- "><tt><i>192</i>             <span class="n">prediction</span> <span class="o">=</span> <span class="n">PredictionResultMapper</span><span class="o">.</span><span class="n">map_to_nominal</span><span class="p">(</span><span class="n">predicted_example_set</span><span class="p">)</span></tt>
             </div>
             <div id="l193"
-               class="code sev- "><tt><i>193</i>         <span class="k">return</span> <span class="n">PredictionResultMapper</span><span class="o">.</span><span class="n">map_confidence</span><span class="p">(</span></tt>
+               class="code sev- "><tt><i>193</i>         <span class="k">return</span> <span class="n">prediction</span></tt>
             </div>
             <div id="l194"
-               class="code sev- "><tt><i>194</i>             <span class="n">predicted_example_set</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">label_unique_values</span></tt>
+               class="code sev- "><tt><i>194</i> &nbsp;</tt>
             </div>
             <div id="l195"
-               class="code sev- "><tt><i>195</i>         <span class="p">)</span></tt>
+               class="code sev- "><tt><i>195</i>     <span class="k">def</span> <span class="nf">_map_confidence</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">predicted_example_set</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">:</span></tt>
             </div>
             <div id="l196"
-               class="code sev- "><tt><i>196</i> &nbsp;</tt>
+               class="code sev- "><tt><i>196</i>         <span class="k">return</span> <span class="n">PredictionResultMapper</span><span class="o">.</span><span class="n">map_confidence</span><span class="p">(</span></tt>
             </div>
             <div id="l197"
-               class="code sev- "><tt><i>197</i>     <span class="k">def</span> <span class="nf">_get_unique_label_values</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">labels</span><span class="p">:</span> <span class="n">Data</span><span class="p">):</span></tt>
+               class="code sev- "><tt><i>197</i>             <span class="n">predicted_example_set</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">label_unique_values</span></tt>
             </div>
             <div id="l198"
-               class="code sev- "><tt><i>198</i>         <span class="n">tmp</span> <span class="o">=</span> <span class="p">{}</span></tt>
+               class="code sev- "><tt><i>198</i>         <span class="p">)</span></tt>
             </div>
             <div id="l199"
-               class="code sev- "><tt><i>199</i>         <span class="k">for</span> <span class="n">label_value</span> <span class="ow">in</span> <span class="n">labels</span><span class="p">:</span></tt>
+               class="code sev- "><tt><i>199</i> &nbsp;</tt>
             </div>
             <div id="l200"
-               class="code sev- "><tt><i>200</i>             <span class="n">tmp</span><span class="p">[</span><span class="n">label_value</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span></tt>
+               class="code sev- "><tt><i>200</i>     <span class="k">def</span> <span class="nf">_get_unique_label_values</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">labels</span><span class="p">:</span> <span class="n">Data</span><span class="p">):</span></tt>
             </div>
             <div id="l201"
-               class="code sev- "><tt><i>201</i>         <span class="bp">self</span><span class="o">.</span><span class="n">label_unique_values</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="n">tmp</span><span class="o">.</span><span class="n">keys</span><span class="p">())</span></tt>
+               class="code sev- "><tt><i>201</i>         <span class="n">tmp</span> <span class="o">=</span> <span class="p">{}</span></tt>
             </div>
             <div id="l202"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (96 > 79 characters)</li>
-               
-               </ul><tt><i>202</i>         <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">label_unique_values</span><span class="p">)</span> <span class="o">&gt;</span> <span class="mi">0</span> <span class="ow">and</span> <span class="nb">isinstance</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">label_unique_values</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="nb">bytes</span><span class="p">):</span></tt>
+               class="code sev- "><tt><i>202</i>         <span class="k">for</span> <span class="n">label_value</span> <span class="ow">in</span> <span class="n">labels</span><span class="p">:</span></tt>
             </div>
             <div id="l203"
-               class="code sev- "><tt><i>203</i>             <span class="bp">self</span><span class="o">.</span><span class="n">label_unique_values</span> <span class="o">=</span> <span class="p">[</span><span class="n">item</span><span class="o">.</span><span class="n">decode</span><span class="p">(</span></tt>
+               class="code sev- "><tt><i>203</i>             <span class="n">tmp</span><span class="p">[</span><span class="n">label_value</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span></tt>
             </div>
             <div id="l204"
-               class="code sev- "><tt><i>204</i>                 <span class="s1">&#39;utf-8&#39;</span><span class="p">)</span> <span class="k">for</span> <span class="n">item</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">label_unique_values</span><span class="p">]</span></tt>
+               class="code sev- "><tt><i>204</i>         <span class="bp">self</span><span class="o">.</span><span class="n">label_unique_values</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="n">tmp</span><span class="o">.</span><span class="n">keys</span><span class="p">())</span></tt>
             </div>
             <div id="l205"
-               class="code sev- "><tt><i>205</i> &nbsp;</tt>
+               class="code sev- "><tt><i>205</i>         <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">label_unique_values</span><span class="p">)</span> <span class="o">&gt;</span> <span class="mi">0</span> <span class="ow">and</span> <span class="nb">isinstance</span><span class="p">(</span></tt>
             </div>
             <div id="l206"
-               class="code sev- "><tt><i>206</i>     <span class="k">def</span> <span class="nf">_prepare_labels</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">labels</span><span class="p">:</span> <span class="n">Data</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Data</span><span class="p">:</span></tt>
+               class="code sev- "><tt><i>206</i>             <span class="bp">self</span><span class="o">.</span><span class="n">label_unique_values</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="nb">bytes</span></tt>
             </div>
             <div id="l207"
-               class="code sev- "><tt><i>207</i>         <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">labels</span><span class="p">,</span> <span class="p">(</span><span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">,</span> <span class="n">pd</span><span class="o">.</span><span class="n">Series</span><span class="p">)):</span></tt>
+               class="code sev- "><tt><i>207</i>         <span class="p">):</span></tt>
             </div>
             <div id="l208"
-               class="code sev- "><tt><i>208</i>             <span class="k">if</span> <span class="n">labels</span><span class="o">.</span><span class="n">dtypes</span><span class="o">.</span><span class="n">name</span> <span class="o">==</span> <span class="s1">&#39;bool&#39;</span><span class="p">:</span></tt>
+               class="code sev- "><tt><i>208</i>             <span class="bp">self</span><span class="o">.</span><span class="n">label_unique_values</span> <span class="o">=</span> <span class="p">[</span></tt>
             </div>
             <div id="l209"
-               class="code sev- "><tt><i>209</i>                 <span class="k">return</span> <span class="n">labels</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="nb">str</span><span class="p">)</span></tt>
+               class="code sev- "><tt><i>209</i>                 <span class="n">item</span><span class="o">.</span><span class="n">decode</span><span class="p">(</span><span class="s2">&quot;utf-8&quot;</span><span class="p">)</span> <span class="k">for</span> <span class="n">item</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">label_unique_values</span></tt>
             </div>
             <div id="l210"
-               class="code sev- "><tt><i>210</i>             <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">labels</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">Number</span><span class="p">):</span></tt>
+               class="code sev- "><tt><i>210</i>             <span class="p">]</span></tt>
             </div>
             <div id="l211"
-               class="code sev- "><tt><i>211</i>                 <span class="bp">self</span><span class="o">.</span><span class="n">_remap_to_numeric</span> <span class="o">=</span> <span class="kc">True</span></tt>
+               class="code sev- "><tt><i>211</i> &nbsp;</tt>
             </div>
             <div id="l212"
-               class="code sev- "><tt><i>212</i>                 <span class="k">return</span> <span class="n">labels</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="nb">str</span><span class="p">)</span></tt>
+               class="code sev- "><tt><i>212</i>     <span class="k">def</span> <span class="nf">_prepare_labels</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">labels</span><span class="p">:</span> <span class="n">Data</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Data</span><span class="p">:</span></tt>
             </div>
             <div id="l213"
-               class="code sev- "><tt><i>213</i>         <span class="k">else</span><span class="p">:</span></tt>
+               class="code sev- "><tt><i>213</i>         <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">labels</span><span class="p">,</span> <span class="p">(</span><span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">,</span> <span class="n">pd</span><span class="o">.</span><span class="n">Series</span><span class="p">)):</span></tt>
             </div>
             <div id="l214"
-               class="code sev- "><tt><i>214</i>             <span class="k">if</span> <span class="p">(</span></tt>
+               class="code sev- "><tt><i>214</i>             <span class="k">if</span> <span class="n">labels</span><span class="o">.</span><span class="n">dtypes</span><span class="o">.</span><span class="n">name</span> <span class="o">==</span> <span class="s2">&quot;bool&quot;</span><span class="p">:</span></tt>
             </div>
             <div id="l215"
-               class="code sev- "><tt><i>215</i>                 <span class="nb">isinstance</span><span class="p">(</span><span class="n">labels</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="nb">bool</span><span class="p">)</span> <span class="ow">or</span></tt>
+               class="code sev- "><tt><i>215</i>                 <span class="k">return</span> <span class="n">labels</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="nb">str</span><span class="p">)</span></tt>
             </div>
             <div id="l216"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (80 > 79 characters)</li>
-               
-               </ul><tt><i>216</i>                 <span class="p">(</span><span class="nb">isinstance</span><span class="p">(</span><span class="n">labels</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">)</span> <span class="ow">and</span> <span class="n">labels</span><span class="o">.</span><span class="n">dtype</span><span class="o">.</span><span class="n">name</span> <span class="o">==</span> <span class="s1">&#39;bool&#39;</span><span class="p">)</span></tt>
+               class="code sev- "><tt><i>216</i>             <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">labels</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">Number</span><span class="p">):</span></tt>
             </div>
             <div id="l217"
-               class="code sev- "><tt><i>217</i>             <span class="p">):</span></tt>
+               class="code sev- "><tt><i>217</i>                 <span class="bp">self</span><span class="o">.</span><span class="n">_remap_to_numeric</span> <span class="o">=</span> <span class="kc">True</span></tt>
             </div>
             <div id="l218"
-               class="code sev- "><tt><i>218</i>                 <span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="nb">list</span><span class="p">(</span><span class="nb">map</span><span class="p">(</span><span class="nb">str</span><span class="p">,</span> <span class="n">labels</span><span class="p">)))</span></tt>
+               class="code sev- "><tt><i>218</i>                 <span class="k">return</span> <span class="n">labels</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="nb">str</span><span class="p">)</span></tt>
             </div>
             <div id="l219"
-               class="code sev- "><tt><i>219</i>             <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">labels</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">Number</span><span class="p">):</span></tt>
+               class="code sev- "><tt><i>219</i>         <span class="k">else</span><span class="p">:</span></tt>
             </div>
             <div id="l220"
-               class="code sev- "><tt><i>220</i>                 <span class="bp">self</span><span class="o">.</span><span class="n">_remap_to_numeric</span> <span class="o">=</span> <span class="kc">True</span></tt>
+               class="code sev- "><tt><i>220</i>             <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">labels</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="nb">bool</span><span class="p">)</span> <span class="ow">or</span> <span class="p">(</span></tt>
             </div>
             <div id="l221"
-               class="code sev- "><tt><i>221</i>                 <span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="nb">list</span><span class="p">(</span><span class="nb">map</span><span class="p">(</span><span class="nb">str</span><span class="p">,</span> <span class="n">labels</span><span class="p">)))</span></tt>
+               class="code sev- "><tt><i>221</i>                 <span class="nb">isinstance</span><span class="p">(</span><span class="n">labels</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">)</span> <span class="ow">and</span> <span class="n">labels</span><span class="o">.</span><span class="n">dtype</span><span class="o">.</span><span class="n">name</span> <span class="o">==</span> <span class="s2">&quot;bool&quot;</span></tt>
             </div>
-            <div id="l222"
-               class="code sev- "><tt><i>222</i>         <span class="k">return</span> <span class="n">labels</span></tt>
-            </div>
-            <div id="l223"
-               class="code sev- "><tt><i>223</i> &nbsp;</tt>
-            </div>
-            <div id="l224"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (100 > 79 characters)</li>
-               
-               </ul><tt><i>224</i>     <span class="k">def</span> <span class="nf">fit</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">:</span> <span class="n">Data</span><span class="p">,</span> <span class="n">labels</span><span class="p">:</span> <span class="n">Data</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">RuleClassifier</span><span class="p">:</span>  <span class="c1"># pylint: disable=arguments-differ</span></tt>
+            <div id="l222"
+               class="code sev- "><tt><i>222</i>             <span class="p">):</span></tt>
+            </div>
+            <div id="l223"
+               class="code sev- "><tt><i>223</i>                 <span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="nb">list</span><span class="p">(</span><span class="nb">map</span><span class="p">(</span><span class="nb">str</span><span class="p">,</span> <span class="n">labels</span><span class="p">)))</span></tt>
+            </div>
+            <div id="l224"
+               class="code sev- "><tt><i>224</i>             <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">labels</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">Number</span><span class="p">):</span></tt>
             </div>
             <div id="l225"
-               class="code sev- "><tt><i>225</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Train model on given dataset.</span></tt>
+               class="code sev- "><tt><i>225</i>                 <span class="bp">self</span><span class="o">.</span><span class="n">_remap_to_numeric</span> <span class="o">=</span> <span class="kc">True</span></tt>
             </div>
             <div id="l226"
-               class="code sev- "><tt><i>226</i> &nbsp;</tt>
+               class="code sev- "><tt><i>226</i>                 <span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="nb">list</span><span class="p">(</span><span class="nb">map</span><span class="p">(</span><span class="nb">str</span><span class="p">,</span> <span class="n">labels</span><span class="p">)))</span></tt>
             </div>
             <div id="l227"
-               class="code sev- "><tt><i>227</i> <span class="sd">        Parameters</span></tt>
+               class="code sev- "><tt><i>227</i>         <span class="k">return</span> <span class="n">labels</span></tt>
             </div>
             <div id="l228"
-               class="code sev- "><tt><i>228</i> <span class="sd">        ----------</span></tt>
+               class="code sev- "><tt><i>228</i> &nbsp;</tt>
             </div>
             <div id="l229"
-               class="code sev- "><tt><i>229</i> <span class="sd">        values : :class:`rulekit.operator.Data`</span></tt>
+               class="code sev- "><tt><i>229</i>     <span class="k">def</span> <span class="nf">fit</span><span class="p">(</span></tt>
             </div>
             <div id="l230"
-               class="code sev- "><tt><i>230</i> <span class="sd">            attributes</span></tt>
+               class="code sev- "><tt><i>230</i>         <span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">:</span> <span class="n">Data</span><span class="p">,</span> <span class="n">labels</span><span class="p">:</span> <span class="n">Data</span></tt>
             </div>
             <div id="l231"
-               class="code sev- "><tt><i>231</i> <span class="sd">        labels : :class:`rulekit.operator.Data`</span></tt>
+               class="code sev- "><tt><i>231</i>     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">RuleClassifier</span><span class="p">:</span>  <span class="c1"># pylint: disable=arguments-differ</span></tt>
             </div>
             <div id="l232"
-               class="code sev- "><tt><i>232</i> <span class="sd">            labels</span></tt>
+               class="code sev- "><tt><i>232</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Train model on given dataset.</span></tt>
             </div>
             <div id="l233"
-               class="code sev- "><tt><i>233</i> <span class="sd">        Returns</span></tt>
+               class="code sev- "><tt><i>233</i> &nbsp;</tt>
             </div>
             <div id="l234"
-               class="code sev- "><tt><i>234</i> <span class="sd">        -------</span></tt>
+               class="code sev- "><tt><i>234</i> <span class="sd">        Parameters</span></tt>
             </div>
             <div id="l235"
-               class="code sev- "><tt><i>235</i> <span class="sd">        self : RuleClassifier</span></tt>
+               class="code sev- "><tt><i>235</i> <span class="sd">        ----------</span></tt>
             </div>
             <div id="l236"
-               class="code sev- "><tt><i>236</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
+               class="code sev- "><tt><i>236</i> <span class="sd">        values : :class:`rulekit.operator.Data`</span></tt>
             </div>
             <div id="l237"
-               class="code sev- "><tt><i>237</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_get_unique_label_values</span><span class="p">(</span><span class="n">labels</span><span class="p">)</span></tt>
+               class="code sev- "><tt><i>237</i> <span class="sd">            attributes</span></tt>
             </div>
             <div id="l238"
-               class="code sev- "><tt><i>238</i>         <span class="n">labels</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_prepare_labels</span><span class="p">(</span><span class="n">labels</span><span class="p">)</span></tt>
+               class="code sev- "><tt><i>238</i> <span class="sd">        labels : :class:`rulekit.operator.Data`</span></tt>
             </div>
             <div id="l239"
-               class="code sev- "><tt><i>239</i>         <span class="n">BaseOperator</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">,</span> <span class="n">labels</span><span class="p">)</span></tt>
+               class="code sev- "><tt><i>239</i> <span class="sd">            labels</span></tt>
             </div>
             <div id="l240"
-               class="code sev- "><tt><i>240</i>         <span class="k">return</span> <span class="bp">self</span></tt>
+               class="code sev- "><tt><i>240</i> <span class="sd">        Returns</span></tt>
             </div>
             <div id="l241"
-               class="code sev- "><tt><i>241</i> &nbsp;</tt>
+               class="code sev- "><tt><i>241</i> <span class="sd">        -------</span></tt>
             </div>
             <div id="l242"
-               class="code sev- "><tt><i>242</i>     <span class="k">def</span> <span class="nf">predict</span><span class="p">(</span></tt>
+               class="code sev- "><tt><i>242</i> <span class="sd">        self : RuleClassifier</span></tt>
             </div>
             <div id="l243"
-               class="code sev- "><tt><i>243</i>         <span class="bp">self</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>243</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
             </div>
             <div id="l244"
-               class="code sev- "><tt><i>244</i>         <span class="n">values</span><span class="p">:</span> <span class="n">Data</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>244</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_get_unique_label_values</span><span class="p">(</span><span class="n">labels</span><span class="p">)</span></tt>
             </div>
             <div id="l245"
-               class="code sev- "><tt><i>245</i>         <span class="n">return_metrics</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span></tt>
+               class="code sev- "><tt><i>245</i>         <span class="n">labels</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_prepare_labels</span><span class="p">(</span><span class="n">labels</span><span class="p">)</span></tt>
             </div>
             <div id="l246"
-               class="code sev- "><tt><i>246</i>     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Union</span><span class="p">[</span><span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">,</span> <span class="nb">tuple</span><span class="p">[</span><span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">,</span> <span class="n">ClassificationPredictionMetrics</span><span class="p">]]:</span></tt>
+               class="code sev- "><tt><i>246</i>         <span class="n">BaseOperator</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">,</span> <span class="n">labels</span><span class="p">)</span></tt>
             </div>
             <div id="l247"
-               class="code sev- "><tt><i>247</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Perform prediction and returns predicted labels.</span></tt>
+               class="code sev- "><tt><i>247</i>         <span class="k">return</span> <span class="bp">self</span></tt>
             </div>
             <div id="l248"
                class="code sev- "><tt><i>248</i> &nbsp;</tt>
             </div>
             <div id="l249"
-               class="code sev- "><tt><i>249</i> <span class="sd">        Parameters</span></tt>
+               class="code sev- "><tt><i>249</i>     <span class="k">def</span> <span class="nf">predict</span><span class="p">(</span></tt>
             </div>
             <div id="l250"
-               class="code sev- "><tt><i>250</i> <span class="sd">        ----------</span></tt>
+               class="code sev- "><tt><i>250</i>         <span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">:</span> <span class="n">Data</span><span class="p">,</span> <span class="n">return_metrics</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span></tt>
             </div>
             <div id="l251"
-               class="code sev- "><tt><i>251</i> <span class="sd">        values : :class:`rulekit.operator.Data`</span></tt>
+               class="code sev- "><tt><i>251</i>     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Union</span><span class="p">[</span><span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">,</span> <span class="nb">tuple</span><span class="p">[</span><span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">,</span> <span class="n">ClassificationPredictionMetrics</span><span class="p">]]:</span></tt>
             </div>
             <div id="l252"
-               class="code sev- "><tt><i>252</i> <span class="sd">            attributes</span></tt>
+               class="code sev- "><tt><i>252</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Perform prediction and returns predicted labels.</span></tt>
             </div>
             <div id="l253"
                class="code sev- "><tt><i>253</i> &nbsp;</tt>
             </div>
             <div id="l254"
-               class="code sev- "><tt><i>254</i> <span class="sd">        return_metrics: bool = False</span></tt>
+               class="code sev- "><tt><i>254</i> <span class="sd">        Parameters</span></tt>
             </div>
             <div id="l255"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (96 > 79 characters)</li>
-               
-               </ul><tt><i>255</i> <span class="sd">            Optional flag. If set to *True* method will calculate some additional model metrics.</span></tt>
+               class="code sev- "><tt><i>255</i> <span class="sd">        ----------</span></tt>
             </div>
             <div id="l256"
-               class="code sev- "><tt><i>256</i> <span class="sd">             Method will then return tuple instead of just predicted labels.</span></tt>
+               class="code sev- "><tt><i>256</i> <span class="sd">        values : :class:`rulekit.operator.Data`</span></tt>
             </div>
             <div id="l257"
-               class="code sev- "><tt><i>257</i> &nbsp;</tt>
+               class="code sev- "><tt><i>257</i> <span class="sd">            attributes</span></tt>
             </div>
             <div id="l258"
-               class="code sev- "><tt><i>258</i> <span class="sd">        Returns</span></tt>
+               class="code sev- "><tt><i>258</i> &nbsp;</tt>
             </div>
             <div id="l259"
-               class="code sev- "><tt><i>259</i> <span class="sd">        -------</span></tt>
+               class="code sev- "><tt><i>259</i> <span class="sd">        return_metrics: bool = False</span></tt>
             </div>
             <div id="l260"
-               class="code sev- "><tt><i>260</i> <span class="sd">        result : Union[</span></tt>
+               class="code sev- "><tt><i>260</i> <span class="sd">            Optional flag. If set to *True* method will calculate some additional model</span></tt>
             </div>
             <div id="l261"
-               class="code sev- "><tt><i>261</i> <span class="sd">            np.ndarray,</span></tt>
+               class="code sev- "><tt><i>261</i> <span class="sd">            metrics. Method will then return tuple instead of just predicted labels.</span></tt>
             </div>
             <div id="l262"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (94 > 79 characters)</li>
-               
-               </ul><tt><i>262</i> <span class="sd">            tuple[np.ndarray, :class:`rulekit.classification.ClassificationPredictionMetrics`]</span></tt>
+               class="code sev- "><tt><i>262</i> &nbsp;</tt>
             </div>
             <div id="l263"
-               class="code sev- "><tt><i>263</i> <span class="sd">        ]</span></tt>
+               class="code sev- "><tt><i>263</i> <span class="sd">        Returns</span></tt>
             </div>
             <div id="l264"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (93 > 79 characters)</li>
-               
-               </ul><tt><i>264</i> <span class="sd">        If *return_metrics* flag wasn&#39;t set it will return just prediction, otherwise a tuple</span></tt>
+               class="code sev- "><tt><i>264</i> <span class="sd">        -------</span></tt>
             </div>
             <div id="l265"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (90 > 79 characters)</li>
-               
-               </ul><tt><i>265</i> <span class="sd">        will be returned with first element being prediction and second one being metrics.</span></tt>
+               class="code sev- "><tt><i>265</i> <span class="sd">        result : Union[np.ndarray, tuple[np.ndarray, :class:`rulekit.classification.\</span></tt>
             </div>
             <div id="l266"
-               class="code sev- "><tt><i>266</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
+               class="code sev- "><tt><i>266</i> <span class="sd">            ClassificationPredictionMetrics`]]</span></tt>
             </div>
             <div id="l267"
-               class="code sev- "><tt><i>267</i>         <span class="n">result_example_set</span> <span class="o">=</span> <span class="n">BaseOperator</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">)</span></tt>
+               class="code sev- "><tt><i>267</i> <span class="sd">            If *return_metrics* flag wasn&#39;t set it will return just prediction,</span></tt>
             </div>
             <div id="l268"
-               class="code sev- "><tt><i>268</i>         <span class="n">y_pred</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_map_result</span><span class="p">(</span><span class="n">result_example_set</span><span class="p">)</span></tt>
+               class="code sev- "><tt><i>268</i> <span class="sd">            otherwise a tuple will be returned with first element being prediction and</span></tt>
             </div>
             <div id="l269"
-               class="code sev- "><tt><i>269</i>         <span class="k">if</span> <span class="n">return_metrics</span><span class="p">:</span></tt>
+               class="code sev- "><tt><i>269</i> <span class="sd">            second one being metrics.</span></tt>
             </div>
             <div id="l270"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (80 > 79 characters)</li>
-               
-               </ul><tt><i>270</i>             <span class="n">metrics_values</span><span class="p">:</span> <span class="nb">dict</span> <span class="o">=</span> <span class="n">BaseClassifier</span><span class="o">.</span><span class="n">_calculate_prediction_metrics</span><span class="p">(</span></tt>
+               class="code sev- "><tt><i>270</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
             </div>
             <div id="l271"
-               class="code sev- "><tt><i>271</i>                 <span class="bp">self</span><span class="p">,</span> <span class="n">result_example_set</span><span class="p">)</span></tt>
+               class="code sev- "><tt><i>271</i>         <span class="n">result_example_set</span> <span class="o">=</span> <span class="n">BaseOperator</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">)</span></tt>
             </div>
             <div id="l272"
-               class="code sev- "><tt><i>272</i>             <span class="k">return</span> <span class="p">(</span><span class="n">y_pred</span><span class="p">,</span> <span class="n">metrics_values</span><span class="p">)</span></tt>
+               class="code sev- "><tt><i>272</i>         <span class="n">y_pred</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_map_result</span><span class="p">(</span><span class="n">result_example_set</span><span class="p">)</span></tt>
             </div>
             <div id="l273"
-               class="code sev- "><tt><i>273</i>         <span class="k">return</span> <span class="n">y_pred</span></tt>
+               class="code sev- "><tt><i>273</i>         <span class="k">if</span> <span class="n">return_metrics</span><span class="p">:</span></tt>
             </div>
             <div id="l274"
-               class="code sev- "><tt><i>274</i> &nbsp;</tt>
+               class="code sev- "><tt><i>274</i>             <span class="n">metrics_values</span><span class="p">:</span> <span class="nb">dict</span> <span class="o">=</span> <span class="n">BaseClassifier</span><span class="o">.</span><span class="n">_calculate_prediction_metrics</span><span class="p">(</span></tt>
             </div>
             <div id="l275"
-               class="code sev- "><tt><i>275</i>     <span class="k">def</span> <span class="nf">predict_proba</span><span class="p">(</span></tt>
+               class="code sev- "><tt><i>275</i>                 <span class="bp">self</span><span class="p">,</span> <span class="n">result_example_set</span></tt>
             </div>
             <div id="l276"
-               class="code sev- "><tt><i>276</i>         <span class="bp">self</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>276</i>             <span class="p">)</span></tt>
             </div>
             <div id="l277"
-               class="code sev- "><tt><i>277</i>         <span class="n">values</span><span class="p">:</span> <span class="n">Data</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>277</i>             <span class="k">return</span> <span class="p">(</span><span class="n">y_pred</span><span class="p">,</span> <span class="n">metrics_values</span><span class="p">)</span></tt>
             </div>
             <div id="l278"
-               class="code sev- "><tt><i>278</i>         <span class="n">return_metrics</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span></tt>
+               class="code sev- "><tt><i>278</i>         <span class="k">return</span> <span class="n">y_pred</span></tt>
             </div>
             <div id="l279"
-               class="code sev- "><tt><i>279</i>     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Union</span><span class="p">[</span><span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">,</span> <span class="nb">tuple</span><span class="p">[</span><span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">,</span> <span class="n">ClassificationPredictionMetrics</span><span class="p">]]:</span></tt>
+               class="code sev- "><tt><i>279</i> &nbsp;</tt>
             </div>
             <div id="l280"
-               class="code sev- "><tt><i>280</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Perform prediction and returns class probabilities for each example.</span></tt>
+               class="code sev- "><tt><i>280</i>     <span class="k">def</span> <span class="nf">predict_proba</span><span class="p">(</span></tt>
             </div>
             <div id="l281"
-               class="code sev- "><tt><i>281</i> &nbsp;</tt>
+               class="code sev- "><tt><i>281</i>         <span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">:</span> <span class="n">Data</span><span class="p">,</span> <span class="n">return_metrics</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span></tt>
             </div>
             <div id="l282"
-               class="code sev- "><tt><i>282</i> <span class="sd">        Parameters</span></tt>
+               class="code sev- "><tt><i>282</i>     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Union</span><span class="p">[</span><span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">,</span> <span class="nb">tuple</span><span class="p">[</span><span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">,</span> <span class="n">ClassificationPredictionMetrics</span><span class="p">]]:</span></tt>
             </div>
             <div id="l283"
-               class="code sev- "><tt><i>283</i> <span class="sd">        ----------</span></tt>
+               class="code sev- "><tt><i>283</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Perform prediction and returns class probabilities for each example.</span></tt>
             </div>
             <div id="l284"
-               class="code sev- "><tt><i>284</i> <span class="sd">        values : :class:`rulekit.operator.Data`</span></tt>
+               class="code sev- "><tt><i>284</i> &nbsp;</tt>
             </div>
             <div id="l285"
-               class="code sev- "><tt><i>285</i> <span class="sd">            attributes</span></tt>
+               class="code sev- "><tt><i>285</i> <span class="sd">        Parameters</span></tt>
             </div>
             <div id="l286"
-               class="code sev- "><tt><i>286</i> &nbsp;</tt>
+               class="code sev- "><tt><i>286</i> <span class="sd">        ----------</span></tt>
             </div>
             <div id="l287"
-               class="code sev- "><tt><i>287</i> <span class="sd">        return_metrics: bool = False</span></tt>
+               class="code sev- "><tt><i>287</i> <span class="sd">        values : :class:`rulekit.operator.Data`</span></tt>
             </div>
             <div id="l288"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (96 > 79 characters)</li>
-               
-               </ul><tt><i>288</i> <span class="sd">            Optional flag. If set to *True* method will calculate some additional model metrics.</span></tt>
+               class="code sev- "><tt><i>288</i> <span class="sd">            attributes</span></tt>
             </div>
             <div id="l289"
-               class="code sev- "><tt><i>289</i> <span class="sd">             Method will then return tuple instead of just probabilities.</span></tt>
+               class="code sev- "><tt><i>289</i> &nbsp;</tt>
             </div>
             <div id="l290"
-               class="code sev- "><tt><i>290</i> &nbsp;</tt>
+               class="code sev- "><tt><i>290</i> <span class="sd">        return_metrics: bool = False</span></tt>
             </div>
             <div id="l291"
-               class="code sev- "><tt><i>291</i> <span class="sd">        Returns</span></tt>
+               class="code sev- "><tt><i>291</i> <span class="sd">            Optional flag. If set to *True* method will calculate some additional model</span></tt>
             </div>
             <div id="l292"
-               class="code sev- "><tt><i>292</i> <span class="sd">        -------</span></tt>
+               class="code sev- "><tt><i>292</i> <span class="sd">            metrics. Method will then return tuple instead of just probabilities.</span></tt>
             </div>
             <div id="l293"
-               class="code sev- "><tt><i>293</i> <span class="sd">        result :</span></tt>
+               class="code sev- "><tt><i>293</i> &nbsp;</tt>
             </div>
             <div id="l294"
-               class="code sev- "><tt><i>294</i> <span class="sd">        Union[</span></tt>
+               class="code sev- "><tt><i>294</i> <span class="sd">        Returns</span></tt>
             </div>
             <div id="l295"
-               class="code sev- "><tt><i>295</i> <span class="sd">            np.ndarray,</span></tt>
+               class="code sev- "><tt><i>295</i> <span class="sd">        -------</span></tt>
             </div>
             <div id="l296"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (94 > 79 characters)</li>
-               
-               </ul><tt><i>296</i> <span class="sd">            tuple[np.ndarray, :class:`rulekit.classification.ClassificationPredictionMetrics`]</span></tt>
+               class="code sev- "><tt><i>296</i> <span class="sd">        result : Union[np.ndarray, tuple[np.ndarray, :class:`rulekit.classification.\</span></tt>
             </div>
             <div id="l297"
-               class="code sev- "><tt><i>297</i> <span class="sd">        ]</span></tt>
+               class="code sev- "><tt><i>297</i> <span class="sd">            ClassificationPredictionMetrics`]]</span></tt>
             </div>
             <div id="l298"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (95 > 79 characters)</li>
-               
-               </ul><tt><i>298</i> <span class="sd">        If *return_metrics* flag wasn&#39;t set it will return just probabilities matrix, otherwise</span></tt>
+               class="code sev- "><tt><i>298</i> <span class="sd">            If *return_metrics* flag wasn&#39;t set it will return just probabilities</span></tt>
             </div>
             <div id="l299"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (98 > 79 characters)</li>
-               
-               </ul><tt><i>299</i> <span class="sd">        a tuple will be returned with first element being prediction and second one being metrics.</span></tt>
+               class="code sev- "><tt><i>299</i> <span class="sd">            matrix, otherwise a tuple will be returned with first element being</span></tt>
             </div>
             <div id="l300"
-               class="code sev- "><tt><i>300</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
+               class="code sev- "><tt><i>300</i> <span class="sd">            prediction and second one being metrics.</span></tt>
             </div>
             <div id="l301"
-               class="code sev- "><tt><i>301</i>         <span class="n">result_example_set</span> <span class="o">=</span> <span class="n">BaseOperator</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">)</span></tt>
+               class="code sev- "><tt><i>301</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
             </div>
             <div id="l302"
-               class="code sev- "><tt><i>302</i>         <span class="n">mapped_result_example_set</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_map_confidence</span><span class="p">(</span><span class="n">result_example_set</span><span class="p">)</span></tt>
+               class="code sev- "><tt><i>302</i>         <span class="n">result_example_set</span> <span class="o">=</span> <span class="n">BaseOperator</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">)</span></tt>
             </div>
             <div id="l303"
-               class="code sev- "><tt><i>303</i>         <span class="k">if</span> <span class="n">return_metrics</span><span class="p">:</span></tt>
+               class="code sev- "><tt><i>303</i>         <span class="n">mapped_result_example_set</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_map_confidence</span><span class="p">(</span><span class="n">result_example_set</span><span class="p">)</span></tt>
             </div>
             <div id="l304"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (80 > 79 characters)</li>
-               
-               </ul><tt><i>304</i>             <span class="n">metrics_values</span><span class="p">:</span> <span class="nb">dict</span> <span class="o">=</span> <span class="n">BaseClassifier</span><span class="o">.</span><span class="n">_calculate_prediction_metrics</span><span class="p">(</span></tt>
+               class="code sev- "><tt><i>304</i>         <span class="k">if</span> <span class="n">return_metrics</span><span class="p">:</span></tt>
             </div>
             <div id="l305"
-               class="code sev- "><tt><i>305</i>                 <span class="bp">self</span><span class="p">,</span> <span class="n">result_example_set</span><span class="p">)</span></tt>
+               class="code sev- "><tt><i>305</i>             <span class="n">metrics_values</span><span class="p">:</span> <span class="nb">dict</span> <span class="o">=</span> <span class="n">BaseClassifier</span><span class="o">.</span><span class="n">_calculate_prediction_metrics</span><span class="p">(</span></tt>
             </div>
             <div id="l306"
-               class="code sev- "><tt><i>306</i>             <span class="k">return</span> <span class="p">(</span><span class="n">mapped_result_example_set</span><span class="p">,</span> <span class="n">metrics_values</span><span class="p">)</span></tt>
+               class="code sev- "><tt><i>306</i>                 <span class="bp">self</span><span class="p">,</span> <span class="n">result_example_set</span></tt>
             </div>
             <div id="l307"
-               class="code sev- "><tt><i>307</i>         <span class="k">return</span> <span class="n">mapped_result_example_set</span></tt>
+               class="code sev- "><tt><i>307</i>             <span class="p">)</span></tt>
             </div>
             <div id="l308"
-               class="code sev- "><tt><i>308</i> &nbsp;</tt>
+               class="code sev- "><tt><i>308</i>             <span class="k">return</span> <span class="p">(</span><span class="n">mapped_result_example_set</span><span class="p">,</span> <span class="n">metrics_values</span><span class="p">)</span></tt>
             </div>
             <div id="l309"
-               class="code sev- "><tt><i>309</i>     <span class="k">def</span> <span class="nf">score</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">:</span> <span class="n">Data</span><span class="p">,</span> <span class="n">labels</span><span class="p">:</span> <span class="n">Data</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">float</span><span class="p">:</span></tt>
+               class="code sev- "><tt><i>309</i>         <span class="k">return</span> <span class="n">mapped_result_example_set</span></tt>
             </div>
             <div id="l310"
-               class="code sev- "><tt><i>310</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Return the accuracy on the given test data and labels.</span></tt>
+               class="code sev- "><tt><i>310</i> &nbsp;</tt>
             </div>
             <div id="l311"
-               class="code sev- "><tt><i>311</i> &nbsp;</tt>
+               class="code sev- "><tt><i>311</i>     <span class="k">def</span> <span class="nf">score</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">:</span> <span class="n">Data</span><span class="p">,</span> <span class="n">labels</span><span class="p">:</span> <span class="n">Data</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">float</span><span class="p">:</span></tt>
             </div>
             <div id="l312"
-               class="code sev- "><tt><i>312</i> <span class="sd">        Parameters</span></tt>
+               class="code sev- "><tt><i>312</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Return the accuracy on the given test data and labels.</span></tt>
             </div>
             <div id="l313"
-               class="code sev- "><tt><i>313</i> <span class="sd">        ----------</span></tt>
+               class="code sev- "><tt><i>313</i> &nbsp;</tt>
             </div>
             <div id="l314"
-               class="code sev- "><tt><i>314</i> <span class="sd">        values : :class:`rulekit.operator.Data`</span></tt>
+               class="code sev- "><tt><i>314</i> <span class="sd">        Parameters</span></tt>
             </div>
             <div id="l315"
-               class="code sev- "><tt><i>315</i> <span class="sd">            attributes</span></tt>
+               class="code sev- "><tt><i>315</i> <span class="sd">        ----------</span></tt>
             </div>
             <div id="l316"
-               class="code sev- "><tt><i>316</i> <span class="sd">        labels : :class:`rulekit.operator.Data`</span></tt>
+               class="code sev- "><tt><i>316</i> <span class="sd">        values : :class:`rulekit.operator.Data`</span></tt>
             </div>
             <div id="l317"
-               class="code sev- "><tt><i>317</i> <span class="sd">            true labels</span></tt>
+               class="code sev- "><tt><i>317</i> <span class="sd">            attributes</span></tt>
             </div>
             <div id="l318"
-               class="code sev- "><tt><i>318</i> &nbsp;</tt>
+               class="code sev- "><tt><i>318</i> <span class="sd">        labels : :class:`rulekit.operator.Data`</span></tt>
             </div>
             <div id="l319"
-               class="code sev- "><tt><i>319</i> <span class="sd">        Returns</span></tt>
+               class="code sev- "><tt><i>319</i> <span class="sd">            true labels</span></tt>
             </div>
             <div id="l320"
-               class="code sev- "><tt><i>320</i> <span class="sd">        -------</span></tt>
+               class="code sev- "><tt><i>320</i> &nbsp;</tt>
             </div>
             <div id="l321"
-               class="code sev- "><tt><i>321</i> <span class="sd">        score : float</span></tt>
+               class="code sev- "><tt><i>321</i> <span class="sd">        Returns</span></tt>
             </div>
             <div id="l322"
-               class="code sev- "><tt><i>322</i> <span class="sd">            Accuracy of self.predict(values) wrt. labels.</span></tt>
+               class="code sev- "><tt><i>322</i> <span class="sd">        -------</span></tt>
             </div>
             <div id="l323"
-               class="code sev- "><tt><i>323</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
+               class="code sev- "><tt><i>323</i> <span class="sd">        score : float</span></tt>
             </div>
             <div id="l324"
-               class="code sev- "><tt><i>324</i>         <span class="n">predicted_labels</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">values</span><span class="p">)</span></tt>
+               class="code sev- "><tt><i>324</i> <span class="sd">            Accuracy of self.predict(values) wrt. labels.</span></tt>
             </div>
             <div id="l325"
-               class="code sev- "><tt><i>325</i>         <span class="k">return</span> <span class="n">metrics</span><span class="o">.</span><span class="n">accuracy_score</span><span class="p">(</span><span class="n">labels</span><span class="p">,</span> <span class="n">predicted_labels</span><span class="p">)</span></tt>
+               class="code sev- "><tt><i>325</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
             </div>
             <div id="l326"
-               class="code sev- "><tt><i>326</i> &nbsp;</tt>
+               class="code sev- "><tt><i>326</i>         <span class="n">predicted_labels</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">values</span><span class="p">)</span></tt>
             </div>
             <div id="l327"
-               class="code sev- "><tt><i>327</i>     <span class="k">def</span> <span class="nf">__getstate__</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">dict</span><span class="p">:</span></tt>
+               class="code sev- "><tt><i>327</i>         <span class="k">return</span> <span class="n">metrics</span><span class="o">.</span><span class="n">accuracy_score</span><span class="p">(</span><span class="n">labels</span><span class="p">,</span> <span class="n">predicted_labels</span><span class="p">)</span></tt>
             </div>
             <div id="l328"
-               class="code sev- "><tt><i>328</i>         <span class="k">return</span> <span class="p">{</span><span class="o">**</span><span class="n">BaseOperator</span><span class="o">.</span><span class="n">__getstate__</span><span class="p">(</span><span class="bp">self</span><span class="p">),</span> <span class="o">**</span><span class="p">{</span></tt>
+               class="code sev- "><tt><i>328</i> &nbsp;</tt>
             </div>
             <div id="l329"
-               class="code sev- "><tt><i>329</i>             <span class="s1">&#39;label_unique_values&#39;</span><span class="p">:</span> <span class="bp">self</span><span class="o">.</span><span class="n">label_unique_values</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>329</i>     <span class="k">def</span> <span class="nf">__getstate__</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">dict</span><span class="p">:</span></tt>
             </div>
             <div id="l330"
-               class="code sev- "><tt><i>330</i>             <span class="s1">&#39;_remap_to_numeric&#39;</span><span class="p">:</span> <span class="bp">self</span><span class="o">.</span><span class="n">_remap_to_numeric</span></tt>
+               class="code sev- "><tt><i>330</i>         <span class="k">return</span> <span class="p">{</span></tt>
             </div>
             <div id="l331"
-               class="code sev- "><tt><i>331</i>         <span class="p">}}</span></tt>
+               class="code sev- "><tt><i>331</i>             <span class="o">**</span><span class="n">BaseOperator</span><span class="o">.</span><span class="n">__getstate__</span><span class="p">(</span><span class="bp">self</span><span class="p">),</span></tt>
             </div>
             <div id="l332"
-               class="code sev- "><tt><i>332</i> &nbsp;</tt>
+               class="code sev- "><tt><i>332</i>             <span class="o">**</span><span class="p">{</span></tt>
             </div>
             <div id="l333"
-               class="code sev- "><tt><i>333</i>     <span class="k">def</span> <span class="nf">__setstate__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">state</span><span class="p">:</span> <span class="nb">dict</span><span class="p">):</span></tt>
+               class="code sev- "><tt><i>333</i>                 <span class="s2">&quot;label_unique_values&quot;</span><span class="p">:</span> <span class="bp">self</span><span class="o">.</span><span class="n">label_unique_values</span><span class="p">,</span></tt>
             </div>
             <div id="l334"
-               class="code sev- "><tt><i>334</i>         <span class="n">BaseOperator</span><span class="o">.</span><span class="n">__setstate__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">state</span><span class="p">)</span></tt>
+               class="code sev- "><tt><i>334</i>                 <span class="s2">&quot;_remap_to_numeric&quot;</span><span class="p">:</span> <span class="bp">self</span><span class="o">.</span><span class="n">_remap_to_numeric</span><span class="p">,</span></tt>
             </div>
             <div id="l335"
-               class="code sev- "><tt><i>335</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_init_classification_rule_performance_classes</span><span class="p">()</span></tt>
+               class="code sev- "><tt><i>335</i>             <span class="p">},</span></tt>
             </div>
             <div id="l336"
-               class="code sev- "><tt><i>336</i>         <span class="bp">self</span><span class="o">.</span><span class="n">label_unique_values</span> <span class="o">=</span> <span class="n">state</span><span class="p">[</span><span class="s1">&#39;label_unique_values&#39;</span><span class="p">]</span></tt>
+               class="code sev- "><tt><i>336</i>         <span class="p">}</span></tt>
             </div>
             <div id="l337"
-               class="code sev- "><tt><i>337</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_remap_to_numeric</span> <span class="o">=</span> <span class="n">state</span><span class="p">[</span><span class="s1">&#39;_remap_to_numeric&#39;</span><span class="p">]</span></tt>
+               class="code sev- "><tt><i>337</i> &nbsp;</tt>
             </div>
             <div id="l338"
-               class="code sev- "><tt><i>338</i> &nbsp;</tt>
+               class="code sev- "><tt><i>338</i>     <span class="k">def</span> <span class="nf">__setstate__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">state</span><span class="p">:</span> <span class="nb">dict</span><span class="p">):</span></tt>
             </div>
             <div id="l339"
-               class="code sev- "><tt><i>339</i>     <span class="k">def</span> <span class="nf">_get_problem_type</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ProblemType</span><span class="p">:</span></tt>
+               class="code sev- "><tt><i>339</i>         <span class="n">BaseOperator</span><span class="o">.</span><span class="n">__setstate__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">state</span><span class="p">)</span></tt>
             </div>
             <div id="l340"
-               class="code sev- "><tt><i>340</i>         <span class="k">return</span> <span class="n">ProblemType</span><span class="o">.</span><span class="n">CLASSIFICATION</span></tt>
+               class="code sev- "><tt><i>340</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_init_classification_rule_performance_classes</span><span class="p">()</span></tt>
             </div>
             <div id="l341"
-               class="code sev- "><tt><i>341</i> &nbsp;</tt>
+               class="code sev- "><tt><i>341</i>         <span class="bp">self</span><span class="o">.</span><span class="n">label_unique_values</span> <span class="o">=</span> <span class="n">state</span><span class="p">[</span><span class="s2">&quot;label_unique_values&quot;</span><span class="p">]</span></tt>
             </div>
             <div id="l342"
-               class="code sev- "><tt><i>342</i> &nbsp;</tt>
+               class="code sev- "><tt><i>342</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_remap_to_numeric</span> <span class="o">=</span> <span class="n">state</span><span class="p">[</span><span class="s2">&quot;_remap_to_numeric&quot;</span><span class="p">]</span></tt>
             </div>
             <div id="l343"
-               class="code sev- "><tt><i>343</i> <span class="k">class</span> <span class="nc">ExpertRuleClassifier</span><span class="p">(</span><span class="n">ExpertKnowledgeOperator</span><span class="p">,</span> <span class="n">RuleClassifier</span><span class="p">):</span></tt>
+               class="code sev- "><tt><i>343</i> &nbsp;</tt>
             </div>
             <div id="l344"
-               class="code sev- "><tt><i>344</i> <span class="w">    </span><span class="sd">&quot;&quot;&quot;Classification model using expert knowledge.&quot;&quot;&quot;</span></tt>
+               class="code sev- "><tt><i>344</i>     <span class="k">def</span> <span class="nf">_get_problem_type</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ProblemType</span><span class="p">:</span></tt>
             </div>
             <div id="l345"
-               class="code sev- "><tt><i>345</i> &nbsp;</tt>
+               class="code sev- "><tt><i>345</i>         <span class="k">return</span> <span class="n">ProblemType</span><span class="o">.</span><span class="n">CLASSIFICATION</span></tt>
             </div>
             <div id="l346"
-               class="code sev- "><tt><i>346</i>     <span class="n">__params_class__</span> <span class="o">=</span> <span class="n">_ClassificationExpertParams</span></tt>
+               class="code sev- "><tt><i>346</i> &nbsp;</tt>
             </div>
             <div id="l347"
                class="code sev- "><tt><i>347</i> &nbsp;</tt>
             </div>
             <div id="l348"
-               class="code sev- "><tt><i>348</i>     <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span>  <span class="c1"># pylint: disable=too-many-arguments,too-many-locals</span></tt>
+               class="code sev- "><tt><i>348</i> <span class="k">class</span> <span class="nc">ExpertRuleClassifier</span><span class="p">(</span><span class="n">ExpertKnowledgeOperator</span><span class="p">,</span> <span class="n">RuleClassifier</span><span class="p">):</span></tt>
             </div>
             <div id="l349"
-               class="code sev- "><tt><i>349</i>         <span class="bp">self</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>349</i> <span class="w">    </span><span class="sd">&quot;&quot;&quot;Classification model using expert knowledge.&quot;&quot;&quot;</span></tt>
             </div>
             <div id="l350"
-               class="code sev- "><tt><i>350</i>         <span class="n">minsupp_new</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;minsupp_new&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>350</i> &nbsp;</tt>
             </div>
             <div id="l351"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (80 > 79 characters)</li>
-               
-               </ul><tt><i>351</i>         <span class="n">induction_measure</span><span class="p">:</span> <span class="n">Measures</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;induction_measure&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>351</i>     <span class="n">__params_class__</span> <span class="o">=</span> <span class="n">_ClassificationExpertParams</span></tt>
             </div>
             <div id="l352"
-               class="code sev- "><tt><i>352</i>         <span class="n">pruning_measure</span><span class="p">:</span> <span class="n">Union</span><span class="p">[</span><span class="n">Measures</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>352</i> &nbsp;</tt>
             </div>
             <div id="l353"
-               class="code sev- "><tt><i>353</i>                                <span class="nb">str</span><span class="p">]</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;pruning_measure&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>353</i>     <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span>  <span class="c1"># pylint: disable=too-many-arguments,too-many-locals</span></tt>
             </div>
             <div id="l354"
-               class="code sev- "><tt><i>354</i>         <span class="n">voting_measure</span><span class="p">:</span> <span class="n">Measures</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;voting_measure&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>354</i>         <span class="bp">self</span><span class="p">,</span></tt>
             </div>
             <div id="l355"
-               class="code sev- "><tt><i>355</i>         <span class="n">max_growing</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;max_growing&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>355</i>         <span class="n">minsupp_new</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;minsupp_new&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l356"
-               class="code sev- "><tt><i>356</i>         <span class="n">enable_pruning</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;enable_pruning&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>356</i>         <span class="n">induction_measure</span><span class="p">:</span> <span class="n">Measures</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;induction_measure&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l357"
-               class="code sev- "><tt><i>357</i>         <span class="n">ignore_missing</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;ignore_missing&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>357</i>         <span class="n">pruning_measure</span><span class="p">:</span> <span class="n">Union</span><span class="p">[</span><span class="n">Measures</span><span class="p">,</span> <span class="nb">str</span><span class="p">]</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;pruning_measure&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l358"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (87 > 79 characters)</li>
-               
-               </ul><tt><i>358</i>         <span class="n">max_uncovered_fraction</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;max_uncovered_fraction&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>358</i>         <span class="n">voting_measure</span><span class="p">:</span> <span class="n">Measures</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;voting_measure&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l359"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (84 > 79 characters)</li>
-               
-               </ul><tt><i>359</i>         <span class="n">select_best_candidate</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;select_best_candidate&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>359</i>         <span class="n">max_growing</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;max_growing&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l360"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (90 > 79 characters)</li>
-               
-               </ul><tt><i>360</i>         <span class="n">complementary_conditions</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;complementary_conditions&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>360</i>         <span class="n">enable_pruning</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;enable_pruning&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l361"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (92 > 79 characters)</li>
-               
-               </ul><tt><i>361</i>         <span class="n">control_apriori_precision</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;control_apriori_precision&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>361</i>         <span class="n">ignore_missing</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;ignore_missing&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l362"
-               class="code sev- "><tt><i>362</i>         <span class="n">max_rule_count</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;max_rule_count&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>362</i>         <span class="n">max_uncovered_fraction</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;max_uncovered_fraction&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l363"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (84 > 79 characters)</li>
-               
-               </ul><tt><i>363</i>         <span class="n">approximate_induction</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;approximate_induction&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>363</i>         <span class="n">select_best_candidate</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;select_best_candidate&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l364"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (85 > 79 characters)</li>
-               
-               </ul><tt><i>364</i>         <span class="n">approximate_bins_count</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;approximate_bins_count&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>364</i>         <span class="n">complementary_conditions</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span></tt>
             </div>
             <div id="l365"
-               class="code sev- "><tt><i>365</i> &nbsp;</tt>
+               class="code sev- "><tt><i>365</i>             <span class="s2">&quot;complementary_conditions&quot;</span></tt>
             </div>
             <div id="l366"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (86 > 79 characters)</li>
-               
-               </ul><tt><i>366</i>         <span class="n">extend_using_preferred</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;extend_using_preferred&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>366</i>         <span class="p">],</span></tt>
             </div>
             <div id="l367"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (86 > 79 characters)</li>
-               
-               </ul><tt><i>367</i>         <span class="n">extend_using_automatic</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;extend_using_automatic&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>367</i>         <span class="n">control_apriori_precision</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span></tt>
             </div>
             <div id="l368"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (86 > 79 characters)</li>
-               
-               </ul><tt><i>368</i>         <span class="n">induce_using_preferred</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;induce_using_preferred&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>368</i>             <span class="s2">&quot;control_apriori_precision&quot;</span></tt>
             </div>
             <div id="l369"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (86 > 79 characters)</li>
-               
-               </ul><tt><i>369</i>         <span class="n">induce_using_automatic</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;induce_using_automatic&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>369</i>         <span class="p">],</span></tt>
             </div>
             <div id="l370"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (86 > 79 characters)</li>
-               
-               </ul><tt><i>370</i>         <span class="n">consider_other_classes</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;consider_other_classes&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>370</i>         <span class="n">max_rule_count</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;max_rule_count&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l371"
-               class="code sev- "><tt><i>371</i>         <span class="n">preferred_conditions_per_rule</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span></tt>
+               class="code sev- "><tt><i>371</i>         <span class="n">approximate_induction</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;approximate_induction&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l372"
-               class="code sev- "><tt><i>372</i>             <span class="s1">&#39;preferred_conditions_per_rule&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>372</i>         <span class="n">approximate_bins_count</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;approximate_bins_count&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l373"
-               class="code sev- "><tt><i>373</i>         <span class="n">preferred_attributes_per_rule</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span></tt>
+               class="code sev- "><tt><i>373</i>         <span class="n">extend_using_preferred</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;extend_using_preferred&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l374"
-               class="code sev- "><tt><i>374</i>             <span class="s1">&#39;preferred_attributes_per_rule&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>374</i>         <span class="n">extend_using_automatic</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;extend_using_automatic&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l375"
-               class="code sev- "><tt><i>375</i>     <span class="p">):</span></tt>
+               class="code sev- "><tt><i>375</i>         <span class="n">induce_using_preferred</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;induce_using_preferred&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l376"
-               class="code sev- "><tt><i>376</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;</span></tt>
+               class="code sev- "><tt><i>376</i>         <span class="n">induce_using_automatic</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;induce_using_automatic&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l377"
-               class="code sev- "><tt><i>377</i> <span class="sd">        Parameters</span></tt>
+               class="code sev- "><tt><i>377</i>         <span class="n">consider_other_classes</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;consider_other_classes&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l378"
-               class="code sev- "><tt><i>378</i> <span class="sd">        ----------</span></tt>
+               class="code sev- "><tt><i>378</i>         <span class="n">preferred_conditions_per_rule</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span></tt>
             </div>
             <div id="l379"
-               class="code sev- "><tt><i>379</i> <span class="sd">        minsupp_new : float = 5.0</span></tt>
+               class="code sev- "><tt><i>379</i>             <span class="s2">&quot;preferred_conditions_per_rule&quot;</span></tt>
             </div>
             <div id="l380"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (87 > 79 characters)</li>
-               
-               </ul><tt><i>380</i> <span class="sd">        a minimum number (or fraction, if value &lt; 1.0) of previously uncovered examples</span></tt>
+               class="code sev- "><tt><i>380</i>         <span class="p">],</span></tt>
             </div>
             <div id="l381"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (84 > 79 characters)</li>
-               
-               </ul><tt><i>381</i> <span class="sd">        to be covered by a new rule (positive examples for classification problems);</span></tt>
+               class="code sev- "><tt><i>381</i>         <span class="n">preferred_attributes_per_rule</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span></tt>
             </div>
             <div id="l382"
-               class="code sev- "><tt><i>382</i> <span class="sd">        default: 5,</span></tt>
+               class="code sev- "><tt><i>382</i>             <span class="s2">&quot;preferred_attributes_per_rule&quot;</span></tt>
             </div>
             <div id="l383"
-               class="code sev- "><tt><i>383</i> &nbsp;</tt>
+               class="code sev- "><tt><i>383</i>         <span class="p">],</span></tt>
             </div>
             <div id="l384"
-               class="code sev- "><tt><i>384</i> <span class="sd">        induction_measure : :class:`rulekit.params.Measures` = \</span></tt>
+               class="code sev- "><tt><i>384</i>     <span class="p">):</span></tt>
             </div>
             <div id="l385"
-               class="code sev- "><tt><i>385</i> <span class="sd">            :class:`rulekit.params.Measures.Correlation`</span></tt>
+               class="code sev- "><tt><i>385</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;</span></tt>
             </div>
             <div id="l386"
-               class="code sev- "><tt><i>386</i> <span class="sd">            measure used during induction; default measure is correlation</span></tt>
+               class="code sev- "><tt><i>386</i> <span class="sd">        Parameters</span></tt>
             </div>
             <div id="l387"
-               class="code sev- "><tt><i>387</i> <span class="sd">        pruning_measure : Union[:class:`rulekit.params.Measures`, str] = \</span></tt>
+               class="code sev- "><tt><i>387</i> <span class="sd">        ----------</span></tt>
             </div>
             <div id="l388"
-               class="code sev- "><tt><i>388</i> <span class="sd">            :class:`rulekit.params.Measures.Correlation`</span></tt>
+               class="code sev- "><tt><i>388</i> <span class="sd">        minsupp_new : float = 5.0</span></tt>
             </div>
             <div id="l389"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (84 > 79 characters)</li>
-               
-               </ul><tt><i>389</i> <span class="sd">            measure used during pruning. Could be user defined (string), for example</span></tt>
+               class="code sev- "><tt><i>389</i> <span class="sd">        a minimum number (or fraction, if value &lt; 1.0) of previously uncovered examples</span></tt>
             </div>
             <div id="l390"
-               class="code sev- "><tt><i>390</i> <span class="sd">             :code:`2 * p / n`; default measure is correlation</span></tt>
+               class="code sev- "><tt><i>390</i> <span class="sd">        to be covered by a new rule (positive examples for classification problems);</span></tt>
             </div>
             <div id="l391"
-               class="code sev- "><tt><i>391</i> <span class="sd">        voting_measure : :class:`rulekit.params.Measures` = \</span></tt>
+               class="code sev- "><tt><i>391</i> <span class="sd">        default: 5,</span></tt>
             </div>
             <div id="l392"
-               class="code sev- "><tt><i>392</i> <span class="sd">            :class:`rulekit.params.Measures.Correlation`</span></tt>
+               class="code sev- "><tt><i>392</i> &nbsp;</tt>
             </div>
             <div id="l393"
-               class="code sev- "><tt><i>393</i> <span class="sd">            measure used during voting; default measure is correlation</span></tt>
+               class="code sev- "><tt><i>393</i> <span class="sd">        induction_measure : :class:`rulekit.params.Measures` = \</span></tt>
             </div>
             <div id="l394"
-               class="code sev- "><tt><i>394</i> <span class="sd">        max_growing : int = 0.0</span></tt>
+               class="code sev- "><tt><i>394</i> <span class="sd">            :class:`rulekit.params.Measures.Correlation`</span></tt>
             </div>
             <div id="l395"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (96 > 79 characters)</li>
-               
-               </ul><tt><i>395</i> <span class="sd">            non-negative integer representing maximum number of conditions which can be added to</span></tt>
+               class="code sev- "><tt><i>395</i> <span class="sd">            measure used during induction; default measure is correlation</span></tt>
             </div>
             <div id="l396"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (98 > 79 characters)</li>
-               
-               </ul><tt><i>396</i> <span class="sd">            the rule in the growing phase (use this parameter for large datasets if execution time</span></tt>
+               class="code sev- "><tt><i>396</i> <span class="sd">        pruning_measure : Union[:class:`rulekit.params.Measures`, str] = \</span></tt>
             </div>
             <div id="l397"
-               class="code sev- "><tt><i>397</i> <span class="sd">            is prohibitive); 0 indicates no limit; default: 0,</span></tt>
+               class="code sev- "><tt><i>397</i> <span class="sd">            :class:`rulekit.params.Measures.Correlation`</span></tt>
             </div>
             <div id="l398"
-               class="code sev- "><tt><i>398</i> <span class="sd">        enable_pruning : bool = True</span></tt>
+               class="code sev- "><tt><i>398</i> <span class="sd">            measure used during pruning. Could be user defined (string), for example</span></tt>
             </div>
             <div id="l399"
-               class="code sev- "><tt><i>399</i> <span class="sd">            enable or disable pruning, default is True.</span></tt>
+               class="code sev- "><tt><i>399</i> <span class="sd">             :code:`2 * p / n`; default measure is correlation</span></tt>
             </div>
             <div id="l400"
-               class="code sev- "><tt><i>400</i> <span class="sd">        ignore_missing : bool = False</span></tt>
+               class="code sev- "><tt><i>400</i> <span class="sd">        voting_measure : :class:`rulekit.params.Measures` = \</span></tt>
             </div>
             <div id="l401"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (97 > 79 characters)</li>
-               
-               </ul><tt><i>401</i> <span class="sd">            boolean telling whether missing values should be ignored (by default, a missing value</span></tt>
+               class="code sev- "><tt><i>401</i> <span class="sd">            :class:`rulekit.params.Measures.Correlation`</span></tt>
             </div>
             <div id="l402"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (94 > 79 characters)</li>
-               
-               </ul><tt><i>402</i> <span class="sd">            of given attribute is always considered as not fulfilling the condition build upon</span></tt>
+               class="code sev- "><tt><i>402</i> <span class="sd">            measure used during voting; default measure is correlation</span></tt>
             </div>
             <div id="l403"
-               class="code sev- "><tt><i>403</i> <span class="sd">             that attribute); default: False.</span></tt>
+               class="code sev- "><tt><i>403</i> <span class="sd">        max_growing : int = 0.0</span></tt>
             </div>
             <div id="l404"
-               class="code sev- "><tt><i>404</i> <span class="sd">        max_uncovered_fraction : float = 0.0</span></tt>
+               class="code sev- "><tt><i>404</i> <span class="sd">            non-negative integer representing maximum number of conditions which can be</span></tt>
             </div>
             <div id="l405"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (95 > 79 characters)</li>
-               
-               </ul><tt><i>405</i> <span class="sd">            Floating-point number from [0,1] interval representing maximum fraction of examples</span></tt>
+               class="code sev- "><tt><i>405</i> <span class="sd">            added to the rule in the growing phase (use this parameter for large</span></tt>
             </div>
             <div id="l406"
-               class="code sev- "><tt><i>406</i> <span class="sd">            that may remain uncovered by the rule set, default: 0.0.</span></tt>
-            </div>
-            <div id="l407"
-               class="code sev- "><tt><i>407</i> <span class="sd">        select_best_candidate : bool = False</span></tt>
+               class="code sev- "><tt><i>406</i> <span class="sd">            datasets if execution time is prohibitive); 0 indicates no limit; default: 0</span></tt>
             </div>
-            <div id="l408"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (94 > 79 characters)</li>
-               
-               </ul><tt><i>408</i> <span class="sd">            Flag determining if best candidate should be selected from growing phase; default:</span></tt>
+            <div id="l407"
+               class="code sev- "><tt><i>407</i> <span class="sd">        enable_pruning : bool = True</span></tt>
+            </div>
+            <div id="l408"
+               class="code sev- "><tt><i>408</i> <span class="sd">            enable or disable pruning, default is True.</span></tt>
             </div>
             <div id="l409"
-               class="code sev- "><tt><i>409</i> <span class="sd">             False.</span></tt>
+               class="code sev- "><tt><i>409</i> <span class="sd">        ignore_missing : bool = False</span></tt>
             </div>
             <div id="l410"
-               class="code sev- "><tt><i>410</i> <span class="sd">        complementary_conditions : bool = False</span></tt>
+               class="code sev- "><tt><i>410</i> <span class="sd">            boolean telling whether missing values should be ignored (by default, a</span></tt>
             </div>
             <div id="l411"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (96 > 79 characters)</li>
-               
-               </ul><tt><i>411</i> <span class="sd">            If enabled, complementary conditions in the form a = !{value} for nominal attributes</span></tt>
+               class="code sev- "><tt><i>411</i> <span class="sd">            missing value of given attribute is always considered as not fulfilling the</span></tt>
             </div>
             <div id="l412"
-               class="code sev- "><tt><i>412</i> <span class="sd">            are supported.</span></tt>
+               class="code sev- "><tt><i>412</i> <span class="sd">            condition build upon that attribute); default: False.</span></tt>
             </div>
             <div id="l413"
-               class="code sev- "><tt><i>413</i> <span class="sd">        control_apriori_precision : bool = True</span></tt>
+               class="code sev- "><tt><i>413</i> <span class="sd">        max_uncovered_fraction : float = 0.0</span></tt>
             </div>
             <div id="l414"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (92 > 79 characters)</li>
-               
-               </ul><tt><i>414</i> <span class="sd">            When inducing classification rules, verify if candidate precision is higher than</span></tt>
+               class="code sev- "><tt><i>414</i> <span class="sd">            Floating-point number from [0,1] interval representing maximum fraction of</span></tt>
             </div>
             <div id="l415"
-               class="code sev- "><tt><i>415</i> <span class="sd">             apriori precision of the investigated class.</span></tt>
+               class="code sev- "><tt><i>415</i> <span class="sd">            examples that may remain uncovered by the rule set, default: 0.0.</span></tt>
             </div>
             <div id="l416"
-               class="code sev- "><tt><i>416</i> <span class="sd">        max_rule_count : int = 0</span></tt>
+               class="code sev- "><tt><i>416</i> <span class="sd">        select_best_candidate : bool = False</span></tt>
             </div>
             <div id="l417"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (92 > 79 characters)</li>
-               
-               </ul><tt><i>417</i> <span class="sd">            Maximum number of rules to be generated (for classification data sets it applies</span></tt>
+               class="code sev- "><tt><i>417</i> <span class="sd">            Flag determining if best candidate should be selected from growing phase;</span></tt>
             </div>
             <div id="l418"
-               class="code sev- "><tt><i>418</i> <span class="sd">             to a single class); 0 indicates no limit.</span></tt>
+               class="code sev- "><tt><i>418</i> <span class="sd">            default: False.</span></tt>
             </div>
             <div id="l419"
-               class="code sev- "><tt><i>419</i> <span class="sd">        approximate_induction: bool = False</span></tt>
+               class="code sev- "><tt><i>419</i> <span class="sd">        complementary_conditions : bool = False</span></tt>
             </div>
             <div id="l420"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (92 > 79 characters)</li>
-               
-               </ul><tt><i>420</i> <span class="sd">            Use an approximate induction heuristic which does not check all possible splits;</span></tt>
+               class="code sev- "><tt><i>420</i> <span class="sd">            If enabled, complementary conditions in the form a = !{value} for nominal</span></tt>
             </div>
             <div id="l421"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (93 > 79 characters)</li>
-               
-               </ul><tt><i>421</i> <span class="sd">            note: this is an experimental feature and currently works only for classification</span></tt>
+               class="code sev- "><tt><i>421</i> <span class="sd">            attributes</span></tt>
             </div>
             <div id="l422"
-               class="code sev- "><tt><i>422</i> <span class="sd">            data sets, results may change in future;</span></tt>
+               class="code sev- "><tt><i>422</i> <span class="sd">            are supported.</span></tt>
             </div>
             <div id="l423"
-               class="code sev- "><tt><i>423</i> <span class="sd">        approximate_bins_count: int = 100</span></tt>
+               class="code sev- "><tt><i>423</i> <span class="sd">        control_apriori_precision : bool = True</span></tt>
             </div>
             <div id="l424"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (91 > 79 characters)</li>
-               
-               </ul><tt><i>424</i> <span class="sd">            maximum number of bins for an attribute evaluated in the approximate induction.</span></tt>
+               class="code sev- "><tt><i>424</i> <span class="sd">            When inducing classification rules, verify if candidate precision is higher</span></tt>
             </div>
             <div id="l425"
-               class="code sev- "><tt><i>425</i> &nbsp;</tt>
+               class="code sev- "><tt><i>425</i> <span class="sd">            than apriori precision of the investigated class.</span></tt>
             </div>
             <div id="l426"
-               class="code sev- "><tt><i>426</i> <span class="sd">        extend_using_preferred : bool = False</span></tt>
+               class="code sev- "><tt><i>426</i> <span class="sd">        max_rule_count : int = 0</span></tt>
             </div>
             <div id="l427"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (95 > 79 characters)</li>
-               
-               </ul><tt><i>427</i> <span class="sd">            boolean indicating whether initial rules should be extended with a use of preferred</span></tt>
+               class="code sev- "><tt><i>427</i> <span class="sd">            Maximum number of rules to be generated (for classification data sets it</span></tt>
             </div>
             <div id="l428"
-               class="code sev- "><tt><i>428</i> <span class="sd">            conditions and attributes; default is False</span></tt>
+               class="code sev- "><tt><i>428</i> <span class="sd">            applies to a single class); 0 indicates no limit.</span></tt>
             </div>
             <div id="l429"
-               class="code sev- "><tt><i>429</i> <span class="sd">        extend_using_automatic : bool = False</span></tt>
+               class="code sev- "><tt><i>429</i> <span class="sd">        approximate_induction: bool = False</span></tt>
             </div>
             <div id="l430"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (95 > 79 characters)</li>
-               
-               </ul><tt><i>430</i> <span class="sd">            boolean indicating whether initial rules should be extended with a use of automatic</span></tt>
+               class="code sev- "><tt><i>430</i> <span class="sd">            Use an approximate induction heuristic which does not check all possible</span></tt>
             </div>
             <div id="l431"
-               class="code sev- "><tt><i>431</i> <span class="sd">             conditions and attributes; default is False</span></tt>
+               class="code sev- "><tt><i>431</i> <span class="sd">            splits; note: this is an experimental feature and currently works only for</span></tt>
             </div>
             <div id="l432"
-               class="code sev- "><tt><i>432</i> <span class="sd">        induce_using_preferred : bool = False</span></tt>
+               class="code sev- "><tt><i>432</i> <span class="sd">            classification data sets, results may change in future;</span></tt>
             </div>
             <div id="l433"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (90 > 79 characters)</li>
-               
-               </ul><tt><i>433</i> <span class="sd">            boolean indicating whether new rules should be induced with a use of preferred</span></tt>
+               class="code sev- "><tt><i>433</i> <span class="sd">        approximate_bins_count: int = 100</span></tt>
             </div>
             <div id="l434"
-               class="code sev- "><tt><i>434</i> <span class="sd">             conditions and attributes; default is False</span></tt>
+               class="code sev- "><tt><i>434</i> <span class="sd">            maximum number of bins for an attribute evaluated in the approximate</span></tt>
             </div>
             <div id="l435"
-               class="code sev- "><tt><i>435</i> <span class="sd">        induce_using_automatic : bool = False</span></tt>
+               class="code sev- "><tt><i>435</i> <span class="sd">            induction.</span></tt>
             </div>
             <div id="l436"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (90 > 79 characters)</li>
-               
-               </ul><tt><i>436</i> <span class="sd">            boolean indicating whether new rules should be induced with a use of automatic</span></tt>
+               class="code sev- "><tt><i>436</i> &nbsp;</tt>
             </div>
             <div id="l437"
-               class="code sev- "><tt><i>437</i> <span class="sd">             conditions and attributes; default is False</span></tt>
+               class="code sev- "><tt><i>437</i> <span class="sd">        extend_using_preferred : bool = False</span></tt>
             </div>
             <div id="l438"
-               class="code sev- "><tt><i>438</i> <span class="sd">        consider_other_classes : bool = False</span></tt>
+               class="code sev- "><tt><i>438</i> <span class="sd">            boolean indicating whether initial rules should be extended with a use of</span></tt>
             </div>
             <div id="l439"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (94 > 79 characters)</li>
-               
-               </ul><tt><i>439</i> <span class="sd">            boolean indicating whether automatic induction should be performed for classes for</span></tt>
+               class="code sev- "><tt><i>439</i> <span class="sd">            preferred conditions and attributes; default is False</span></tt>
             </div>
             <div id="l440"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (97 > 79 characters)</li>
-               
-               </ul><tt><i>440</i> <span class="sd">              which no user&#39;s knowledge has been defined (classification only); default is False.</span></tt>
+               class="code sev- "><tt><i>440</i> <span class="sd">        extend_using_automatic : bool = False</span></tt>
             </div>
             <div id="l441"
-               class="code sev- "><tt><i>441</i> <span class="sd">        preferred_conditions_per_rule : int = None</span></tt>
+               class="code sev- "><tt><i>441</i> <span class="sd">            boolean indicating whether initial rules should be extended with a use of</span></tt>
             </div>
             <div id="l442"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (80 > 79 characters)</li>
-               
-               </ul><tt><i>442</i> <span class="sd">            maximum number of preferred conditions per rule; default: unlimited,</span></tt>
+               class="code sev- "><tt><i>442</i> <span class="sd">            automatic conditions and attributes; default is False</span></tt>
             </div>
             <div id="l443"
-               class="code sev- "><tt><i>443</i> <span class="sd">        preferred_attributes_per_rule : int = None</span></tt>
+               class="code sev- "><tt><i>443</i> <span class="sd">        induce_using_preferred : bool = False</span></tt>
             </div>
             <div id="l444"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (80 > 79 characters)</li>
-               
-               </ul><tt><i>444</i> <span class="sd">            maximum number of preferred attributes per rule; default: unlimited.</span></tt>
+               class="code sev- "><tt><i>444</i> <span class="sd">            boolean indicating whether new rules should be induced with a use of</span></tt>
             </div>
             <div id="l445"
-               class="code sev- "><tt><i>445</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
+               class="code sev- "><tt><i>445</i> <span class="sd">            preferred conditions and attributes; default is False</span></tt>
             </div>
             <div id="l446"
-               class="code sev- "><tt><i>446</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_remap_to_numeric</span> <span class="o">=</span> <span class="kc">False</span></tt>
+               class="code sev- "><tt><i>446</i> <span class="sd">        induce_using_automatic : bool = False</span></tt>
             </div>
             <div id="l447"
-               class="code sev- "><tt><i>447</i>         <span class="n">RuleClassifier</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span></tt>
+               class="code sev- "><tt><i>447</i> <span class="sd">            boolean indicating whether new rules should be induced with a use of</span></tt>
             </div>
             <div id="l448"
-               class="code sev- "><tt><i>448</i>             <span class="bp">self</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>448</i> <span class="sd">            automatic conditions and attributes; default is False</span></tt>
             </div>
             <div id="l449"
-               class="code sev- "><tt><i>449</i>             <span class="n">minsupp_new</span><span class="o">=</span><span class="n">minsupp_new</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>449</i> <span class="sd">        consider_other_classes : bool = False</span></tt>
             </div>
             <div id="l450"
-               class="code sev- "><tt><i>450</i>             <span class="n">induction_measure</span><span class="o">=</span><span class="n">induction_measure</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>450</i> <span class="sd">            boolean indicating whether automatic induction should be performed for</span></tt>
             </div>
             <div id="l451"
-               class="code sev- "><tt><i>451</i>             <span class="n">pruning_measure</span><span class="o">=</span><span class="n">pruning_measure</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>451</i> <span class="sd">            classes for which no user&#39;s knowledge has been defined</span></tt>
             </div>
             <div id="l452"
-               class="code sev- "><tt><i>452</i>             <span class="n">voting_measure</span><span class="o">=</span><span class="n">voting_measure</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>452</i> <span class="sd">            (classification only); default is False.</span></tt>
             </div>
             <div id="l453"
-               class="code sev- "><tt><i>453</i>             <span class="n">max_growing</span><span class="o">=</span><span class="n">max_growing</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>453</i> <span class="sd">        preferred_conditions_per_rule : int = None</span></tt>
             </div>
             <div id="l454"
-               class="code sev- "><tt><i>454</i>             <span class="n">enable_pruning</span><span class="o">=</span><span class="n">enable_pruning</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>454</i> <span class="sd">            maximum number of preferred conditions per rule; default: unlimited,</span></tt>
             </div>
             <div id="l455"
-               class="code sev- "><tt><i>455</i>             <span class="n">ignore_missing</span><span class="o">=</span><span class="n">ignore_missing</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>455</i> <span class="sd">        preferred_attributes_per_rule : int = None</span></tt>
             </div>
             <div id="l456"
-               class="code sev- "><tt><i>456</i>             <span class="n">max_uncovered_fraction</span><span class="o">=</span><span class="n">max_uncovered_fraction</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>456</i> <span class="sd">            maximum number of preferred attributes per rule; default: unlimited.</span></tt>
             </div>
             <div id="l457"
-               class="code sev- "><tt><i>457</i>             <span class="n">select_best_candidate</span><span class="o">=</span><span class="n">select_best_candidate</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>457</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
             </div>
             <div id="l458"
-               class="code sev- "><tt><i>458</i>             <span class="n">complementary_conditions</span><span class="o">=</span><span class="n">complementary_conditions</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>458</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_remap_to_numeric</span> <span class="o">=</span> <span class="kc">False</span></tt>
             </div>
             <div id="l459"
-               class="code sev- "><tt><i>459</i>             <span class="n">control_apriori_precision</span><span class="o">=</span><span class="n">control_apriori_precision</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>459</i>         <span class="n">RuleClassifier</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span></tt>
             </div>
             <div id="l460"
-               class="code sev- "><tt><i>460</i>             <span class="n">max_rule_count</span><span class="o">=</span><span class="n">max_rule_count</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>460</i>             <span class="bp">self</span><span class="p">,</span></tt>
             </div>
             <div id="l461"
-               class="code sev- "><tt><i>461</i>             <span class="n">approximate_induction</span><span class="o">=</span><span class="n">approximate_induction</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>461</i>             <span class="n">minsupp_new</span><span class="o">=</span><span class="n">minsupp_new</span><span class="p">,</span></tt>
             </div>
             <div id="l462"
-               class="code sev- "><tt><i>462</i>             <span class="n">approximate_bins_count</span><span class="o">=</span><span class="n">approximate_bins_count</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>462</i>             <span class="n">induction_measure</span><span class="o">=</span><span class="n">induction_measure</span><span class="p">,</span></tt>
             </div>
             <div id="l463"
-               class="code sev- "><tt><i>463</i>         <span class="p">)</span></tt>
+               class="code sev- "><tt><i>463</i>             <span class="n">pruning_measure</span><span class="o">=</span><span class="n">pruning_measure</span><span class="p">,</span></tt>
             </div>
             <div id="l464"
-               class="code sev- "><tt><i>464</i>         <span class="n">ExpertKnowledgeOperator</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span></tt>
+               class="code sev- "><tt><i>464</i>             <span class="n">voting_measure</span><span class="o">=</span><span class="n">voting_measure</span><span class="p">,</span></tt>
             </div>
             <div id="l465"
-               class="code sev- "><tt><i>465</i>             <span class="bp">self</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>465</i>             <span class="n">max_growing</span><span class="o">=</span><span class="n">max_growing</span><span class="p">,</span></tt>
             </div>
             <div id="l466"
-               class="code sev- "><tt><i>466</i>             <span class="n">minsupp_new</span><span class="o">=</span><span class="n">minsupp_new</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>466</i>             <span class="n">enable_pruning</span><span class="o">=</span><span class="n">enable_pruning</span><span class="p">,</span></tt>
             </div>
             <div id="l467"
-               class="code sev- "><tt><i>467</i>             <span class="n">induction_measure</span><span class="o">=</span><span class="n">induction_measure</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>467</i>             <span class="n">ignore_missing</span><span class="o">=</span><span class="n">ignore_missing</span><span class="p">,</span></tt>
             </div>
             <div id="l468"
-               class="code sev- "><tt><i>468</i>             <span class="n">pruning_measure</span><span class="o">=</span><span class="n">pruning_measure</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>468</i>             <span class="n">max_uncovered_fraction</span><span class="o">=</span><span class="n">max_uncovered_fraction</span><span class="p">,</span></tt>
             </div>
             <div id="l469"
-               class="code sev- "><tt><i>469</i>             <span class="n">voting_measure</span><span class="o">=</span><span class="n">voting_measure</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>469</i>             <span class="n">select_best_candidate</span><span class="o">=</span><span class="n">select_best_candidate</span><span class="p">,</span></tt>
             </div>
             <div id="l470"
-               class="code sev- "><tt><i>470</i>             <span class="n">max_growing</span><span class="o">=</span><span class="n">max_growing</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>470</i>             <span class="n">complementary_conditions</span><span class="o">=</span><span class="n">complementary_conditions</span><span class="p">,</span></tt>
             </div>
             <div id="l471"
-               class="code sev- "><tt><i>471</i>             <span class="n">enable_pruning</span><span class="o">=</span><span class="n">enable_pruning</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>471</i>             <span class="n">control_apriori_precision</span><span class="o">=</span><span class="n">control_apriori_precision</span><span class="p">,</span></tt>
             </div>
             <div id="l472"
-               class="code sev- "><tt><i>472</i>             <span class="n">ignore_missing</span><span class="o">=</span><span class="n">ignore_missing</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>472</i>             <span class="n">max_rule_count</span><span class="o">=</span><span class="n">max_rule_count</span><span class="p">,</span></tt>
             </div>
             <div id="l473"
-               class="code sev- "><tt><i>473</i>             <span class="n">max_uncovered_fraction</span><span class="o">=</span><span class="n">max_uncovered_fraction</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>473</i>             <span class="n">approximate_induction</span><span class="o">=</span><span class="n">approximate_induction</span><span class="p">,</span></tt>
             </div>
             <div id="l474"
-               class="code sev- "><tt><i>474</i>             <span class="n">select_best_candidate</span><span class="o">=</span><span class="n">select_best_candidate</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>474</i>             <span class="n">approximate_bins_count</span><span class="o">=</span><span class="n">approximate_bins_count</span><span class="p">,</span></tt>
             </div>
             <div id="l475"
-               class="code sev- "><tt><i>475</i>             <span class="n">complementary_conditions</span><span class="o">=</span><span class="n">complementary_conditions</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>475</i>         <span class="p">)</span></tt>
             </div>
             <div id="l476"
-               class="code sev- "><tt><i>476</i>             <span class="n">extend_using_preferred</span><span class="o">=</span><span class="n">extend_using_preferred</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>476</i>         <span class="n">ExpertKnowledgeOperator</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span></tt>
             </div>
             <div id="l477"
-               class="code sev- "><tt><i>477</i>             <span class="n">extend_using_automatic</span><span class="o">=</span><span class="n">extend_using_automatic</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>477</i>             <span class="bp">self</span><span class="p">,</span></tt>
             </div>
             <div id="l478"
-               class="code sev- "><tt><i>478</i>             <span class="n">induce_using_preferred</span><span class="o">=</span><span class="n">induce_using_preferred</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>478</i>             <span class="n">minsupp_new</span><span class="o">=</span><span class="n">minsupp_new</span><span class="p">,</span></tt>
             </div>
             <div id="l479"
-               class="code sev- "><tt><i>479</i>             <span class="n">induce_using_automatic</span><span class="o">=</span><span class="n">induce_using_automatic</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>479</i>             <span class="n">induction_measure</span><span class="o">=</span><span class="n">induction_measure</span><span class="p">,</span></tt>
             </div>
             <div id="l480"
-               class="code sev- "><tt><i>480</i>             <span class="n">consider_other_classes</span><span class="o">=</span><span class="n">consider_other_classes</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>480</i>             <span class="n">pruning_measure</span><span class="o">=</span><span class="n">pruning_measure</span><span class="p">,</span></tt>
             </div>
             <div id="l481"
-               class="code sev- "><tt><i>481</i>             <span class="n">preferred_conditions_per_rule</span><span class="o">=</span><span class="n">preferred_conditions_per_rule</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>481</i>             <span class="n">voting_measure</span><span class="o">=</span><span class="n">voting_measure</span><span class="p">,</span></tt>
             </div>
             <div id="l482"
-               class="code sev- "><tt><i>482</i>             <span class="n">preferred_attributes_per_rule</span><span class="o">=</span><span class="n">preferred_attributes_per_rule</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>482</i>             <span class="n">max_growing</span><span class="o">=</span><span class="n">max_growing</span><span class="p">,</span></tt>
             </div>
             <div id="l483"
-               class="code sev- "><tt><i>483</i>             <span class="n">control_apriori_precision</span><span class="o">=</span><span class="n">control_apriori_precision</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>483</i>             <span class="n">enable_pruning</span><span class="o">=</span><span class="n">enable_pruning</span><span class="p">,</span></tt>
             </div>
             <div id="l484"
-               class="code sev- "><tt><i>484</i>             <span class="n">max_rule_count</span><span class="o">=</span><span class="n">max_rule_count</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>484</i>             <span class="n">ignore_missing</span><span class="o">=</span><span class="n">ignore_missing</span><span class="p">,</span></tt>
             </div>
             <div id="l485"
-               class="code sev- "><tt><i>485</i>             <span class="n">approximate_induction</span><span class="o">=</span><span class="n">approximate_induction</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>485</i>             <span class="n">max_uncovered_fraction</span><span class="o">=</span><span class="n">max_uncovered_fraction</span><span class="p">,</span></tt>
             </div>
             <div id="l486"
-               class="code sev- "><tt><i>486</i>             <span class="n">approximate_bins_count</span><span class="o">=</span><span class="n">approximate_bins_count</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>486</i>             <span class="n">select_best_candidate</span><span class="o">=</span><span class="n">select_best_candidate</span><span class="p">,</span></tt>
             </div>
             <div id="l487"
-               class="code sev- "><tt><i>487</i>         <span class="p">)</span></tt>
+               class="code sev- "><tt><i>487</i>             <span class="n">complementary_conditions</span><span class="o">=</span><span class="n">complementary_conditions</span><span class="p">,</span></tt>
             </div>
             <div id="l488"
-               class="code sev- "><tt><i>488</i>         <span class="bp">self</span><span class="o">.</span><span class="n">model</span><span class="p">:</span> <span class="n">RuleSet</span><span class="p">[</span><span class="n">ClassificationRule</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span></tt>
+               class="code sev- "><tt><i>488</i>             <span class="n">extend_using_preferred</span><span class="o">=</span><span class="n">extend_using_preferred</span><span class="p">,</span></tt>
             </div>
             <div id="l489"
-               class="code sev- "><tt><i>489</i> &nbsp;</tt>
+               class="code sev- "><tt><i>489</i>             <span class="n">extend_using_automatic</span><span class="o">=</span><span class="n">extend_using_automatic</span><span class="p">,</span></tt>
             </div>
             <div id="l490"
-               class="code sev- "><tt><i>490</i>     <span class="k">def</span> <span class="nf">fit</span><span class="p">(</span>  <span class="c1"># pylint: disable=arguments-differ,too-many-arguments</span></tt>
+               class="code sev- "><tt><i>490</i>             <span class="n">induce_using_preferred</span><span class="o">=</span><span class="n">induce_using_preferred</span><span class="p">,</span></tt>
             </div>
             <div id="l491"
-               class="code sev- "><tt><i>491</i>         <span class="bp">self</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>491</i>             <span class="n">induce_using_automatic</span><span class="o">=</span><span class="n">induce_using_automatic</span><span class="p">,</span></tt>
             </div>
             <div id="l492"
-               class="code sev- "><tt><i>492</i>         <span class="n">values</span><span class="p">:</span> <span class="n">Data</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>492</i>             <span class="n">consider_other_classes</span><span class="o">=</span><span class="n">consider_other_classes</span><span class="p">,</span></tt>
             </div>
             <div id="l493"
-               class="code sev- "><tt><i>493</i>         <span class="n">labels</span><span class="p">:</span> <span class="n">Data</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>493</i>             <span class="n">preferred_conditions_per_rule</span><span class="o">=</span><span class="n">preferred_conditions_per_rule</span><span class="p">,</span></tt>
             </div>
             <div id="l494"
-               class="code sev- "><tt><i>494</i> &nbsp;</tt>
+               class="code sev- "><tt><i>494</i>             <span class="n">preferred_attributes_per_rule</span><span class="o">=</span><span class="n">preferred_attributes_per_rule</span><span class="p">,</span></tt>
             </div>
             <div id="l495"
-               class="code sev- "><tt><i>495</i>         <span class="n">expert_rules</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="n">Union</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="nb">tuple</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="nb">str</span><span class="p">]]]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>495</i>             <span class="n">control_apriori_precision</span><span class="o">=</span><span class="n">control_apriori_precision</span><span class="p">,</span></tt>
             </div>
             <div id="l496"
-               class="code sev- "><tt><i>496</i>         <span class="n">expert_preferred_conditions</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="n">Union</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="nb">tuple</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="nb">str</span><span class="p">]]]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>496</i>             <span class="n">max_rule_count</span><span class="o">=</span><span class="n">max_rule_count</span><span class="p">,</span></tt>
             </div>
             <div id="l497"
-               class="code sev- "><tt><i>497</i>         <span class="n">expert_forbidden_conditions</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="n">Union</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="nb">tuple</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="nb">str</span><span class="p">]]]</span> <span class="o">=</span> <span class="kc">None</span></tt>
+               class="code sev- "><tt><i>497</i>             <span class="n">approximate_induction</span><span class="o">=</span><span class="n">approximate_induction</span><span class="p">,</span></tt>
             </div>
             <div id="l498"
-               class="code sev- "><tt><i>498</i>     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ExpertRuleClassifier</span><span class="p">:</span></tt>
+               class="code sev- "><tt><i>498</i>             <span class="n">approximate_bins_count</span><span class="o">=</span><span class="n">approximate_bins_count</span><span class="p">,</span></tt>
             </div>
             <div id="l499"
-               class="code sev- "><tt><i>499</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Train model on given dataset.</span></tt>
+               class="code sev- "><tt><i>499</i>         <span class="p">)</span></tt>
             </div>
             <div id="l500"
-               class="code sev- "><tt><i>500</i> &nbsp;</tt>
+               class="code sev- "><tt><i>500</i>         <span class="bp">self</span><span class="o">.</span><span class="n">model</span><span class="p">:</span> <span class="n">RuleSet</span><span class="p">[</span><span class="n">ClassificationRule</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span></tt>
             </div>
             <div id="l501"
-               class="code sev- "><tt><i>501</i> <span class="sd">        Parameters</span></tt>
+               class="code sev- "><tt><i>501</i> &nbsp;</tt>
             </div>
             <div id="l502"
-               class="code sev- "><tt><i>502</i> <span class="sd">        ----------</span></tt>
+               class="code sev- "><tt><i>502</i>     <span class="k">def</span> <span class="nf">fit</span><span class="p">(</span>  <span class="c1"># pylint: disable=arguments-differ,too-many-arguments</span></tt>
             </div>
             <div id="l503"
-               class="code sev- "><tt><i>503</i> <span class="sd">        values : :class:`rulekit.operator.Data`</span></tt>
+               class="code sev- "><tt><i>503</i>         <span class="bp">self</span><span class="p">,</span></tt>
             </div>
             <div id="l504"
-               class="code sev- "><tt><i>504</i> <span class="sd">            attributes</span></tt>
+               class="code sev- "><tt><i>504</i>         <span class="n">values</span><span class="p">:</span> <span class="n">Data</span><span class="p">,</span></tt>
             </div>
             <div id="l505"
-               class="code sev- "><tt><i>505</i> <span class="sd">        labels : :class:`rulekit.operator.Data`</span></tt>
+               class="code sev- "><tt><i>505</i>         <span class="n">labels</span><span class="p">:</span> <span class="n">Data</span><span class="p">,</span></tt>
             </div>
             <div id="l506"
-               class="code sev- "><tt><i>506</i> <span class="sd">            labels</span></tt>
+               class="code sev- "><tt><i>506</i>         <span class="n">expert_rules</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="n">Union</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="nb">tuple</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="nb">str</span><span class="p">]]]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span></tt>
             </div>
             <div id="l507"
-               class="code sev- "><tt><i>507</i> &nbsp;</tt>
+               class="code sev- "><tt><i>507</i>         <span class="n">expert_preferred_conditions</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="n">Union</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="nb">tuple</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="nb">str</span><span class="p">]]]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span></tt>
             </div>
             <div id="l508"
-               class="code sev- "><tt><i>508</i> <span class="sd">        expert_rules : List[Union[str, Tuple[str, str]]]</span></tt>
+               class="code sev- "><tt><i>508</i>         <span class="n">expert_forbidden_conditions</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="n">Union</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="nb">tuple</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="nb">str</span><span class="p">]]]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span></tt>
             </div>
             <div id="l509"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (98 > 79 characters)</li>
-               
-               </ul><tt><i>509</i> <span class="sd">            set of initial rules, either passed as a list of strings representing rules or as list</span></tt>
+               class="code sev- "><tt><i>509</i>     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ExpertRuleClassifier</span><span class="p">:</span></tt>
             </div>
             <div id="l510"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (92 > 79 characters)</li>
-               
-               </ul><tt><i>510</i> <span class="sd">            of tuples where first element is name of the rule and second one is rule string.</span></tt>
+               class="code sev- "><tt><i>510</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Train model on given dataset.</span></tt>
             </div>
             <div id="l511"
-               class="code sev- "><tt><i>511</i> <span class="sd">        expert_preferred_conditions : List[Union[str, Tuple[str, str]]]</span></tt>
+               class="code sev- "><tt><i>511</i> &nbsp;</tt>
             </div>
             <div id="l512"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (94 > 79 characters)</li>
-               
-               </ul><tt><i>512</i> <span class="sd">            multiset of preferred conditions (used also for specifying preferred attributes by</span></tt>
+               class="code sev- "><tt><i>512</i> <span class="sd">        Parameters</span></tt>
             </div>
             <div id="l513"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (97 > 79 characters)</li>
-               
-               </ul><tt><i>513</i> <span class="sd">            using special value Any). Either passed as a list of strings representing rules or as</span></tt>
+               class="code sev- "><tt><i>513</i> <span class="sd">        ----------</span></tt>
             </div>
             <div id="l514"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (97 > 79 characters)</li>
-               
-               </ul><tt><i>514</i> <span class="sd">            list of tuples where first element is name of the rule and second one is rule string.</span></tt>
+               class="code sev- "><tt><i>514</i> <span class="sd">        values : :class:`rulekit.operator.Data`</span></tt>
             </div>
             <div id="l515"
-               class="code sev- "><tt><i>515</i> <span class="sd">        expert_forbidden_conditions : List[Union[str, Tuple[str, str]]]</span></tt>
+               class="code sev- "><tt><i>515</i> <span class="sd">            attributes</span></tt>
             </div>
             <div id="l516"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (95 > 79 characters)</li>
-               
-               </ul><tt><i>516</i> <span class="sd">            set of forbidden conditions (used also for specifying forbidden attributes by using</span></tt>
+               class="code sev- "><tt><i>516</i> <span class="sd">        labels : :class:`rulekit.operator.Data`</span></tt>
             </div>
             <div id="l517"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (97 > 79 characters)</li>
-               
-               </ul><tt><i>517</i> <span class="sd">             special valye Any). Either passed as a list of strings representing rules or as list</span></tt>
+               class="code sev- "><tt><i>517</i> <span class="sd">            labels</span></tt>
             </div>
             <div id="l518"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (92 > 79 characters)</li>
-               
-               </ul><tt><i>518</i> <span class="sd">            of tuples where first element is name of the rule and second one is rule string.</span></tt>
+               class="code sev- "><tt><i>518</i> &nbsp;</tt>
             </div>
             <div id="l519"
-               class="code sev- "><tt><i>519</i> <span class="sd">        Returns</span></tt>
+               class="code sev- "><tt><i>519</i> <span class="sd">        expert_rules : List[Union[str, Tuple[str, str]]]</span></tt>
             </div>
             <div id="l520"
-               class="code sev- "><tt><i>520</i> <span class="sd">        -------</span></tt>
+               class="code sev- "><tt><i>520</i> <span class="sd">            set of initial rules, either passed as a list of strings representing rules</span></tt>
             </div>
             <div id="l521"
-               class="code sev- "><tt><i>521</i> <span class="sd">        self : ExpertRuleClassifier</span></tt>
+               class="code sev- "><tt><i>521</i> <span class="sd">            or as list of tuples where first element is name of the rule and second one</span></tt>
             </div>
             <div id="l522"
-               class="code sev- "><tt><i>522</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
+               class="code sev- "><tt><i>522</i> <span class="sd">            is rule string.</span></tt>
             </div>
             <div id="l523"
-               class="code sev- "><tt><i>523</i>         <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">labels</span><span class="p">,</span> <span class="p">(</span><span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">,</span> <span class="n">pd</span><span class="o">.</span><span class="n">Series</span><span class="p">)):</span></tt>
+               class="code sev- "><tt><i>523</i> <span class="sd">        expert_preferred_conditions : List[Union[str, Tuple[str, str]]]</span></tt>
             </div>
             <div id="l524"
-               class="code sev- "><tt><i>524</i>             <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">labels</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">Number</span><span class="p">):</span></tt>
+               class="code sev- "><tt><i>524</i> <span class="sd">            multiset of preferred conditions (used also for specifying preferred</span></tt>
             </div>
             <div id="l525"
-               class="code sev- "><tt><i>525</i>                 <span class="bp">self</span><span class="o">.</span><span class="n">_remap_to_numeric</span> <span class="o">=</span> <span class="kc">True</span></tt>
+               class="code sev- "><tt><i>525</i> <span class="sd">            attributes by using special value Any). Either passed as a list of strings</span></tt>
             </div>
             <div id="l526"
-               class="code sev- "><tt><i>526</i>                 <span class="n">labels</span> <span class="o">=</span> <span class="n">labels</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="nb">str</span><span class="p">)</span></tt>
+               class="code sev- "><tt><i>526</i> <span class="sd">            representing rules or as list of tuples where first element is name of the</span></tt>
             </div>
             <div id="l527"
-               class="code sev- "><tt><i>527</i>         <span class="k">else</span><span class="p">:</span></tt>
+               class="code sev- "><tt><i>527</i> <span class="sd">            rule and second one is rule string.</span></tt>
             </div>
             <div id="l528"
-               class="code sev- "><tt><i>528</i>             <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">labels</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">Number</span><span class="p">):</span></tt>
+               class="code sev- "><tt><i>528</i> <span class="sd">        expert_forbidden_conditions : List[Union[str, Tuple[str, str]]]</span></tt>
             </div>
             <div id="l529"
-               class="code sev- "><tt><i>529</i>                 <span class="bp">self</span><span class="o">.</span><span class="n">_remap_to_numeric</span> <span class="o">=</span> <span class="kc">True</span></tt>
+               class="code sev- "><tt><i>529</i> <span class="sd">            set of forbidden conditions (used also for specifying forbidden attributes</span></tt>
             </div>
             <div id="l530"
-               class="code sev- "><tt><i>530</i>                 <span class="n">labels</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="nb">map</span><span class="p">(</span><span class="nb">str</span><span class="p">,</span> <span class="n">labels</span><span class="p">))</span></tt>
+               class="code sev- "><tt><i>530</i> <span class="sd">            by using special value Any). Either passed as a list of strings representing</span></tt>
             </div>
             <div id="l531"
-               class="code sev- "><tt><i>531</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_get_unique_label_values</span><span class="p">(</span><span class="n">labels</span><span class="p">)</span></tt>
+               class="code sev- "><tt><i>531</i> <span class="sd">            rules or as list of tuples where first element is name of the rule and</span></tt>
             </div>
             <div id="l532"
-               class="code sev- "><tt><i>532</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_prepare_labels</span><span class="p">(</span><span class="n">labels</span><span class="p">)</span></tt>
+               class="code sev- "><tt><i>532</i> <span class="sd">            second one is rule string.</span></tt>
             </div>
             <div id="l533"
-               class="code sev- "><tt><i>533</i>         <span class="k">return</span> <span class="n">ExpertKnowledgeOperator</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span></tt>
+               class="code sev- "><tt><i>533</i> <span class="sd">        Returns</span></tt>
             </div>
             <div id="l534"
-               class="code sev- "><tt><i>534</i>             <span class="bp">self</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>534</i> <span class="sd">        -------</span></tt>
             </div>
             <div id="l535"
-               class="code sev- "><tt><i>535</i>             <span class="n">values</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>535</i> <span class="sd">        self : ExpertRuleClassifier</span></tt>
             </div>
             <div id="l536"
-               class="code sev- "><tt><i>536</i>             <span class="n">labels</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>536</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
             </div>
             <div id="l537"
-               class="code sev- "><tt><i>537</i>             <span class="n">expert_rules</span><span class="o">=</span><span class="n">expert_rules</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>537</i>         <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">labels</span><span class="p">,</span> <span class="p">(</span><span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">,</span> <span class="n">pd</span><span class="o">.</span><span class="n">Series</span><span class="p">)):</span></tt>
             </div>
             <div id="l538"
-               class="code sev- "><tt><i>538</i>             <span class="n">expert_preferred_conditions</span><span class="o">=</span><span class="n">expert_preferred_conditions</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>538</i>             <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">labels</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">Number</span><span class="p">):</span></tt>
             </div>
             <div id="l539"
-               class="code sev- "><tt><i>539</i>             <span class="n">expert_forbidden_conditions</span><span class="o">=</span><span class="n">expert_forbidden_conditions</span></tt>
+               class="code sev- "><tt><i>539</i>                 <span class="bp">self</span><span class="o">.</span><span class="n">_remap_to_numeric</span> <span class="o">=</span> <span class="kc">True</span></tt>
             </div>
             <div id="l540"
-               class="code sev- "><tt><i>540</i>         <span class="p">)</span></tt>
+               class="code sev- "><tt><i>540</i>                 <span class="n">labels</span> <span class="o">=</span> <span class="n">labels</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="nb">str</span><span class="p">)</span></tt>
             </div>
             <div id="l541"
-               class="code sev- "><tt><i>541</i> &nbsp;</tt>
+               class="code sev- "><tt><i>541</i>         <span class="k">else</span><span class="p">:</span></tt>
             </div>
             <div id="l542"
-               class="code sev- "><tt><i>542</i>     <span class="k">def</span> <span class="nf">predict</span><span class="p">(</span></tt>
+               class="code sev- "><tt><i>542</i>             <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">labels</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">Number</span><span class="p">):</span></tt>
             </div>
             <div id="l543"
-               class="code sev- "><tt><i>543</i>         <span class="bp">self</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>543</i>                 <span class="bp">self</span><span class="o">.</span><span class="n">_remap_to_numeric</span> <span class="o">=</span> <span class="kc">True</span></tt>
             </div>
             <div id="l544"
-               class="code sev- "><tt><i>544</i>         <span class="n">values</span><span class="p">:</span> <span class="n">Data</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>544</i>                 <span class="n">labels</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="nb">map</span><span class="p">(</span><span class="nb">str</span><span class="p">,</span> <span class="n">labels</span><span class="p">))</span></tt>
             </div>
             <div id="l545"
-               class="code sev- "><tt><i>545</i>         <span class="n">return_metrics</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span></tt>
+               class="code sev- "><tt><i>545</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_get_unique_label_values</span><span class="p">(</span><span class="n">labels</span><span class="p">)</span></tt>
             </div>
             <div id="l546"
-               class="code sev- "><tt><i>546</i>     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Union</span><span class="p">[</span><span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">,</span> <span class="nb">tuple</span><span class="p">[</span><span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">,</span> <span class="n">ClassificationPredictionMetrics</span><span class="p">]]:</span></tt>
+               class="code sev- "><tt><i>546</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_prepare_labels</span><span class="p">(</span><span class="n">labels</span><span class="p">)</span></tt>
             </div>
             <div id="l547"
-               class="code sev- "><tt><i>547</i>         <span class="k">return</span> <span class="n">RuleClassifier</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">,</span> <span class="n">return_metrics</span><span class="p">)</span></tt>
+               class="code sev- "><tt><i>547</i>         <span class="k">return</span> <span class="n">ExpertKnowledgeOperator</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span></tt>
             </div>
             <div id="l548"
-               class="code sev- "><tt><i>548</i> &nbsp;</tt>
+               class="code sev- "><tt><i>548</i>             <span class="bp">self</span><span class="p">,</span></tt>
             </div>
             <div id="l549"
-               class="code sev- "><tt><i>549</i>     <span class="k">def</span> <span class="nf">__getstate__</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">dict</span><span class="p">:</span></tt>
+               class="code sev- "><tt><i>549</i>             <span class="n">values</span><span class="p">,</span></tt>
             </div>
             <div id="l550"
-               class="code sev- "><tt><i>550</i>         <span class="k">return</span> <span class="p">{</span><span class="o">**</span><span class="n">BaseOperator</span><span class="o">.</span><span class="n">__getstate__</span><span class="p">(</span><span class="bp">self</span><span class="p">),</span> <span class="o">**</span><span class="p">{</span></tt>
+               class="code sev- "><tt><i>550</i>             <span class="n">labels</span><span class="p">,</span></tt>
             </div>
             <div id="l551"
-               class="code sev- "><tt><i>551</i>             <span class="s1">&#39;_remap_to_numeric&#39;</span><span class="p">:</span> <span class="bp">self</span><span class="o">.</span><span class="n">_remap_to_numeric</span></tt>
+               class="code sev- "><tt><i>551</i>             <span class="n">expert_rules</span><span class="o">=</span><span class="n">expert_rules</span><span class="p">,</span></tt>
             </div>
             <div id="l552"
-               class="code sev- "><tt><i>552</i>         <span class="p">}}</span></tt>
+               class="code sev- "><tt><i>552</i>             <span class="n">expert_preferred_conditions</span><span class="o">=</span><span class="n">expert_preferred_conditions</span><span class="p">,</span></tt>
             </div>
             <div id="l553"
-               class="code sev- "><tt><i>553</i> &nbsp;</tt>
+               class="code sev- "><tt><i>553</i>             <span class="n">expert_forbidden_conditions</span><span class="o">=</span><span class="n">expert_forbidden_conditions</span><span class="p">,</span></tt>
             </div>
             <div id="l554"
-               class="code sev- "><tt><i>554</i>     <span class="k">def</span> <span class="nf">__setstate__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">state</span><span class="p">:</span> <span class="nb">dict</span><span class="p">):</span></tt>
+               class="code sev- "><tt><i>554</i>         <span class="p">)</span></tt>
             </div>
             <div id="l555"
-               class="code sev- "><tt><i>555</i>         <span class="n">BaseOperator</span><span class="o">.</span><span class="n">__setstate__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">state</span><span class="p">)</span></tt>
+               class="code sev- "><tt><i>555</i> &nbsp;</tt>
             </div>
             <div id="l556"
-               class="code sev- "><tt><i>556</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_remap_to_numeric</span> <span class="o">=</span> <span class="n">state</span><span class="p">[</span><span class="s1">&#39;_remap_to_numeric&#39;</span><span class="p">]</span></tt>
+               class="code sev- "><tt><i>556</i>     <span class="k">def</span> <span class="nf">predict</span><span class="p">(</span></tt>
             </div>
             <div id="l557"
-               class="code sev- "><tt><i>557</i> &nbsp;</tt>
+               class="code sev- "><tt><i>557</i>         <span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">:</span> <span class="n">Data</span><span class="p">,</span> <span class="n">return_metrics</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span></tt>
             </div>
             <div id="l558"
-               class="code sev- "><tt><i>558</i>     <span class="k">def</span> <span class="nf">_get_problem_type</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ProblemType</span><span class="p">:</span></tt>
+               class="code sev- "><tt><i>558</i>     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Union</span><span class="p">[</span><span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">,</span> <span class="nb">tuple</span><span class="p">[</span><span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">,</span> <span class="n">ClassificationPredictionMetrics</span><span class="p">]]:</span></tt>
             </div>
             <div id="l559"
-               class="code sev- "><tt><i>559</i>         <span class="k">return</span> <span class="n">ProblemType</span><span class="o">.</span><span class="n">CLASSIFICATION</span></tt>
+               class="code sev- "><tt><i>559</i>         <span class="k">return</span> <span class="n">RuleClassifier</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">,</span> <span class="n">return_metrics</span><span class="p">)</span></tt>
             </div>
             <div id="l560"
                class="code sev- "><tt><i>560</i> &nbsp;</tt>
             </div>
             <div id="l561"
-               class="code sev- "><tt><i>561</i> &nbsp;</tt>
+               class="code sev- "><tt><i>561</i>     <span class="k">def</span> <span class="nf">__getstate__</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">dict</span><span class="p">:</span></tt>
             </div>
             <div id="l562"
-               class="code sev- "><tt><i>562</i> <span class="k">class</span> <span class="nc">ContrastSetRuleClassifier</span><span class="p">(</span><span class="n">BaseOperator</span><span class="p">,</span> <span class="n">BaseClassifier</span><span class="p">):</span></tt>
+               class="code sev- "><tt><i>562</i>         <span class="k">return</span> <span class="p">{</span></tt>
             </div>
             <div id="l563"
-               class="code sev- "><tt><i>563</i> <span class="w">    </span><span class="sd">&quot;&quot;&quot;Contrast set classification model.&quot;&quot;&quot;</span></tt>
+               class="code sev- "><tt><i>563</i>             <span class="o">**</span><span class="n">BaseOperator</span><span class="o">.</span><span class="n">__getstate__</span><span class="p">(</span><span class="bp">self</span><span class="p">),</span></tt>
             </div>
             <div id="l564"
-               class="code sev- "><tt><i>564</i> &nbsp;</tt>
+               class="code sev- "><tt><i>564</i>             <span class="o">**</span><span class="p">{</span><span class="s2">&quot;_remap_to_numeric&quot;</span><span class="p">:</span> <span class="bp">self</span><span class="o">.</span><span class="n">_remap_to_numeric</span><span class="p">},</span></tt>
             </div>
             <div id="l565"
-               class="code sev- "><tt><i>565</i>     <span class="n">__params_class__</span> <span class="o">=</span> <span class="n">ContrastSetModelParams</span></tt>
+               class="code sev- "><tt><i>565</i>         <span class="p">}</span></tt>
             </div>
             <div id="l566"
                class="code sev- "><tt><i>566</i> &nbsp;</tt>
             </div>
             <div id="l567"
-               class="code sev- "><tt><i>567</i>     <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span>  <span class="c1"># pylint: disable=too-many-arguments,too-many-locals</span></tt>
+               class="code sev- "><tt><i>567</i>     <span class="k">def</span> <span class="nf">__setstate__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">state</span><span class="p">:</span> <span class="nb">dict</span><span class="p">):</span></tt>
             </div>
             <div id="l568"
-               class="code sev- "><tt><i>568</i>         <span class="bp">self</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>568</i>         <span class="n">BaseOperator</span><span class="o">.</span><span class="n">__setstate__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">state</span><span class="p">)</span></tt>
             </div>
             <div id="l569"
-               class="code sev- "><tt><i>569</i>         <span class="n">minsupp_all</span><span class="p">:</span> <span class="n">Tuple</span><span class="p">[</span><span class="nb">float</span><span class="p">,</span> <span class="nb">float</span><span class="p">,</span> <span class="nb">float</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>569</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_remap_to_numeric</span> <span class="o">=</span> <span class="n">state</span><span class="p">[</span><span class="s2">&quot;_remap_to_numeric&quot;</span><span class="p">]</span></tt>
             </div>
             <div id="l570"
-               class="code sev- "><tt><i>570</i>                            <span class="nb">float</span><span class="p">]</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;minsupp_all&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>570</i> &nbsp;</tt>
             </div>
             <div id="l571"
-               class="code sev- "><tt><i>571</i>         <span class="n">max_neg2pos</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;max_neg2pos&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>571</i>     <span class="k">def</span> <span class="nf">_get_problem_type</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ProblemType</span><span class="p">:</span></tt>
             </div>
             <div id="l572"
-               class="code sev- "><tt><i>572</i>         <span class="n">max_passes_count</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;max_passes_count&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>572</i>         <span class="k">return</span> <span class="n">ProblemType</span><span class="o">.</span><span class="n">CLASSIFICATION</span></tt>
             </div>
             <div id="l573"
-               class="code sev- "><tt><i>573</i>         <span class="n">penalty_strength</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;penalty_strength&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>573</i> &nbsp;</tt>
             </div>
             <div id="l574"
-               class="code sev- "><tt><i>574</i>         <span class="n">penalty_saturation</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;penalty_saturation&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>574</i> &nbsp;</tt>
             </div>
             <div id="l575"
-               class="code sev- "><tt><i>575</i> &nbsp;</tt>
+               class="code sev- "><tt><i>575</i> <span class="k">class</span> <span class="nc">ContrastSetRuleClassifier</span><span class="p">(</span><span class="n">BaseOperator</span><span class="p">,</span> <span class="n">BaseClassifier</span><span class="p">):</span></tt>
             </div>
             <div id="l576"
-               class="code sev- "><tt><i>576</i>         <span class="n">minsupp_new</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;minsupp_new&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>576</i> <span class="w">    </span><span class="sd">&quot;&quot;&quot;Contrast set classification model.&quot;&quot;&quot;</span></tt>
             </div>
             <div id="l577"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (80 > 79 characters)</li>
-               
-               </ul><tt><i>577</i>         <span class="n">induction_measure</span><span class="p">:</span> <span class="n">Measures</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;induction_measure&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>577</i> &nbsp;</tt>
             </div>
             <div id="l578"
-               class="code sev- "><tt><i>578</i>         <span class="n">pruning_measure</span><span class="p">:</span> <span class="n">Union</span><span class="p">[</span><span class="n">Measures</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>578</i>     <span class="n">__params_class__</span> <span class="o">=</span> <span class="n">ContrastSetModelParams</span></tt>
             </div>
             <div id="l579"
-               class="code sev- "><tt><i>579</i>                                <span class="nb">str</span><span class="p">]</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;pruning_measure&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>579</i> &nbsp;</tt>
             </div>
             <div id="l580"
-               class="code sev- "><tt><i>580</i>         <span class="n">voting_measure</span><span class="p">:</span> <span class="n">Measures</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;voting_measure&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>580</i>     <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span>  <span class="c1"># pylint: disable=too-many-arguments,too-many-locals</span></tt>
             </div>
             <div id="l581"
-               class="code sev- "><tt><i>581</i>         <span class="n">max_growing</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;max_growing&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>581</i>         <span class="bp">self</span><span class="p">,</span></tt>
             </div>
             <div id="l582"
-               class="code sev- "><tt><i>582</i>         <span class="n">enable_pruning</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;enable_pruning&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>582</i>         <span class="n">minsupp_all</span><span class="p">:</span> <span class="n">Tuple</span><span class="p">[</span><span class="nb">float</span><span class="p">,</span> <span class="nb">float</span><span class="p">,</span> <span class="nb">float</span><span class="p">,</span> <span class="nb">float</span><span class="p">]</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span></tt>
             </div>
             <div id="l583"
-               class="code sev- "><tt><i>583</i>         <span class="n">ignore_missing</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;ignore_missing&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>583</i>             <span class="s2">&quot;minsupp_all&quot;</span></tt>
             </div>
             <div id="l584"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (87 > 79 characters)</li>
-               
-               </ul><tt><i>584</i>         <span class="n">max_uncovered_fraction</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;max_uncovered_fraction&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>584</i>         <span class="p">],</span></tt>
             </div>
             <div id="l585"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (84 > 79 characters)</li>
-               
-               </ul><tt><i>585</i>         <span class="n">select_best_candidate</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;select_best_candidate&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>585</i>         <span class="n">max_neg2pos</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;max_neg2pos&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l586"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (90 > 79 characters)</li>
-               
-               </ul><tt><i>586</i>         <span class="n">complementary_conditions</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;complementary_conditions&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>586</i>         <span class="n">max_passes_count</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;max_passes_count&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l587"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (92 > 79 characters)</li>
-               
-               </ul><tt><i>587</i>         <span class="n">control_apriori_precision</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;control_apriori_precision&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>587</i>         <span class="n">penalty_strength</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;penalty_strength&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l588"
-               class="code sev- "><tt><i>588</i>         <span class="n">max_rule_count</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;max_rule_count&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>588</i>         <span class="n">penalty_saturation</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;penalty_saturation&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l589"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (84 > 79 characters)</li>
-               
-               </ul><tt><i>589</i>         <span class="n">approximate_induction</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;approximate_induction&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>589</i>         <span class="n">minsupp_new</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;minsupp_new&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l590"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (85 > 79 characters)</li>
-               
-               </ul><tt><i>590</i>         <span class="n">approximate_bins_count</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;approximate_bins_count&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>590</i>         <span class="n">induction_measure</span><span class="p">:</span> <span class="n">Measures</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;induction_measure&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l591"
-               class="code sev- "><tt><i>591</i>     <span class="p">):</span></tt>
+               class="code sev- "><tt><i>591</i>         <span class="n">pruning_measure</span><span class="p">:</span> <span class="n">Union</span><span class="p">[</span><span class="n">Measures</span><span class="p">,</span> <span class="nb">str</span><span class="p">]</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;pruning_measure&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l592"
-               class="code sev- "><tt><i>592</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;</span></tt>
+               class="code sev- "><tt><i>592</i>         <span class="n">voting_measure</span><span class="p">:</span> <span class="n">Measures</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;voting_measure&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l593"
-               class="code sev- "><tt><i>593</i> <span class="sd">        Parameters</span></tt>
+               class="code sev- "><tt><i>593</i>         <span class="n">max_growing</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;max_growing&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l594"
-               class="code sev- "><tt><i>594</i> <span class="sd">        ----------</span></tt>
-            </div>
-            <div id="l595"
-               class="code sev- "><tt><i>595</i> <span class="sd">        minsupp_all: Tuple[float, float, float, float]</span></tt>
-            </div>
-            <div id="l596"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (99 > 79 characters)</li>
-               
-               </ul><tt><i>596</i> <span class="sd">            a minimum positive support of a contrast set (p/P). When multiple values are specified,</span></tt>
+               class="code sev- "><tt><i>594</i>         <span class="n">enable_pruning</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;enable_pruning&quot;</span><span class="p">],</span></tt>
             </div>
-            <div id="l597"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (97 > 79 characters)</li>
-               
-               </ul><tt><i>597</i> <span class="sd">            a metainduction is performed; Default and recommended sequence is: 0.8, 0.5, 0.2, 0.1</span></tt>
+            <div id="l595"
+               class="code sev- "><tt><i>595</i>         <span class="n">ignore_missing</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;ignore_missing&quot;</span><span class="p">],</span></tt>
+            </div>
+            <div id="l596"
+               class="code sev- "><tt><i>596</i>         <span class="n">max_uncovered_fraction</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;max_uncovered_fraction&quot;</span><span class="p">],</span></tt>
+            </div>
+            <div id="l597"
+               class="code sev- "><tt><i>597</i>         <span class="n">select_best_candidate</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;select_best_candidate&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l598"
-               class="code sev- "><tt><i>598</i> <span class="sd">        max_neg2pos: float</span></tt>
+               class="code sev- "><tt><i>598</i>         <span class="n">complementary_conditions</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span></tt>
             </div>
             <div id="l599"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (84 > 79 characters)</li>
-               
-               </ul><tt><i>599</i> <span class="sd">            a maximum ratio of negative to positive supports (nP/pN); Default is 0.5</span></tt>
+               class="code sev- "><tt><i>599</i>             <span class="s2">&quot;complementary_conditions&quot;</span></tt>
             </div>
             <div id="l600"
-               class="code sev- "><tt><i>600</i> <span class="sd">        max_passes_count: int</span></tt>
+               class="code sev- "><tt><i>600</i>         <span class="p">],</span></tt>
             </div>
             <div id="l601"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (97 > 79 characters)</li>
-               
-               </ul><tt><i>601</i> <span class="sd">            a maximum number of sequential covering passes for a single minsupp-all; Default is 5</span></tt>
+               class="code sev- "><tt><i>601</i>         <span class="n">control_apriori_precision</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span></tt>
             </div>
             <div id="l602"
-               class="code sev- "><tt><i>602</i> <span class="sd">        penalty_strength: float</span></tt>
+               class="code sev- "><tt><i>602</i>             <span class="s2">&quot;control_apriori_precision&quot;</span></tt>
             </div>
             <div id="l603"
-               class="code sev- "><tt><i>603</i> <span class="sd">            (s) - penalty strength; Default is 0.5</span></tt>
+               class="code sev- "><tt><i>603</i>         <span class="p">],</span></tt>
             </div>
             <div id="l604"
-               class="code sev- "><tt><i>604</i> <span class="sd">        penalty_saturation: float</span></tt>
+               class="code sev- "><tt><i>604</i>         <span class="n">max_rule_count</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;max_rule_count&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l605"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (85 > 79 characters)</li>
-               
-               </ul><tt><i>605</i> <span class="sd">            the value of p_new / P at which penalty reward saturates; Default is 0.2.</span></tt>
+               class="code sev- "><tt><i>605</i>         <span class="n">approximate_induction</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;approximate_induction&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l606"
-               class="code sev- "><tt><i>606</i> <span class="sd">        minsupp_new : float = 5.0</span></tt>
+               class="code sev- "><tt><i>606</i>         <span class="n">approximate_bins_count</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;approximate_bins_count&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l607"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (91 > 79 characters)</li>
-               
-               </ul><tt><i>607</i> <span class="sd">            a minimum number (or fraction, if value &lt; 1.0) of previously uncovered examples</span></tt>
+               class="code sev- "><tt><i>607</i>     <span class="p">):</span></tt>
             </div>
             <div id="l608"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (101 > 79 characters)</li>
-               
-               </ul><tt><i>608</i> <span class="sd">             to be covered by a new rule (positive examples for classification problems); default: 5,</span></tt>
+               class="code sev- "><tt><i>608</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;</span></tt>
             </div>
             <div id="l609"
-               class="code sev- "><tt><i>609</i> <span class="sd">        induction_measure : :class:`rulekit.params.Measures` = \</span></tt>
+               class="code sev- "><tt><i>609</i> <span class="sd">        Parameters</span></tt>
             </div>
             <div id="l610"
-               class="code sev- "><tt><i>610</i> <span class="sd">            :class:`rulekit.params.Measures.Correlation`</span></tt>
+               class="code sev- "><tt><i>610</i> <span class="sd">        ----------</span></tt>
             </div>
             <div id="l611"
-               class="code sev- "><tt><i>611</i> <span class="sd">            measure used during induction; default measure is correlation</span></tt>
+               class="code sev- "><tt><i>611</i> <span class="sd">        minsupp_all: Tuple[float, float, float, float]</span></tt>
             </div>
             <div id="l612"
-               class="code sev- "><tt><i>612</i> <span class="sd">        pruning_measure : Union[:class:`rulekit.params.Measures`, str] = \</span></tt>
+               class="code sev- "><tt><i>612</i> <span class="sd">            a minimum positive support of a contrast set (p/P). When multiple values</span></tt>
             </div>
             <div id="l613"
-               class="code sev- "><tt><i>613</i> <span class="sd">            :class:`rulekit.params.Measures.Correlation`</span></tt>
+               class="code sev- "><tt><i>613</i> <span class="sd">            are specified, a metainduction is performed; Default and recommended</span></tt>
             </div>
             <div id="l614"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (84 > 79 characters)</li>
-               
-               </ul><tt><i>614</i> <span class="sd">            measure used during pruning. Could be user defined (string), for example</span></tt>
+               class="code sev- "><tt><i>614</i> <span class="sd">            sequence is: 0.8, 0.5, 0.2, 0.1</span></tt>
             </div>
             <div id="l615"
-               class="code sev- "><tt><i>615</i> <span class="sd">             :code:`2 * p / n`; default measure is correlation</span></tt>
+               class="code sev- "><tt><i>615</i> <span class="sd">        max_neg2pos: float</span></tt>
             </div>
             <div id="l616"
-               class="code sev- "><tt><i>616</i> <span class="sd">        voting_measure : :class:`rulekit.params.Measures` = \</span></tt>
+               class="code sev- "><tt><i>616</i> <span class="sd">            a maximum ratio of negative to positive supports (nP/pN); Default is 0.5</span></tt>
             </div>
             <div id="l617"
-               class="code sev- "><tt><i>617</i> <span class="sd">            :class:`rulekit.params.Measures.Correlation`</span></tt>
+               class="code sev- "><tt><i>617</i> <span class="sd">        max_passes_count: int</span></tt>
             </div>
             <div id="l618"
-               class="code sev- "><tt><i>618</i> <span class="sd">            measure used during voting; default measure is correlation</span></tt>
+               class="code sev- "><tt><i>618</i> <span class="sd">            a maximum number of sequential covering passes for a single minsupp-all;</span></tt>
             </div>
             <div id="l619"
-               class="code sev- "><tt><i>619</i> <span class="sd">        max_growing : int = 0.0</span></tt>
+               class="code sev- "><tt><i>619</i> <span class="sd">            Default is 5</span></tt>
             </div>
             <div id="l620"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (96 > 79 characters)</li>
-               
-               </ul><tt><i>620</i> <span class="sd">            non-negative integer representing maximum number of conditions which can be added to</span></tt>
+               class="code sev- "><tt><i>620</i> <span class="sd">        penalty_strength: float</span></tt>
             </div>
             <div id="l621"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (98 > 79 characters)</li>
-               
-               </ul><tt><i>621</i> <span class="sd">            the rule in the growing phase (use this parameter for large datasets if execution time</span></tt>
+               class="code sev- "><tt><i>621</i> <span class="sd">            (s) - penalty strength; Default is 0.5</span></tt>
             </div>
             <div id="l622"
-               class="code sev- "><tt><i>622</i> <span class="sd">            is prohibitive); 0 indicates no limit; default: 0,</span></tt>
+               class="code sev- "><tt><i>622</i> <span class="sd">        penalty_saturation: float</span></tt>
             </div>
             <div id="l623"
-               class="code sev- "><tt><i>623</i> <span class="sd">        enable_pruning : bool = True</span></tt>
+               class="code sev- "><tt><i>623</i> <span class="sd">            the value of p_new / P at which penalty reward saturates; Default is 0.2.</span></tt>
             </div>
             <div id="l624"
-               class="code sev- "><tt><i>624</i> <span class="sd">            enable or disable pruning, default is True.</span></tt>
+               class="code sev- "><tt><i>624</i> <span class="sd">        minsupp_new : float = 5.0</span></tt>
             </div>
             <div id="l625"
-               class="code sev- "><tt><i>625</i> <span class="sd">        ignore_missing : bool = False</span></tt>
+               class="code sev- "><tt><i>625</i> <span class="sd">            a minimum number (or fraction, if value &lt; 1.0) of previously uncovered</span></tt>
             </div>
             <div id="l626"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (97 > 79 characters)</li>
-               
-               </ul><tt><i>626</i> <span class="sd">            boolean telling whether missing values should be ignored (by default, a missing value</span></tt>
+               class="code sev- "><tt><i>626</i> <span class="sd">            examples to be covered by a new rule (positive examples for classification</span></tt>
             </div>
             <div id="l627"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (94 > 79 characters)</li>
-               
-               </ul><tt><i>627</i> <span class="sd">            of given attribute is always considered as not fulfilling the condition build upon</span></tt>
+               class="code sev- "><tt><i>627</i> <span class="sd">            problems); default: 5,</span></tt>
             </div>
             <div id="l628"
-               class="code sev- "><tt><i>628</i> <span class="sd">             that attribute); default: False.</span></tt>
+               class="code sev- "><tt><i>628</i> <span class="sd">        induction_measure : :class:`rulekit.params.Measures` = \</span></tt>
             </div>
             <div id="l629"
-               class="code sev- "><tt><i>629</i> <span class="sd">        max_uncovered_fraction : float = 0.0</span></tt>
+               class="code sev- "><tt><i>629</i> <span class="sd">            :class:`rulekit.params.Measures.Correlation`</span></tt>
             </div>
             <div id="l630"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (95 > 79 characters)</li>
-               
-               </ul><tt><i>630</i> <span class="sd">            Floating-point number from [0,1] interval representing maximum fraction of examples</span></tt>
+               class="code sev- "><tt><i>630</i> <span class="sd">            measure used during induction; default measure is correlation</span></tt>
             </div>
             <div id="l631"
-               class="code sev- "><tt><i>631</i> <span class="sd">             that may remain uncovered by the rule set, default: 0.0.</span></tt>
+               class="code sev- "><tt><i>631</i> <span class="sd">        pruning_measure : Union[:class:`rulekit.params.Measures`, str] = \</span></tt>
             </div>
             <div id="l632"
-               class="code sev- "><tt><i>632</i> <span class="sd">        select_best_candidate : bool = False</span></tt>
+               class="code sev- "><tt><i>632</i> <span class="sd">            :class:`rulekit.params.Measures.Correlation`</span></tt>
             </div>
             <div id="l633"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (85 > 79 characters)</li>
-               
-               </ul><tt><i>633</i> <span class="sd">            Flag determining if best candidate should be selected from growing phase;</span></tt>
+               class="code sev- "><tt><i>633</i> <span class="sd">            measure used during pruning. Could be user defined (string), for example</span></tt>
             </div>
             <div id="l634"
-               class="code sev- "><tt><i>634</i> <span class="sd">             default: False.</span></tt>
+               class="code sev- "><tt><i>634</i> <span class="sd">             :code:`2 * p / n`; default measure is correlation</span></tt>
             </div>
             <div id="l635"
-               class="code sev- "><tt><i>635</i> <span class="sd">        complementary_conditions : bool = False</span></tt>
+               class="code sev- "><tt><i>635</i> <span class="sd">        voting_measure : :class:`rulekit.params.Measures` = \</span></tt>
             </div>
             <div id="l636"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (96 > 79 characters)</li>
-               
-               </ul><tt><i>636</i> <span class="sd">            If enabled, complementary conditions in the form a = !{value} for nominal attributes</span></tt>
+               class="code sev- "><tt><i>636</i> <span class="sd">            :class:`rulekit.params.Measures.Correlation`</span></tt>
             </div>
             <div id="l637"
-               class="code sev- "><tt><i>637</i> <span class="sd">            are supported.</span></tt>
+               class="code sev- "><tt><i>637</i> <span class="sd">            measure used during voting; default measure is correlation</span></tt>
             </div>
             <div id="l638"
-               class="code sev- "><tt><i>638</i> <span class="sd">        control_apriori_precision : bool = True</span></tt>
+               class="code sev- "><tt><i>638</i> <span class="sd">        max_growing : int = 0.0</span></tt>
             </div>
             <div id="l639"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (92 > 79 characters)</li>
-               
-               </ul><tt><i>639</i> <span class="sd">            When inducing classification rules, verify if candidate precision is higher than</span></tt>
+               class="code sev- "><tt><i>639</i> <span class="sd">            non-negative integer representing maximum number of conditions which can be</span></tt>
             </div>
             <div id="l640"
-               class="code sev- "><tt><i>640</i> <span class="sd">             apriori precision of the investigated class.</span></tt>
+               class="code sev- "><tt><i>640</i> <span class="sd">            added to the rule in the growing phase (use this parameter for large</span></tt>
             </div>
             <div id="l641"
-               class="code sev- "><tt><i>641</i> <span class="sd">        max_rule_count : int = 0</span></tt>
+               class="code sev- "><tt><i>641</i> <span class="sd">            datasets if execution time is prohibitive); 0 indicates no limit; default: 0</span></tt>
             </div>
             <div id="l642"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (92 > 79 characters)</li>
-               
-               </ul><tt><i>642</i> <span class="sd">            Maximum number of rules to be generated (for classification data sets it applies</span></tt>
+               class="code sev- "><tt><i>642</i> <span class="sd">        enable_pruning : bool = True</span></tt>
             </div>
             <div id="l643"
-               class="code sev- "><tt><i>643</i> <span class="sd">             to a single class); 0 indicates no limit.</span></tt>
+               class="code sev- "><tt><i>643</i> <span class="sd">            enable or disable pruning, default is True.</span></tt>
             </div>
             <div id="l644"
-               class="code sev- "><tt><i>644</i> <span class="sd">        approximate_induction: bool = False</span></tt>
+               class="code sev- "><tt><i>644</i> <span class="sd">        ignore_missing : bool = False</span></tt>
             </div>
             <div id="l645"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (92 > 79 characters)</li>
-               
-               </ul><tt><i>645</i> <span class="sd">            Use an approximate induction heuristic which does not check all possible splits;</span></tt>
+               class="code sev- "><tt><i>645</i> <span class="sd">            boolean telling whether missing values should be ignored (by default, a</span></tt>
             </div>
             <div id="l646"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (93 > 79 characters)</li>
-               
-               </ul><tt><i>646</i> <span class="sd">            note: this is an experimental feature and currently works only for classification</span></tt>
+               class="code sev- "><tt><i>646</i> <span class="sd">            missing value of given attribute is always considered as not fulfilling the</span></tt>
             </div>
             <div id="l647"
-               class="code sev- "><tt><i>647</i> <span class="sd">            data sets, results may change in future;</span></tt>
+               class="code sev- "><tt><i>647</i> <span class="sd">            condition build upon that attribute); default: False.</span></tt>
             </div>
             <div id="l648"
-               class="code sev- "><tt><i>648</i> <span class="sd">        approximate_bins_count: int = 100</span></tt>
+               class="code sev- "><tt><i>648</i> <span class="sd">        max_uncovered_fraction : float = 0.0</span></tt>
             </div>
             <div id="l649"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (91 > 79 characters)</li>
-               
-               </ul><tt><i>649</i> <span class="sd">            maximum number of bins for an attribute evaluated in the approximate induction.</span></tt>
+               class="code sev- "><tt><i>649</i> <span class="sd">            Floating-point number from [0,1] interval representing maximum fraction of</span></tt>
             </div>
             <div id="l650"
-               class="code sev- "><tt><i>650</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
+               class="code sev- "><tt><i>650</i> <span class="sd">            examples that may remain uncovered by the rule set, default: 0.0.</span></tt>
             </div>
             <div id="l651"
-               class="code sev- "><tt><i>651</i>         <span class="n">BaseOperator</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span></tt>
+               class="code sev- "><tt><i>651</i> <span class="sd">        select_best_candidate : bool = False</span></tt>
             </div>
             <div id="l652"
-               class="code sev- "><tt><i>652</i>             <span class="bp">self</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>652</i> <span class="sd">            Flag determining if best candidate should be selected from growing phase;</span></tt>
             </div>
             <div id="l653"
-               class="code sev- "><tt><i>653</i>             <span class="n">minsupp_all</span><span class="o">=</span><span class="n">minsupp_all</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>653</i> <span class="sd">             default: False.</span></tt>
             </div>
             <div id="l654"
-               class="code sev- "><tt><i>654</i>             <span class="n">max_neg2pos</span><span class="o">=</span><span class="n">max_neg2pos</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>654</i> <span class="sd">        complementary_conditions : bool = False</span></tt>
             </div>
             <div id="l655"
-               class="code sev- "><tt><i>655</i>             <span class="n">max_passes_count</span><span class="o">=</span><span class="n">max_passes_count</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>655</i> <span class="sd">            If enabled, complementary conditions in the form a = !{value} for nominal</span></tt>
             </div>
             <div id="l656"
-               class="code sev- "><tt><i>656</i>             <span class="n">penalty_strength</span><span class="o">=</span><span class="n">penalty_strength</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>656</i> <span class="sd">            attributes are supported.</span></tt>
             </div>
             <div id="l657"
-               class="code sev- "><tt><i>657</i>             <span class="n">penalty_saturation</span><span class="o">=</span><span class="n">penalty_saturation</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>657</i> <span class="sd">        control_apriori_precision : bool = True</span></tt>
             </div>
             <div id="l658"
-               class="code sev- "><tt><i>658</i>             <span class="n">minsupp_new</span><span class="o">=</span><span class="n">minsupp_new</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>658</i> <span class="sd">            When inducing classification rules, verify if candidate precision is higher</span></tt>
             </div>
             <div id="l659"
-               class="code sev- "><tt><i>659</i>             <span class="n">induction_measure</span><span class="o">=</span><span class="n">induction_measure</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>659</i> <span class="sd">            than apriori precision of the investigated class.</span></tt>
             </div>
             <div id="l660"
-               class="code sev- "><tt><i>660</i>             <span class="n">pruning_measure</span><span class="o">=</span><span class="n">pruning_measure</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>660</i> <span class="sd">        max_rule_count : int = 0</span></tt>
             </div>
             <div id="l661"
-               class="code sev- "><tt><i>661</i>             <span class="n">voting_measure</span><span class="o">=</span><span class="n">voting_measure</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>661</i> <span class="sd">            Maximum number of rules to be generated (for classification data sets it</span></tt>
             </div>
             <div id="l662"
-               class="code sev- "><tt><i>662</i>             <span class="n">max_growing</span><span class="o">=</span><span class="n">max_growing</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>662</i> <span class="sd">            applies to a single class); 0 indicates no limit.</span></tt>
             </div>
             <div id="l663"
-               class="code sev- "><tt><i>663</i>             <span class="n">enable_pruning</span><span class="o">=</span><span class="n">enable_pruning</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>663</i> <span class="sd">        approximate_induction: bool = False</span></tt>
             </div>
             <div id="l664"
-               class="code sev- "><tt><i>664</i>             <span class="n">ignore_missing</span><span class="o">=</span><span class="n">ignore_missing</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>664</i> <span class="sd">            Use an approximate induction heuristic which does not check all possible</span></tt>
             </div>
             <div id="l665"
-               class="code sev- "><tt><i>665</i>             <span class="n">max_uncovered_fraction</span><span class="o">=</span><span class="n">max_uncovered_fraction</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>665</i> <span class="sd">            splits; note: this is an experimental feature and currently works only for</span></tt>
             </div>
             <div id="l666"
-               class="code sev- "><tt><i>666</i>             <span class="n">select_best_candidate</span><span class="o">=</span><span class="n">select_best_candidate</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>666</i> <span class="sd">            classification data sets, results may change in future;</span></tt>
             </div>
             <div id="l667"
-               class="code sev- "><tt><i>667</i>             <span class="n">complementary_conditions</span><span class="o">=</span><span class="n">complementary_conditions</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>667</i> <span class="sd">        approximate_bins_count: int = 100</span></tt>
             </div>
             <div id="l668"
-               class="code sev- "><tt><i>668</i>             <span class="n">control_apriori_precision</span><span class="o">=</span><span class="n">control_apriori_precision</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>668</i> <span class="sd">            maximum number of bins for an attribute evaluated in the approximate</span></tt>
             </div>
             <div id="l669"
-               class="code sev- "><tt><i>669</i>             <span class="n">max_rule_count</span><span class="o">=</span><span class="n">max_rule_count</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>669</i> <span class="sd">            induction.</span></tt>
             </div>
             <div id="l670"
-               class="code sev- "><tt><i>670</i>             <span class="n">approximate_induction</span><span class="o">=</span><span class="n">approximate_induction</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>670</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
             </div>
             <div id="l671"
-               class="code sev- "><tt><i>671</i>             <span class="n">approximate_bins_count</span><span class="o">=</span><span class="n">approximate_bins_count</span></tt>
+               class="code sev- "><tt><i>671</i>         <span class="n">BaseOperator</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span></tt>
             </div>
             <div id="l672"
-               class="code sev- "><tt><i>672</i>         <span class="p">)</span></tt>
+               class="code sev- "><tt><i>672</i>             <span class="bp">self</span><span class="p">,</span></tt>
             </div>
             <div id="l673"
-               class="code sev- "><tt><i>673</i>         <span class="n">BaseClassifier</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span></tt>
+               class="code sev- "><tt><i>673</i>             <span class="n">minsupp_all</span><span class="o">=</span><span class="n">minsupp_all</span><span class="p">,</span></tt>
             </div>
             <div id="l674"
-               class="code sev- "><tt><i>674</i>         <span class="bp">self</span><span class="o">.</span><span class="n">contrast_attribute</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="kc">None</span></tt>
+               class="code sev- "><tt><i>674</i>             <span class="n">max_neg2pos</span><span class="o">=</span><span class="n">max_neg2pos</span><span class="p">,</span></tt>
             </div>
             <div id="l675"
-               class="code sev- "><tt><i>675</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_remap_to_numeric</span> <span class="o">=</span> <span class="kc">False</span></tt>
+               class="code sev- "><tt><i>675</i>             <span class="n">max_passes_count</span><span class="o">=</span><span class="n">max_passes_count</span><span class="p">,</span></tt>
             </div>
             <div id="l676"
-               class="code sev- "><tt><i>676</i>         <span class="bp">self</span><span class="o">.</span><span class="n">label_unique_values</span> <span class="o">=</span> <span class="p">[]</span></tt>
+               class="code sev- "><tt><i>676</i>             <span class="n">penalty_strength</span><span class="o">=</span><span class="n">penalty_strength</span><span class="p">,</span></tt>
             </div>
             <div id="l677"
-               class="code sev- "><tt><i>677</i>         <span class="bp">self</span><span class="o">.</span><span class="n">model</span><span class="p">:</span> <span class="n">RuleSet</span><span class="p">[</span><span class="n">ClassificationRule</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span></tt>
+               class="code sev- "><tt><i>677</i>             <span class="n">penalty_saturation</span><span class="o">=</span><span class="n">penalty_saturation</span><span class="p">,</span></tt>
             </div>
             <div id="l678"
-               class="code sev- "><tt><i>678</i> &nbsp;</tt>
+               class="code sev- "><tt><i>678</i>             <span class="n">minsupp_new</span><span class="o">=</span><span class="n">minsupp_new</span><span class="p">,</span></tt>
             </div>
             <div id="l679"
-               class="code sev- "><tt><i>679</i>     <span class="k">def</span> <span class="nf">_map_result</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">predicted_example_set</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">:</span></tt>
+               class="code sev- "><tt><i>679</i>             <span class="n">induction_measure</span><span class="o">=</span><span class="n">induction_measure</span><span class="p">,</span></tt>
             </div>
             <div id="l680"
-               class="code sev- "><tt><i>680</i>         <span class="n">prediction</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span></tt>
+               class="code sev- "><tt><i>680</i>             <span class="n">pruning_measure</span><span class="o">=</span><span class="n">pruning_measure</span><span class="p">,</span></tt>
             </div>
             <div id="l681"
-               class="code sev- "><tt><i>681</i>         <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">_remap_to_numeric</span><span class="p">:</span></tt>
+               class="code sev- "><tt><i>681</i>             <span class="n">voting_measure</span><span class="o">=</span><span class="n">voting_measure</span><span class="p">,</span></tt>
             </div>
             <div id="l682"
-               class="code sev- "><tt><i>682</i>             <span class="n">prediction</span> <span class="o">=</span> <span class="n">PredictionResultMapper</span><span class="o">.</span><span class="n">map_to_numerical</span><span class="p">(</span></tt>
+               class="code sev- "><tt><i>682</i>             <span class="n">max_growing</span><span class="o">=</span><span class="n">max_growing</span><span class="p">,</span></tt>
             </div>
             <div id="l683"
-               class="code sev- "><tt><i>683</i>                 <span class="n">predicted_example_set</span><span class="p">)</span></tt>
+               class="code sev- "><tt><i>683</i>             <span class="n">enable_pruning</span><span class="o">=</span><span class="n">enable_pruning</span><span class="p">,</span></tt>
             </div>
             <div id="l684"
-               class="code sev- "><tt><i>684</i>         <span class="k">else</span><span class="p">:</span></tt>
+               class="code sev- "><tt><i>684</i>             <span class="n">ignore_missing</span><span class="o">=</span><span class="n">ignore_missing</span><span class="p">,</span></tt>
             </div>
             <div id="l685"
-               class="code sev- "><tt><i>685</i>             <span class="n">prediction</span> <span class="o">=</span> <span class="n">PredictionResultMapper</span><span class="o">.</span><span class="n">map_to_nominal</span><span class="p">(</span></tt>
+               class="code sev- "><tt><i>685</i>             <span class="n">max_uncovered_fraction</span><span class="o">=</span><span class="n">max_uncovered_fraction</span><span class="p">,</span></tt>
             </div>
             <div id="l686"
-               class="code sev- "><tt><i>686</i>                 <span class="n">predicted_example_set</span><span class="p">)</span></tt>
+               class="code sev- "><tt><i>686</i>             <span class="n">select_best_candidate</span><span class="o">=</span><span class="n">select_best_candidate</span><span class="p">,</span></tt>
             </div>
             <div id="l687"
-               class="code sev- "><tt><i>687</i>         <span class="k">return</span> <span class="n">prediction</span></tt>
+               class="code sev- "><tt><i>687</i>             <span class="n">complementary_conditions</span><span class="o">=</span><span class="n">complementary_conditions</span><span class="p">,</span></tt>
             </div>
             <div id="l688"
-               class="code sev- "><tt><i>688</i> &nbsp;</tt>
+               class="code sev- "><tt><i>688</i>             <span class="n">control_apriori_precision</span><span class="o">=</span><span class="n">control_apriori_precision</span><span class="p">,</span></tt>
             </div>
             <div id="l689"
-               class="code sev- "><tt><i>689</i>     <span class="k">def</span> <span class="nf">_get_unique_label_values</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">labels</span><span class="p">:</span> <span class="n">Data</span><span class="p">):</span></tt>
+               class="code sev- "><tt><i>689</i>             <span class="n">max_rule_count</span><span class="o">=</span><span class="n">max_rule_count</span><span class="p">,</span></tt>
             </div>
             <div id="l690"
-               class="code sev- "><tt><i>690</i>         <span class="n">tmp</span> <span class="o">=</span> <span class="p">{}</span></tt>
+               class="code sev- "><tt><i>690</i>             <span class="n">approximate_induction</span><span class="o">=</span><span class="n">approximate_induction</span><span class="p">,</span></tt>
             </div>
             <div id="l691"
-               class="code sev- "><tt><i>691</i>         <span class="k">for</span> <span class="n">label_value</span> <span class="ow">in</span> <span class="n">labels</span><span class="p">:</span></tt>
+               class="code sev- "><tt><i>691</i>             <span class="n">approximate_bins_count</span><span class="o">=</span><span class="n">approximate_bins_count</span><span class="p">,</span></tt>
             </div>
             <div id="l692"
-               class="code sev- "><tt><i>692</i>             <span class="n">tmp</span><span class="p">[</span><span class="n">label_value</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span></tt>
+               class="code sev- "><tt><i>692</i>         <span class="p">)</span></tt>
             </div>
             <div id="l693"
-               class="code sev- "><tt><i>693</i>         <span class="bp">self</span><span class="o">.</span><span class="n">label_unique_values</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="n">tmp</span><span class="o">.</span><span class="n">keys</span><span class="p">())</span></tt>
+               class="code sev- "><tt><i>693</i>         <span class="n">BaseClassifier</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span></tt>
             </div>
             <div id="l694"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (96 > 79 characters)</li>
-               
-               </ul><tt><i>694</i>         <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">label_unique_values</span><span class="p">)</span> <span class="o">&gt;</span> <span class="mi">0</span> <span class="ow">and</span> <span class="nb">isinstance</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">label_unique_values</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="nb">bytes</span><span class="p">):</span></tt>
+               class="code sev- "><tt><i>694</i>         <span class="bp">self</span><span class="o">.</span><span class="n">contrast_attribute</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="kc">None</span></tt>
             </div>
             <div id="l695"
-               class="code sev- "><tt><i>695</i>             <span class="bp">self</span><span class="o">.</span><span class="n">label_unique_values</span> <span class="o">=</span> <span class="p">[</span><span class="n">item</span><span class="o">.</span><span class="n">decode</span><span class="p">(</span></tt>
+               class="code sev- "><tt><i>695</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_remap_to_numeric</span> <span class="o">=</span> <span class="kc">False</span></tt>
             </div>
             <div id="l696"
-               class="code sev- "><tt><i>696</i>                 <span class="s1">&#39;utf-8&#39;</span><span class="p">)</span> <span class="k">for</span> <span class="n">item</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">label_unique_values</span><span class="p">]</span></tt>
+               class="code sev- "><tt><i>696</i>         <span class="bp">self</span><span class="o">.</span><span class="n">label_unique_values</span> <span class="o">=</span> <span class="p">[]</span></tt>
             </div>
             <div id="l697"
-               class="code sev- "><tt><i>697</i> &nbsp;</tt>
+               class="code sev- "><tt><i>697</i>         <span class="bp">self</span><span class="o">.</span><span class="n">model</span><span class="p">:</span> <span class="n">RuleSet</span><span class="p">[</span><span class="n">ClassificationRule</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span></tt>
             </div>
             <div id="l698"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (136 > 79 characters)</li>
-               
-               </ul><tt><i>698</i>     <span class="k">def</span> <span class="nf">fit</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">:</span> <span class="n">Data</span><span class="p">,</span> <span class="n">labels</span><span class="p">:</span> <span class="n">Data</span><span class="p">,</span> <span class="n">contrast_attribute</span><span class="p">:</span> <span class="nb">str</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ContrastSetRuleClassifier</span><span class="p">:</span>  <span class="c1"># pylint: disable=arguments-differ</span></tt>
+               class="code sev- "><tt><i>698</i> &nbsp;</tt>
             </div>
             <div id="l699"
-               class="code sev- "><tt><i>699</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Train model on given dataset.</span></tt>
+               class="code sev- "><tt><i>699</i>     <span class="k">def</span> <span class="nf">_map_result</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">predicted_example_set</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">:</span></tt>
             </div>
             <div id="l700"
-               class="code sev- "><tt><i>700</i> &nbsp;</tt>
+               class="code sev- "><tt><i>700</i>         <span class="n">prediction</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span></tt>
             </div>
             <div id="l701"
-               class="code sev- "><tt><i>701</i> <span class="sd">        Parameters</span></tt>
+               class="code sev- "><tt><i>701</i>         <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">_remap_to_numeric</span><span class="p">:</span></tt>
             </div>
             <div id="l702"
-               class="code sev- "><tt><i>702</i> <span class="sd">        ----------</span></tt>
+               class="code sev- "><tt><i>702</i>             <span class="n">prediction</span> <span class="o">=</span> <span class="n">PredictionResultMapper</span><span class="o">.</span><span class="n">map_to_numerical</span><span class="p">(</span><span class="n">predicted_example_set</span><span class="p">)</span></tt>
             </div>
             <div id="l703"
-               class="code sev- "><tt><i>703</i> <span class="sd">        values : :class:`rulekit.operator.Data`</span></tt>
+               class="code sev- "><tt><i>703</i>         <span class="k">else</span><span class="p">:</span></tt>
             </div>
             <div id="l704"
-               class="code sev- "><tt><i>704</i> <span class="sd">            attributes</span></tt>
+               class="code sev- "><tt><i>704</i>             <span class="n">prediction</span> <span class="o">=</span> <span class="n">PredictionResultMapper</span><span class="o">.</span><span class="n">map_to_nominal</span><span class="p">(</span><span class="n">predicted_example_set</span><span class="p">)</span></tt>
             </div>
             <div id="l705"
-               class="code sev- "><tt><i>705</i> <span class="sd">        labels : :class:`rulekit.operator.Data`</span></tt>
+               class="code sev- "><tt><i>705</i>         <span class="k">return</span> <span class="n">prediction</span></tt>
             </div>
             <div id="l706"
-               class="code sev- "><tt><i>706</i> <span class="sd">            labels</span></tt>
+               class="code sev- "><tt><i>706</i> &nbsp;</tt>
             </div>
             <div id="l707"
-               class="code sev- "><tt><i>707</i> <span class="sd">        contrast_attribute: str</span></tt>
+               class="code sev- "><tt><i>707</i>     <span class="k">def</span> <span class="nf">_get_unique_label_values</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">labels</span><span class="p">:</span> <span class="n">Data</span><span class="p">):</span></tt>
             </div>
             <div id="l708"
-               class="code sev- "><tt><i>708</i> <span class="sd">            group attribute</span></tt>
+               class="code sev- "><tt><i>708</i>         <span class="n">tmp</span> <span class="o">=</span> <span class="p">{}</span></tt>
             </div>
             <div id="l709"
-               class="code sev- "><tt><i>709</i> <span class="sd">        Returns</span></tt>
+               class="code sev- "><tt><i>709</i>         <span class="k">for</span> <span class="n">label_value</span> <span class="ow">in</span> <span class="n">labels</span><span class="p">:</span></tt>
             </div>
             <div id="l710"
-               class="code sev- "><tt><i>710</i> <span class="sd">        -------</span></tt>
+               class="code sev- "><tt><i>710</i>             <span class="n">tmp</span><span class="p">[</span><span class="n">label_value</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span></tt>
             </div>
             <div id="l711"
-               class="code sev- "><tt><i>711</i> <span class="sd">        self : ContrastSetRuleClassifier</span></tt>
+               class="code sev- "><tt><i>711</i>         <span class="bp">self</span><span class="o">.</span><span class="n">label_unique_values</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="n">tmp</span><span class="o">.</span><span class="n">keys</span><span class="p">())</span></tt>
             </div>
             <div id="l712"
-               class="code sev- "><tt><i>712</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
+               class="code sev- "><tt><i>712</i>         <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">label_unique_values</span><span class="p">)</span> <span class="o">&gt;</span> <span class="mi">0</span> <span class="ow">and</span> <span class="nb">isinstance</span><span class="p">(</span></tt>
             </div>
             <div id="l713"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (84 > 79 characters)</li>
-               
-               </ul><tt><i>713</i>         <span class="n">RuleClassifier</span><span class="o">.</span><span class="n">_get_unique_label_values</span><span class="p">(</span>  <span class="c1"># pylint: disable=protected-access</span></tt>
+               class="code sev- "><tt><i>713</i>             <span class="bp">self</span><span class="o">.</span><span class="n">label_unique_values</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="nb">bytes</span></tt>
             </div>
             <div id="l714"
-               class="code sev- "><tt><i>714</i>             <span class="bp">self</span><span class="p">,</span> <span class="n">labels</span></tt>
+               class="code sev- "><tt><i>714</i>         <span class="p">):</span></tt>
             </div>
             <div id="l715"
-               class="code sev- "><tt><i>715</i>         <span class="p">)</span></tt>
+               class="code sev- "><tt><i>715</i>             <span class="bp">self</span><span class="o">.</span><span class="n">label_unique_values</span> <span class="o">=</span> <span class="p">[</span></tt>
             </div>
             <div id="l716"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (92 > 79 characters)</li>
-               
-               </ul><tt><i>716</i>         <span class="n">RuleClassifier</span><span class="o">.</span><span class="n">_prepare_labels</span><span class="p">(</span>  <span class="c1"># pylint: disable=protected-access,protected-access</span></tt>
+               class="code sev- "><tt><i>716</i>                 <span class="n">item</span><span class="o">.</span><span class="n">decode</span><span class="p">(</span><span class="s2">&quot;utf-8&quot;</span><span class="p">)</span> <span class="k">for</span> <span class="n">item</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">label_unique_values</span></tt>
             </div>
             <div id="l717"
-               class="code sev- "><tt><i>717</i>             <span class="bp">self</span><span class="p">,</span> <span class="n">labels</span></tt>
+               class="code sev- "><tt><i>717</i>             <span class="p">]</span></tt>
             </div>
             <div id="l718"
-               class="code sev- "><tt><i>718</i>         <span class="p">)</span></tt>
+               class="code sev- "><tt><i>718</i> &nbsp;</tt>
             </div>
             <div id="l719"
-               class="code sev- "><tt><i>719</i>         <span class="n">BaseOperator</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span></tt>
+               class="code sev- "><tt><i>719</i>     <span class="k">def</span> <span class="nf">fit</span><span class="p">(</span></tt>
             </div>
             <div id="l720"
-               class="code sev- "><tt><i>720</i>             <span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">,</span> <span class="n">labels</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>720</i>         <span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">:</span> <span class="n">Data</span><span class="p">,</span> <span class="n">labels</span><span class="p">:</span> <span class="n">Data</span><span class="p">,</span> <span class="n">contrast_attribute</span><span class="p">:</span> <span class="nb">str</span></tt>
             </div>
             <div id="l721"
-               class="code sev- "><tt><i>721</i>             <span class="n">contrast_attribute</span><span class="o">=</span><span class="n">contrast_attribute</span></tt>
+               class="code sev- "><tt><i>721</i>     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ContrastSetRuleClassifier</span><span class="p">:</span>  <span class="c1"># pylint: disable=arguments-differ</span></tt>
             </div>
             <div id="l722"
-               class="code sev- "><tt><i>722</i>         <span class="p">)</span></tt>
+               class="code sev- "><tt><i>722</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Train model on given dataset.</span></tt>
             </div>
             <div id="l723"
-               class="code sev- "><tt><i>723</i>         <span class="bp">self</span><span class="o">.</span><span class="n">contrast_attribute</span> <span class="o">=</span> <span class="n">contrast_attribute</span></tt>
+               class="code sev- "><tt><i>723</i> &nbsp;</tt>
             </div>
             <div id="l724"
-               class="code sev- "><tt><i>724</i>         <span class="k">return</span> <span class="bp">self</span></tt>
+               class="code sev- "><tt><i>724</i> <span class="sd">        Parameters</span></tt>
             </div>
             <div id="l725"
-               class="code sev- "><tt><i>725</i> &nbsp;</tt>
+               class="code sev- "><tt><i>725</i> <span class="sd">        ----------</span></tt>
             </div>
             <div id="l726"
-               class="code sev- "><tt><i>726</i>     <span class="k">def</span> <span class="nf">predict</span><span class="p">(</span></tt>
+               class="code sev- "><tt><i>726</i> <span class="sd">        values : :class:`rulekit.operator.Data`</span></tt>
             </div>
             <div id="l727"
-               class="code sev- "><tt><i>727</i>         <span class="bp">self</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>727</i> <span class="sd">            attributes</span></tt>
             </div>
             <div id="l728"
-               class="code sev- "><tt><i>728</i>         <span class="n">values</span><span class="p">:</span> <span class="n">Data</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>728</i> <span class="sd">        labels : :class:`rulekit.operator.Data`</span></tt>
             </div>
             <div id="l729"
-               class="code sev- "><tt><i>729</i>         <span class="n">return_metrics</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span></tt>
+               class="code sev- "><tt><i>729</i> <span class="sd">            labels</span></tt>
             </div>
             <div id="l730"
-               class="code sev- "><tt><i>730</i>     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Union</span><span class="p">[</span><span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">,</span> <span class="nb">tuple</span><span class="p">[</span><span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">,</span> <span class="n">ClassificationPredictionMetrics</span><span class="p">]]:</span></tt>
+               class="code sev- "><tt><i>730</i> <span class="sd">        contrast_attribute: str</span></tt>
             </div>
             <div id="l731"
-               class="code sev- "><tt><i>731</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Perform prediction and returns predicted labels.</span></tt>
+               class="code sev- "><tt><i>731</i> <span class="sd">            group attribute</span></tt>
             </div>
             <div id="l732"
-               class="code sev- "><tt><i>732</i> &nbsp;</tt>
+               class="code sev- "><tt><i>732</i> <span class="sd">        Returns</span></tt>
             </div>
             <div id="l733"
-               class="code sev- "><tt><i>733</i> <span class="sd">        Parameters</span></tt>
+               class="code sev- "><tt><i>733</i> <span class="sd">        -------</span></tt>
             </div>
             <div id="l734"
-               class="code sev- "><tt><i>734</i> <span class="sd">        ----------</span></tt>
+               class="code sev- "><tt><i>734</i> <span class="sd">        self : ContrastSetRuleClassifier</span></tt>
             </div>
             <div id="l735"
-               class="code sev- "><tt><i>735</i> <span class="sd">        values : :class:`rulekit.operator.Data`</span></tt>
+               class="code sev- "><tt><i>735</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
             </div>
             <div id="l736"
-               class="code sev- "><tt><i>736</i> <span class="sd">            attributes</span></tt>
+               class="code sev- "><tt><i>736</i>         <span class="n">RuleClassifier</span><span class="o">.</span><span class="n">_get_unique_label_values</span><span class="p">(</span>  <span class="c1"># pylint: disable=protected-access</span></tt>
             </div>
             <div id="l737"
-               class="code sev- "><tt><i>737</i> &nbsp;</tt>
+               class="code sev- "><tt><i>737</i>             <span class="bp">self</span><span class="p">,</span> <span class="n">labels</span></tt>
             </div>
             <div id="l738"
-               class="code sev- "><tt><i>738</i> <span class="sd">        return_metrics: bool = False</span></tt>
+               class="code sev- "><tt><i>738</i>         <span class="p">)</span></tt>
             </div>
             <div id="l739"
                class="code sev-2  le">
@@ -3300,285 +2238,279 @@ <h1>
                      <span class="count sev-2">
                         E501
                      </span>
-                     Line too long (96 > 79 characters)</li>
+                     Line too long (92 > 88 characters)</li>
                
-               </ul><tt><i>739</i> <span class="sd">            Optional flag. If set to *True* method will calculate some additional model metrics.</span></tt>
+               </ul><tt><i>739</i>         <span class="n">RuleClassifier</span><span class="o">.</span><span class="n">_prepare_labels</span><span class="p">(</span>  <span class="c1"># pylint: disable=protected-access,protected-access</span></tt>
             </div>
             <div id="l740"
-               class="code sev- "><tt><i>740</i> <span class="sd">             Method will then return tuple instead of just predicted labels.</span></tt>
+               class="code sev- "><tt><i>740</i>             <span class="bp">self</span><span class="p">,</span> <span class="n">labels</span></tt>
             </div>
             <div id="l741"
-               class="code sev- "><tt><i>741</i> &nbsp;</tt>
+               class="code sev- "><tt><i>741</i>         <span class="p">)</span></tt>
             </div>
             <div id="l742"
-               class="code sev- "><tt><i>742</i> <span class="sd">        Returns</span></tt>
+               class="code sev- "><tt><i>742</i>         <span class="n">BaseOperator</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">,</span> <span class="n">labels</span><span class="p">,</span> <span class="n">contrast_attribute</span><span class="o">=</span><span class="n">contrast_attribute</span><span class="p">)</span></tt>
             </div>
             <div id="l743"
-               class="code sev- "><tt><i>743</i> <span class="sd">        -------</span></tt>
+               class="code sev- "><tt><i>743</i>         <span class="bp">self</span><span class="o">.</span><span class="n">contrast_attribute</span> <span class="o">=</span> <span class="n">contrast_attribute</span></tt>
             </div>
             <div id="l744"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (118 > 79 characters)</li>
-               
-               </ul><tt><i>744</i> <span class="sd">        result : Union[np.ndarray, tuple[np.ndarray, :class:`rulekit.classification.ClassificationPredictionMetrics`]]</span></tt>
+               class="code sev- "><tt><i>744</i>         <span class="k">return</span> <span class="bp">self</span></tt>
             </div>
             <div id="l745"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (97 > 79 characters)</li>
-               
-               </ul><tt><i>745</i> <span class="sd">            If *return_metrics* flag wasn&#39;t set it will return just prediction, otherwise a tuple</span></tt>
+               class="code sev- "><tt><i>745</i> &nbsp;</tt>
             </div>
             <div id="l746"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (94 > 79 characters)</li>
-               
-               </ul><tt><i>746</i> <span class="sd">            will be returned with first element being prediction and second one being metrics.</span></tt>
+               class="code sev- "><tt><i>746</i>     <span class="k">def</span> <span class="nf">predict</span><span class="p">(</span></tt>
             </div>
             <div id="l747"
-               class="code sev- "><tt><i>747</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
+               class="code sev- "><tt><i>747</i>         <span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">:</span> <span class="n">Data</span><span class="p">,</span> <span class="n">return_metrics</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span></tt>
             </div>
             <div id="l748"
-               class="code sev- "><tt><i>748</i>         <span class="k">return</span> <span class="n">RuleClassifier</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">,</span> <span class="n">return_metrics</span><span class="p">)</span></tt>
+               class="code sev- "><tt><i>748</i>     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Union</span><span class="p">[</span><span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">,</span> <span class="nb">tuple</span><span class="p">[</span><span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">,</span> <span class="n">ClassificationPredictionMetrics</span><span class="p">]]:</span></tt>
             </div>
             <div id="l749"
-               class="code sev- "><tt><i>749</i> &nbsp;</tt>
+               class="code sev- "><tt><i>749</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Perform prediction and returns predicted labels.</span></tt>
             </div>
             <div id="l750"
-               class="code sev- "><tt><i>750</i>     <span class="k">def</span> <span class="nf">predict_proba</span><span class="p">(</span></tt>
+               class="code sev- "><tt><i>750</i> &nbsp;</tt>
             </div>
             <div id="l751"
-               class="code sev- "><tt><i>751</i>         <span class="bp">self</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>751</i> <span class="sd">        Parameters</span></tt>
             </div>
             <div id="l752"
-               class="code sev- "><tt><i>752</i>         <span class="n">values</span><span class="p">:</span> <span class="n">Data</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>752</i> <span class="sd">        ----------</span></tt>
             </div>
             <div id="l753"
-               class="code sev- "><tt><i>753</i>         <span class="n">return_metrics</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span></tt>
+               class="code sev- "><tt><i>753</i> <span class="sd">        values : :class:`rulekit.operator.Data`</span></tt>
             </div>
             <div id="l754"
-               class="code sev- "><tt><i>754</i>     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Union</span><span class="p">[</span><span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">,</span> <span class="nb">tuple</span><span class="p">[</span><span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">,</span> <span class="n">ClassificationPredictionMetrics</span><span class="p">]]:</span></tt>
+               class="code sev- "><tt><i>754</i> <span class="sd">            attributes</span></tt>
             </div>
             <div id="l755"
-               class="code sev- "><tt><i>755</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Perform prediction and returns class probabilities for each example.</span></tt>
+               class="code sev- "><tt><i>755</i> &nbsp;</tt>
             </div>
             <div id="l756"
-               class="code sev- "><tt><i>756</i> &nbsp;</tt>
+               class="code sev- "><tt><i>756</i> <span class="sd">        return_metrics: bool = False</span></tt>
             </div>
             <div id="l757"
-               class="code sev- "><tt><i>757</i> <span class="sd">        Parameters</span></tt>
+               class="code sev- "><tt><i>757</i> <span class="sd">            Optional flag. If set to *True* method will calculate some additional model</span></tt>
             </div>
             <div id="l758"
-               class="code sev- "><tt><i>758</i> <span class="sd">        ----------</span></tt>
+               class="code sev- "><tt><i>758</i> <span class="sd">            metrics. Method will then return tuple instead of just predicted labels.</span></tt>
             </div>
             <div id="l759"
-               class="code sev- "><tt><i>759</i> <span class="sd">        values : :class:`rulekit.operator.Data`</span></tt>
+               class="code sev- "><tt><i>759</i> &nbsp;</tt>
             </div>
             <div id="l760"
-               class="code sev- "><tt><i>760</i> <span class="sd">            attributes</span></tt>
+               class="code sev- "><tt><i>760</i> <span class="sd">        Returns</span></tt>
             </div>
             <div id="l761"
-               class="code sev- "><tt><i>761</i> &nbsp;</tt>
+               class="code sev- "><tt><i>761</i> <span class="sd">        -------</span></tt>
             </div>
             <div id="l762"
-               class="code sev- "><tt><i>762</i> <span class="sd">        return_metrics: bool = False</span></tt>
+               class="code sev- "><tt><i>762</i> <span class="sd">        result : Union[np.ndarray, tuple[np.ndarray, :class:`rulekit.classification.\</span></tt>
             </div>
             <div id="l763"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (96 > 79 characters)</li>
-               
-               </ul><tt><i>763</i> <span class="sd">            Optional flag. If set to *True* method will calculate some additional model metrics.</span></tt>
+               class="code sev- "><tt><i>763</i> <span class="sd">            ClassificationPredictionMetrics`]]</span></tt>
             </div>
             <div id="l764"
-               class="code sev- "><tt><i>764</i> <span class="sd">             Method will then return tuple instead of just probabilities.</span></tt>
+               class="code sev- "><tt><i>764</i> <span class="sd">            If *return_metrics* flag wasn&#39;t set it will return just prediction,</span></tt>
             </div>
             <div id="l765"
-               class="code sev- "><tt><i>765</i> &nbsp;</tt>
+               class="code sev- "><tt><i>765</i> <span class="sd">            otherwise a tuple will be returned with first element being prediction and</span></tt>
             </div>
             <div id="l766"
-               class="code sev- "><tt><i>766</i> <span class="sd">        Returns</span></tt>
+               class="code sev- "><tt><i>766</i> <span class="sd">            second one being metrics.</span></tt>
             </div>
             <div id="l767"
-               class="code sev- "><tt><i>767</i> <span class="sd">        -------</span></tt>
+               class="code sev- "><tt><i>767</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
             </div>
             <div id="l768"
-               class="code sev- "><tt><i>768</i> <span class="sd">        result : Union[ \</span></tt>
+               class="code sev- "><tt><i>768</i>         <span class="k">return</span> <span class="n">RuleClassifier</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">,</span> <span class="n">return_metrics</span><span class="p">)</span></tt>
             </div>
             <div id="l769"
-               class="code sev- "><tt><i>769</i> <span class="sd">            np.ndarray,  \</span></tt>
+               class="code sev- "><tt><i>769</i> &nbsp;</tt>
             </div>
             <div id="l770"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (96 > 79 characters)</li>
-               
-               </ul><tt><i>770</i> <span class="sd">            tuple[np.ndarray, :class:`rulekit.classification.ClassificationPredictionMetrics`] \</span></tt>
+               class="code sev- "><tt><i>770</i>     <span class="k">def</span> <span class="nf">predict_proba</span><span class="p">(</span></tt>
             </div>
             <div id="l771"
-               class="code sev- "><tt><i>771</i> <span class="sd">        ] \</span></tt>
+               class="code sev- "><tt><i>771</i>         <span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">:</span> <span class="n">Data</span><span class="p">,</span> <span class="n">return_metrics</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span></tt>
             </div>
             <div id="l772"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (97 > 79 characters)</li>
-               
-               </ul><tt><i>772</i> <span class="sd">        If *return_metrics* flag wasn&#39;t set it will return just probabilities matrix, otherwise \</span></tt>
+               class="code sev- "><tt><i>772</i>     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Union</span><span class="p">[</span><span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">,</span> <span class="nb">tuple</span><span class="p">[</span><span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">,</span> <span class="n">ClassificationPredictionMetrics</span><span class="p">]]:</span></tt>
             </div>
             <div id="l773"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (91 > 79 characters)</li>
-               
-               </ul><tt><i>773</i> <span class="sd">        a tuple will be returned with first element being prediction and second one being \</span></tt>
+               class="code sev- "><tt><i>773</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Perform prediction and returns class probabilities for each example.</span></tt>
             </div>
             <div id="l774"
-               class="code sev- "><tt><i>774</i> <span class="sd">        metrics.</span></tt>
+               class="code sev- "><tt><i>774</i> &nbsp;</tt>
             </div>
             <div id="l775"
-               class="code sev- "><tt><i>775</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
+               class="code sev- "><tt><i>775</i> <span class="sd">        Parameters</span></tt>
             </div>
             <div id="l776"
-               class="code sev- "><tt><i>776</i>         <span class="k">return</span> <span class="n">RuleClassifier</span><span class="o">.</span><span class="n">predict_proba</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">,</span> <span class="n">return_metrics</span><span class="p">)</span></tt>
+               class="code sev- "><tt><i>776</i> <span class="sd">        ----------</span></tt>
             </div>
             <div id="l777"
-               class="code sev- "><tt><i>777</i> &nbsp;</tt>
+               class="code sev- "><tt><i>777</i> <span class="sd">        values : :class:`rulekit.operator.Data`</span></tt>
             </div>
             <div id="l778"
-               class="code sev- "><tt><i>778</i>     <span class="k">def</span> <span class="nf">score</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">:</span> <span class="n">Data</span><span class="p">,</span> <span class="n">labels</span><span class="p">:</span> <span class="n">Data</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">float</span><span class="p">:</span></tt>
+               class="code sev- "><tt><i>778</i> <span class="sd">            attributes</span></tt>
             </div>
             <div id="l779"
-               class="code sev- "><tt><i>779</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Return the accuracy on the given test data and labels.</span></tt>
+               class="code sev- "><tt><i>779</i> &nbsp;</tt>
             </div>
             <div id="l780"
-               class="code sev- "><tt><i>780</i> &nbsp;</tt>
+               class="code sev- "><tt><i>780</i> <span class="sd">        return_metrics: bool = False</span></tt>
             </div>
             <div id="l781"
-               class="code sev- "><tt><i>781</i> <span class="sd">        Parameters</span></tt>
+               class="code sev- "><tt><i>781</i> <span class="sd">            Optional flag. If set to *True* method will calculate some additional model</span></tt>
             </div>
             <div id="l782"
-               class="code sev- "><tt><i>782</i> <span class="sd">        ----------</span></tt>
+               class="code sev- "><tt><i>782</i> <span class="sd">            metrics. Method will then return tuple instead of just probabilities.</span></tt>
             </div>
             <div id="l783"
-               class="code sev- "><tt><i>783</i> <span class="sd">        values : :class:`rulekit.operator.Data`</span></tt>
+               class="code sev- "><tt><i>783</i> &nbsp;</tt>
             </div>
             <div id="l784"
-               class="code sev- "><tt><i>784</i> <span class="sd">            attributes</span></tt>
+               class="code sev- "><tt><i>784</i> <span class="sd">        Returns</span></tt>
             </div>
             <div id="l785"
-               class="code sev- "><tt><i>785</i> <span class="sd">        labels : :class:`rulekit.operator.Data`</span></tt>
+               class="code sev- "><tt><i>785</i> <span class="sd">        -------</span></tt>
             </div>
             <div id="l786"
-               class="code sev- "><tt><i>786</i> <span class="sd">            true labels</span></tt>
+               class="code sev- "><tt><i>786</i> <span class="sd">        result : Union[np.ndarray, tuple[np.ndarray, :class:`rulekit.classification.\</span></tt>
             </div>
             <div id="l787"
-               class="code sev- "><tt><i>787</i> &nbsp;</tt>
+               class="code sev- "><tt><i>787</i> <span class="sd">            ClassificationPredictionMetrics`]]</span></tt>
             </div>
             <div id="l788"
-               class="code sev- "><tt><i>788</i> <span class="sd">        Returns</span></tt>
+               class="code sev- "><tt><i>788</i> <span class="sd">            If *return_metrics* flag wasn&#39;t set it will return just probabilities</span></tt>
             </div>
             <div id="l789"
-               class="code sev- "><tt><i>789</i> <span class="sd">        -------</span></tt>
+               class="code sev- "><tt><i>789</i> <span class="sd">            matrix, otherwise a tuple will be returned with first element being</span></tt>
             </div>
             <div id="l790"
-               class="code sev- "><tt><i>790</i> <span class="sd">        score : float</span></tt>
+               class="code sev- "><tt><i>790</i> <span class="sd">            prediction and second one being metrics.</span></tt>
             </div>
             <div id="l791"
-               class="code sev- "><tt><i>791</i> <span class="sd">            Accuracy of self.predict(values) wrt. labels.</span></tt>
+               class="code sev- "><tt><i>791</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
             </div>
             <div id="l792"
-               class="code sev- "><tt><i>792</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
+               class="code sev- "><tt><i>792</i>         <span class="k">return</span> <span class="n">RuleClassifier</span><span class="o">.</span><span class="n">predict_proba</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">,</span> <span class="n">return_metrics</span><span class="p">)</span></tt>
             </div>
             <div id="l793"
-               class="code sev- "><tt><i>793</i>         <span class="k">return</span> <span class="n">RuleClassifier</span><span class="o">.</span><span class="n">score</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">,</span> <span class="n">labels</span><span class="p">)</span></tt>
+               class="code sev- "><tt><i>793</i> &nbsp;</tt>
             </div>
             <div id="l794"
-               class="code sev- "><tt><i>794</i> &nbsp;</tt>
+               class="code sev- "><tt><i>794</i>     <span class="k">def</span> <span class="nf">score</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">:</span> <span class="n">Data</span><span class="p">,</span> <span class="n">labels</span><span class="p">:</span> <span class="n">Data</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">float</span><span class="p">:</span></tt>
             </div>
             <div id="l795"
-               class="code sev- "><tt><i>795</i>     <span class="k">def</span> <span class="nf">__getstate__</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">dict</span><span class="p">:</span></tt>
+               class="code sev- "><tt><i>795</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Return the accuracy on the given test data and labels.</span></tt>
             </div>
             <div id="l796"
-               class="code sev- "><tt><i>796</i>         <span class="k">return</span> <span class="p">{</span><span class="o">**</span><span class="n">BaseOperator</span><span class="o">.</span><span class="n">__getstate__</span><span class="p">(</span><span class="bp">self</span><span class="p">),</span> <span class="o">**</span><span class="p">{</span></tt>
+               class="code sev- "><tt><i>796</i> &nbsp;</tt>
             </div>
             <div id="l797"
-               class="code sev- "><tt><i>797</i>             <span class="s1">&#39;label_unique_values&#39;</span><span class="p">:</span> <span class="bp">self</span><span class="o">.</span><span class="n">label_unique_values</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>797</i> <span class="sd">        Parameters</span></tt>
             </div>
             <div id="l798"
-               class="code sev- "><tt><i>798</i>             <span class="s1">&#39;_remap_to_numeric&#39;</span><span class="p">:</span> <span class="bp">self</span><span class="o">.</span><span class="n">_remap_to_numeric</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>798</i> <span class="sd">        ----------</span></tt>
             </div>
             <div id="l799"
-               class="code sev- "><tt><i>799</i>             <span class="s1">&#39;contrast_attribute&#39;</span><span class="p">:</span> <span class="bp">self</span><span class="o">.</span><span class="n">contrast_attribute</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>799</i> <span class="sd">        values : :class:`rulekit.operator.Data`</span></tt>
             </div>
             <div id="l800"
-               class="code sev- "><tt><i>800</i>         <span class="p">}}</span></tt>
+               class="code sev- "><tt><i>800</i> <span class="sd">            attributes</span></tt>
             </div>
             <div id="l801"
-               class="code sev- "><tt><i>801</i> &nbsp;</tt>
+               class="code sev- "><tt><i>801</i> <span class="sd">        labels : :class:`rulekit.operator.Data`</span></tt>
             </div>
             <div id="l802"
-               class="code sev- "><tt><i>802</i>     <span class="k">def</span> <span class="nf">__setstate__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">state</span><span class="p">:</span> <span class="nb">dict</span><span class="p">):</span></tt>
+               class="code sev- "><tt><i>802</i> <span class="sd">            true labels</span></tt>
             </div>
             <div id="l803"
-               class="code sev- "><tt><i>803</i>         <span class="n">BaseOperator</span><span class="o">.</span><span class="n">__setstate__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">state</span><span class="p">)</span></tt>
+               class="code sev- "><tt><i>803</i> &nbsp;</tt>
             </div>
             <div id="l804"
-               class="code sev- "><tt><i>804</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_init_classification_rule_performance_classes</span><span class="p">()</span></tt>
+               class="code sev- "><tt><i>804</i> <span class="sd">        Returns</span></tt>
             </div>
             <div id="l805"
-               class="code sev- "><tt><i>805</i>         <span class="bp">self</span><span class="o">.</span><span class="n">label_unique_values</span> <span class="o">=</span> <span class="n">state</span><span class="p">[</span><span class="s1">&#39;label_unique_values&#39;</span><span class="p">]</span></tt>
+               class="code sev- "><tt><i>805</i> <span class="sd">        -------</span></tt>
             </div>
             <div id="l806"
-               class="code sev- "><tt><i>806</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_remap_to_numeric</span> <span class="o">=</span> <span class="n">state</span><span class="p">[</span><span class="s1">&#39;_remap_to_numeric&#39;</span><span class="p">]</span></tt>
+               class="code sev- "><tt><i>806</i> <span class="sd">        score : float</span></tt>
             </div>
             <div id="l807"
-               class="code sev- "><tt><i>807</i>         <span class="bp">self</span><span class="o">.</span><span class="n">contrast_attribute</span> <span class="o">=</span> <span class="n">state</span><span class="p">[</span><span class="s1">&#39;contrast_attribute&#39;</span><span class="p">]</span></tt>
+               class="code sev- "><tt><i>807</i> <span class="sd">            Accuracy of self.predict(values) wrt. labels.</span></tt>
             </div>
             <div id="l808"
-               class="code sev- "><tt><i>808</i> &nbsp;</tt>
+               class="code sev- "><tt><i>808</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
             </div>
             <div id="l809"
-               class="code sev- "><tt><i>809</i>     <span class="k">def</span> <span class="nf">_get_problem_type</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ProblemType</span><span class="p">:</span></tt>
+               class="code sev- "><tt><i>809</i>         <span class="k">return</span> <span class="n">RuleClassifier</span><span class="o">.</span><span class="n">score</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">,</span> <span class="n">labels</span><span class="p">)</span></tt>
             </div>
             <div id="l810"
-               class="code sev- "><tt><i>810</i>         <span class="k">return</span> <span class="n">ProblemType</span><span class="o">.</span><span class="n">CONTRAST_CLASSIFICATION</span></tt>
+               class="code sev- "><tt><i>810</i> &nbsp;</tt>
+            </div>
+            <div id="l811"
+               class="code sev- "><tt><i>811</i>     <span class="k">def</span> <span class="nf">__getstate__</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">dict</span><span class="p">:</span></tt>
+            </div>
+            <div id="l812"
+               class="code sev- "><tt><i>812</i>         <span class="k">return</span> <span class="p">{</span></tt>
+            </div>
+            <div id="l813"
+               class="code sev- "><tt><i>813</i>             <span class="o">**</span><span class="n">BaseOperator</span><span class="o">.</span><span class="n">__getstate__</span><span class="p">(</span><span class="bp">self</span><span class="p">),</span></tt>
+            </div>
+            <div id="l814"
+               class="code sev- "><tt><i>814</i>             <span class="o">**</span><span class="p">{</span></tt>
+            </div>
+            <div id="l815"
+               class="code sev- "><tt><i>815</i>                 <span class="s2">&quot;label_unique_values&quot;</span><span class="p">:</span> <span class="bp">self</span><span class="o">.</span><span class="n">label_unique_values</span><span class="p">,</span></tt>
+            </div>
+            <div id="l816"
+               class="code sev- "><tt><i>816</i>                 <span class="s2">&quot;_remap_to_numeric&quot;</span><span class="p">:</span> <span class="bp">self</span><span class="o">.</span><span class="n">_remap_to_numeric</span><span class="p">,</span></tt>
+            </div>
+            <div id="l817"
+               class="code sev- "><tt><i>817</i>                 <span class="s2">&quot;contrast_attribute&quot;</span><span class="p">:</span> <span class="bp">self</span><span class="o">.</span><span class="n">contrast_attribute</span><span class="p">,</span></tt>
+            </div>
+            <div id="l818"
+               class="code sev- "><tt><i>818</i>             <span class="p">},</span></tt>
+            </div>
+            <div id="l819"
+               class="code sev- "><tt><i>819</i>         <span class="p">}</span></tt>
+            </div>
+            <div id="l820"
+               class="code sev- "><tt><i>820</i> &nbsp;</tt>
+            </div>
+            <div id="l821"
+               class="code sev- "><tt><i>821</i>     <span class="k">def</span> <span class="nf">__setstate__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">state</span><span class="p">:</span> <span class="nb">dict</span><span class="p">):</span></tt>
+            </div>
+            <div id="l822"
+               class="code sev- "><tt><i>822</i>         <span class="n">BaseOperator</span><span class="o">.</span><span class="n">__setstate__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">state</span><span class="p">)</span></tt>
+            </div>
+            <div id="l823"
+               class="code sev- "><tt><i>823</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_init_classification_rule_performance_classes</span><span class="p">()</span></tt>
+            </div>
+            <div id="l824"
+               class="code sev- "><tt><i>824</i>         <span class="bp">self</span><span class="o">.</span><span class="n">label_unique_values</span> <span class="o">=</span> <span class="n">state</span><span class="p">[</span><span class="s2">&quot;label_unique_values&quot;</span><span class="p">]</span></tt>
+            </div>
+            <div id="l825"
+               class="code sev- "><tt><i>825</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_remap_to_numeric</span> <span class="o">=</span> <span class="n">state</span><span class="p">[</span><span class="s2">&quot;_remap_to_numeric&quot;</span><span class="p">]</span></tt>
+            </div>
+            <div id="l826"
+               class="code sev- "><tt><i>826</i>         <span class="bp">self</span><span class="o">.</span><span class="n">contrast_attribute</span> <span class="o">=</span> <span class="n">state</span><span class="p">[</span><span class="s2">&quot;contrast_attribute&quot;</span><span class="p">]</span></tt>
+            </div>
+            <div id="l827"
+               class="code sev- "><tt><i>827</i> &nbsp;</tt>
+            </div>
+            <div id="l828"
+               class="code sev- "><tt><i>828</i>     <span class="k">def</span> <span class="nf">_get_problem_type</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ProblemType</span><span class="p">:</span></tt>
+            </div>
+            <div id="l829"
+               class="code sev- "><tt><i>829</i>         <span class="k">return</span> <span class="n">ProblemType</span><span class="o">.</span><span class="n">CONTRAST_CLASSIFICATION</span></tt>
             </div>
             
          </div>
diff --git a/docs/reports/flake8/rulekit.events.report.html b/docs/reports/flake8/rulekit.events.report.html
index edf0594..3b006f7 100644
--- a/docs/reports/flake8/rulekit.events.report.html
+++ b/docs/reports/flake8/rulekit.events.report.html
@@ -54,7 +54,7 @@ <h1>
                <span class="count sev-2">
                   2
                </span>
-               <strong>E501:</strong> line too long (94 > 79 characters)
+               <strong>E501:</strong> line too long (94 > 88 characters)
                
                   (and 1 similar)
                
@@ -62,14 +62,14 @@ <h1>
             <ul class="details">
             <li>
                
-               <p>Line too long (94 > 79 characters):</p>
+               <p>Line too long (94 > 88 characters):</p>
                
                <a href="rulekit.events.source.html#l58">
                   <tt><i>58</i>         <span class="n">ICommandListener</span>  <span class="c1"># pylint: disable=import-outside-toplevel,import-error,line-too-long</span></tt>
                </a>
             </li><li>
                
-               <p>Line too long (100 > 79 characters):</p>
+               <p>Line too long (100 > 88 characters):</p>
                
                <a href="rulekit.events.source.html#l61">
                   <tt><i>61</i>     <span class="k">class</span> <span class="nc">_CommandListener</span><span class="p">:</span>  <span class="c1"># pylint: disable=invalid-name,missing-function-docstring,line-too-long</span></tt>
diff --git a/docs/reports/flake8/rulekit.events.source.html b/docs/reports/flake8/rulekit.events.source.html
index 50f4820..06eb89e 100644
--- a/docs/reports/flake8/rulekit.events.source.html
+++ b/docs/reports/flake8/rulekit.events.source.html
@@ -195,7 +195,7 @@ <h1>
                      <span class="count sev-2">
                         E501
                      </span>
-                     Line too long (94 > 79 characters)</li>
+                     Line too long (94 > 88 characters)</li>
                
                </ul><tt><i>58</i>         <span class="n">ICommandListener</span>  <span class="c1"># pylint: disable=import-outside-toplevel,import-error,line-too-long</span></tt>
             </div>
@@ -213,7 +213,7 @@ <h1>
                      <span class="count sev-2">
                         E501
                      </span>
-                     Line too long (100 > 79 characters)</li>
+                     Line too long (100 > 88 characters)</li>
                
                </ul><tt><i>61</i>     <span class="k">class</span> <span class="nc">_CommandListener</span><span class="p">:</span>  <span class="c1"># pylint: disable=invalid-name,missing-function-docstring,line-too-long</span></tt>
             </div>
diff --git a/docs/reports/flake8/rulekit.main.report.html b/docs/reports/flake8/rulekit.main.report.html
deleted file mode 100644
index 5dc3b50..0000000
--- a/docs/reports/flake8/rulekit.main.report.html
+++ /dev/null
@@ -1,196 +0,0 @@
-<!DOCTYPE html>
-<html>
-   <head>
-      <title>flake8 violations: rulekit\main.py</title>
-      <meta http-equiv="Content-Type" value="text/html; charset=UTF-8">
-      <link rel="stylesheet" href="styles.css">
-<script>
-function bindHandler(link) {
-   var code = link.getAttribute('data-code');
-   var key = location.pathname + '#' + code;
-
-   var ul = link.parentNode.querySelector('.details');
-   if (sessionStorage[key] != 'open') {
-      ul.style.display = 'none';
-   }
-   link.addEventListener('click', function (event) {
-      if (!ul.style.display || ul.style.display == 'none') {
-         ul.style.display = 'block';
-         sessionStorage[key] = 'open';
-      } else {
-         ul.style.display = 'none';
-         sessionStorage[key] = 'closed';
-      }
-   });
-}
-
-window.addEventListener('DOMContentLoaded', function () {
-   var links = document.querySelectorAll('#index > li > a');
-   for (var i = 0; i < links.length; i++) {
-      bindHandler(links[i]);
-   }
-});
-</script>
-   </head>
-   <body>
-      <div id="masthead" class="sev-2"></div>
-      <div id="page">
-         <p id="srclink">
-            <a title="View full annotated source"
-               href="rulekit.main.source.html">
-               <img src="file.svg" alt="&#x2261;">
-            </a></p>
-         <h1>
-            <a href="index.html">
-               <img src="back.svg" alt="&#x2B05;">
-               rulekit\main.py
-            </a>
-         </h1>
-
-         <ul id="index">
-         
-         <li>
-            <a data-code="E501">
-               <span class="count sev-2">
-                  18
-               </span>
-               <strong>E501:</strong> line too long (92 > 79 characters)
-               
-                  (and 12 similar)
-               
-            </a>
-            <ul class="details">
-            <li>
-               
-               <p>Line too long (92 > 79 characters):</p>
-               
-               <a href="rulekit.main.source.html#l28">
-                  <tt><i>28</i> <span class="w">    </span><span class="sd">&quot;&quot;&quot;Class used for initializing RuleKit. It starts JVM underhood and setups it with jars.</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (82 > 79 characters):</p>
-               
-               <a href="rulekit.main.source.html#l30">
-                  <tt><i>30</i> <span class="sd">    .. note:: Since version 1.7.0 there is no need to manually initialize RuleKit.</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (84 > 79 characters):</p>
-               
-               <a href="rulekit.main.source.html#l31">
-                  <tt><i>31</i> <span class="sd">    You may just skip the **RuleKit.init()** line. However in certain scenarios when</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (83 > 79 characters):</p>
-               
-               <a href="rulekit.main.source.html#l32">
-                  <tt><i>32</i> <span class="sd">    you want use a custom RuleKit jar file or modify Java VM parameters, this class</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (85 > 79 characters):</p>
-               
-               <a href="rulekit.main.source.html#l39">
-                  <tt><i>39</i> <span class="sd">        version of RuleKit jar used by wrapper (not equal to python package version).</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (83 > 79 characters):</p>
-               
-               <a href="rulekit.main.source.html#l53">
-                  <tt><i>53</i>             <span class="k">with</span> <span class="n">Popen</span><span class="p">([</span><span class="s2">&quot;java&quot;</span><span class="p">,</span> <span class="s2">&quot;-version&quot;</span><span class="p">],</span> <span class="n">stderr</span><span class="o">=</span><span class="n">STDOUT</span><span class="p">,</span> <span class="n">stdout</span><span class="o">=</span><span class="n">PIPE</span><span class="p">)</span> <span class="k">as</span> <span class="n">output</span><span class="p">:</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (88 > 79 characters):</p>
-               
-               <a href="rulekit.main.source.html#l61">
-                  <tt><i>61</i>                 <span class="s1">&#39;RuletKit requires java JRE to be installed (version 1.8.0 recommended)&#39;</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (97 > 79 characters):</p>
-               
-               <a href="rulekit.main.source.html#l74">
-                  <tt><i>74</i> <span class="sd">        .. note:: Since version 1.7.0 it don&#39;t have to be called before using any operator class.</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (98 > 79 characters):</p>
-               
-               <a href="rulekit.main.source.html#l75">
-                  <tt><i>75</i> <span class="sd">        However in certain scenarios when you want use a custom RuleKit jar file or modify Java VM</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (84 > 79 characters):</p>
-               
-               <a href="rulekit.main.source.html#l87">
-                  <tt><i>87</i> <span class="sd">                You probably don&#39;t need to use this parameter unless you want to use</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (85 > 79 characters):</p>
-               
-               <a href="rulekit.main.source.html#l88">
-                  <tt><i>88</i> <span class="sd">                your own custom version of RuleKit jar file. Otherwise leave it as it</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (82 > 79 characters):</p>
-               
-               <a href="rulekit.main.source.html#l89">
-                  <tt><i>89</i> <span class="sd">                is and the package will use the official RuleKit release jar file.</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (115 > 79 characters):</p>
-               
-               <a href="rulekit.main.source.html#l122">
-                  <tt><i>122</i> <span class="s1">Failed to load RuleKit jar file. Check if valid rulekit jar file is present in &quot;</span><span class="si">{</span><span class="n">RuleKit</span><span class="o">.</span><span class="n">_jar_dir_path</span><span class="si">}</span><span class="s1">&quot; directory.</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (99 > 79 characters):</p>
-               
-               <a href="rulekit.main.source.html#l124">
-                  <tt><i>124</i> <span class="s1">If you&#39;re running this package for the first time you need to download RuleKit jar file by running:</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (81 > 79 characters):</p>
-               
-               <a href="rulekit.main.source.html#l138">
-                  <tt><i>138</i>         <span class="k">with</span> <span class="n">zipfile</span><span class="o">.</span><span class="n">ZipFile</span><span class="p">(</span><span class="n">RuleKit</span><span class="o">.</span><span class="n">_rulekit_jar_file_path</span><span class="p">,</span> <span class="s1">&#39;r&#39;</span><span class="p">)</span> <span class="k">as</span> <span class="n">jar_archive</span><span class="p">:</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (93 > 79 characters):</p>
-               
-               <a href="rulekit.main.source.html#l143">
-                  <tt><i>143</i>                     <span class="sa">r</span><span class="s1">&#39;Implementation-Version: \S+\r&#39;</span><span class="p">,</span> <span class="n">manifest_file_content</span><span class="p">)[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="s1">&#39; &#39;</span><span class="p">)[</span><span class="mi">1</span><span class="p">]</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (81 > 79 characters):</p>
-               
-               <a href="rulekit.main.source.html#l171">
-                  <tt><i>171</i> <span class="sd">        method unless you want too deep dive into the process of rules inductions</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (89 > 79 characters):</p>
-               
-               <a href="rulekit.main.source.html#l187">
-                  <tt><i>187</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Returns the Java logger configuration configured using `configure_java_logger`</span></tt>
-               </a>
-            </li>
-            </ul>
-         </li>
-         
-         </ul>
-      </div>
-   </body>
-</html>
\ No newline at end of file
diff --git a/docs/reports/flake8/rulekit.main.source.html b/docs/reports/flake8/rulekit.main.source.html
deleted file mode 100644
index dd3baac..0000000
--- a/docs/reports/flake8/rulekit.main.source.html
+++ /dev/null
@@ -1,764 +0,0 @@
-<!DOCTYPE html>
-<html>
-   <head>
-      <title>rulekit\main.py - flake8 annotated source</title>
-      <meta http-equiv="Content-Type" value="text/html; charset=UTF-8">
-      <link rel="stylesheet" href="styles.css">
-   </head>
-   <body>
-      <div id="masthead" class="sev-2"></div>
-      <div id="page">
-         <h1>
-            <a href="rulekit.main.report.html">
-               <img src="back.svg" alt="&#x2B05;">
-               rulekit\main.py source
-            </a>
-         </h1>
-
-         <div id="doc">
-            <div id="l1"
-               class="code sev- "><tt><i>1</i> <span class="sd">&quot;&quot;&quot;Contains classes for initializing RuleKit Java backend</span></tt>
-            </div>
-            <div id="l2"
-               class="code sev- "><tt><i>2</i> <span class="sd">&quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l3"
-               class="code sev- "><tt><i>3</i> <span class="kn">import</span> <span class="nn">logging</span></tt>
-            </div>
-            <div id="l4"
-               class="code sev- "><tt><i>4</i> <span class="kn">import</span> <span class="nn">os</span></tt>
-            </div>
-            <div id="l5"
-               class="code sev- "><tt><i>5</i> <span class="kn">import</span> <span class="nn">re</span></tt>
-            </div>
-            <div id="l6"
-               class="code sev- "><tt><i>6</i> <span class="kn">import</span> <span class="nn">zipfile</span></tt>
-            </div>
-            <div id="l7"
-               class="code sev- "><tt><i>7</i> <span class="kn">from</span> <span class="nn">enum</span> <span class="kn">import</span> <span class="n">Enum</span></tt>
-            </div>
-            <div id="l8"
-               class="code sev- "><tt><i>8</i> <span class="kn">from</span> <span class="nn">subprocess</span> <span class="kn">import</span> <span class="n">PIPE</span></tt>
-            </div>
-            <div id="l9"
-               class="code sev- "><tt><i>9</i> <span class="kn">from</span> <span class="nn">subprocess</span> <span class="kn">import</span> <span class="n">Popen</span></tt>
-            </div>
-            <div id="l10"
-               class="code sev- "><tt><i>10</i> <span class="kn">from</span> <span class="nn">subprocess</span> <span class="kn">import</span> <span class="n">STDOUT</span></tt>
-            </div>
-            <div id="l11"
-               class="code sev- "><tt><i>11</i> <span class="kn">from</span> <span class="nn">typing</span> <span class="kn">import</span> <span class="n">Optional</span></tt>
-            </div>
-            <div id="l12"
-               class="code sev- "><tt><i>12</i> &nbsp;</tt>
-            </div>
-            <div id="l13"
-               class="code sev- "><tt><i>13</i> <span class="kn">import</span> <span class="nn">jpype.imports</span></tt>
-            </div>
-            <div id="l14"
-               class="code sev- "><tt><i>14</i> &nbsp;</tt>
-            </div>
-            <div id="l15"
-               class="code sev- "><tt><i>15</i> <span class="kn">from</span> <span class="nn">rulekit._logging</span> <span class="kn">import</span> <span class="n">_RuleKitJavaLoggerConfig</span></tt>
-            </div>
-            <div id="l16"
-               class="code sev- "><tt><i>16</i> &nbsp;</tt>
-            </div>
-            <div id="l17"
-               class="code sev- "><tt><i>17</i> <span class="n">__RULEKIT_RELEASE_VERSION__</span> <span class="o">=</span> <span class="s1">&#39;2.1.21&#39;</span></tt>
-            </div>
-            <div id="l18"
-               class="code sev- "><tt><i>18</i> <span class="n">__VERSION__</span> <span class="o">=</span> <span class="sa">f</span><span class="s1">&#39;</span><span class="si">{</span><span class="n">__RULEKIT_RELEASE_VERSION__</span><span class="si">}</span><span class="s1">.0&#39;</span></tt>
-            </div>
-            <div id="l19"
-               class="code sev- "><tt><i>19</i> &nbsp;</tt>
-            </div>
-            <div id="l20"
-               class="code sev- "><tt><i>20</i> &nbsp;</tt>
-            </div>
-            <div id="l21"
-               class="code sev- "><tt><i>21</i> <span class="k">class</span> <span class="nc">JRE_Type</span><span class="p">(</span><span class="n">Enum</span><span class="p">):</span>  <span class="c1"># pylint: disable=invalid-name</span></tt>
-            </div>
-            <div id="l22"
-               class="code sev- "><tt><i>22</i> <span class="w">    </span><span class="sd">&quot;&quot;&quot;:meta private:&quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l23"
-               class="code sev- "><tt><i>23</i>     <span class="n">OPEN_JDK</span> <span class="o">=</span> <span class="s1">&#39;open_jdk&#39;</span></tt>
-            </div>
-            <div id="l24"
-               class="code sev- "><tt><i>24</i>     <span class="n">ORACLE</span> <span class="o">=</span> <span class="s1">&#39;oracle&#39;</span></tt>
-            </div>
-            <div id="l25"
-               class="code sev- "><tt><i>25</i> &nbsp;</tt>
-            </div>
-            <div id="l26"
-               class="code sev- "><tt><i>26</i> &nbsp;</tt>
-            </div>
-            <div id="l27"
-               class="code sev- "><tt><i>27</i> <span class="k">class</span> <span class="nc">RuleKit</span><span class="p">:</span></tt>
-            </div>
-            <div id="l28"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (92 > 79 characters)</li>
-               
-               </ul><tt><i>28</i> <span class="w">    </span><span class="sd">&quot;&quot;&quot;Class used for initializing RuleKit. It starts JVM underhood and setups it with jars.</span></tt>
-            </div>
-            <div id="l29"
-               class="code sev- "><tt><i>29</i> &nbsp;</tt>
-            </div>
-            <div id="l30"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (82 > 79 characters)</li>
-               
-               </ul><tt><i>30</i> <span class="sd">    .. note:: Since version 1.7.0 there is no need to manually initialize RuleKit.</span></tt>
-            </div>
-            <div id="l31"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (84 > 79 characters)</li>
-               
-               </ul><tt><i>31</i> <span class="sd">    You may just skip the **RuleKit.init()** line. However in certain scenarios when</span></tt>
-            </div>
-            <div id="l32"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (83 > 79 characters)</li>
-               
-               </ul><tt><i>32</i> <span class="sd">    you want use a custom RuleKit jar file or modify Java VM parameters, this class</span></tt>
-            </div>
-            <div id="l33"
-               class="code sev- "><tt><i>33</i> <span class="sd">    can be used.</span></tt>
-            </div>
-            <div id="l34"
-               class="code sev- "><tt><i>34</i> &nbsp;</tt>
-            </div>
-            <div id="l35"
-               class="code sev- "><tt><i>35</i> &nbsp;</tt>
-            </div>
-            <div id="l36"
-               class="code sev- "><tt><i>36</i> <span class="sd">    Attributes</span></tt>
-            </div>
-            <div id="l37"
-               class="code sev- "><tt><i>37</i> <span class="sd">    ----------</span></tt>
-            </div>
-            <div id="l38"
-               class="code sev- "><tt><i>38</i> <span class="sd">    version : str</span></tt>
-            </div>
-            <div id="l39"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (85 > 79 characters)</li>
-               
-               </ul><tt><i>39</i> <span class="sd">        version of RuleKit jar used by wrapper (not equal to python package version).</span></tt>
-            </div>
-            <div id="l40"
-               class="code sev- "><tt><i>40</i> <span class="sd">    &quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l41"
-               class="code sev- "><tt><i>41</i>     <span class="n">version</span><span class="p">:</span> <span class="nb">str</span></tt>
-            </div>
-            <div id="l42"
-               class="code sev- "><tt><i>42</i>     <span class="n">_logger</span><span class="p">:</span> <span class="n">logging</span><span class="o">.</span><span class="n">Logger</span> <span class="o">=</span> <span class="kc">None</span></tt>
-            </div>
-            <div id="l43"
-               class="code sev- "><tt><i>43</i>     <span class="n">_jar_dir_path</span><span class="p">:</span> <span class="nb">str</span></tt>
-            </div>
-            <div id="l44"
-               class="code sev- "><tt><i>44</i>     <span class="n">_class_path</span><span class="p">:</span> <span class="nb">str</span></tt>
-            </div>
-            <div id="l45"
-               class="code sev- "><tt><i>45</i>     <span class="n">_rulekit_jar_file_path</span><span class="p">:</span> <span class="nb">str</span></tt>
-            </div>
-            <div id="l46"
-               class="code sev- "><tt><i>46</i>     <span class="n">_jre_type</span><span class="p">:</span> <span class="n">JRE_Type</span></tt>
-            </div>
-            <div id="l47"
-               class="code sev- "><tt><i>47</i>     <span class="n">_java_logger_config</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">_RuleKitJavaLoggerConfig</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span></tt>
-            </div>
-            <div id="l48"
-               class="code sev- "><tt><i>48</i>     <span class="n">initialized</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span></tt>
-            </div>
-            <div id="l49"
-               class="code sev- "><tt><i>49</i> &nbsp;</tt>
-            </div>
-            <div id="l50"
-               class="code sev- "><tt><i>50</i>     <span class="nd">@staticmethod</span></tt>
-            </div>
-            <div id="l51"
-               class="code sev- "><tt><i>51</i>     <span class="k">def</span> <span class="nf">_detect_jre_type</span><span class="p">():</span></tt>
-            </div>
-            <div id="l52"
-               class="code sev- "><tt><i>52</i>         <span class="k">try</span><span class="p">:</span></tt>
-            </div>
-            <div id="l53"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (83 > 79 characters)</li>
-               
-               </ul><tt><i>53</i>             <span class="k">with</span> <span class="n">Popen</span><span class="p">([</span><span class="s2">&quot;java&quot;</span><span class="p">,</span> <span class="s2">&quot;-version&quot;</span><span class="p">],</span> <span class="n">stderr</span><span class="o">=</span><span class="n">STDOUT</span><span class="p">,</span> <span class="n">stdout</span><span class="o">=</span><span class="n">PIPE</span><span class="p">)</span> <span class="k">as</span> <span class="n">output</span><span class="p">:</span></tt>
-            </div>
-            <div id="l54"
-               class="code sev- "><tt><i>54</i>                 <span class="n">output</span> <span class="o">=</span> <span class="nb">str</span><span class="p">(</span><span class="n">output</span><span class="o">.</span><span class="n">communicate</span><span class="p">()[</span><span class="mi">0</span><span class="p">])</span></tt>
-            </div>
-            <div id="l55"
-               class="code sev- "><tt><i>55</i>                 <span class="k">if</span> <span class="s1">&#39;openjdk&#39;</span> <span class="ow">in</span> <span class="n">output</span><span class="p">:</span></tt>
-            </div>
-            <div id="l56"
-               class="code sev- "><tt><i>56</i>                     <span class="n">RuleKit</span><span class="o">.</span><span class="n">_jre_type</span> <span class="o">=</span> <span class="n">JRE_Type</span><span class="o">.</span><span class="n">OPEN_JDK</span></tt>
-            </div>
-            <div id="l57"
-               class="code sev- "><tt><i>57</i>                 <span class="k">else</span><span class="p">:</span></tt>
-            </div>
-            <div id="l58"
-               class="code sev- "><tt><i>58</i>                     <span class="n">RuleKit</span><span class="o">.</span><span class="n">_jre_type</span> <span class="o">=</span> <span class="n">JRE_Type</span><span class="o">.</span><span class="n">ORACLE</span></tt>
-            </div>
-            <div id="l59"
-               class="code sev- "><tt><i>59</i>         <span class="k">except</span> <span class="ne">FileNotFoundError</span> <span class="k">as</span> <span class="n">error</span><span class="p">:</span></tt>
-            </div>
-            <div id="l60"
-               class="code sev- "><tt><i>60</i>             <span class="k">raise</span> <span class="ne">RuntimeError</span><span class="p">(</span></tt>
-            </div>
-            <div id="l61"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (88 > 79 characters)</li>
-               
-               </ul><tt><i>61</i>                 <span class="s1">&#39;RuletKit requires java JRE to be installed (version 1.8.0 recommended)&#39;</span></tt>
-            </div>
-            <div id="l62"
-               class="code sev- "><tt><i>62</i>             <span class="p">)</span> <span class="kn">from</span> <span class="nn">error</span></tt>
-            </div>
-            <div id="l63"
-               class="code sev- "><tt><i>63</i> &nbsp;</tt>
-            </div>
-            <div id="l64"
-               class="code sev- "><tt><i>64</i>     <span class="nd">@staticmethod</span></tt>
-            </div>
-            <div id="l65"
-               class="code sev- "><tt><i>65</i>     <span class="k">def</span> <span class="nf">init</span><span class="p">(</span></tt>
-            </div>
-            <div id="l66"
-               class="code sev- "><tt><i>66</i>         <span class="n">initial_heap_size</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span></tt>
-            </div>
-            <div id="l67"
-               class="code sev- "><tt><i>67</i>         <span class="n">max_heap_size</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span></tt>
-            </div>
-            <div id="l68"
-               class="code sev- "><tt><i>68</i>         <span class="n">rulekit_jar_file_path</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="kc">None</span></tt>
-            </div>
-            <div id="l69"
-               class="code sev- "><tt><i>69</i>     <span class="p">):</span></tt>
-            </div>
-            <div id="l70"
-               class="code sev- "><tt><i>70</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Initialize package.</span></tt>
-            </div>
-            <div id="l71"
-               class="code sev- "><tt><i>71</i> &nbsp;</tt>
-            </div>
-            <div id="l72"
-               class="code sev- "><tt><i>72</i> <span class="sd">        This method configure and starts JVM and load RuleKit jar file.</span></tt>
-            </div>
-            <div id="l73"
-               class="code sev- "><tt><i>73</i> &nbsp;</tt>
-            </div>
-            <div id="l74"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (97 > 79 characters)</li>
-               
-               </ul><tt><i>74</i> <span class="sd">        .. note:: Since version 1.7.0 it don&#39;t have to be called before using any operator class.</span></tt>
-            </div>
-            <div id="l75"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (98 > 79 characters)</li>
-               
-               </ul><tt><i>75</i> <span class="sd">        However in certain scenarios when you want use a custom RuleKit jar file or modify Java VM</span></tt>
-            </div>
-            <div id="l76"
-               class="code sev- "><tt><i>76</i> <span class="sd">        parameters, this method can be used.</span></tt>
-            </div>
-            <div id="l77"
-               class="code sev- "><tt><i>77</i> &nbsp;</tt>
-            </div>
-            <div id="l78"
-               class="code sev- "><tt><i>78</i> <span class="sd">        Parameters</span></tt>
-            </div>
-            <div id="l79"
-               class="code sev- "><tt><i>79</i> <span class="sd">        ----------</span></tt>
-            </div>
-            <div id="l80"
-               class="code sev- "><tt><i>80</i> <span class="sd">        initial_heap_size : int</span></tt>
-            </div>
-            <div id="l81"
-               class="code sev- "><tt><i>81</i> <span class="sd">            JVM initial heap size in mb</span></tt>
-            </div>
-            <div id="l82"
-               class="code sev- "><tt><i>82</i> <span class="sd">        max_heap_size : int</span></tt>
-            </div>
-            <div id="l83"
-               class="code sev- "><tt><i>83</i> <span class="sd">            JVM max heap size in mb</span></tt>
-            </div>
-            <div id="l84"
-               class="code sev- "><tt><i>84</i> <span class="sd">        rulekit_jar_file_path : str</span></tt>
-            </div>
-            <div id="l85"
-               class="code sev- "><tt><i>85</i> <span class="sd">            Path to the RuleKit jar file. This parameters.</span></tt>
-            </div>
-            <div id="l86"
-               class="code sev- "><tt><i>86</i> <span class="sd">            .. note::</span></tt>
-            </div>
-            <div id="l87"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (84 > 79 characters)</li>
-               
-               </ul><tt><i>87</i> <span class="sd">                You probably don&#39;t need to use this parameter unless you want to use</span></tt>
-            </div>
-            <div id="l88"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (85 > 79 characters)</li>
-               
-               </ul><tt><i>88</i> <span class="sd">                your own custom version of RuleKit jar file. Otherwise leave it as it</span></tt>
-            </div>
-            <div id="l89"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (82 > 79 characters)</li>
-               
-               </ul><tt><i>89</i> <span class="sd">                is and the package will use the official RuleKit release jar file.</span></tt>
-            </div>
-            <div id="l90"
-               class="code sev- "><tt><i>90</i> &nbsp;</tt>
-            </div>
-            <div id="l91"
-               class="code sev- "><tt><i>91</i> <span class="sd">        Raises</span></tt>
-            </div>
-            <div id="l92"
-               class="code sev- "><tt><i>92</i> <span class="sd">        ------</span></tt>
-            </div>
-            <div id="l93"
-               class="code sev- "><tt><i>93</i> <span class="sd">        Exception</span></tt>
-            </div>
-            <div id="l94"
-               class="code sev- "><tt><i>94</i> <span class="sd">            If failed to load RuleKit jar file.</span></tt>
-            </div>
-            <div id="l95"
-               class="code sev- "><tt><i>95</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l96"
-               class="code sev- "><tt><i>96</i>         <span class="k">if</span> <span class="n">RuleKit</span><span class="o">.</span><span class="n">initialized</span><span class="p">:</span></tt>
-            </div>
-            <div id="l97"
-               class="code sev- "><tt><i>97</i>             <span class="k">return</span></tt>
-            </div>
-            <div id="l98"
-               class="code sev- "><tt><i>98</i>         <span class="n">RuleKit</span><span class="o">.</span><span class="n">_setup_logger</span><span class="p">()</span></tt>
-            </div>
-            <div id="l99"
-               class="code sev- "><tt><i>99</i> &nbsp;</tt>
-            </div>
-            <div id="l100"
-               class="code sev- "><tt><i>100</i>         <span class="n">RuleKit</span><span class="o">.</span><span class="n">_detect_jre_type</span><span class="p">()</span></tt>
-            </div>
-            <div id="l101"
-               class="code sev- "><tt><i>101</i>         <span class="n">current_path</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="n">os</span><span class="o">.</span><span class="n">path</span><span class="o">.</span><span class="n">dirname</span><span class="p">(</span><span class="n">os</span><span class="o">.</span><span class="n">path</span><span class="o">.</span><span class="n">realpath</span><span class="p">(</span><span class="vm">__file__</span><span class="p">))</span></tt>
-            </div>
-            <div id="l102"
-               class="code sev- "><tt><i>102</i>         <span class="n">RuleKit</span><span class="o">.</span><span class="n">_jar_dir_path</span> <span class="o">=</span> <span class="sa">f</span><span class="s2">&quot;</span><span class="si">{</span><span class="n">current_path</span><span class="si">}</span><span class="s2">/jar&quot;</span></tt>
-            </div>
-            <div id="l103"
-               class="code sev- "><tt><i>103</i>         <span class="n">class_path_separator</span> <span class="o">=</span> <span class="n">os</span><span class="o">.</span><span class="n">pathsep</span></tt>
-            </div>
-            <div id="l104"
-               class="code sev- "><tt><i>104</i>         <span class="k">try</span><span class="p">:</span></tt>
-            </div>
-            <div id="l105"
-               class="code sev- "><tt><i>105</i>             <span class="n">jar_file_name</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="p">(</span></tt>
-            </div>
-            <div id="l106"
-               class="code sev- "><tt><i>106</i>                 <span class="s1">&#39;rulekit-&#39;</span> <span class="o">+</span></tt>
-            </div>
-            <div id="l107"
-               class="code sev- "><tt><i>107</i>                 <span class="sa">f</span><span class="s1">&#39;</span><span class="si">{</span><span class="n">__RULEKIT_RELEASE_VERSION__</span><span class="si">}</span><span class="s1">-all.jar&#39;</span></tt>
-            </div>
-            <div id="l108"
-               class="code sev- "><tt><i>108</i>             <span class="p">)</span></tt>
-            </div>
-            <div id="l109"
-               class="code sev- "><tt><i>109</i>             <span class="n">RuleKit</span><span class="o">.</span><span class="n">_rulekit_jar_file_path</span> <span class="o">=</span> <span class="n">os</span><span class="o">.</span><span class="n">path</span><span class="o">.</span><span class="n">join</span><span class="p">(</span></tt>
-            </div>
-            <div id="l110"
-               class="code sev- "><tt><i>110</i>                 <span class="n">RuleKit</span><span class="o">.</span><span class="n">_jar_dir_path</span><span class="p">,</span> <span class="n">jar_file_name</span><span class="p">)</span></tt>
-            </div>
-            <div id="l111"
-               class="code sev- "><tt><i>111</i>             <span class="n">jars_paths</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="nb">str</span><span class="p">]</span> <span class="o">=</span> <span class="p">[</span><span class="n">RuleKit</span><span class="o">.</span><span class="n">_rulekit_jar_file_path</span><span class="p">]</span></tt>
-            </div>
-            <div id="l112"
-               class="code sev- "><tt><i>112</i>             <span class="k">if</span> <span class="n">rulekit_jar_file_path</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span></tt>
-            </div>
-            <div id="l113"
-               class="code sev- "><tt><i>113</i>                 <span class="n">jars_paths</span><span class="o">.</span><span class="n">remove</span><span class="p">(</span><span class="n">RuleKit</span><span class="o">.</span><span class="n">_rulekit_jar_file_path</span><span class="p">)</span></tt>
-            </div>
-            <div id="l114"
-               class="code sev- "><tt><i>114</i>                 <span class="n">jars_paths</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">rulekit_jar_file_path</span><span class="p">)</span></tt>
-            </div>
-            <div id="l115"
-               class="code sev- "><tt><i>115</i>                 <span class="n">RuleKit</span><span class="o">.</span><span class="n">_rulekit_jar_file_path</span> <span class="o">=</span> <span class="n">rulekit_jar_file_path</span></tt>
-            </div>
-            <div id="l116"
-               class="code sev- "><tt><i>116</i>             <span class="n">RuleKit</span><span class="o">.</span><span class="n">_class_path</span> <span class="o">=</span> <span class="p">(</span></tt>
-            </div>
-            <div id="l117"
-               class="code sev- "><tt><i>117</i>                 <span class="sa">f</span><span class="s1">&#39;</span><span class="si">{</span><span class="nb">str</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">class_path_separator</span><span class="p">,</span><span class="w"> </span><span class="n">jars_paths</span><span class="p">)</span><span class="si">}</span><span class="s1">&#39;</span></tt>
-            </div>
-            <div id="l118"
-               class="code sev- "><tt><i>118</i>             <span class="p">)</span></tt>
-            </div>
-            <div id="l119"
-               class="code sev- "><tt><i>119</i>         <span class="k">except</span> <span class="ne">IndexError</span> <span class="k">as</span> <span class="n">error</span><span class="p">:</span></tt>
-            </div>
-            <div id="l120"
-               class="code sev- "><tt><i>120</i>             <span class="n">RuleKit</span><span class="o">.</span><span class="n">_logger</span><span class="o">.</span><span class="n">error</span><span class="p">(</span><span class="s1">&#39;Failed to load jar files&#39;</span><span class="p">)</span></tt>
-            </div>
-            <div id="l121"
-               class="code sev- "><tt><i>121</i>             <span class="k">raise</span> <span class="ne">RuntimeError</span><span class="p">(</span><span class="sa">f</span><span class="s1">&#39;&#39;&#39;</span><span class="se">\n</span></tt>
-            </div>
-            <div id="l122"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (115 > 79 characters)</li>
-               
-               </ul><tt><i>122</i> <span class="s1">Failed to load RuleKit jar file. Check if valid rulekit jar file is present in &quot;</span><span class="si">{</span><span class="n">RuleKit</span><span class="o">.</span><span class="n">_jar_dir_path</span><span class="si">}</span><span class="s1">&quot; directory.</span></tt>
-            </div>
-            <div id="l123"
-               class="code sev- "><tt><i>123</i> &nbsp;</tt>
-            </div>
-            <div id="l124"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (99 > 79 characters)</li>
-               
-               </ul><tt><i>124</i> <span class="s1">If you&#39;re running this package for the first time you need to download RuleKit jar file by running:</span></tt>
-            </div>
-            <div id="l125"
-               class="code sev- "><tt><i>125</i> <span class="s1">    python -m rulekit download_jar</span></tt>
-            </div>
-            <div id="l126"
-               class="code sev- "><tt><i>126</i> <span class="s1">        &#39;&#39;&#39;</span><span class="p">)</span> <span class="kn">from</span> <span class="nn">error</span></tt>
-            </div>
-            <div id="l127"
-               class="code sev- "><tt><i>127</i>         <span class="n">RuleKit</span><span class="o">.</span><span class="n">_read_versions</span><span class="p">()</span></tt>
-            </div>
-            <div id="l128"
-               class="code sev- "><tt><i>128</i>         <span class="n">RuleKit</span><span class="o">.</span><span class="n">_launch_jvm</span><span class="p">(</span><span class="n">initial_heap_size</span><span class="p">,</span> <span class="n">max_heap_size</span><span class="p">)</span></tt>
-            </div>
-            <div id="l129"
-               class="code sev- "><tt><i>129</i>         <span class="n">RuleKit</span><span class="o">.</span><span class="n">initialized</span> <span class="o">=</span> <span class="kc">True</span></tt>
-            </div>
-            <div id="l130"
-               class="code sev- "><tt><i>130</i> &nbsp;</tt>
-            </div>
-            <div id="l131"
-               class="code sev- "><tt><i>131</i>     <span class="nd">@staticmethod</span></tt>
-            </div>
-            <div id="l132"
-               class="code sev- "><tt><i>132</i>     <span class="k">def</span> <span class="nf">_setup_logger</span><span class="p">():</span></tt>
-            </div>
-            <div id="l133"
-               class="code sev- "><tt><i>133</i>         <span class="n">logging</span><span class="o">.</span><span class="n">basicConfig</span><span class="p">()</span></tt>
-            </div>
-            <div id="l134"
-               class="code sev- "><tt><i>134</i>         <span class="n">RuleKit</span><span class="o">.</span><span class="n">_logger</span> <span class="o">=</span> <span class="n">logging</span><span class="o">.</span><span class="n">getLogger</span><span class="p">(</span><span class="s1">&#39;RuleKit&#39;</span><span class="p">)</span></tt>
-            </div>
-            <div id="l135"
-               class="code sev- "><tt><i>135</i> &nbsp;</tt>
-            </div>
-            <div id="l136"
-               class="code sev- "><tt><i>136</i>     <span class="nd">@staticmethod</span></tt>
-            </div>
-            <div id="l137"
-               class="code sev- "><tt><i>137</i>     <span class="k">def</span> <span class="nf">_read_versions</span><span class="p">():</span></tt>
-            </div>
-            <div id="l138"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (81 > 79 characters)</li>
-               
-               </ul><tt><i>138</i>         <span class="k">with</span> <span class="n">zipfile</span><span class="o">.</span><span class="n">ZipFile</span><span class="p">(</span><span class="n">RuleKit</span><span class="o">.</span><span class="n">_rulekit_jar_file_path</span><span class="p">,</span> <span class="s1">&#39;r&#39;</span><span class="p">)</span> <span class="k">as</span> <span class="n">jar_archive</span><span class="p">:</span></tt>
-            </div>
-            <div id="l139"
-               class="code sev- "><tt><i>139</i>             <span class="k">try</span><span class="p">:</span></tt>
-            </div>
-            <div id="l140"
-               class="code sev- "><tt><i>140</i>                 <span class="n">manifest_file_content</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="n">jar_archive</span><span class="o">.</span><span class="n">read</span><span class="p">(</span></tt>
-            </div>
-            <div id="l141"
-               class="code sev- "><tt><i>141</i>                     <span class="s1">&#39;META-INF/MANIFEST.MF&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">decode</span><span class="p">(</span><span class="s1">&#39;utf-8&#39;</span><span class="p">)</span></tt>
-            </div>
-            <div id="l142"
-               class="code sev- "><tt><i>142</i>                 <span class="n">RuleKit</span><span class="o">.</span><span class="n">version</span> <span class="o">=</span> <span class="n">re</span><span class="o">.</span><span class="n">findall</span><span class="p">(</span></tt>
-            </div>
-            <div id="l143"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (93 > 79 characters)</li>
-               
-               </ul><tt><i>143</i>                     <span class="sa">r</span><span class="s1">&#39;Implementation-Version: \S+\r&#39;</span><span class="p">,</span> <span class="n">manifest_file_content</span><span class="p">)[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="s1">&#39; &#39;</span><span class="p">)[</span><span class="mi">1</span><span class="p">]</span></tt>
-            </div>
-            <div id="l144"
-               class="code sev- "><tt><i>144</i>             <span class="k">except</span> <span class="ne">Exception</span> <span class="k">as</span> <span class="n">error</span><span class="p">:</span></tt>
-            </div>
-            <div id="l145"
-               class="code sev- "><tt><i>145</i>                 <span class="n">RuleKit</span><span class="o">.</span><span class="n">_logger</span><span class="o">.</span><span class="n">error</span><span class="p">(</span></tt>
-            </div>
-            <div id="l146"
-               class="code sev- "><tt><i>146</i>                     <span class="s1">&#39;Failed to read RuleKit versions from jar file&#39;</span><span class="p">)</span></tt>
-            </div>
-            <div id="l147"
-               class="code sev- "><tt><i>147</i>                 <span class="n">RuleKit</span><span class="o">.</span><span class="n">_logger</span><span class="o">.</span><span class="n">error</span><span class="p">(</span><span class="n">error</span><span class="p">)</span></tt>
-            </div>
-            <div id="l148"
-               class="code sev- "><tt><i>148</i>                 <span class="k">raise</span> <span class="n">error</span></tt>
-            </div>
-            <div id="l149"
-               class="code sev- "><tt><i>149</i> &nbsp;</tt>
-            </div>
-            <div id="l150"
-               class="code sev- "><tt><i>150</i>     <span class="nd">@staticmethod</span></tt>
-            </div>
-            <div id="l151"
-               class="code sev- "><tt><i>151</i>     <span class="k">def</span> <span class="nf">_launch_jvm</span><span class="p">(</span><span class="n">initial_heap_size</span><span class="p">:</span> <span class="nb">int</span><span class="p">,</span> <span class="n">max_heap_size</span><span class="p">:</span> <span class="nb">int</span><span class="p">):</span></tt>
-            </div>
-            <div id="l152"
-               class="code sev- "><tt><i>152</i>         <span class="k">if</span> <span class="n">jpype</span><span class="o">.</span><span class="n">isJVMStarted</span><span class="p">():</span></tt>
-            </div>
-            <div id="l153"
-               class="code sev- "><tt><i>153</i>             <span class="n">RuleKit</span><span class="o">.</span><span class="n">_logger</span><span class="o">.</span><span class="n">info</span><span class="p">(</span><span class="s1">&#39;JVM already running&#39;</span><span class="p">)</span></tt>
-            </div>
-            <div id="l154"
-               class="code sev- "><tt><i>154</i>         <span class="k">else</span><span class="p">:</span></tt>
-            </div>
-            <div id="l155"
-               class="code sev- "><tt><i>155</i>             <span class="n">params</span> <span class="o">=</span> <span class="p">[</span></tt>
-            </div>
-            <div id="l156"
-               class="code sev- "><tt><i>156</i>                 <span class="sa">f</span><span class="s1">&#39;-Djava.class.path=</span><span class="si">{</span><span class="n">RuleKit</span><span class="o">.</span><span class="n">_class_path</span><span class="si">}</span><span class="s1">&#39;</span><span class="p">,</span></tt>
-            </div>
-            <div id="l157"
-               class="code sev- "><tt><i>157</i>             <span class="p">]</span></tt>
-            </div>
-            <div id="l158"
-               class="code sev- "><tt><i>158</i>             <span class="k">if</span> <span class="n">initial_heap_size</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span></tt>
-            </div>
-            <div id="l159"
-               class="code sev- "><tt><i>159</i>                 <span class="n">params</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="sa">f</span><span class="s1">&#39;-Xms</span><span class="si">{</span><span class="n">initial_heap_size</span><span class="si">}</span><span class="s1">m&#39;</span><span class="p">)</span></tt>
-            </div>
-            <div id="l160"
-               class="code sev- "><tt><i>160</i>             <span class="k">if</span> <span class="n">max_heap_size</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span></tt>
-            </div>
-            <div id="l161"
-               class="code sev- "><tt><i>161</i>                 <span class="n">params</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="sa">f</span><span class="s1">&#39;-Xmx</span><span class="si">{</span><span class="n">max_heap_size</span><span class="si">}</span><span class="s1">m&#39;</span><span class="p">)</span></tt>
-            </div>
-            <div id="l162"
-               class="code sev- "><tt><i>162</i>             <span class="n">jpype</span><span class="o">.</span><span class="n">startJVM</span><span class="p">(</span><span class="n">jpype</span><span class="o">.</span><span class="n">getDefaultJVMPath</span><span class="p">(),</span> <span class="o">*</span></tt>
-            </div>
-            <div id="l163"
-               class="code sev- "><tt><i>163</i>                            <span class="n">params</span><span class="p">,</span> <span class="n">convertStrings</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span></tt>
-            </div>
-            <div id="l164"
-               class="code sev- "><tt><i>164</i> &nbsp;</tt>
-            </div>
-            <div id="l165"
-               class="code sev- "><tt><i>165</i>     <span class="nd">@staticmethod</span></tt>
-            </div>
-            <div id="l166"
-               class="code sev- "><tt><i>166</i>     <span class="k">def</span> <span class="nf">configure_java_logger</span><span class="p">(</span></tt>
-            </div>
-            <div id="l167"
-               class="code sev- "><tt><i>167</i>         <span class="n">log_file_path</span><span class="p">:</span> <span class="nb">str</span><span class="p">,</span></tt>
-            </div>
-            <div id="l168"
-               class="code sev- "><tt><i>168</i>         <span class="n">verbosity_level</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">1</span><span class="p">,</span></tt>
-            </div>
-            <div id="l169"
-               class="code sev- "><tt><i>169</i>     <span class="p">):</span></tt>
-            </div>
-            <div id="l170"
-               class="code sev- "><tt><i>170</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Enable Java debug logging. You probably don&#39;t need to use this</span></tt>
-            </div>
-            <div id="l171"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (81 > 79 characters)</li>
-               
-               </ul><tt><i>171</i> <span class="sd">        method unless you want too deep dive into the process of rules inductions</span></tt>
-            </div>
-            <div id="l172"
-               class="code sev- "><tt><i>172</i> <span class="sd">         or your&#39;re debugging some issues.</span></tt>
-            </div>
-            <div id="l173"
-               class="code sev- "><tt><i>173</i> &nbsp;</tt>
-            </div>
-            <div id="l174"
-               class="code sev- "><tt><i>174</i> &nbsp;</tt>
-            </div>
-            <div id="l175"
-               class="code sev- "><tt><i>175</i> <span class="sd">        Args:</span></tt>
-            </div>
-            <div id="l176"
-               class="code sev- "><tt><i>176</i> <span class="sd">            log_file_path (str): Path to the file where logs will be stored</span></tt>
-            </div>
-            <div id="l177"
-               class="code sev- "><tt><i>177</i> <span class="sd">            verbosity_level (int, optional): Verbosity level.</span></tt>
-            </div>
-            <div id="l178"
-               class="code sev- "><tt><i>178</i> <span class="sd">                Minimum value is 1, maximum value is 2, default value is 1.</span></tt>
-            </div>
-            <div id="l179"
-               class="code sev- "><tt><i>179</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l180"
-               class="code sev- "><tt><i>180</i>         <span class="n">RuleKit</span><span class="o">.</span><span class="n">_java_logger_config</span> <span class="o">=</span> <span class="n">_RuleKitJavaLoggerConfig</span><span class="p">(</span></tt>
-            </div>
-            <div id="l181"
-               class="code sev- "><tt><i>181</i>             <span class="n">verbosity_level</span><span class="o">=</span><span class="n">verbosity_level</span><span class="p">,</span></tt>
-            </div>
-            <div id="l182"
-               class="code sev- "><tt><i>182</i>             <span class="n">log_file_path</span><span class="o">=</span><span class="n">log_file_path</span></tt>
-            </div>
-            <div id="l183"
-               class="code sev- "><tt><i>183</i>         <span class="p">)</span></tt>
-            </div>
-            <div id="l184"
-               class="code sev- "><tt><i>184</i> &nbsp;</tt>
-            </div>
-            <div id="l185"
-               class="code sev- "><tt><i>185</i>     <span class="nd">@staticmethod</span></tt>
-            </div>
-            <div id="l186"
-               class="code sev- "><tt><i>186</i>     <span class="k">def</span> <span class="nf">get_java_logger_config</span><span class="p">()</span> <span class="o">-&gt;</span> <span class="n">Optional</span><span class="p">[</span><span class="n">_RuleKitJavaLoggerConfig</span><span class="p">]:</span></tt>
-            </div>
-            <div id="l187"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (89 > 79 characters)</li>
-               
-               </ul><tt><i>187</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Returns the Java logger configuration configured using `configure_java_logger`</span></tt>
-            </div>
-            <div id="l188"
-               class="code sev- "><tt><i>188</i> <span class="sd">        method</span></tt>
-            </div>
-            <div id="l189"
-               class="code sev- "><tt><i>189</i> &nbsp;</tt>
-            </div>
-            <div id="l190"
-               class="code sev- "><tt><i>190</i> <span class="sd">        Returns:</span></tt>
-            </div>
-            <div id="l191"
-               class="code sev- "><tt><i>191</i> <span class="sd">            Optional[_RuleKitJavaLoggerConfig]: Java logger configuration</span></tt>
-            </div>
-            <div id="l192"
-               class="code sev- "><tt><i>192</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l193"
-               class="code sev- "><tt><i>193</i>         <span class="k">return</span> <span class="n">RuleKit</span><span class="o">.</span><span class="n">_java_logger_config</span></tt>
-            </div>
-            
-         </div>
-      </div>
-   </body>
-</html>
\ No newline at end of file
diff --git a/docs/reports/flake8/rulekit.params.report.html b/docs/reports/flake8/rulekit.params.report.html
deleted file mode 100644
index f71d051..0000000
--- a/docs/reports/flake8/rulekit.params.report.html
+++ /dev/null
@@ -1,189 +0,0 @@
-<!DOCTYPE html>
-<html>
-   <head>
-      <title>flake8 violations: rulekit\params.py</title>
-      <meta http-equiv="Content-Type" value="text/html; charset=UTF-8">
-      <link rel="stylesheet" href="styles.css">
-<script>
-function bindHandler(link) {
-   var code = link.getAttribute('data-code');
-   var key = location.pathname + '#' + code;
-
-   var ul = link.parentNode.querySelector('.details');
-   if (sessionStorage[key] != 'open') {
-      ul.style.display = 'none';
-   }
-   link.addEventListener('click', function (event) {
-      if (!ul.style.display || ul.style.display == 'none') {
-         ul.style.display = 'block';
-         sessionStorage[key] = 'open';
-      } else {
-         ul.style.display = 'none';
-         sessionStorage[key] = 'closed';
-      }
-   });
-}
-
-window.addEventListener('DOMContentLoaded', function () {
-   var links = document.querySelectorAll('#index > li > a');
-   for (var i = 0; i < links.length; i++) {
-      bindHandler(links[i]);
-   }
-});
-</script>
-   </head>
-   <body>
-      <div id="masthead" class="sev-2"></div>
-      <div id="page">
-         <p id="srclink">
-            <a title="View full annotated source"
-               href="rulekit.params.source.html">
-               <img src="file.svg" alt="&#x2261;">
-            </a></p>
-         <h1>
-            <a href="index.html">
-               <img src="back.svg" alt="&#x2B05;">
-               rulekit\params.py
-            </a>
-         </h1>
-
-         <ul id="index">
-         
-         <li>
-            <a data-code="E501">
-               <span class="count sev-2">
-                  17
-               </span>
-               <strong>E501:</strong> line too long (82 > 79 characters)
-               
-                  (and 10 similar)
-               
-            </a>
-            <ul class="details">
-            <li>
-               
-               <p>Line too long (82 > 79 characters):</p>
-               
-               <a href="rulekit.params.source.html#l24">
-                  <tt><i>24</i>     <span class="k">class</span> <span class="nc">_UserMeasure</span><span class="p">:</span>  <span class="c1"># pylint: disable=invalid-name,missing-function-docstring</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (85 > 79 characters):</p>
-               
-               <a href="rulekit.params.source.html#l27">
-                  <tt><i>27</i>         <span class="k">def</span> <span class="nf">getResult</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">p</span><span class="p">:</span> <span class="n">JDouble</span><span class="p">,</span> <span class="n">n</span><span class="p">:</span> <span class="n">JDouble</span><span class="p">,</span> <span class="n">P</span><span class="p">:</span> <span class="n">JDouble</span><span class="p">,</span> <span class="n">N</span><span class="p">:</span> <span class="n">JDouble</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">float</span><span class="p">:</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (92 > 79 characters):</p>
-               
-               <a href="rulekit.params.source.html#l125">
-                  <tt><i>125</i>     <span class="n">induction_measure</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">_QualityMeasure</span><span class="p">]</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;induction_measure&#39;</span><span class="p">]</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (88 > 79 characters):</p>
-               
-               <a href="rulekit.params.source.html#l126">
-                  <tt><i>126</i>     <span class="n">pruning_measure</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">_QualityMeasure</span><span class="p">]</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;pruning_measure&#39;</span><span class="p">]</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (86 > 79 characters):</p>
-               
-               <a href="rulekit.params.source.html#l127">
-                  <tt><i>127</i>     <span class="n">voting_measure</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">_QualityMeasure</span><span class="p">]</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;voting_measure&#39;</span><span class="p">]</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (92 > 79 characters):</p>
-               
-               <a href="rulekit.params.source.html#l131">
-                  <tt><i>131</i>     <span class="n">max_uncovered_fraction</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">float</span><span class="p">]</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;max_uncovered_fraction&#39;</span><span class="p">]</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (89 > 79 characters):</p>
-               
-               <a href="rulekit.params.source.html#l132">
-                  <tt><i>132</i>     <span class="n">select_best_candidate</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">bool</span><span class="p">]</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;select_best_candidate&#39;</span><span class="p">]</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (95 > 79 characters):</p>
-               
-               <a href="rulekit.params.source.html#l133">
-                  <tt><i>133</i>     <span class="n">complementary_conditions</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">bool</span><span class="p">]</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;complementary_conditions&#39;</span><span class="p">]</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (91 > 79 characters):</p>
-               
-               <a href="rulekit.params.source.html#l140">
-                  <tt><i>140</i>     <span class="n">extend_using_preferred</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">bool</span><span class="p">]</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;extend_using_preferred&#39;</span><span class="p">]</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (91 > 79 characters):</p>
-               
-               <a href="rulekit.params.source.html#l141">
-                  <tt><i>141</i>     <span class="n">extend_using_automatic</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">bool</span><span class="p">]</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;extend_using_automatic&#39;</span><span class="p">]</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (91 > 79 characters):</p>
-               
-               <a href="rulekit.params.source.html#l142">
-                  <tt><i>142</i>     <span class="n">induce_using_preferred</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">bool</span><span class="p">]</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;induce_using_preferred&#39;</span><span class="p">]</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (91 > 79 characters):</p>
-               
-               <a href="rulekit.params.source.html#l143">
-                  <tt><i>143</i>     <span class="n">induce_using_automatic</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">bool</span><span class="p">]</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;induce_using_automatic&#39;</span><span class="p">]</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (91 > 79 characters):</p>
-               
-               <a href="rulekit.params.source.html#l144">
-                  <tt><i>144</i>     <span class="n">consider_other_classes</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">bool</span><span class="p">]</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;consider_other_classes&#39;</span><span class="p">]</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (104 > 79 characters):</p>
-               
-               <a href="rulekit.params.source.html#l145">
-                  <tt><i>145</i>     <span class="n">preferred_conditions_per_rule</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">int</span><span class="p">]</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;preferred_conditions_per_rule&#39;</span><span class="p">]</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (104 > 79 characters):</p>
-               
-               <a href="rulekit.params.source.html#l146">
-                  <tt><i>146</i>     <span class="n">preferred_attributes_per_rule</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">int</span><span class="p">]</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;preferred_attributes_per_rule&#39;</span><span class="p">]</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (80 > 79 characters):</p>
-               
-               <a href="rulekit.params.source.html#l157">
-                  <tt><i>157</i>     <span class="n">penalty_strength</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">float</span><span class="p">]</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;penalty_strength&#39;</span><span class="p">]</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (84 > 79 characters):</p>
-               
-               <a href="rulekit.params.source.html#l158">
-                  <tt><i>158</i>     <span class="n">penalty_saturation</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">float</span><span class="p">]</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;penalty_saturation&#39;</span><span class="p">]</span></tt>
-               </a>
-            </li>
-            </ul>
-         </li>
-         
-         </ul>
-      </div>
-   </body>
-</html>
\ No newline at end of file
diff --git a/docs/reports/flake8/rulekit.params.source.html b/docs/reports/flake8/rulekit.params.source.html
deleted file mode 100644
index d01aafe..0000000
--- a/docs/reports/flake8/rulekit.params.source.html
+++ /dev/null
@@ -1,650 +0,0 @@
-<!DOCTYPE html>
-<html>
-   <head>
-      <title>rulekit\params.py - flake8 annotated source</title>
-      <meta http-equiv="Content-Type" value="text/html; charset=UTF-8">
-      <link rel="stylesheet" href="styles.css">
-   </head>
-   <body>
-      <div id="masthead" class="sev-2"></div>
-      <div id="page">
-         <h1>
-            <a href="rulekit.params.report.html">
-               <img src="back.svg" alt="&#x2B05;">
-               rulekit\params.py source
-            </a>
-         </h1>
-
-         <div id="doc">
-            <div id="l1"
-               class="code sev- "><tt><i>1</i> <span class="sd">&quot;&quot;&quot;Contains constants and classes for specyfing models parameters</span></tt>
-            </div>
-            <div id="l2"
-               class="code sev- "><tt><i>2</i> <span class="sd">&quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l3"
-               class="code sev- "><tt><i>3</i> <span class="kn">from</span> <span class="nn">enum</span> <span class="kn">import</span> <span class="n">Enum</span></tt>
-            </div>
-            <div id="l4"
-               class="code sev- "><tt><i>4</i> <span class="kn">from</span> <span class="nn">typing</span> <span class="kn">import</span> <span class="n">Callable</span></tt>
-            </div>
-            <div id="l5"
-               class="code sev- "><tt><i>5</i> <span class="kn">from</span> <span class="nn">typing</span> <span class="kn">import</span> <span class="n">Optional</span></tt>
-            </div>
-            <div id="l6"
-               class="code sev- "><tt><i>6</i> <span class="kn">from</span> <span class="nn">typing</span> <span class="kn">import</span> <span class="n">Tuple</span></tt>
-            </div>
-            <div id="l7"
-               class="code sev- "><tt><i>7</i> <span class="kn">from</span> <span class="nn">typing</span> <span class="kn">import</span> <span class="n">Union</span></tt>
-            </div>
-            <div id="l8"
-               class="code sev- "><tt><i>8</i> &nbsp;</tt>
-            </div>
-            <div id="l9"
-               class="code sev- "><tt><i>9</i> <span class="kn">from</span> <span class="nn">jpype</span> <span class="kn">import</span> <span class="n">JImplements</span></tt>
-            </div>
-            <div id="l10"
-               class="code sev- "><tt><i>10</i> <span class="kn">from</span> <span class="nn">jpype</span> <span class="kn">import</span> <span class="n">JOverride</span></tt>
-            </div>
-            <div id="l11"
-               class="code sev- "><tt><i>11</i> <span class="kn">from</span> <span class="nn">jpype.types</span> <span class="kn">import</span> <span class="n">JDouble</span></tt>
-            </div>
-            <div id="l12"
-               class="code sev- "><tt><i>12</i> <span class="kn">from</span> <span class="nn">pydantic</span> <span class="kn">import</span> <span class="n">BaseModel</span>  <span class="c1"># pylint: disable=no-name-in-module</span></tt>
-            </div>
-            <div id="l13"
-               class="code sev- "><tt><i>13</i> &nbsp;</tt>
-            </div>
-            <div id="l14"
-               class="code sev- "><tt><i>14</i> <span class="n">MAX_INT</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">2147483647</span>  <span class="c1"># max integer value in Java</span></tt>
-            </div>
-            <div id="l15"
-               class="code sev- "><tt><i>15</i> &nbsp;</tt>
-            </div>
-            <div id="l16"
-               class="code sev- "><tt><i>16</i> <span class="n">_UserDefinedMeasure</span> <span class="o">=</span> <span class="n">Callable</span><span class="p">[[</span><span class="nb">float</span><span class="p">,</span> <span class="nb">float</span><span class="p">,</span> <span class="nb">float</span><span class="p">,</span> <span class="nb">float</span><span class="p">],</span> <span class="nb">float</span><span class="p">]</span></tt>
-            </div>
-            <div id="l17"
-               class="code sev- "><tt><i>17</i> &nbsp;</tt>
-            </div>
-            <div id="l18"
-               class="code sev- "><tt><i>18</i> &nbsp;</tt>
-            </div>
-            <div id="l19"
-               class="code sev- "><tt><i>19</i> <span class="k">def</span> <span class="nf">_user_defined_measure_factory</span><span class="p">(</span><span class="n">measure_function</span><span class="p">:</span> <span class="n">_UserDefinedMeasure</span><span class="p">):</span></tt>
-            </div>
-            <div id="l20"
-               class="code sev- "><tt><i>20</i>     <span class="kn">from</span> <span class="nn">adaa.analytics.rules.logic.quality</span> <span class="kn">import</span> \</tt>
-            </div>
-            <div id="l21"
-               class="code sev- "><tt><i>21</i>         <span class="n">IUserMeasure</span>  <span class="c1"># pylint: disable=import-outside-toplevel,import-error</span></tt>
-            </div>
-            <div id="l22"
-               class="code sev- "><tt><i>22</i> &nbsp;</tt>
-            </div>
-            <div id="l23"
-               class="code sev- "><tt><i>23</i>     <span class="nd">@JImplements</span><span class="p">(</span><span class="n">IUserMeasure</span><span class="p">)</span></tt>
-            </div>
-            <div id="l24"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (82 > 79 characters)</li>
-               
-               </ul><tt><i>24</i>     <span class="k">class</span> <span class="nc">_UserMeasure</span><span class="p">:</span>  <span class="c1"># pylint: disable=invalid-name,missing-function-docstring</span></tt>
-            </div>
-            <div id="l25"
-               class="code sev- "><tt><i>25</i> &nbsp;</tt>
-            </div>
-            <div id="l26"
-               class="code sev- "><tt><i>26</i>         <span class="nd">@JOverride</span></tt>
-            </div>
-            <div id="l27"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (85 > 79 characters)</li>
-               
-               </ul><tt><i>27</i>         <span class="k">def</span> <span class="nf">getResult</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">p</span><span class="p">:</span> <span class="n">JDouble</span><span class="p">,</span> <span class="n">n</span><span class="p">:</span> <span class="n">JDouble</span><span class="p">,</span> <span class="n">P</span><span class="p">:</span> <span class="n">JDouble</span><span class="p">,</span> <span class="n">N</span><span class="p">:</span> <span class="n">JDouble</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">float</span><span class="p">:</span></tt>
-            </div>
-            <div id="l28"
-               class="code sev- "><tt><i>28</i>             <span class="k">return</span> <span class="n">measure_function</span><span class="p">(</span></tt>
-            </div>
-            <div id="l29"
-               class="code sev- "><tt><i>29</i>                 <span class="nb">float</span><span class="p">(</span><span class="n">p</span><span class="p">),</span> <span class="nb">float</span><span class="p">(</span><span class="n">n</span><span class="p">),</span> <span class="nb">float</span><span class="p">(</span><span class="n">P</span><span class="p">),</span> <span class="nb">float</span><span class="p">(</span><span class="n">N</span><span class="p">)</span></tt>
-            </div>
-            <div id="l30"
-               class="code sev- "><tt><i>30</i>             <span class="p">)</span></tt>
-            </div>
-            <div id="l31"
-               class="code sev- "><tt><i>31</i> &nbsp;</tt>
-            </div>
-            <div id="l32"
-               class="code sev- "><tt><i>32</i>     <span class="k">return</span> <span class="n">_UserMeasure</span><span class="p">()</span></tt>
-            </div>
-            <div id="l33"
-               class="code sev- "><tt><i>33</i> &nbsp;</tt>
-            </div>
-            <div id="l34"
-               class="code sev- "><tt><i>34</i> &nbsp;</tt>
-            </div>
-            <div id="l35"
-               class="code sev- "><tt><i>35</i> <span class="k">class</span> <span class="nc">Measures</span><span class="p">(</span><span class="n">Enum</span><span class="p">):</span></tt>
-            </div>
-            <div id="l36"
-               class="code sev- "><tt><i>36</i>     <span class="c1"># pylint: disable=invalid-name</span></tt>
-            </div>
-            <div id="l37"
-               class="code sev- "><tt><i>37</i> <span class="w">    </span><span class="sd">&quot;&quot;&quot;Enum for different measures used during induction, pruning and voting.</span></tt>
-            </div>
-            <div id="l38"
-               class="code sev- "><tt><i>38</i> &nbsp;</tt>
-            </div>
-            <div id="l39"
-               class="code sev- "><tt><i>39</i> <span class="sd">    You can ream more about each measure and its implementation</span></tt>
-            </div>
-            <div id="l40"
-               class="code sev- "><tt><i>40</i> <span class="sd">    #41-rule-quality&gt;`_ .</span></tt>
-            </div>
-            <div id="l41"
-               class="code sev- "><tt><i>41</i> <span class="sd">    `here &lt;https://github.com/adaa-polsl/RuleKit/wiki/4-Quality-and-evaluation</span></tt>
-            </div>
-            <div id="l42"
-               class="code sev- "><tt><i>42</i> <span class="sd">    &quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l43"
-               class="code sev- "><tt><i>43</i>     <span class="n">Accuracy</span> <span class="o">=</span> <span class="s1">&#39;Accuracy&#39;</span></tt>
-            </div>
-            <div id="l44"
-               class="code sev- "><tt><i>44</i>     <span class="n">BinaryEntropy</span> <span class="o">=</span> <span class="s1">&#39;BinaryEntropy&#39;</span></tt>
-            </div>
-            <div id="l45"
-               class="code sev- "><tt><i>45</i>     <span class="n">C1</span> <span class="o">=</span> <span class="s1">&#39;C1&#39;</span></tt>
-            </div>
-            <div id="l46"
-               class="code sev- "><tt><i>46</i>     <span class="n">C2</span> <span class="o">=</span> <span class="s1">&#39;C2&#39;</span></tt>
-            </div>
-            <div id="l47"
-               class="code sev- "><tt><i>47</i>     <span class="n">CFoil</span> <span class="o">=</span> <span class="s1">&#39;CFoil&#39;</span></tt>
-            </div>
-            <div id="l48"
-               class="code sev- "><tt><i>48</i>     <span class="n">CN2Significnce</span> <span class="o">=</span> <span class="s1">&#39;CN2Significnce&#39;</span></tt>
-            </div>
-            <div id="l49"
-               class="code sev- "><tt><i>49</i>     <span class="n">Correlation</span> <span class="o">=</span> <span class="s1">&#39;Correlation&#39;</span></tt>
-            </div>
-            <div id="l50"
-               class="code sev- "><tt><i>50</i>     <span class="n">Coverage</span> <span class="o">=</span> <span class="s1">&#39;Coverage&#39;</span></tt>
-            </div>
-            <div id="l51"
-               class="code sev- "><tt><i>51</i>     <span class="n">FBayesianConfirmation</span> <span class="o">=</span> <span class="s1">&#39;FBayesianConfirmation&#39;</span></tt>
-            </div>
-            <div id="l52"
-               class="code sev- "><tt><i>52</i>     <span class="n">FMeasure</span> <span class="o">=</span> <span class="s1">&#39;FMeasure&#39;</span></tt>
-            </div>
-            <div id="l53"
-               class="code sev- "><tt><i>53</i>     <span class="n">FullCoverage</span> <span class="o">=</span> <span class="s1">&#39;FullCoverage&#39;</span></tt>
-            </div>
-            <div id="l54"
-               class="code sev- "><tt><i>54</i>     <span class="n">GeoRSS</span> <span class="o">=</span> <span class="s1">&#39;GeoRSS&#39;</span></tt>
-            </div>
-            <div id="l55"
-               class="code sev- "><tt><i>55</i>     <span class="n">GMeasure</span> <span class="o">=</span> <span class="s1">&#39;GMeasure&#39;</span></tt>
-            </div>
-            <div id="l56"
-               class="code sev- "><tt><i>56</i>     <span class="n">InformationGain</span> <span class="o">=</span> <span class="s1">&#39;InformationGain&#39;</span></tt>
-            </div>
-            <div id="l57"
-               class="code sev- "><tt><i>57</i>     <span class="n">JMeasure</span> <span class="o">=</span> <span class="s1">&#39;JMeasure&#39;</span></tt>
-            </div>
-            <div id="l58"
-               class="code sev- "><tt><i>58</i>     <span class="n">Kappa</span> <span class="o">=</span> <span class="s1">&#39;Kappa&#39;</span></tt>
-            </div>
-            <div id="l59"
-               class="code sev- "><tt><i>59</i>     <span class="n">Klosgen</span> <span class="o">=</span> <span class="s1">&#39;Klosgen&#39;</span></tt>
-            </div>
-            <div id="l60"
-               class="code sev- "><tt><i>60</i>     <span class="n">Laplace</span> <span class="o">=</span> <span class="s1">&#39;Laplace&#39;</span></tt>
-            </div>
-            <div id="l61"
-               class="code sev- "><tt><i>61</i>     <span class="n">Lift</span> <span class="o">=</span> <span class="s1">&#39;Lift&#39;</span></tt>
-            </div>
-            <div id="l62"
-               class="code sev- "><tt><i>62</i>     <span class="n">LogicalSufficiency</span> <span class="o">=</span> <span class="s1">&#39;LogicalSufficiency&#39;</span></tt>
-            </div>
-            <div id="l63"
-               class="code sev- "><tt><i>63</i>     <span class="n">LogRank</span> <span class="o">=</span> <span class="s1">&#39;LogRank&#39;</span></tt>
-            </div>
-            <div id="l64"
-               class="code sev- "><tt><i>64</i>     <span class="n">MEstimate</span> <span class="o">=</span> <span class="s1">&#39;MEstimate&#39;</span></tt>
-            </div>
-            <div id="l65"
-               class="code sev- "><tt><i>65</i>     <span class="n">MutualSupport</span> <span class="o">=</span> <span class="s1">&#39;MutualSupport&#39;</span></tt>
-            </div>
-            <div id="l66"
-               class="code sev- "><tt><i>66</i>     <span class="n">Novelty</span> <span class="o">=</span> <span class="s1">&#39;Novelty&#39;</span></tt>
-            </div>
-            <div id="l67"
-               class="code sev- "><tt><i>67</i>     <span class="n">OddsRatio</span> <span class="o">=</span> <span class="s1">&#39;OddsRatio&#39;</span></tt>
-            </div>
-            <div id="l68"
-               class="code sev- "><tt><i>68</i>     <span class="n">OneWaySupport</span> <span class="o">=</span> <span class="s1">&#39;OneWaySupport&#39;</span></tt>
-            </div>
-            <div id="l69"
-               class="code sev- "><tt><i>69</i>     <span class="n">PawlakDependencyFactor</span> <span class="o">=</span> <span class="s1">&#39;PawlakDependencyFactor&#39;</span></tt>
-            </div>
-            <div id="l70"
-               class="code sev- "><tt><i>70</i>     <span class="n">Precision</span> <span class="o">=</span> <span class="s1">&#39;Precision&#39;</span></tt>
-            </div>
-            <div id="l71"
-               class="code sev- "><tt><i>71</i>     <span class="n">Q2</span> <span class="o">=</span> <span class="s1">&#39;Q2&#39;</span></tt>
-            </div>
-            <div id="l72"
-               class="code sev- "><tt><i>72</i>     <span class="n">RelativeRisk</span> <span class="o">=</span> <span class="s1">&#39;RelativeRisk&#39;</span></tt>
-            </div>
-            <div id="l73"
-               class="code sev- "><tt><i>73</i>     <span class="n">Ripper</span> <span class="o">=</span> <span class="s1">&#39;Ripper&#39;</span></tt>
-            </div>
-            <div id="l74"
-               class="code sev- "><tt><i>74</i>     <span class="n">RSS</span> <span class="o">=</span> <span class="s1">&#39;RSS&#39;</span></tt>
-            </div>
-            <div id="l75"
-               class="code sev- "><tt><i>75</i>     <span class="n">RuleInterest</span> <span class="o">=</span> <span class="s1">&#39;RuleInterest&#39;</span></tt>
-            </div>
-            <div id="l76"
-               class="code sev- "><tt><i>76</i>     <span class="n">SBayesian</span> <span class="o">=</span> <span class="s1">&#39;SBayesian&#39;</span></tt>
-            </div>
-            <div id="l77"
-               class="code sev- "><tt><i>77</i>     <span class="n">Sensitivity</span> <span class="o">=</span> <span class="s1">&#39;Sensitivity&#39;</span></tt>
-            </div>
-            <div id="l78"
-               class="code sev- "><tt><i>78</i>     <span class="n">Specificity</span> <span class="o">=</span> <span class="s1">&#39;Specificity&#39;</span></tt>
-            </div>
-            <div id="l79"
-               class="code sev- "><tt><i>79</i>     <span class="n">TwoWaySupport</span> <span class="o">=</span> <span class="s1">&#39;TwoWaySupport&#39;</span></tt>
-            </div>
-            <div id="l80"
-               class="code sev- "><tt><i>80</i>     <span class="n">WeightedLaplace</span> <span class="o">=</span> <span class="s1">&#39;WeightedLaplace&#39;</span></tt>
-            </div>
-            <div id="l81"
-               class="code sev- "><tt><i>81</i>     <span class="n">WeightedRelativeAccuracy</span> <span class="o">=</span> <span class="s1">&#39;WeightedRelativeAccuracy&#39;</span></tt>
-            </div>
-            <div id="l82"
-               class="code sev- "><tt><i>82</i>     <span class="n">YAILS</span> <span class="o">=</span> <span class="s1">&#39;YAILS&#39;</span></tt>
-            </div>
-            <div id="l83"
-               class="code sev- "><tt><i>83</i> &nbsp;</tt>
-            </div>
-            <div id="l84"
-               class="code sev- "><tt><i>84</i> &nbsp;</tt>
-            </div>
-            <div id="l85"
-               class="code sev- "><tt><i>85</i> <span class="n">DEFAULT_PARAMS_VALUE</span> <span class="o">=</span> <span class="p">{</span></tt>
-            </div>
-            <div id="l86"
-               class="code sev- "><tt><i>86</i>     <span class="s1">&#39;minsupp_new&#39;</span><span class="p">:</span> <span class="mf">0.05</span><span class="p">,</span></tt>
-            </div>
-            <div id="l87"
-               class="code sev- "><tt><i>87</i>     <span class="s1">&#39;induction_measure&#39;</span><span class="p">:</span> <span class="n">Measures</span><span class="o">.</span><span class="n">Correlation</span><span class="p">,</span></tt>
-            </div>
-            <div id="l88"
-               class="code sev- "><tt><i>88</i>     <span class="s1">&#39;pruning_measure&#39;</span><span class="p">:</span>  <span class="n">Measures</span><span class="o">.</span><span class="n">Correlation</span><span class="p">,</span></tt>
-            </div>
-            <div id="l89"
-               class="code sev- "><tt><i>89</i>     <span class="s1">&#39;voting_measure&#39;</span><span class="p">:</span> <span class="n">Measures</span><span class="o">.</span><span class="n">Correlation</span><span class="p">,</span></tt>
-            </div>
-            <div id="l90"
-               class="code sev- "><tt><i>90</i>     <span class="s1">&#39;max_growing&#39;</span><span class="p">:</span> <span class="mf">0.0</span><span class="p">,</span></tt>
-            </div>
-            <div id="l91"
-               class="code sev- "><tt><i>91</i>     <span class="s1">&#39;enable_pruning&#39;</span><span class="p">:</span> <span class="kc">True</span><span class="p">,</span></tt>
-            </div>
-            <div id="l92"
-               class="code sev- "><tt><i>92</i>     <span class="s1">&#39;ignore_missing&#39;</span><span class="p">:</span> <span class="kc">False</span><span class="p">,</span></tt>
-            </div>
-            <div id="l93"
-               class="code sev- "><tt><i>93</i>     <span class="s1">&#39;max_uncovered_fraction&#39;</span><span class="p">:</span> <span class="mf">0.0</span><span class="p">,</span></tt>
-            </div>
-            <div id="l94"
-               class="code sev- "><tt><i>94</i>     <span class="s1">&#39;select_best_candidate&#39;</span><span class="p">:</span> <span class="kc">False</span><span class="p">,</span></tt>
-            </div>
-            <div id="l95"
-               class="code sev- "><tt><i>95</i>     <span class="s1">&#39;complementary_conditions&#39;</span><span class="p">:</span> <span class="kc">False</span><span class="p">,</span></tt>
-            </div>
-            <div id="l96"
-               class="code sev- "><tt><i>96</i>     <span class="s1">&#39;control_apriori_precision&#39;</span><span class="p">:</span> <span class="kc">True</span><span class="p">,</span></tt>
-            </div>
-            <div id="l97"
-               class="code sev- "><tt><i>97</i>     <span class="s1">&#39;max_rule_count&#39;</span><span class="p">:</span> <span class="mi">0</span><span class="p">,</span></tt>
-            </div>
-            <div id="l98"
-               class="code sev- "><tt><i>98</i>     <span class="s1">&#39;approximate_induction&#39;</span><span class="p">:</span> <span class="kc">False</span><span class="p">,</span></tt>
-            </div>
-            <div id="l99"
-               class="code sev- "><tt><i>99</i>     <span class="s1">&#39;approximate_bins_count&#39;</span><span class="p">:</span> <span class="mi">100</span><span class="p">,</span></tt>
-            </div>
-            <div id="l100"
-               class="code sev- "><tt><i>100</i>     <span class="s1">&#39;mean_based_regression&#39;</span><span class="p">:</span> <span class="kc">True</span><span class="p">,</span></tt>
-            </div>
-            <div id="l101"
-               class="code sev- "><tt><i>101</i> &nbsp;</tt>
-            </div>
-            <div id="l102"
-               class="code sev- "><tt><i>102</i>     <span class="s1">&#39;extend_using_preferred&#39;</span><span class="p">:</span> <span class="kc">False</span><span class="p">,</span></tt>
-            </div>
-            <div id="l103"
-               class="code sev- "><tt><i>103</i>     <span class="s1">&#39;extend_using_automatic&#39;</span><span class="p">:</span> <span class="kc">False</span><span class="p">,</span></tt>
-            </div>
-            <div id="l104"
-               class="code sev- "><tt><i>104</i>     <span class="s1">&#39;induce_using_preferred&#39;</span><span class="p">:</span> <span class="kc">False</span><span class="p">,</span></tt>
-            </div>
-            <div id="l105"
-               class="code sev- "><tt><i>105</i>     <span class="s1">&#39;induce_using_automatic&#39;</span><span class="p">:</span> <span class="kc">False</span><span class="p">,</span></tt>
-            </div>
-            <div id="l106"
-               class="code sev- "><tt><i>106</i>     <span class="s1">&#39;consider_other_classes&#39;</span><span class="p">:</span> <span class="kc">False</span><span class="p">,</span></tt>
-            </div>
-            <div id="l107"
-               class="code sev- "><tt><i>107</i>     <span class="s1">&#39;preferred_conditions_per_rule&#39;</span><span class="p">:</span> <span class="n">MAX_INT</span><span class="p">,</span></tt>
-            </div>
-            <div id="l108"
-               class="code sev- "><tt><i>108</i>     <span class="s1">&#39;preferred_attributes_per_rule&#39;</span><span class="p">:</span> <span class="n">MAX_INT</span><span class="p">,</span></tt>
-            </div>
-            <div id="l109"
-               class="code sev- "><tt><i>109</i> &nbsp;</tt>
-            </div>
-            <div id="l110"
-               class="code sev- "><tt><i>110</i>     <span class="c1"># Contrast sets</span></tt>
-            </div>
-            <div id="l111"
-               class="code sev- "><tt><i>111</i>     <span class="s1">&#39;minsupp_all&#39;</span><span class="p">:</span> <span class="p">(</span><span class="mf">0.8</span><span class="p">,</span> <span class="mf">0.5</span><span class="p">,</span> <span class="mf">0.2</span><span class="p">,</span> <span class="mf">0.1</span><span class="p">),</span></tt>
-            </div>
-            <div id="l112"
-               class="code sev- "><tt><i>112</i>     <span class="s1">&#39;max_neg2pos&#39;</span><span class="p">:</span> <span class="mf">0.5</span><span class="p">,</span></tt>
-            </div>
-            <div id="l113"
-               class="code sev- "><tt><i>113</i>     <span class="s1">&#39;max_passes_count&#39;</span><span class="p">:</span> <span class="mi">5</span><span class="p">,</span></tt>
-            </div>
-            <div id="l114"
-               class="code sev- "><tt><i>114</i>     <span class="s1">&#39;penalty_strength&#39;</span><span class="p">:</span> <span class="mf">0.5</span><span class="p">,</span></tt>
-            </div>
-            <div id="l115"
-               class="code sev- "><tt><i>115</i>     <span class="s1">&#39;penalty_saturation&#39;</span><span class="p">:</span> <span class="mf">0.2</span><span class="p">,</span></tt>
-            </div>
-            <div id="l116"
-               class="code sev- "><tt><i>116</i> <span class="p">}</span></tt>
-            </div>
-            <div id="l117"
-               class="code sev- "><tt><i>117</i> &nbsp;</tt>
-            </div>
-            <div id="l118"
-               class="code sev- "><tt><i>118</i> <span class="n">_QualityMeasure</span> <span class="o">=</span> <span class="n">Union</span><span class="p">[</span><span class="n">Measures</span><span class="p">,</span> <span class="n">_UserDefinedMeasure</span><span class="p">]</span></tt>
-            </div>
-            <div id="l119"
-               class="code sev- "><tt><i>119</i> &nbsp;</tt>
-            </div>
-            <div id="l120"
-               class="code sev- "><tt><i>120</i> &nbsp;</tt>
-            </div>
-            <div id="l121"
-               class="code sev- "><tt><i>121</i> <span class="k">class</span> <span class="nc">ModelsParams</span><span class="p">(</span><span class="n">BaseModel</span><span class="p">):</span></tt>
-            </div>
-            <div id="l122"
-               class="code sev- "><tt><i>122</i> <span class="w">    </span><span class="sd">&quot;&quot;&quot;Model for validating models hyperparameters</span></tt>
-            </div>
-            <div id="l123"
-               class="code sev- "><tt><i>123</i> <span class="sd">    &quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l124"
-               class="code sev- "><tt><i>124</i>     <span class="n">minsupp_new</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">float</span><span class="p">]</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;minsupp_new&#39;</span><span class="p">]</span></tt>
-            </div>
-            <div id="l125"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (92 > 79 characters)</li>
-               
-               </ul><tt><i>125</i>     <span class="n">induction_measure</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">_QualityMeasure</span><span class="p">]</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;induction_measure&#39;</span><span class="p">]</span></tt>
-            </div>
-            <div id="l126"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (88 > 79 characters)</li>
-               
-               </ul><tt><i>126</i>     <span class="n">pruning_measure</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">_QualityMeasure</span><span class="p">]</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;pruning_measure&#39;</span><span class="p">]</span></tt>
-            </div>
-            <div id="l127"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (86 > 79 characters)</li>
-               
-               </ul><tt><i>127</i>     <span class="n">voting_measure</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">_QualityMeasure</span><span class="p">]</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;voting_measure&#39;</span><span class="p">]</span></tt>
-            </div>
-            <div id="l128"
-               class="code sev- "><tt><i>128</i>     <span class="n">max_growing</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">float</span><span class="p">]</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;max_growing&#39;</span><span class="p">]</span></tt>
-            </div>
-            <div id="l129"
-               class="code sev- "><tt><i>129</i>     <span class="n">enable_pruning</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">bool</span><span class="p">]</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;enable_pruning&#39;</span><span class="p">]</span></tt>
-            </div>
-            <div id="l130"
-               class="code sev- "><tt><i>130</i>     <span class="n">ignore_missing</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">bool</span><span class="p">]</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;ignore_missing&#39;</span><span class="p">]</span></tt>
-            </div>
-            <div id="l131"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (92 > 79 characters)</li>
-               
-               </ul><tt><i>131</i>     <span class="n">max_uncovered_fraction</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">float</span><span class="p">]</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;max_uncovered_fraction&#39;</span><span class="p">]</span></tt>
-            </div>
-            <div id="l132"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (89 > 79 characters)</li>
-               
-               </ul><tt><i>132</i>     <span class="n">select_best_candidate</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">bool</span><span class="p">]</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;select_best_candidate&#39;</span><span class="p">]</span></tt>
-            </div>
-            <div id="l133"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (95 > 79 characters)</li>
-               
-               </ul><tt><i>133</i>     <span class="n">complementary_conditions</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">bool</span><span class="p">]</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;complementary_conditions&#39;</span><span class="p">]</span></tt>
-            </div>
-            <div id="l134"
-               class="code sev- "><tt><i>134</i>     <span class="n">max_rule_count</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;max_rule_count&#39;</span><span class="p">]</span></tt>
-            </div>
-            <div id="l135"
-               class="code sev- "><tt><i>135</i> &nbsp;</tt>
-            </div>
-            <div id="l136"
-               class="code sev- "><tt><i>136</i> &nbsp;</tt>
-            </div>
-            <div id="l137"
-               class="code sev- "><tt><i>137</i> <span class="k">class</span> <span class="nc">ExpertModelParams</span><span class="p">(</span><span class="n">ModelsParams</span><span class="p">):</span></tt>
-            </div>
-            <div id="l138"
-               class="code sev- "><tt><i>138</i> <span class="w">    </span><span class="sd">&quot;&quot;&quot;Model for validating expert models hyperparameters</span></tt>
-            </div>
-            <div id="l139"
-               class="code sev- "><tt><i>139</i> <span class="sd">    &quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l140"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (91 > 79 characters)</li>
-               
-               </ul><tt><i>140</i>     <span class="n">extend_using_preferred</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">bool</span><span class="p">]</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;extend_using_preferred&#39;</span><span class="p">]</span></tt>
-            </div>
-            <div id="l141"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (91 > 79 characters)</li>
-               
-               </ul><tt><i>141</i>     <span class="n">extend_using_automatic</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">bool</span><span class="p">]</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;extend_using_automatic&#39;</span><span class="p">]</span></tt>
-            </div>
-            <div id="l142"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (91 > 79 characters)</li>
-               
-               </ul><tt><i>142</i>     <span class="n">induce_using_preferred</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">bool</span><span class="p">]</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;induce_using_preferred&#39;</span><span class="p">]</span></tt>
-            </div>
-            <div id="l143"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (91 > 79 characters)</li>
-               
-               </ul><tt><i>143</i>     <span class="n">induce_using_automatic</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">bool</span><span class="p">]</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;induce_using_automatic&#39;</span><span class="p">]</span></tt>
-            </div>
-            <div id="l144"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (91 > 79 characters)</li>
-               
-               </ul><tt><i>144</i>     <span class="n">consider_other_classes</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">bool</span><span class="p">]</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;consider_other_classes&#39;</span><span class="p">]</span></tt>
-            </div>
-            <div id="l145"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (104 > 79 characters)</li>
-               
-               </ul><tt><i>145</i>     <span class="n">preferred_conditions_per_rule</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">int</span><span class="p">]</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;preferred_conditions_per_rule&#39;</span><span class="p">]</span></tt>
-            </div>
-            <div id="l146"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (104 > 79 characters)</li>
-               
-               </ul><tt><i>146</i>     <span class="n">preferred_attributes_per_rule</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">int</span><span class="p">]</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;preferred_attributes_per_rule&#39;</span><span class="p">]</span></tt>
-            </div>
-            <div id="l147"
-               class="code sev- "><tt><i>147</i> &nbsp;</tt>
-            </div>
-            <div id="l148"
-               class="code sev- "><tt><i>148</i> &nbsp;</tt>
-            </div>
-            <div id="l149"
-               class="code sev- "><tt><i>149</i> <span class="k">class</span> <span class="nc">ContrastSetModelParams</span><span class="p">(</span><span class="n">ModelsParams</span><span class="p">):</span></tt>
-            </div>
-            <div id="l150"
-               class="code sev- "><tt><i>150</i> <span class="w">    </span><span class="sd">&quot;&quot;&quot;Model for validating contrast set models hyperparameters</span></tt>
-            </div>
-            <div id="l151"
-               class="code sev- "><tt><i>151</i> <span class="sd">    &quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l152"
-               class="code sev- "><tt><i>152</i>     <span class="n">minsupp_all</span><span class="p">:</span> <span class="n">Tuple</span><span class="p">[</span></tt>
-            </div>
-            <div id="l153"
-               class="code sev- "><tt><i>153</i>         <span class="nb">float</span><span class="p">,</span> <span class="nb">float</span><span class="p">,</span> <span class="nb">float</span><span class="p">,</span> <span class="nb">float</span></tt>
-            </div>
-            <div id="l154"
-               class="code sev- "><tt><i>154</i>     <span class="p">]</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;minsupp_all&#39;</span><span class="p">]</span></tt>
-            </div>
-            <div id="l155"
-               class="code sev- "><tt><i>155</i>     <span class="n">max_neg2pos</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">float</span><span class="p">]</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;max_neg2pos&#39;</span><span class="p">]</span></tt>
-            </div>
-            <div id="l156"
-               class="code sev- "><tt><i>156</i>     <span class="n">max_passes_count</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">int</span><span class="p">]</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;max_passes_count&#39;</span><span class="p">]</span></tt>
-            </div>
-            <div id="l157"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (80 > 79 characters)</li>
-               
-               </ul><tt><i>157</i>     <span class="n">penalty_strength</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">float</span><span class="p">]</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;penalty_strength&#39;</span><span class="p">]</span></tt>
-            </div>
-            <div id="l158"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (84 > 79 characters)</li>
-               
-               </ul><tt><i>158</i>     <span class="n">penalty_saturation</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">float</span><span class="p">]</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;penalty_saturation&#39;</span><span class="p">]</span></tt>
-            </div>
-            
-         </div>
-      </div>
-   </body>
-</html>
\ No newline at end of file
diff --git a/docs/reports/flake8/rulekit.regression.report.html b/docs/reports/flake8/rulekit.regression.report.html
index 75540c1..8025a76 100644
--- a/docs/reports/flake8/rulekit.regression.report.html
+++ b/docs/reports/flake8/rulekit.regression.report.html
@@ -52,559 +52,16 @@ <h1>
          <li>
             <a data-code="E501">
                <span class="count sev-2">
-                  78
+                  1
                </span>
-               <strong>E501:</strong> line too long (80 > 79 characters)
-               
-                  (and 18 similar)
+               <strong>E501:</strong> line too long (89 > 88 characters)
                
             </a>
             <ul class="details">
             <li>
                
-               <p>Line too long (80 > 79 characters):</p>
-               
-               <a href="rulekit.regression.source.html#l43">
-                  <tt><i>43</i>         <span class="n">induction_measure</span><span class="p">:</span> <span class="n">Measures</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;induction_measure&#39;</span><span class="p">],</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (87 > 79 characters):</p>
-               
-               <a href="rulekit.regression.source.html#l50">
-                  <tt><i>50</i>         <span class="n">max_uncovered_fraction</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;max_uncovered_fraction&#39;</span><span class="p">],</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (84 > 79 characters):</p>
-               
-               <a href="rulekit.regression.source.html#l51">
-                  <tt><i>51</i>         <span class="n">select_best_candidate</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;select_best_candidate&#39;</span><span class="p">],</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (90 > 79 characters):</p>
-               
-               <a href="rulekit.regression.source.html#l52">
-                  <tt><i>52</i>         <span class="n">complementary_conditions</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;complementary_conditions&#39;</span><span class="p">],</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (84 > 79 characters):</p>
-               
-               <a href="rulekit.regression.source.html#l53">
-                  <tt><i>53</i>         <span class="n">mean_based_regression</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;mean_based_regression&#39;</span><span class="p">],</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (91 > 79 characters):</p>
-               
-               <a href="rulekit.regression.source.html#l60">
-                  <tt><i>60</i> <span class="sd">            a minimum number (or fraction, if value &lt; 1.0) of previously uncovered examples</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (101 > 79 characters):</p>
-               
-               <a href="rulekit.regression.source.html#l61">
-                  <tt><i>61</i> <span class="sd">             to be covered by a new rule (positive examples for classification problems); default: 5,</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (84 > 79 characters):</p>
-               
-               <a href="rulekit.regression.source.html#l67">
-                  <tt><i>67</i> <span class="sd">            measure used during pruning. Could be user defined (string), for example</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (96 > 79 characters):</p>
-               
-               <a href="rulekit.regression.source.html#l73">
-                  <tt><i>73</i> <span class="sd">            non-negative integer representing maximum number of conditions which can be added to</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (98 > 79 characters):</p>
-               
-               <a href="rulekit.regression.source.html#l74">
-                  <tt><i>74</i> <span class="sd">            the rule in the growing phase (use this parameter for large datasets if execution time</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (97 > 79 characters):</p>
-               
-               <a href="rulekit.regression.source.html#l79">
-                  <tt><i>79</i> <span class="sd">            boolean telling whether missing values should be ignored (by default, a missing value</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (99 > 79 characters):</p>
-               
-               <a href="rulekit.regression.source.html#l80">
-                  <tt><i>80</i> <span class="sd">            of given attribute is always considered as not fulfilling the condition build upon that</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (95 > 79 characters):</p>
-               
-               <a href="rulekit.regression.source.html#l83">
-                  <tt><i>83</i> <span class="sd">            Floating-point number from [0,1] interval representing maximum fraction of examples</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (85 > 79 characters):</p>
-               
-               <a href="rulekit.regression.source.html#l86">
-                  <tt><i>86</i> <span class="sd">            Flag determining if best candidate should be selected from growing phase;</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (96 > 79 characters):</p>
-               
-               <a href="rulekit.regression.source.html#l89">
-                  <tt><i>89</i> <span class="sd">            If enabled, complementary conditions in the form a = !{value} for nominal attributes</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (97 > 79 characters):</p>
-               
-               <a href="rulekit.regression.source.html#l92">
-                  <tt><i>92</i> <span class="sd">            Enable fast induction of mean-based regression rules instead of default median-based.</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (92 > 79 characters):</p>
-               
-               <a href="rulekit.regression.source.html#l94">
-                  <tt><i>94</i> <span class="sd">            Maximum number of rules to be generated (for classification data sets it applies</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (81 > 79 characters):</p>
-               
-               <a href="rulekit.regression.source.html#l120">
-                  <tt><i>120</i>                 <span class="sa">f</span><span class="s1">&#39;</span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="vm">__class__</span><span class="o">.</span><span class="vm">__name__</span><span class="si">}</span><span class="s1"> requires lables values to be numeric&#39;</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (99 > 79 characters):</p>
-               
-               <a href="rulekit.regression.source.html#l123">
-                  <tt><i>123</i>     <span class="k">def</span> <span class="nf">fit</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">:</span> <span class="n">Data</span><span class="p">,</span> <span class="n">labels</span><span class="p">:</span> <span class="n">Data</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">RuleRegressor</span><span class="p">:</span>  <span class="c1"># pylint: disable=arguments-differ</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (90 > 79 characters):</p>
-               
-               <a href="rulekit.regression.source.html#l174">
-                  <tt><i>174</i>         <span class="k">return</span> <span class="n">PredictionResultMapper</span><span class="o">.</span><span class="n">map_to_numerical</span><span class="p">(</span><span class="n">predicted_example_set</span><span class="p">,</span> <span class="n">remap</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (80 > 79 characters):</p>
-               
-               <a href="rulekit.regression.source.html#l188">
-                  <tt><i>188</i>         <span class="n">induction_measure</span><span class="p">:</span> <span class="n">Measures</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;induction_measure&#39;</span><span class="p">],</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (87 > 79 characters):</p>
-               
-               <a href="rulekit.regression.source.html#l195">
-                  <tt><i>195</i>         <span class="n">max_uncovered_fraction</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;max_uncovered_fraction&#39;</span><span class="p">],</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (84 > 79 characters):</p>
-               
-               <a href="rulekit.regression.source.html#l196">
-                  <tt><i>196</i>         <span class="n">select_best_candidate</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;select_best_candidate&#39;</span><span class="p">],</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (90 > 79 characters):</p>
-               
-               <a href="rulekit.regression.source.html#l197">
-                  <tt><i>197</i>         <span class="n">complementary_conditions</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;complementary_conditions&#39;</span><span class="p">],</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (84 > 79 characters):</p>
-               
-               <a href="rulekit.regression.source.html#l198">
-                  <tt><i>198</i>         <span class="n">mean_based_regression</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;mean_based_regression&#39;</span><span class="p">],</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (86 > 79 characters):</p>
-               
-               <a href="rulekit.regression.source.html#l201">
-                  <tt><i>201</i>         <span class="n">extend_using_preferred</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;extend_using_preferred&#39;</span><span class="p">],</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (86 > 79 characters):</p>
-               
-               <a href="rulekit.regression.source.html#l202">
-                  <tt><i>202</i>         <span class="n">extend_using_automatic</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;extend_using_automatic&#39;</span><span class="p">],</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (86 > 79 characters):</p>
-               
-               <a href="rulekit.regression.source.html#l203">
-                  <tt><i>203</i>         <span class="n">induce_using_preferred</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;induce_using_preferred&#39;</span><span class="p">],</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (86 > 79 characters):</p>
-               
-               <a href="rulekit.regression.source.html#l204">
-                  <tt><i>204</i>         <span class="n">induce_using_automatic</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;induce_using_automatic&#39;</span><span class="p">],</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (91 > 79 characters):</p>
-               
-               <a href="rulekit.regression.source.html#l214">
-                  <tt><i>214</i> <span class="sd">            a minimum number (or fraction, if value &lt; 1.0) of previously uncovered examples</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (101 > 79 characters):</p>
-               
-               <a href="rulekit.regression.source.html#l215">
-                  <tt><i>215</i> <span class="sd">             to be covered by a new rule (positive examples for classification problems); default: 5,</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (84 > 79 characters):</p>
-               
-               <a href="rulekit.regression.source.html#l221">
-                  <tt><i>221</i> <span class="sd">            measure used during pruning. Could be user defined (string), for example</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (96 > 79 characters):</p>
-               
-               <a href="rulekit.regression.source.html#l227">
-                  <tt><i>227</i> <span class="sd">            non-negative integer representing maximum number of conditions which can be added to</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (98 > 79 characters):</p>
-               
-               <a href="rulekit.regression.source.html#l228">
-                  <tt><i>228</i> <span class="sd">            the rule in the growing phase (use this parameter for large datasets if execution time</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (97 > 79 characters):</p>
-               
-               <a href="rulekit.regression.source.html#l233">
-                  <tt><i>233</i> <span class="sd">            boolean telling whether missing values should be ignored (by default, a missing value</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (99 > 79 characters):</p>
-               
-               <a href="rulekit.regression.source.html#l234">
-                  <tt><i>234</i> <span class="sd">            of given attribute is always considered as not fulfilling the condition build upon that</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (95 > 79 characters):</p>
-               
-               <a href="rulekit.regression.source.html#l237">
-                  <tt><i>237</i> <span class="sd">            Floating-point number from [0,1] interval representing maximum fraction of examples</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (85 > 79 characters):</p>
-               
-               <a href="rulekit.regression.source.html#l240">
-                  <tt><i>240</i> <span class="sd">            Flag determining if best candidate should be selected from growing phase;</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (96 > 79 characters):</p>
-               
-               <a href="rulekit.regression.source.html#l243">
-                  <tt><i>243</i> <span class="sd">            If enabled, complementary conditions in the form a = !{value} for nominal attributes</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (97 > 79 characters):</p>
-               
-               <a href="rulekit.regression.source.html#l246">
-                  <tt><i>246</i> <span class="sd">            Enable fast induction of mean-based regression rules instead of default median-based.</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (92 > 79 characters):</p>
-               
-               <a href="rulekit.regression.source.html#l248">
-                  <tt><i>248</i> <span class="sd">            Maximum number of rules to be generated (for classification data sets it applies</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (95 > 79 characters):</p>
-               
-               <a href="rulekit.regression.source.html#l252">
-                  <tt><i>252</i> <span class="sd">            boolean indicating whether initial rules should be extended with a use of preferred</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (95 > 79 characters):</p>
-               
-               <a href="rulekit.regression.source.html#l255">
-                  <tt><i>255</i> <span class="sd">            boolean indicating whether initial rules should be extended with a use of automatic</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (90 > 79 characters):</p>
-               
-               <a href="rulekit.regression.source.html#l258">
-                  <tt><i>258</i> <span class="sd">            boolean indicating whether new rules should be induced with a use of preferred</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (90 > 79 characters):</p>
-               
-               <a href="rulekit.regression.source.html#l261">
-                  <tt><i>261</i> <span class="sd">            boolean indicating whether new rules should be induced with a use of automatic</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (80 > 79 characters):</p>
-               
-               <a href="rulekit.regression.source.html#l264">
-                  <tt><i>264</i> <span class="sd">            maximum number of preferred conditions per rule; default: unlimited,</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (80 > 79 characters):</p>
-               
-               <a href="rulekit.regression.source.html#l266">
-                  <tt><i>266</i> <span class="sd">            maximum number of preferred attributes per rule; default: unlimited.</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (98 > 79 characters):</p>
-               
-               <a href="rulekit.regression.source.html#l325">
-                  <tt><i>325</i> <span class="sd">            set of initial rules, either passed as a list of strings representing rules or as list</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (92 > 79 characters):</p>
-               
-               <a href="rulekit.regression.source.html#l326">
-                  <tt><i>326</i> <span class="sd">            of tuples where first element is name of the rule and second one is rule string.</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (94 > 79 characters):</p>
-               
-               <a href="rulekit.regression.source.html#l328">
-                  <tt><i>328</i> <span class="sd">            multiset of preferred conditions (used also for specifying preferred attributes by</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (98 > 79 characters):</p>
-               
-               <a href="rulekit.regression.source.html#l329">
-                  <tt><i>329</i> <span class="sd">             using special value Any). Either passed as a list of strings representing rules or as</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (98 > 79 characters):</p>
-               
-               <a href="rulekit.regression.source.html#l330">
-                  <tt><i>330</i> <span class="sd">             list of tuples where first element is name of the rule and second one is rule string.</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (95 > 79 characters):</p>
-               
-               <a href="rulekit.regression.source.html#l332">
-                  <tt><i>332</i> <span class="sd">            set of forbidden conditions (used also for specifying forbidden attributes by using</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (97 > 79 characters):</p>
-               
-               <a href="rulekit.regression.source.html#l333">
-                  <tt><i>333</i> <span class="sd">             special valye Any). Either passed as a list of strings representing rules or as list</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (93 > 79 characters):</p>
-               
-               <a href="rulekit.regression.source.html#l334">
-                  <tt><i>334</i> <span class="sd">             of tuples where first element is name of the rule and second one is rule string.</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (80 > 79 characters):</p>
-               
-               <a href="rulekit.regression.source.html#l371">
-                  <tt><i>371</i>         <span class="n">induction_measure</span><span class="p">:</span> <span class="n">Measures</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;induction_measure&#39;</span><span class="p">],</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (87 > 79 characters):</p>
-               
-               <a href="rulekit.regression.source.html#l378">
-                  <tt><i>378</i>         <span class="n">max_uncovered_fraction</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;max_uncovered_fraction&#39;</span><span class="p">],</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (84 > 79 characters):</p>
-               
-               <a href="rulekit.regression.source.html#l379">
-                  <tt><i>379</i>         <span class="n">select_best_candidate</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;select_best_candidate&#39;</span><span class="p">],</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (90 > 79 characters):</p>
-               
-               <a href="rulekit.regression.source.html#l380">
-                  <tt><i>380</i>         <span class="n">complementary_conditions</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;complementary_conditions&#39;</span><span class="p">],</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (84 > 79 characters):</p>
-               
-               <a href="rulekit.regression.source.html#l381">
-                  <tt><i>381</i>         <span class="n">mean_based_regression</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;mean_based_regression&#39;</span><span class="p">],</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (99 > 79 characters):</p>
-               
-               <a href="rulekit.regression.source.html#l388">
-                  <tt><i>388</i> <span class="sd">            a minimum positive support of a contrast set (p/P). When multiple values are specified,</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (97 > 79 characters):</p>
-               
-               <a href="rulekit.regression.source.html#l389">
-                  <tt><i>389</i> <span class="sd">            a metainduction is performed; Default and recommended sequence is: 0.8, 0.5, 0.2, 0.1</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (84 > 79 characters):</p>
-               
-               <a href="rulekit.regression.source.html#l391">
-                  <tt><i>391</i> <span class="sd">            a maximum ratio of negative to positive supports (nP/pN); Default is 0.5</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (97 > 79 characters):</p>
-               
-               <a href="rulekit.regression.source.html#l393">
-                  <tt><i>393</i> <span class="sd">            a maximum number of sequential covering passes for a single minsupp-all; Default is 5</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (85 > 79 characters):</p>
-               
-               <a href="rulekit.regression.source.html#l397">
-                  <tt><i>397</i> <span class="sd">            the value of p_new / P at which penalty reward saturates; Default is 0.2.</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (91 > 79 characters):</p>
-               
-               <a href="rulekit.regression.source.html#l399">
-                  <tt><i>399</i> <span class="sd">            a minimum number (or fraction, if value &lt; 1.0) of previously uncovered examples</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (101 > 79 characters):</p>
-               
-               <a href="rulekit.regression.source.html#l400">
-                  <tt><i>400</i> <span class="sd">             to be covered by a new rule (positive examples for classification problems); default: 5,</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (84 > 79 characters):</p>
-               
-               <a href="rulekit.regression.source.html#l406">
-                  <tt><i>406</i> <span class="sd">            measure used during pruning. Could be user defined (string), for example</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (96 > 79 characters):</p>
-               
-               <a href="rulekit.regression.source.html#l412">
-                  <tt><i>412</i> <span class="sd">            non-negative integer representing maximum number of conditions which can be added to</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (98 > 79 characters):</p>
-               
-               <a href="rulekit.regression.source.html#l413">
-                  <tt><i>413</i> <span class="sd">            the rule in the growing phase (use this parameter for large datasets if execution time</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (97 > 79 characters):</p>
-               
-               <a href="rulekit.regression.source.html#l418">
-                  <tt><i>418</i> <span class="sd">            boolean telling whether missing values should be ignored (by default, a missing value</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (100 > 79 characters):</p>
-               
-               <a href="rulekit.regression.source.html#l419">
-                  <tt><i>419</i> <span class="sd">             of given attribute is always considered as not fulfilling the condition build upon that</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (95 > 79 characters):</p>
-               
-               <a href="rulekit.regression.source.html#l422">
-                  <tt><i>422</i> <span class="sd">            Floating-point number from [0,1] interval representing maximum fraction of examples</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (85 > 79 characters):</p>
-               
-               <a href="rulekit.regression.source.html#l425">
-                  <tt><i>425</i> <span class="sd">            Flag determining if best candidate should be selected from growing phase;</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (96 > 79 characters):</p>
-               
-               <a href="rulekit.regression.source.html#l428">
-                  <tt><i>428</i> <span class="sd">            If enabled, complementary conditions in the form a = !{value} for nominal attributes</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (97 > 79 characters):</p>
-               
-               <a href="rulekit.regression.source.html#l431">
-                  <tt><i>431</i> <span class="sd">            Enable fast induction of mean-based regression rules instead of default median-based.</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (92 > 79 characters):</p>
-               
-               <a href="rulekit.regression.source.html#l433">
-                  <tt><i>433</i> <span class="sd">            Maximum number of rules to be generated (for classification data sets it applies</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (135 > 79 characters):</p>
-               
-               <a href="rulekit.regression.source.html#l458">
-                  <tt><i>458</i>     <span class="k">def</span> <span class="nf">fit</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">:</span> <span class="n">Data</span><span class="p">,</span> <span class="n">labels</span><span class="p">:</span> <span class="n">Data</span><span class="p">,</span> <span class="n">contrast_attribute</span><span class="p">:</span> <span class="nb">str</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ContrastSetRuleRegressor</span><span class="p">:</span>  <span class="c1"># pylint: disable=arguments-differ</span></tt>
+               <a href="rulekit.regression.source.html#l232">
+                  <tt><i>232</i> <span class="sd">            datasets if execution time is prohibitive); 0 indicates no limit; default: 0,</span></tt>
                </a>
             </li>
             </ul>
diff --git a/docs/reports/flake8/rulekit.regression.source.html b/docs/reports/flake8/rulekit.regression.source.html
index 2965dcc..daab125 100644
--- a/docs/reports/flake8/rulekit.regression.source.html
+++ b/docs/reports/flake8/rulekit.regression.source.html
@@ -23,19 +23,19 @@ <h1>
                class="code sev- "><tt><i>2</i> <span class="sd">&quot;&quot;&quot;</span></tt>
             </div>
             <div id="l3"
-               class="code sev- "><tt><i>3</i> <span class="kn">from</span> <span class="nn">__future__</span> <span class="kn">import</span> <span class="n">annotations</span></tt>
+               class="code sev- "><tt><i>3</i> &nbsp;</tt>
             </div>
             <div id="l4"
-               class="code sev- "><tt><i>4</i> &nbsp;</tt>
+               class="code sev- "><tt><i>4</i> <span class="kn">from</span> <span class="nn">__future__</span> <span class="kn">import</span> <span class="n">annotations</span></tt>
             </div>
             <div id="l5"
-               class="code sev- "><tt><i>5</i> <span class="kn">from</span> <span class="nn">numbers</span> <span class="kn">import</span> <span class="n">Number</span></tt>
+               class="code sev- "><tt><i>5</i> &nbsp;</tt>
             </div>
             <div id="l6"
-               class="code sev- "><tt><i>6</i> <span class="kn">from</span> <span class="nn">typing</span> <span class="kn">import</span> <span class="n">Tuple</span></tt>
+               class="code sev- "><tt><i>6</i> <span class="kn">from</span> <span class="nn">numbers</span> <span class="kn">import</span> <span class="n">Number</span></tt>
             </div>
             <div id="l7"
-               class="code sev- "><tt><i>7</i> <span class="kn">from</span> <span class="nn">typing</span> <span class="kn">import</span> <span class="n">Union</span></tt>
+               class="code sev- "><tt><i>7</i> <span class="kn">from</span> <span class="nn">typing</span> <span class="kn">import</span> <span class="n">Tuple</span><span class="p">,</span> <span class="n">Union</span></tt>
             </div>
             <div id="l8"
                class="code sev- "><tt><i>8</i> &nbsp;</tt>
@@ -56,667 +56,487 @@ <h1>
                class="code sev- "><tt><i>13</i> <span class="kn">from</span> <span class="nn">rulekit._helpers</span> <span class="kn">import</span> <span class="n">PredictionResultMapper</span></tt>
             </div>
             <div id="l14"
-               class="code sev- "><tt><i>14</i> <span class="kn">from</span> <span class="nn">rulekit._operator</span> <span class="kn">import</span> <span class="n">BaseOperator</span></tt>
+               class="code sev- "><tt><i>14</i> <span class="kn">from</span> <span class="nn">rulekit._operator</span> <span class="kn">import</span> <span class="n">BaseOperator</span><span class="p">,</span> <span class="n">Data</span><span class="p">,</span> <span class="n">ExpertKnowledgeOperator</span></tt>
             </div>
             <div id="l15"
-               class="code sev- "><tt><i>15</i> <span class="kn">from</span> <span class="nn">rulekit._operator</span> <span class="kn">import</span> <span class="n">Data</span></tt>
+               class="code sev- "><tt><i>15</i> <span class="kn">from</span> <span class="nn">rulekit._problem_types</span> <span class="kn">import</span> <span class="n">ProblemType</span></tt>
             </div>
             <div id="l16"
-               class="code sev- "><tt><i>16</i> <span class="kn">from</span> <span class="nn">rulekit._operator</span> <span class="kn">import</span> <span class="n">ExpertKnowledgeOperator</span></tt>
+               class="code sev- "><tt><i>16</i> <span class="kn">from</span> <span class="nn">rulekit.params</span> <span class="kn">import</span> <span class="p">(</span><span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">,</span> <span class="n">ContrastSetModelParams</span><span class="p">,</span></tt>
             </div>
             <div id="l17"
-               class="code sev- "><tt><i>17</i> <span class="kn">from</span> <span class="nn">rulekit._problem_types</span> <span class="kn">import</span> <span class="n">ProblemType</span></tt>
+               class="code sev- "><tt><i>17</i>                             <span class="n">ExpertModelParams</span><span class="p">,</span> <span class="n">Measures</span><span class="p">,</span> <span class="n">ModelsParams</span><span class="p">)</span></tt>
             </div>
             <div id="l18"
-               class="code sev- "><tt><i>18</i> <span class="kn">from</span> <span class="nn">rulekit.params</span> <span class="kn">import</span> <span class="n">ContrastSetModelParams</span></tt>
+               class="code sev- "><tt><i>18</i> <span class="kn">from</span> <span class="nn">rulekit.rules</span> <span class="kn">import</span> <span class="n">RegressionRule</span><span class="p">,</span> <span class="n">RuleSet</span></tt>
             </div>
             <div id="l19"
-               class="code sev- "><tt><i>19</i> <span class="kn">from</span> <span class="nn">rulekit.params</span> <span class="kn">import</span> <span class="n">DEFAULT_PARAMS_VALUE</span></tt>
+               class="code sev- "><tt><i>19</i> &nbsp;</tt>
             </div>
             <div id="l20"
-               class="code sev- "><tt><i>20</i> <span class="kn">from</span> <span class="nn">rulekit.params</span> <span class="kn">import</span> <span class="n">ExpertModelParams</span></tt>
+               class="code sev- "><tt><i>20</i> &nbsp;</tt>
             </div>
             <div id="l21"
-               class="code sev- "><tt><i>21</i> <span class="kn">from</span> <span class="nn">rulekit.params</span> <span class="kn">import</span> <span class="n">Measures</span></tt>
+               class="code sev- "><tt><i>21</i> <span class="k">class</span> <span class="nc">_RegressionModelParams</span><span class="p">(</span><span class="n">ModelsParams</span><span class="p">):</span></tt>
             </div>
             <div id="l22"
-               class="code sev- "><tt><i>22</i> <span class="kn">from</span> <span class="nn">rulekit.params</span> <span class="kn">import</span> <span class="n">ModelsParams</span></tt>
+               class="code sev- "><tt><i>22</i>     <span class="n">mean_based_regression</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;mean_based_regression&quot;</span><span class="p">]</span></tt>
             </div>
             <div id="l23"
-               class="code sev- "><tt><i>23</i> <span class="kn">from</span> <span class="nn">rulekit.rules</span> <span class="kn">import</span> <span class="n">RegressionRule</span></tt>
+               class="code sev- "><tt><i>23</i> &nbsp;</tt>
             </div>
             <div id="l24"
-               class="code sev- "><tt><i>24</i> <span class="kn">from</span> <span class="nn">rulekit.rules</span> <span class="kn">import</span> <span class="n">RuleSet</span></tt>
+               class="code sev- "><tt><i>24</i> &nbsp;</tt>
             </div>
             <div id="l25"
-               class="code sev- "><tt><i>25</i> &nbsp;</tt>
+               class="code sev- "><tt><i>25</i> <span class="k">class</span> <span class="nc">_RegressionExpertModelParams</span><span class="p">(</span><span class="n">_RegressionModelParams</span><span class="p">,</span> <span class="n">ExpertModelParams</span><span class="p">):</span></tt>
             </div>
             <div id="l26"
-               class="code sev- "><tt><i>26</i> &nbsp;</tt>
+               class="code sev- "><tt><i>26</i>     <span class="k">pass</span></tt>
             </div>
             <div id="l27"
-               class="code sev- "><tt><i>27</i> <span class="k">class</span> <span class="nc">_RegressionModelParams</span><span class="p">(</span><span class="n">ModelsParams</span><span class="p">):</span></tt>
+               class="code sev- "><tt><i>27</i> &nbsp;</tt>
             </div>
             <div id="l28"
-               class="code sev- "><tt><i>28</i>     <span class="n">mean_based_regression</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;mean_based_regression&#39;</span><span class="p">]</span></tt>
+               class="code sev- "><tt><i>28</i> &nbsp;</tt>
             </div>
             <div id="l29"
-               class="code sev- "><tt><i>29</i> &nbsp;</tt>
+               class="code sev- "><tt><i>29</i> <span class="k">class</span> <span class="nc">RuleRegressor</span><span class="p">(</span><span class="n">BaseOperator</span><span class="p">):</span></tt>
             </div>
             <div id="l30"
-               class="code sev- "><tt><i>30</i> &nbsp;</tt>
+               class="code sev- "><tt><i>30</i> <span class="w">    </span><span class="sd">&quot;&quot;&quot;Regression model.&quot;&quot;&quot;</span></tt>
             </div>
             <div id="l31"
-               class="code sev- "><tt><i>31</i> <span class="k">class</span> <span class="nc">_RegressionExpertModelParams</span><span class="p">(</span><span class="n">_RegressionModelParams</span><span class="p">,</span> <span class="n">ExpertModelParams</span><span class="p">):</span></tt>
+               class="code sev- "><tt><i>31</i> &nbsp;</tt>
             </div>
             <div id="l32"
-               class="code sev- "><tt><i>32</i>     <span class="k">pass</span></tt>
+               class="code sev- "><tt><i>32</i>     <span class="n">__params_class__</span> <span class="o">=</span> <span class="n">_RegressionModelParams</span></tt>
             </div>
             <div id="l33"
                class="code sev- "><tt><i>33</i> &nbsp;</tt>
             </div>
             <div id="l34"
-               class="code sev- "><tt><i>34</i> &nbsp;</tt>
+               class="code sev- "><tt><i>34</i>     <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span>  <span class="c1"># pylint: disable=too-many-arguments</span></tt>
             </div>
             <div id="l35"
-               class="code sev- "><tt><i>35</i> <span class="k">class</span> <span class="nc">RuleRegressor</span><span class="p">(</span><span class="n">BaseOperator</span><span class="p">):</span></tt>
+               class="code sev- "><tt><i>35</i>         <span class="bp">self</span><span class="p">,</span></tt>
             </div>
             <div id="l36"
-               class="code sev- "><tt><i>36</i> <span class="w">    </span><span class="sd">&quot;&quot;&quot;Regression model.&quot;&quot;&quot;</span></tt>
+               class="code sev- "><tt><i>36</i>         <span class="n">minsupp_new</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;minsupp_new&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l37"
-               class="code sev- "><tt><i>37</i> &nbsp;</tt>
+               class="code sev- "><tt><i>37</i>         <span class="n">induction_measure</span><span class="p">:</span> <span class="n">Measures</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;induction_measure&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l38"
-               class="code sev- "><tt><i>38</i>     <span class="n">__params_class__</span> <span class="o">=</span> <span class="n">_RegressionModelParams</span></tt>
+               class="code sev- "><tt><i>38</i>         <span class="n">pruning_measure</span><span class="p">:</span> <span class="n">Union</span><span class="p">[</span><span class="n">Measures</span><span class="p">,</span> <span class="nb">str</span><span class="p">]</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;pruning_measure&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l39"
-               class="code sev- "><tt><i>39</i> &nbsp;</tt>
+               class="code sev- "><tt><i>39</i>         <span class="n">voting_measure</span><span class="p">:</span> <span class="n">Measures</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;voting_measure&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l40"
-               class="code sev- "><tt><i>40</i>     <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span>  <span class="c1"># pylint: disable=too-many-arguments</span></tt>
+               class="code sev- "><tt><i>40</i>         <span class="n">max_growing</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;max_growing&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l41"
-               class="code sev- "><tt><i>41</i>         <span class="bp">self</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>41</i>         <span class="n">enable_pruning</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;enable_pruning&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l42"
-               class="code sev- "><tt><i>42</i>         <span class="n">minsupp_new</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;minsupp_new&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>42</i>         <span class="n">ignore_missing</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;ignore_missing&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l43"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (80 > 79 characters)</li>
-               
-               </ul><tt><i>43</i>         <span class="n">induction_measure</span><span class="p">:</span> <span class="n">Measures</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;induction_measure&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>43</i>         <span class="n">max_uncovered_fraction</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;max_uncovered_fraction&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l44"
-               class="code sev- "><tt><i>44</i>         <span class="n">pruning_measure</span><span class="p">:</span> <span class="n">Union</span><span class="p">[</span><span class="n">Measures</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>44</i>         <span class="n">select_best_candidate</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;select_best_candidate&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l45"
-               class="code sev- "><tt><i>45</i>                                <span class="nb">str</span><span class="p">]</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;pruning_measure&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>45</i>         <span class="n">complementary_conditions</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span></tt>
             </div>
             <div id="l46"
-               class="code sev- "><tt><i>46</i>         <span class="n">voting_measure</span><span class="p">:</span> <span class="n">Measures</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;voting_measure&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>46</i>             <span class="s2">&quot;complementary_conditions&quot;</span></tt>
             </div>
             <div id="l47"
-               class="code sev- "><tt><i>47</i>         <span class="n">max_growing</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;max_growing&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>47</i>         <span class="p">],</span></tt>
             </div>
             <div id="l48"
-               class="code sev- "><tt><i>48</i>         <span class="n">enable_pruning</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;enable_pruning&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>48</i>         <span class="n">mean_based_regression</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;mean_based_regression&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l49"
-               class="code sev- "><tt><i>49</i>         <span class="n">ignore_missing</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;ignore_missing&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>49</i>         <span class="n">max_rule_count</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;max_rule_count&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l50"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (87 > 79 characters)</li>
-               
-               </ul><tt><i>50</i>         <span class="n">max_uncovered_fraction</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;max_uncovered_fraction&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>50</i>     <span class="p">):</span></tt>
             </div>
             <div id="l51"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (84 > 79 characters)</li>
-               
-               </ul><tt><i>51</i>         <span class="n">select_best_candidate</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;select_best_candidate&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>51</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;</span></tt>
             </div>
             <div id="l52"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (90 > 79 characters)</li>
-               
-               </ul><tt><i>52</i>         <span class="n">complementary_conditions</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;complementary_conditions&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>52</i> <span class="sd">        Parameters</span></tt>
             </div>
             <div id="l53"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (84 > 79 characters)</li>
-               
-               </ul><tt><i>53</i>         <span class="n">mean_based_regression</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;mean_based_regression&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>53</i> <span class="sd">        ----------</span></tt>
             </div>
             <div id="l54"
-               class="code sev- "><tt><i>54</i>         <span class="n">max_rule_count</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;max_rule_count&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>54</i> <span class="sd">        minsupp_new : float = 5.0</span></tt>
             </div>
             <div id="l55"
-               class="code sev- "><tt><i>55</i>     <span class="p">):</span></tt>
+               class="code sev- "><tt><i>55</i> <span class="sd">            a minimum number (or fraction, if value &lt; 1.0) of previously uncovered</span></tt>
             </div>
             <div id="l56"
-               class="code sev- "><tt><i>56</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;</span></tt>
+               class="code sev- "><tt><i>56</i> <span class="sd">            examples to be covered by a new rule (positive examples for classification</span></tt>
             </div>
             <div id="l57"
-               class="code sev- "><tt><i>57</i> <span class="sd">        Parameters</span></tt>
+               class="code sev- "><tt><i>57</i> <span class="sd">            problems); default: 5,</span></tt>
             </div>
             <div id="l58"
-               class="code sev- "><tt><i>58</i> <span class="sd">        ----------</span></tt>
+               class="code sev- "><tt><i>58</i> <span class="sd">        induction_measure : :class:`rulekit.params.Measures` = \</span></tt>
             </div>
             <div id="l59"
-               class="code sev- "><tt><i>59</i> <span class="sd">        minsupp_new : float = 5.0</span></tt>
+               class="code sev- "><tt><i>59</i> <span class="sd">            :class:`rulekit.params.Measures.Correlation`</span></tt>
             </div>
             <div id="l60"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (91 > 79 characters)</li>
-               
-               </ul><tt><i>60</i> <span class="sd">            a minimum number (or fraction, if value &lt; 1.0) of previously uncovered examples</span></tt>
+               class="code sev- "><tt><i>60</i> <span class="sd">            measure used during induction; default measure is correlation</span></tt>
             </div>
             <div id="l61"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (101 > 79 characters)</li>
-               
-               </ul><tt><i>61</i> <span class="sd">             to be covered by a new rule (positive examples for classification problems); default: 5,</span></tt>
+               class="code sev- "><tt><i>61</i> <span class="sd">        pruning_measure : Union[:class:`rulekit.params.Measures`, str] = \</span></tt>
             </div>
             <div id="l62"
-               class="code sev- "><tt><i>62</i> <span class="sd">        induction_measure : :class:`rulekit.params.Measures` = \</span></tt>
+               class="code sev- "><tt><i>62</i> <span class="sd">            :class:`rulekit.params.Measures.Correlation`</span></tt>
             </div>
             <div id="l63"
-               class="code sev- "><tt><i>63</i> <span class="sd">            :class:`rulekit.params.Measures.Correlation`</span></tt>
+               class="code sev- "><tt><i>63</i> <span class="sd">            measure used during pruning. Could be user defined (string), for example</span></tt>
             </div>
             <div id="l64"
-               class="code sev- "><tt><i>64</i> <span class="sd">            measure used during induction; default measure is correlation</span></tt>
+               class="code sev- "><tt><i>64</i> <span class="sd">             :code:`2 * p / n`; default measure is correlation</span></tt>
             </div>
             <div id="l65"
-               class="code sev- "><tt><i>65</i> <span class="sd">        pruning_measure : Union[:class:`rulekit.params.Measures`, str] = \</span></tt>
+               class="code sev- "><tt><i>65</i> <span class="sd">        voting_measure : :class:`rulekit.params.Measures` = \</span></tt>
             </div>
             <div id="l66"
                class="code sev- "><tt><i>66</i> <span class="sd">            :class:`rulekit.params.Measures.Correlation`</span></tt>
             </div>
             <div id="l67"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (84 > 79 characters)</li>
-               
-               </ul><tt><i>67</i> <span class="sd">            measure used during pruning. Could be user defined (string), for example</span></tt>
+               class="code sev- "><tt><i>67</i> <span class="sd">            measure used during voting; default measure is correlation</span></tt>
             </div>
             <div id="l68"
-               class="code sev- "><tt><i>68</i> <span class="sd">             :code:`2 * p / n`; default measure is correlation</span></tt>
+               class="code sev- "><tt><i>68</i> <span class="sd">        max_growing : int = 0.0</span></tt>
             </div>
             <div id="l69"
-               class="code sev- "><tt><i>69</i> <span class="sd">        voting_measure : :class:`rulekit.params.Measures` = \</span></tt>
+               class="code sev- "><tt><i>69</i> <span class="sd">            non-negative integer representing maximum number of conditions which can be</span></tt>
             </div>
             <div id="l70"
-               class="code sev- "><tt><i>70</i> <span class="sd">            :class:`rulekit.params.Measures.Correlation`</span></tt>
+               class="code sev- "><tt><i>70</i> <span class="sd">            added to the rule in the growing phase (use this parameter for large</span></tt>
             </div>
             <div id="l71"
-               class="code sev- "><tt><i>71</i> <span class="sd">            measure used during voting; default measure is correlation</span></tt>
+               class="code sev- "><tt><i>71</i> <span class="sd">            datasets if execution time is prohibitive); 0 indicates no limit; default: 0</span></tt>
             </div>
             <div id="l72"
-               class="code sev- "><tt><i>72</i> <span class="sd">        max_growing : int = 0.0</span></tt>
+               class="code sev- "><tt><i>72</i> <span class="sd">        enable_pruning : bool = True</span></tt>
             </div>
             <div id="l73"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (96 > 79 characters)</li>
-               
-               </ul><tt><i>73</i> <span class="sd">            non-negative integer representing maximum number of conditions which can be added to</span></tt>
+               class="code sev- "><tt><i>73</i> <span class="sd">            enable or disable pruning, default is True.</span></tt>
             </div>
             <div id="l74"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (98 > 79 characters)</li>
-               
-               </ul><tt><i>74</i> <span class="sd">            the rule in the growing phase (use this parameter for large datasets if execution time</span></tt>
+               class="code sev- "><tt><i>74</i> <span class="sd">        ignore_missing : bool = False</span></tt>
             </div>
             <div id="l75"
-               class="code sev- "><tt><i>75</i> <span class="sd">            is prohibitive); 0 indicates no limit; default: 0,</span></tt>
+               class="code sev- "><tt><i>75</i> <span class="sd">            boolean telling whether missing values should be ignored (by default, a</span></tt>
             </div>
             <div id="l76"
-               class="code sev- "><tt><i>76</i> <span class="sd">        enable_pruning : bool = True</span></tt>
+               class="code sev- "><tt><i>76</i> <span class="sd">            missing value of given attribute is always considered as not fulfilling the</span></tt>
             </div>
             <div id="l77"
-               class="code sev- "><tt><i>77</i> <span class="sd">            enable or disable pruning, default is True.</span></tt>
+               class="code sev- "><tt><i>77</i> <span class="sd">            condition build upon that attribute); default: False.</span></tt>
             </div>
             <div id="l78"
-               class="code sev- "><tt><i>78</i> <span class="sd">        ignore_missing : bool = False</span></tt>
+               class="code sev- "><tt><i>78</i> <span class="sd">        max_uncovered_fraction : float = 0.0</span></tt>
             </div>
             <div id="l79"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (97 > 79 characters)</li>
-               
-               </ul><tt><i>79</i> <span class="sd">            boolean telling whether missing values should be ignored (by default, a missing value</span></tt>
+               class="code sev- "><tt><i>79</i> <span class="sd">            Floating-point number from [0,1] interval representing maximum fraction of</span></tt>
             </div>
             <div id="l80"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (99 > 79 characters)</li>
-               
-               </ul><tt><i>80</i> <span class="sd">            of given attribute is always considered as not fulfilling the condition build upon that</span></tt>
+               class="code sev- "><tt><i>80</i> <span class="sd">            examples that may remain uncovered by the rule set, default: 0.0.</span></tt>
             </div>
             <div id="l81"
-               class="code sev- "><tt><i>81</i> <span class="sd">            attribute); default: False.</span></tt>
+               class="code sev- "><tt><i>81</i> <span class="sd">        select_best_candidate : bool = False</span></tt>
             </div>
             <div id="l82"
-               class="code sev- "><tt><i>82</i> <span class="sd">        max_uncovered_fraction : float = 0.0</span></tt>
+               class="code sev- "><tt><i>82</i> <span class="sd">            Flag determining if best candidate should be selected from growing phase;</span></tt>
             </div>
             <div id="l83"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (95 > 79 characters)</li>
-               
-               </ul><tt><i>83</i> <span class="sd">            Floating-point number from [0,1] interval representing maximum fraction of examples</span></tt>
+               class="code sev- "><tt><i>83</i> <span class="sd">             default: False.</span></tt>
             </div>
             <div id="l84"
-               class="code sev- "><tt><i>84</i> <span class="sd">             that may remain uncovered by the rule set, default: 0.0.</span></tt>
+               class="code sev- "><tt><i>84</i> <span class="sd">        complementary_conditions : bool = False</span></tt>
             </div>
             <div id="l85"
-               class="code sev- "><tt><i>85</i> <span class="sd">        select_best_candidate : bool = False</span></tt>
+               class="code sev- "><tt><i>85</i> <span class="sd">            If enabled, complementary conditions in the form a = !{value} for nominal</span></tt>
             </div>
             <div id="l86"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (85 > 79 characters)</li>
-               
-               </ul><tt><i>86</i> <span class="sd">            Flag determining if best candidate should be selected from growing phase;</span></tt>
+               class="code sev- "><tt><i>86</i> <span class="sd">            attributes are supported.</span></tt>
             </div>
             <div id="l87"
-               class="code sev- "><tt><i>87</i> <span class="sd">             default: False.</span></tt>
+               class="code sev- "><tt><i>87</i> <span class="sd">        mean_based_regression : bool = True</span></tt>
             </div>
             <div id="l88"
-               class="code sev- "><tt><i>88</i> <span class="sd">        complementary_conditions : bool = False</span></tt>
+               class="code sev- "><tt><i>88</i> <span class="sd">            Enable fast induction of mean-based regression rules instead of default</span></tt>
             </div>
             <div id="l89"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (96 > 79 characters)</li>
-               
-               </ul><tt><i>89</i> <span class="sd">            If enabled, complementary conditions in the form a = !{value} for nominal attributes</span></tt>
+               class="code sev- "><tt><i>89</i> <span class="sd">            median-based.</span></tt>
             </div>
             <div id="l90"
-               class="code sev- "><tt><i>90</i> <span class="sd">            are supported.</span></tt>
+               class="code sev- "><tt><i>90</i> <span class="sd">        max_rule_count : int = 0</span></tt>
             </div>
             <div id="l91"
-               class="code sev- "><tt><i>91</i> <span class="sd">        mean_based_regression : bool = True</span></tt>
+               class="code sev- "><tt><i>91</i> <span class="sd">            Maximum number of rules to be generated; 0 indicates no limit. Default: 0</span></tt>
             </div>
             <div id="l92"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (97 > 79 characters)</li>
-               
-               </ul><tt><i>92</i> <span class="sd">            Enable fast induction of mean-based regression rules instead of default median-based.</span></tt>
+               class="code sev- "><tt><i>92</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
             </div>
             <div id="l93"
-               class="code sev- "><tt><i>93</i> <span class="sd">        max_rule_count : int = 0</span></tt>
+               class="code sev- "><tt><i>93</i>         <span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span></tt>
             </div>
             <div id="l94"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (92 > 79 characters)</li>
-               
-               </ul><tt><i>94</i> <span class="sd">            Maximum number of rules to be generated (for classification data sets it applies</span></tt>
+               class="code sev- "><tt><i>94</i>             <span class="n">minsupp_new</span><span class="o">=</span><span class="n">minsupp_new</span><span class="p">,</span></tt>
             </div>
             <div id="l95"
-               class="code sev- "><tt><i>95</i> <span class="sd">             to a single class); 0 indicates no limit.</span></tt>
+               class="code sev- "><tt><i>95</i>             <span class="n">induction_measure</span><span class="o">=</span><span class="n">induction_measure</span><span class="p">,</span></tt>
             </div>
             <div id="l96"
-               class="code sev- "><tt><i>96</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
+               class="code sev- "><tt><i>96</i>             <span class="n">pruning_measure</span><span class="o">=</span><span class="n">pruning_measure</span><span class="p">,</span></tt>
             </div>
             <div id="l97"
-               class="code sev- "><tt><i>97</i>         <span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span></tt>
+               class="code sev- "><tt><i>97</i>             <span class="n">voting_measure</span><span class="o">=</span><span class="n">voting_measure</span><span class="p">,</span></tt>
             </div>
             <div id="l98"
-               class="code sev- "><tt><i>98</i>             <span class="n">minsupp_new</span><span class="o">=</span><span class="n">minsupp_new</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>98</i>             <span class="n">max_growing</span><span class="o">=</span><span class="n">max_growing</span><span class="p">,</span></tt>
             </div>
             <div id="l99"
-               class="code sev- "><tt><i>99</i>             <span class="n">induction_measure</span><span class="o">=</span><span class="n">induction_measure</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>99</i>             <span class="n">enable_pruning</span><span class="o">=</span><span class="n">enable_pruning</span><span class="p">,</span></tt>
             </div>
             <div id="l100"
-               class="code sev- "><tt><i>100</i>             <span class="n">pruning_measure</span><span class="o">=</span><span class="n">pruning_measure</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>100</i>             <span class="n">ignore_missing</span><span class="o">=</span><span class="n">ignore_missing</span><span class="p">,</span></tt>
             </div>
             <div id="l101"
-               class="code sev- "><tt><i>101</i>             <span class="n">voting_measure</span><span class="o">=</span><span class="n">voting_measure</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>101</i>             <span class="n">max_uncovered_fraction</span><span class="o">=</span><span class="n">max_uncovered_fraction</span><span class="p">,</span></tt>
             </div>
             <div id="l102"
-               class="code sev- "><tt><i>102</i>             <span class="n">max_growing</span><span class="o">=</span><span class="n">max_growing</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>102</i>             <span class="n">select_best_candidate</span><span class="o">=</span><span class="n">select_best_candidate</span><span class="p">,</span></tt>
             </div>
             <div id="l103"
-               class="code sev- "><tt><i>103</i>             <span class="n">enable_pruning</span><span class="o">=</span><span class="n">enable_pruning</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>103</i>             <span class="n">complementary_conditions</span><span class="o">=</span><span class="n">complementary_conditions</span><span class="p">,</span></tt>
             </div>
             <div id="l104"
-               class="code sev- "><tt><i>104</i>             <span class="n">ignore_missing</span><span class="o">=</span><span class="n">ignore_missing</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>104</i>             <span class="n">mean_based_regression</span><span class="o">=</span><span class="n">mean_based_regression</span><span class="p">,</span></tt>
             </div>
             <div id="l105"
-               class="code sev- "><tt><i>105</i>             <span class="n">max_uncovered_fraction</span><span class="o">=</span><span class="n">max_uncovered_fraction</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>105</i>             <span class="n">max_rule_count</span><span class="o">=</span><span class="n">max_rule_count</span><span class="p">,</span></tt>
             </div>
             <div id="l106"
-               class="code sev- "><tt><i>106</i>             <span class="n">select_best_candidate</span><span class="o">=</span><span class="n">select_best_candidate</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>106</i>         <span class="p">)</span></tt>
             </div>
             <div id="l107"
-               class="code sev- "><tt><i>107</i>             <span class="n">complementary_conditions</span><span class="o">=</span><span class="n">complementary_conditions</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>107</i>         <span class="bp">self</span><span class="o">.</span><span class="n">model</span><span class="p">:</span> <span class="n">RuleSet</span><span class="p">[</span><span class="n">RegressionRule</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span></tt>
             </div>
             <div id="l108"
-               class="code sev- "><tt><i>108</i>             <span class="n">mean_based_regression</span><span class="o">=</span><span class="n">mean_based_regression</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>108</i> &nbsp;</tt>
             </div>
             <div id="l109"
-               class="code sev- "><tt><i>109</i>             <span class="n">max_rule_count</span><span class="o">=</span><span class="n">max_rule_count</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>109</i>     <span class="k">def</span> <span class="nf">_validate_labels</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">labels</span><span class="p">:</span> <span class="n">Data</span><span class="p">):</span></tt>
             </div>
             <div id="l110"
-               class="code sev- "><tt><i>110</i>         <span class="p">)</span></tt>
+               class="code sev- "><tt><i>110</i>         <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">labels</span><span class="p">,</span> <span class="p">(</span><span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">,</span> <span class="n">pd</span><span class="o">.</span><span class="n">Series</span><span class="p">)):</span></tt>
             </div>
             <div id="l111"
-               class="code sev- "><tt><i>111</i>         <span class="bp">self</span><span class="o">.</span><span class="n">model</span><span class="p">:</span> <span class="n">RuleSet</span><span class="p">[</span><span class="n">RegressionRule</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span></tt>
+               class="code sev- "><tt><i>111</i>             <span class="n">first_label</span> <span class="o">=</span> <span class="n">labels</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span></tt>
             </div>
             <div id="l112"
-               class="code sev- "><tt><i>112</i> &nbsp;</tt>
+               class="code sev- "><tt><i>112</i>         <span class="k">else</span><span class="p">:</span></tt>
             </div>
             <div id="l113"
-               class="code sev- "><tt><i>113</i>     <span class="k">def</span> <span class="nf">_validate_labels</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">labels</span><span class="p">:</span> <span class="n">Data</span><span class="p">):</span></tt>
+               class="code sev- "><tt><i>113</i>             <span class="n">first_label</span> <span class="o">=</span> <span class="n">labels</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span></tt>
             </div>
             <div id="l114"
-               class="code sev- "><tt><i>114</i>         <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">labels</span><span class="p">,</span> <span class="p">(</span><span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">,</span> <span class="n">pd</span><span class="o">.</span><span class="n">Series</span><span class="p">)):</span></tt>
+               class="code sev- "><tt><i>114</i>         <span class="k">if</span> <span class="ow">not</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">first_label</span><span class="p">,</span> <span class="n">Number</span><span class="p">):</span></tt>
             </div>
             <div id="l115"
-               class="code sev- "><tt><i>115</i>             <span class="n">first_label</span> <span class="o">=</span> <span class="n">labels</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span></tt>
+               class="code sev- "><tt><i>115</i>             <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span></tt>
             </div>
             <div id="l116"
-               class="code sev- "><tt><i>116</i>         <span class="k">else</span><span class="p">:</span></tt>
+               class="code sev- "><tt><i>116</i>                 <span class="sa">f</span><span class="s2">&quot;</span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="vm">__class__</span><span class="o">.</span><span class="vm">__name__</span><span class="si">}</span><span class="s2"> requires lables values to be numeric&quot;</span></tt>
             </div>
             <div id="l117"
-               class="code sev- "><tt><i>117</i>             <span class="n">first_label</span> <span class="o">=</span> <span class="n">labels</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span></tt>
+               class="code sev- "><tt><i>117</i>             <span class="p">)</span></tt>
             </div>
             <div id="l118"
-               class="code sev- "><tt><i>118</i>         <span class="k">if</span> <span class="ow">not</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">first_label</span><span class="p">,</span> <span class="n">Number</span><span class="p">):</span></tt>
+               class="code sev- "><tt><i>118</i> &nbsp;</tt>
             </div>
             <div id="l119"
-               class="code sev- "><tt><i>119</i>             <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span></tt>
+               class="code sev- "><tt><i>119</i>     <span class="k">def</span> <span class="nf">fit</span><span class="p">(</span>  <span class="c1"># pylint: disable=arguments-differ</span></tt>
             </div>
             <div id="l120"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (81 > 79 characters)</li>
-               
-               </ul><tt><i>120</i>                 <span class="sa">f</span><span class="s1">&#39;</span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="vm">__class__</span><span class="o">.</span><span class="vm">__name__</span><span class="si">}</span><span class="s1"> requires lables values to be numeric&#39;</span></tt>
+               class="code sev- "><tt><i>120</i>         <span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">:</span> <span class="n">Data</span><span class="p">,</span> <span class="n">labels</span><span class="p">:</span> <span class="n">Data</span></tt>
             </div>
             <div id="l121"
-               class="code sev- "><tt><i>121</i>             <span class="p">)</span></tt>
+               class="code sev- "><tt><i>121</i>     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">RuleRegressor</span><span class="p">:</span></tt>
             </div>
             <div id="l122"
-               class="code sev- "><tt><i>122</i> &nbsp;</tt>
+               class="code sev- "><tt><i>122</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Train model on given dataset.</span></tt>
             </div>
             <div id="l123"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (99 > 79 characters)</li>
-               
-               </ul><tt><i>123</i>     <span class="k">def</span> <span class="nf">fit</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">:</span> <span class="n">Data</span><span class="p">,</span> <span class="n">labels</span><span class="p">:</span> <span class="n">Data</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">RuleRegressor</span><span class="p">:</span>  <span class="c1"># pylint: disable=arguments-differ</span></tt>
+               class="code sev- "><tt><i>123</i> &nbsp;</tt>
             </div>
             <div id="l124"
-               class="code sev- "><tt><i>124</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Train model on given dataset.</span></tt>
+               class="code sev- "><tt><i>124</i> <span class="sd">        Parameters</span></tt>
             </div>
             <div id="l125"
-               class="code sev- "><tt><i>125</i> &nbsp;</tt>
+               class="code sev- "><tt><i>125</i> <span class="sd">        ----------</span></tt>
             </div>
             <div id="l126"
-               class="code sev- "><tt><i>126</i> <span class="sd">        Parameters</span></tt>
+               class="code sev- "><tt><i>126</i> <span class="sd">        values : :class:`rulekit.operator.Data`</span></tt>
             </div>
             <div id="l127"
-               class="code sev- "><tt><i>127</i> <span class="sd">        ----------</span></tt>
+               class="code sev- "><tt><i>127</i> <span class="sd">            attributes</span></tt>
             </div>
             <div id="l128"
-               class="code sev- "><tt><i>128</i> <span class="sd">        values : :class:`rulekit.operator.Data`</span></tt>
+               class="code sev- "><tt><i>128</i> <span class="sd">        labels : :class:`rulekit.operator.Data`</span></tt>
             </div>
             <div id="l129"
-               class="code sev- "><tt><i>129</i> <span class="sd">            attributes</span></tt>
+               class="code sev- "><tt><i>129</i> <span class="sd">            target values</span></tt>
             </div>
             <div id="l130"
-               class="code sev- "><tt><i>130</i> <span class="sd">        labels : :class:`rulekit.operator.Data`</span></tt>
+               class="code sev- "><tt><i>130</i> <span class="sd">        Returns</span></tt>
             </div>
             <div id="l131"
-               class="code sev- "><tt><i>131</i> <span class="sd">            target values</span></tt>
+               class="code sev- "><tt><i>131</i> <span class="sd">        -------</span></tt>
             </div>
             <div id="l132"
-               class="code sev- "><tt><i>132</i> <span class="sd">        Returns</span></tt>
+               class="code sev- "><tt><i>132</i> <span class="sd">        self : RuleRegressor</span></tt>
             </div>
             <div id="l133"
-               class="code sev- "><tt><i>133</i> <span class="sd">        -------</span></tt>
+               class="code sev- "><tt><i>133</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
             </div>
             <div id="l134"
-               class="code sev- "><tt><i>134</i> <span class="sd">        self : RuleRegressor</span></tt>
+               class="code sev- "><tt><i>134</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_validate_labels</span><span class="p">(</span><span class="n">labels</span><span class="p">)</span></tt>
             </div>
             <div id="l135"
-               class="code sev- "><tt><i>135</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
+               class="code sev- "><tt><i>135</i>         <span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">values</span><span class="p">,</span> <span class="n">labels</span><span class="p">)</span></tt>
             </div>
             <div id="l136"
-               class="code sev- "><tt><i>136</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_validate_labels</span><span class="p">(</span><span class="n">labels</span><span class="p">)</span></tt>
+               class="code sev- "><tt><i>136</i>         <span class="k">return</span> <span class="bp">self</span></tt>
             </div>
             <div id="l137"
-               class="code sev- "><tt><i>137</i>         <span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">values</span><span class="p">,</span> <span class="n">labels</span><span class="p">)</span></tt>
+               class="code sev- "><tt><i>137</i> &nbsp;</tt>
             </div>
             <div id="l138"
-               class="code sev- "><tt><i>138</i>         <span class="k">return</span> <span class="bp">self</span></tt>
+               class="code sev- "><tt><i>138</i>     <span class="k">def</span> <span class="nf">predict</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">:</span> <span class="n">Data</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">:</span></tt>
             </div>
             <div id="l139"
-               class="code sev- "><tt><i>139</i> &nbsp;</tt>
+               class="code sev- "><tt><i>139</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Perform prediction and returns predicted values.</span></tt>
             </div>
             <div id="l140"
-               class="code sev- "><tt><i>140</i>     <span class="k">def</span> <span class="nf">predict</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">:</span> <span class="n">Data</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">:</span></tt>
+               class="code sev- "><tt><i>140</i> &nbsp;</tt>
             </div>
             <div id="l141"
-               class="code sev- "><tt><i>141</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Perform prediction and returns predicted values.</span></tt>
+               class="code sev- "><tt><i>141</i> <span class="sd">        Parameters</span></tt>
             </div>
             <div id="l142"
-               class="code sev- "><tt><i>142</i> &nbsp;</tt>
+               class="code sev- "><tt><i>142</i> <span class="sd">        ----------</span></tt>
             </div>
             <div id="l143"
-               class="code sev- "><tt><i>143</i> <span class="sd">        Parameters</span></tt>
+               class="code sev- "><tt><i>143</i> <span class="sd">        values : :class:`rulekit.operator.Data`</span></tt>
             </div>
             <div id="l144"
-               class="code sev- "><tt><i>144</i> <span class="sd">        ----------</span></tt>
+               class="code sev- "><tt><i>144</i> <span class="sd">            attributes</span></tt>
             </div>
             <div id="l145"
-               class="code sev- "><tt><i>145</i> <span class="sd">        values : :class:`rulekit.operator.Data`</span></tt>
+               class="code sev- "><tt><i>145</i> &nbsp;</tt>
             </div>
             <div id="l146"
-               class="code sev- "><tt><i>146</i> <span class="sd">            attributes</span></tt>
+               class="code sev- "><tt><i>146</i> <span class="sd">        Returns</span></tt>
             </div>
             <div id="l147"
-               class="code sev- "><tt><i>147</i> &nbsp;</tt>
+               class="code sev- "><tt><i>147</i> <span class="sd">        -------</span></tt>
             </div>
             <div id="l148"
-               class="code sev- "><tt><i>148</i> <span class="sd">        Returns</span></tt>
+               class="code sev- "><tt><i>148</i> <span class="sd">        result : np.ndarray</span></tt>
             </div>
             <div id="l149"
-               class="code sev- "><tt><i>149</i> <span class="sd">        -------</span></tt>
+               class="code sev- "><tt><i>149</i> <span class="sd">            predicted values</span></tt>
             </div>
             <div id="l150"
-               class="code sev- "><tt><i>150</i> <span class="sd">        result : np.ndarray</span></tt>
+               class="code sev- "><tt><i>150</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
             </div>
             <div id="l151"
-               class="code sev- "><tt><i>151</i> <span class="sd">            predicted values</span></tt>
+               class="code sev- "><tt><i>151</i>         <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_map_result</span><span class="p">(</span><span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">values</span><span class="p">))</span></tt>
             </div>
             <div id="l152"
-               class="code sev- "><tt><i>152</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
+               class="code sev- "><tt><i>152</i> &nbsp;</tt>
             </div>
             <div id="l153"
-               class="code sev- "><tt><i>153</i>         <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_map_result</span><span class="p">(</span><span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">values</span><span class="p">))</span></tt>
+               class="code sev- "><tt><i>153</i>     <span class="k">def</span> <span class="nf">score</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">:</span> <span class="n">Data</span><span class="p">,</span> <span class="n">labels</span><span class="p">:</span> <span class="n">Data</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">float</span><span class="p">:</span></tt>
             </div>
             <div id="l154"
-               class="code sev- "><tt><i>154</i> &nbsp;</tt>
+               class="code sev- "><tt><i>154</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Return the coefficient of determination R2 of the prediction</span></tt>
             </div>
             <div id="l155"
-               class="code sev- "><tt><i>155</i>     <span class="k">def</span> <span class="nf">score</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">:</span> <span class="n">Data</span><span class="p">,</span> <span class="n">labels</span><span class="p">:</span> <span class="n">Data</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">float</span><span class="p">:</span></tt>
+               class="code sev- "><tt><i>155</i> &nbsp;</tt>
             </div>
             <div id="l156"
-               class="code sev- "><tt><i>156</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Return the coefficient of determination R2 of the prediction</span></tt>
+               class="code sev- "><tt><i>156</i> <span class="sd">        Parameters</span></tt>
             </div>
             <div id="l157"
-               class="code sev- "><tt><i>157</i> &nbsp;</tt>
+               class="code sev- "><tt><i>157</i> <span class="sd">        ----------</span></tt>
             </div>
             <div id="l158"
-               class="code sev- "><tt><i>158</i> <span class="sd">        Parameters</span></tt>
+               class="code sev- "><tt><i>158</i> <span class="sd">        values : :class:`rulekit.operator.Data`</span></tt>
             </div>
             <div id="l159"
-               class="code sev- "><tt><i>159</i> <span class="sd">        ----------</span></tt>
+               class="code sev- "><tt><i>159</i> <span class="sd">            attributes</span></tt>
             </div>
             <div id="l160"
-               class="code sev- "><tt><i>160</i> <span class="sd">        values : :class:`rulekit.operator.Data`</span></tt>
+               class="code sev- "><tt><i>160</i> <span class="sd">        labels : :class:`rulekit.operator.Data`</span></tt>
             </div>
             <div id="l161"
-               class="code sev- "><tt><i>161</i> <span class="sd">            attributes</span></tt>
+               class="code sev- "><tt><i>161</i> <span class="sd">            true target values</span></tt>
             </div>
             <div id="l162"
-               class="code sev- "><tt><i>162</i> <span class="sd">        labels : :class:`rulekit.operator.Data`</span></tt>
+               class="code sev- "><tt><i>162</i> &nbsp;</tt>
             </div>
             <div id="l163"
-               class="code sev- "><tt><i>163</i> <span class="sd">            true target values</span></tt>
+               class="code sev- "><tt><i>163</i> <span class="sd">        Returns</span></tt>
             </div>
             <div id="l164"
-               class="code sev- "><tt><i>164</i> &nbsp;</tt>
+               class="code sev- "><tt><i>164</i> <span class="sd">        -------</span></tt>
             </div>
             <div id="l165"
-               class="code sev- "><tt><i>165</i> <span class="sd">        Returns</span></tt>
+               class="code sev- "><tt><i>165</i> <span class="sd">        score : float</span></tt>
             </div>
             <div id="l166"
-               class="code sev- "><tt><i>166</i> <span class="sd">        -------</span></tt>
+               class="code sev- "><tt><i>166</i> <span class="sd">            R2 of self.predict(values) wrt. labels.</span></tt>
             </div>
             <div id="l167"
-               class="code sev- "><tt><i>167</i> <span class="sd">        score : float</span></tt>
+               class="code sev- "><tt><i>167</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
             </div>
             <div id="l168"
-               class="code sev- "><tt><i>168</i> <span class="sd">            R2 of self.predict(values) wrt. labels.</span></tt>
+               class="code sev- "><tt><i>168</i>         <span class="n">predicted_labels</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">values</span><span class="p">)</span></tt>
             </div>
             <div id="l169"
-               class="code sev- "><tt><i>169</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
+               class="code sev- "><tt><i>169</i>         <span class="k">return</span> <span class="n">metrics</span><span class="o">.</span><span class="n">r2_score</span><span class="p">(</span><span class="n">labels</span><span class="p">,</span> <span class="n">predicted_labels</span><span class="p">)</span></tt>
             </div>
             <div id="l170"
-               class="code sev- "><tt><i>170</i>         <span class="n">predicted_labels</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">values</span><span class="p">)</span></tt>
+               class="code sev- "><tt><i>170</i> &nbsp;</tt>
             </div>
             <div id="l171"
-               class="code sev- "><tt><i>171</i>         <span class="k">return</span> <span class="n">metrics</span><span class="o">.</span><span class="n">r2_score</span><span class="p">(</span><span class="n">labels</span><span class="p">,</span> <span class="n">predicted_labels</span><span class="p">)</span></tt>
+               class="code sev- "><tt><i>171</i>     <span class="k">def</span> <span class="nf">_map_result</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">predicted_example_set</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">:</span></tt>
             </div>
             <div id="l172"
-               class="code sev- "><tt><i>172</i> &nbsp;</tt>
+               class="code sev- "><tt><i>172</i>         <span class="k">return</span> <span class="n">PredictionResultMapper</span><span class="o">.</span><span class="n">map_to_numerical</span><span class="p">(</span></tt>
             </div>
             <div id="l173"
-               class="code sev- "><tt><i>173</i>     <span class="k">def</span> <span class="nf">_map_result</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">predicted_example_set</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">:</span></tt>
+               class="code sev- "><tt><i>173</i>             <span class="n">predicted_example_set</span><span class="p">,</span> <span class="n">remap</span><span class="o">=</span><span class="kc">False</span></tt>
             </div>
             <div id="l174"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (90 > 79 characters)</li>
-               
-               </ul><tt><i>174</i>         <span class="k">return</span> <span class="n">PredictionResultMapper</span><span class="o">.</span><span class="n">map_to_numerical</span><span class="p">(</span><span class="n">predicted_example_set</span><span class="p">,</span> <span class="n">remap</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span></tt>
+               class="code sev- "><tt><i>174</i>         <span class="p">)</span></tt>
             </div>
             <div id="l175"
                class="code sev- "><tt><i>175</i> &nbsp;</tt>
@@ -749,276 +569,147 @@ <h1>
                class="code sev- "><tt><i>184</i> &nbsp;</tt>
             </div>
             <div id="l185"
-               class="code sev- "><tt><i>185</i>     <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span>   <span class="c1"># pylint: disable=too-many-arguments,too-many-locals</span></tt>
+               class="code sev- "><tt><i>185</i>     <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span>  <span class="c1"># pylint: disable=too-many-arguments,too-many-locals</span></tt>
             </div>
             <div id="l186"
                class="code sev- "><tt><i>186</i>         <span class="bp">self</span><span class="p">,</span></tt>
             </div>
             <div id="l187"
-               class="code sev- "><tt><i>187</i>         <span class="n">minsupp_new</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;minsupp_new&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>187</i>         <span class="n">minsupp_new</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;minsupp_new&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l188"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (80 > 79 characters)</li>
-               
-               </ul><tt><i>188</i>         <span class="n">induction_measure</span><span class="p">:</span> <span class="n">Measures</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;induction_measure&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>188</i>         <span class="n">induction_measure</span><span class="p">:</span> <span class="n">Measures</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;induction_measure&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l189"
-               class="code sev- "><tt><i>189</i>         <span class="n">pruning_measure</span><span class="p">:</span> <span class="n">Union</span><span class="p">[</span><span class="n">Measures</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>189</i>         <span class="n">pruning_measure</span><span class="p">:</span> <span class="n">Union</span><span class="p">[</span><span class="n">Measures</span><span class="p">,</span> <span class="nb">str</span><span class="p">]</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;pruning_measure&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l190"
-               class="code sev- "><tt><i>190</i>                                <span class="nb">str</span><span class="p">]</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;pruning_measure&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>190</i>         <span class="n">voting_measure</span><span class="p">:</span> <span class="n">Measures</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;voting_measure&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l191"
-               class="code sev- "><tt><i>191</i>         <span class="n">voting_measure</span><span class="p">:</span> <span class="n">Measures</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;voting_measure&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>191</i>         <span class="n">max_growing</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;max_growing&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l192"
-               class="code sev- "><tt><i>192</i>         <span class="n">max_growing</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;max_growing&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>192</i>         <span class="n">enable_pruning</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;enable_pruning&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l193"
-               class="code sev- "><tt><i>193</i>         <span class="n">enable_pruning</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;enable_pruning&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>193</i>         <span class="n">ignore_missing</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;ignore_missing&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l194"
-               class="code sev- "><tt><i>194</i>         <span class="n">ignore_missing</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;ignore_missing&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>194</i>         <span class="n">max_uncovered_fraction</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;max_uncovered_fraction&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l195"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (87 > 79 characters)</li>
-               
-               </ul><tt><i>195</i>         <span class="n">max_uncovered_fraction</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;max_uncovered_fraction&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>195</i>         <span class="n">select_best_candidate</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;select_best_candidate&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l196"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (84 > 79 characters)</li>
-               
-               </ul><tt><i>196</i>         <span class="n">select_best_candidate</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;select_best_candidate&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>196</i>         <span class="n">complementary_conditions</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span></tt>
             </div>
             <div id="l197"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (90 > 79 characters)</li>
-               
-               </ul><tt><i>197</i>         <span class="n">complementary_conditions</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;complementary_conditions&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>197</i>             <span class="s2">&quot;complementary_conditions&quot;</span></tt>
             </div>
             <div id="l198"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (84 > 79 characters)</li>
-               
-               </ul><tt><i>198</i>         <span class="n">mean_based_regression</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;mean_based_regression&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>198</i>         <span class="p">],</span></tt>
             </div>
             <div id="l199"
-               class="code sev- "><tt><i>199</i>         <span class="n">max_rule_count</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;max_rule_count&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>199</i>         <span class="n">mean_based_regression</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;mean_based_regression&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l200"
-               class="code sev- "><tt><i>200</i> &nbsp;</tt>
+               class="code sev- "><tt><i>200</i>         <span class="n">max_rule_count</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;max_rule_count&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l201"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (86 > 79 characters)</li>
-               
-               </ul><tt><i>201</i>         <span class="n">extend_using_preferred</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;extend_using_preferred&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>201</i>         <span class="n">extend_using_preferred</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;extend_using_preferred&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l202"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (86 > 79 characters)</li>
-               
-               </ul><tt><i>202</i>         <span class="n">extend_using_automatic</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;extend_using_automatic&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>202</i>         <span class="n">extend_using_automatic</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;extend_using_automatic&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l203"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (86 > 79 characters)</li>
-               
-               </ul><tt><i>203</i>         <span class="n">induce_using_preferred</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;induce_using_preferred&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>203</i>         <span class="n">induce_using_preferred</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;induce_using_preferred&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l204"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (86 > 79 characters)</li>
-               
-               </ul><tt><i>204</i>         <span class="n">induce_using_automatic</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;induce_using_automatic&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>204</i>         <span class="n">induce_using_automatic</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;induce_using_automatic&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l205"
                class="code sev- "><tt><i>205</i>         <span class="n">preferred_conditions_per_rule</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span></tt>
             </div>
             <div id="l206"
-               class="code sev- "><tt><i>206</i>             <span class="s1">&#39;preferred_conditions_per_rule&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>206</i>             <span class="s2">&quot;preferred_conditions_per_rule&quot;</span></tt>
             </div>
             <div id="l207"
-               class="code sev- "><tt><i>207</i>         <span class="n">preferred_attributes_per_rule</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span></tt>
+               class="code sev- "><tt><i>207</i>         <span class="p">],</span></tt>
             </div>
             <div id="l208"
-               class="code sev- "><tt><i>208</i>             <span class="s1">&#39;preferred_attributes_per_rule&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>208</i>         <span class="n">preferred_attributes_per_rule</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span></tt>
             </div>
             <div id="l209"
-               class="code sev- "><tt><i>209</i>     <span class="p">):</span></tt>
+               class="code sev- "><tt><i>209</i>             <span class="s2">&quot;preferred_attributes_per_rule&quot;</span></tt>
             </div>
             <div id="l210"
-               class="code sev- "><tt><i>210</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;</span></tt>
+               class="code sev- "><tt><i>210</i>         <span class="p">],</span></tt>
             </div>
             <div id="l211"
-               class="code sev- "><tt><i>211</i> <span class="sd">        Parameters</span></tt>
+               class="code sev- "><tt><i>211</i>     <span class="p">):</span></tt>
             </div>
             <div id="l212"
-               class="code sev- "><tt><i>212</i> <span class="sd">        ----------</span></tt>
+               class="code sev- "><tt><i>212</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;</span></tt>
             </div>
             <div id="l213"
-               class="code sev- "><tt><i>213</i> <span class="sd">        minsupp_new : float = 5.0</span></tt>
+               class="code sev- "><tt><i>213</i> <span class="sd">        Parameters</span></tt>
             </div>
             <div id="l214"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (91 > 79 characters)</li>
-               
-               </ul><tt><i>214</i> <span class="sd">            a minimum number (or fraction, if value &lt; 1.0) of previously uncovered examples</span></tt>
+               class="code sev- "><tt><i>214</i> <span class="sd">        ----------</span></tt>
             </div>
             <div id="l215"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (101 > 79 characters)</li>
-               
-               </ul><tt><i>215</i> <span class="sd">             to be covered by a new rule (positive examples for classification problems); default: 5,</span></tt>
+               class="code sev- "><tt><i>215</i> <span class="sd">        minsupp_new : float = 5.0</span></tt>
             </div>
             <div id="l216"
-               class="code sev- "><tt><i>216</i> <span class="sd">        induction_measure : :class:`rulekit.params.Measures` = \</span></tt>
+               class="code sev- "><tt><i>216</i> <span class="sd">            a minimum number (or fraction, if value &lt; 1.0) of previously uncovered</span></tt>
             </div>
             <div id="l217"
-               class="code sev- "><tt><i>217</i> <span class="sd">            :class:`rulekit.params.Measures.Correlation`</span></tt>
+               class="code sev- "><tt><i>217</i> <span class="sd">            examples  to be covered by a new rule (positive examples for classification</span></tt>
             </div>
             <div id="l218"
-               class="code sev- "><tt><i>218</i> <span class="sd">            measure used during induction; default measure is correlation</span></tt>
+               class="code sev- "><tt><i>218</i> <span class="sd">            problems); default: 5,</span></tt>
             </div>
             <div id="l219"
-               class="code sev- "><tt><i>219</i> <span class="sd">        pruning_measure : Union[:class:`rulekit.params.Measures`, str] = \</span></tt>
+               class="code sev- "><tt><i>219</i> <span class="sd">        induction_measure : :class:`rulekit.params.Measures` = \</span></tt>
             </div>
             <div id="l220"
                class="code sev- "><tt><i>220</i> <span class="sd">            :class:`rulekit.params.Measures.Correlation`</span></tt>
             </div>
             <div id="l221"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (84 > 79 characters)</li>
-               
-               </ul><tt><i>221</i> <span class="sd">            measure used during pruning. Could be user defined (string), for example</span></tt>
+               class="code sev- "><tt><i>221</i> <span class="sd">            measure used during induction; default measure is correlation</span></tt>
             </div>
             <div id="l222"
-               class="code sev- "><tt><i>222</i> <span class="sd">             :code:`2 * p / n`; default measure is correlation</span></tt>
+               class="code sev- "><tt><i>222</i> <span class="sd">        pruning_measure : Union[:class:`rulekit.params.Measures`, str] = \</span></tt>
             </div>
             <div id="l223"
-               class="code sev- "><tt><i>223</i> <span class="sd">        voting_measure : :class:`rulekit.params.Measures` = \</span></tt>
+               class="code sev- "><tt><i>223</i> <span class="sd">            :class:`rulekit.params.Measures.Correlation`</span></tt>
             </div>
             <div id="l224"
-               class="code sev- "><tt><i>224</i> <span class="sd">            :class:`rulekit.params.Measures.Correlation`</span></tt>
+               class="code sev- "><tt><i>224</i> <span class="sd">            measure used during pruning. Could be user defined (string), for example</span></tt>
             </div>
             <div id="l225"
-               class="code sev- "><tt><i>225</i> <span class="sd">            measure used during voting; default measure is correlation</span></tt>
+               class="code sev- "><tt><i>225</i> <span class="sd">             :code:`2 * p / n`; default measure is correlation</span></tt>
             </div>
             <div id="l226"
-               class="code sev- "><tt><i>226</i> <span class="sd">        max_growing : int = 0.0</span></tt>
+               class="code sev- "><tt><i>226</i> <span class="sd">        voting_measure : :class:`rulekit.params.Measures` = \</span></tt>
             </div>
             <div id="l227"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (96 > 79 characters)</li>
-               
-               </ul><tt><i>227</i> <span class="sd">            non-negative integer representing maximum number of conditions which can be added to</span></tt>
+               class="code sev- "><tt><i>227</i> <span class="sd">            :class:`rulekit.params.Measures.Correlation`</span></tt>
             </div>
             <div id="l228"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (98 > 79 characters)</li>
-               
-               </ul><tt><i>228</i> <span class="sd">            the rule in the growing phase (use this parameter for large datasets if execution time</span></tt>
+               class="code sev- "><tt><i>228</i> <span class="sd">            measure used during voting; default measure is correlation</span></tt>
             </div>
             <div id="l229"
-               class="code sev- "><tt><i>229</i> <span class="sd">             is prohibitive); 0 indicates no limit; default: 0,</span></tt>
+               class="code sev- "><tt><i>229</i> <span class="sd">        max_growing : int = 0.0</span></tt>
             </div>
             <div id="l230"
-               class="code sev- "><tt><i>230</i> <span class="sd">        enable_pruning : bool = True</span></tt>
+               class="code sev- "><tt><i>230</i> <span class="sd">            non-negative integer representing maximum number of conditions which can be</span></tt>
             </div>
             <div id="l231"
-               class="code sev- "><tt><i>231</i> <span class="sd">            enable or disable pruning, default is True.</span></tt>
+               class="code sev- "><tt><i>231</i> <span class="sd">            added to the rule in the growing phase (use this parameter for large</span></tt>
             </div>
             <div id="l232"
-               class="code sev- "><tt><i>232</i> <span class="sd">        ignore_missing : bool = False</span></tt>
-            </div>
-            <div id="l233"
                class="code sev-2  le">
                <ul class="violations">
                
@@ -1026,1263 +717,918 @@ <h1>
                      <span class="count sev-2">
                         E501
                      </span>
-                     Line too long (97 > 79 characters)</li>
+                     Line too long (89 > 88 characters)</li>
                
-               </ul><tt><i>233</i> <span class="sd">            boolean telling whether missing values should be ignored (by default, a missing value</span></tt>
+               </ul><tt><i>232</i> <span class="sd">            datasets if execution time is prohibitive); 0 indicates no limit; default: 0,</span></tt>
+            </div>
+            <div id="l233"
+               class="code sev- "><tt><i>233</i> <span class="sd">        enable_pruning : bool = True</span></tt>
             </div>
             <div id="l234"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (99 > 79 characters)</li>
-               
-               </ul><tt><i>234</i> <span class="sd">            of given attribute is always considered as not fulfilling the condition build upon that</span></tt>
+               class="code sev- "><tt><i>234</i> <span class="sd">            enable or disable pruning, default is True.</span></tt>
             </div>
             <div id="l235"
-               class="code sev- "><tt><i>235</i> <span class="sd">            attribute); default: False.</span></tt>
+               class="code sev- "><tt><i>235</i> <span class="sd">        ignore_missing : bool = False</span></tt>
             </div>
             <div id="l236"
-               class="code sev- "><tt><i>236</i> <span class="sd">        max_uncovered_fraction : float = 0.0</span></tt>
+               class="code sev- "><tt><i>236</i> <span class="sd">            boolean telling whether missing values should be ignored (by default, a</span></tt>
             </div>
             <div id="l237"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (95 > 79 characters)</li>
-               
-               </ul><tt><i>237</i> <span class="sd">            Floating-point number from [0,1] interval representing maximum fraction of examples</span></tt>
+               class="code sev- "><tt><i>237</i> <span class="sd">            missing value of given attribute is always considered as not fulfilling the</span></tt>
             </div>
             <div id="l238"
-               class="code sev- "><tt><i>238</i> <span class="sd">            that may remain uncovered by the rule set, default: 0.0.</span></tt>
+               class="code sev- "><tt><i>238</i> <span class="sd">            condition build upon that attribute); default: False.</span></tt>
             </div>
             <div id="l239"
-               class="code sev- "><tt><i>239</i> <span class="sd">        select_best_candidate : bool = False</span></tt>
+               class="code sev- "><tt><i>239</i> <span class="sd">        max_uncovered_fraction : float = 0.0</span></tt>
             </div>
             <div id="l240"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (85 > 79 characters)</li>
-               
-               </ul><tt><i>240</i> <span class="sd">            Flag determining if best candidate should be selected from growing phase;</span></tt>
+               class="code sev- "><tt><i>240</i> <span class="sd">            Floating-point number from [0,1] interval representing maximum fraction of</span></tt>
             </div>
             <div id="l241"
-               class="code sev- "><tt><i>241</i> <span class="sd">            default: False.</span></tt>
+               class="code sev- "><tt><i>241</i> <span class="sd">            examples that may remain uncovered by the rule set, default: 0.0.</span></tt>
             </div>
             <div id="l242"
-               class="code sev- "><tt><i>242</i> <span class="sd">        complementary_conditions : bool = False</span></tt>
+               class="code sev- "><tt><i>242</i> <span class="sd">        select_best_candidate : bool = False</span></tt>
             </div>
             <div id="l243"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (96 > 79 characters)</li>
-               
-               </ul><tt><i>243</i> <span class="sd">            If enabled, complementary conditions in the form a = !{value} for nominal attributes</span></tt>
+               class="code sev- "><tt><i>243</i> <span class="sd">            Flag determining if best candidate should be selected from growing phase;</span></tt>
             </div>
             <div id="l244"
-               class="code sev- "><tt><i>244</i> <span class="sd">            are supported.</span></tt>
+               class="code sev- "><tt><i>244</i> <span class="sd">            default: False.</span></tt>
             </div>
             <div id="l245"
-               class="code sev- "><tt><i>245</i> <span class="sd">        mean_based_regression : bool = True</span></tt>
+               class="code sev- "><tt><i>245</i> <span class="sd">        complementary_conditions : bool = False</span></tt>
             </div>
             <div id="l246"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (97 > 79 characters)</li>
-               
-               </ul><tt><i>246</i> <span class="sd">            Enable fast induction of mean-based regression rules instead of default median-based.</span></tt>
+               class="code sev- "><tt><i>246</i> <span class="sd">            If enabled, complementary conditions in the form a = !{value} for nominal</span></tt>
             </div>
             <div id="l247"
-               class="code sev- "><tt><i>247</i> <span class="sd">        max_rule_count : int = 0</span></tt>
+               class="code sev- "><tt><i>247</i> <span class="sd">            attributes are supported.</span></tt>
             </div>
             <div id="l248"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (92 > 79 characters)</li>
-               
-               </ul><tt><i>248</i> <span class="sd">            Maximum number of rules to be generated (for classification data sets it applies</span></tt>
+               class="code sev- "><tt><i>248</i> <span class="sd">        mean_based_regression : bool = True</span></tt>
             </div>
             <div id="l249"
-               class="code sev- "><tt><i>249</i> <span class="sd">             to a single class); 0 indicates no limit.</span></tt>
+               class="code sev- "><tt><i>249</i> <span class="sd">            Enable fast induction of mean-based regression rules instead of default</span></tt>
             </div>
             <div id="l250"
-               class="code sev- "><tt><i>250</i> &nbsp;</tt>
+               class="code sev- "><tt><i>250</i> <span class="sd">            median-based.</span></tt>
             </div>
             <div id="l251"
-               class="code sev- "><tt><i>251</i> <span class="sd">        extend_using_preferred : bool = False</span></tt>
+               class="code sev- "><tt><i>251</i> <span class="sd">        max_rule_count : int = 0</span></tt>
             </div>
             <div id="l252"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (95 > 79 characters)</li>
-               
-               </ul><tt><i>252</i> <span class="sd">            boolean indicating whether initial rules should be extended with a use of preferred</span></tt>
+               class="code sev- "><tt><i>252</i> <span class="sd">            Maximum number of rules to be generated (for classification data sets it</span></tt>
             </div>
             <div id="l253"
-               class="code sev- "><tt><i>253</i> <span class="sd">            conditions and attributes; default is False</span></tt>
+               class="code sev- "><tt><i>253</i> <span class="sd">            applies to a single class); 0 indicates no limit.</span></tt>
             </div>
             <div id="l254"
-               class="code sev- "><tt><i>254</i> <span class="sd">        extend_using_automatic : bool = False</span></tt>
+               class="code sev- "><tt><i>254</i> &nbsp;</tt>
             </div>
             <div id="l255"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (95 > 79 characters)</li>
-               
-               </ul><tt><i>255</i> <span class="sd">            boolean indicating whether initial rules should be extended with a use of automatic</span></tt>
+               class="code sev- "><tt><i>255</i> <span class="sd">        extend_using_preferred : bool = False</span></tt>
             </div>
             <div id="l256"
-               class="code sev- "><tt><i>256</i> <span class="sd">            conditions and attributes; default is False</span></tt>
+               class="code sev- "><tt><i>256</i> <span class="sd">            boolean indicating whether initial rules should be extended with a use of</span></tt>
             </div>
             <div id="l257"
-               class="code sev- "><tt><i>257</i> <span class="sd">        induce_using_preferred : bool = False</span></tt>
+               class="code sev- "><tt><i>257</i> <span class="sd">            preferred conditions and attributes; default is False</span></tt>
             </div>
             <div id="l258"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (90 > 79 characters)</li>
-               
-               </ul><tt><i>258</i> <span class="sd">            boolean indicating whether new rules should be induced with a use of preferred</span></tt>
+               class="code sev- "><tt><i>258</i> <span class="sd">        extend_using_automatic : bool = False</span></tt>
             </div>
             <div id="l259"
-               class="code sev- "><tt><i>259</i> <span class="sd">            conditions and attributes; default is False</span></tt>
+               class="code sev- "><tt><i>259</i> <span class="sd">            boolean indicating whether initial rules should be extended with a use of</span></tt>
             </div>
             <div id="l260"
-               class="code sev- "><tt><i>260</i> <span class="sd">        induce_using_automatic : bool = False</span></tt>
+               class="code sev- "><tt><i>260</i> <span class="sd">            automatic conditions and attributes; default is False</span></tt>
             </div>
             <div id="l261"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (90 > 79 characters)</li>
-               
-               </ul><tt><i>261</i> <span class="sd">            boolean indicating whether new rules should be induced with a use of automatic</span></tt>
+               class="code sev- "><tt><i>261</i> <span class="sd">        induce_using_preferred : bool = False</span></tt>
             </div>
             <div id="l262"
-               class="code sev- "><tt><i>262</i> <span class="sd">            conditions and attributes; default is False</span></tt>
+               class="code sev- "><tt><i>262</i> <span class="sd">            boolean indicating whether new rules should be induced with a use of</span></tt>
             </div>
             <div id="l263"
-               class="code sev- "><tt><i>263</i> <span class="sd">        preferred_conditions_per_rule : int = None</span></tt>
+               class="code sev- "><tt><i>263</i> <span class="sd">            preferred conditions and attributes; default is False</span></tt>
             </div>
             <div id="l264"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (80 > 79 characters)</li>
-               
-               </ul><tt><i>264</i> <span class="sd">            maximum number of preferred conditions per rule; default: unlimited,</span></tt>
+               class="code sev- "><tt><i>264</i> <span class="sd">        induce_using_automatic : bool = False</span></tt>
             </div>
             <div id="l265"
-               class="code sev- "><tt><i>265</i> <span class="sd">        preferred_attributes_per_rule : int = None</span></tt>
+               class="code sev- "><tt><i>265</i> <span class="sd">            boolean indicating whether new rules should be induced with a use of</span></tt>
             </div>
             <div id="l266"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (80 > 79 characters)</li>
-               
-               </ul><tt><i>266</i> <span class="sd">            maximum number of preferred attributes per rule; default: unlimited.</span></tt>
+               class="code sev- "><tt><i>266</i> <span class="sd">            automatic conditions and attributes; default is False</span></tt>
             </div>
             <div id="l267"
-               class="code sev- "><tt><i>267</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
+               class="code sev- "><tt><i>267</i> <span class="sd">        preferred_conditions_per_rule : int = None</span></tt>
             </div>
             <div id="l268"
-               class="code sev- "><tt><i>268</i>         <span class="n">RuleRegressor</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span></tt>
+               class="code sev- "><tt><i>268</i> <span class="sd">            maximum number of preferred conditions per rule; default: unlimited,</span></tt>
             </div>
             <div id="l269"
-               class="code sev- "><tt><i>269</i>             <span class="bp">self</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>269</i> <span class="sd">        preferred_attributes_per_rule : int = None</span></tt>
             </div>
             <div id="l270"
-               class="code sev- "><tt><i>270</i>             <span class="n">minsupp_new</span><span class="o">=</span><span class="n">minsupp_new</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>270</i> <span class="sd">            maximum number of preferred attributes per rule; default: unlimited.</span></tt>
             </div>
             <div id="l271"
-               class="code sev- "><tt><i>271</i>             <span class="n">induction_measure</span><span class="o">=</span><span class="n">induction_measure</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>271</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
             </div>
             <div id="l272"
-               class="code sev- "><tt><i>272</i>             <span class="n">pruning_measure</span><span class="o">=</span><span class="n">pruning_measure</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>272</i>         <span class="n">RuleRegressor</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span></tt>
             </div>
             <div id="l273"
-               class="code sev- "><tt><i>273</i>             <span class="n">voting_measure</span><span class="o">=</span><span class="n">voting_measure</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>273</i>             <span class="bp">self</span><span class="p">,</span></tt>
             </div>
             <div id="l274"
-               class="code sev- "><tt><i>274</i>             <span class="n">max_growing</span><span class="o">=</span><span class="n">max_growing</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>274</i>             <span class="n">minsupp_new</span><span class="o">=</span><span class="n">minsupp_new</span><span class="p">,</span></tt>
             </div>
             <div id="l275"
-               class="code sev- "><tt><i>275</i>             <span class="n">enable_pruning</span><span class="o">=</span><span class="n">enable_pruning</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>275</i>             <span class="n">induction_measure</span><span class="o">=</span><span class="n">induction_measure</span><span class="p">,</span></tt>
             </div>
             <div id="l276"
-               class="code sev- "><tt><i>276</i>             <span class="n">ignore_missing</span><span class="o">=</span><span class="n">ignore_missing</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>276</i>             <span class="n">pruning_measure</span><span class="o">=</span><span class="n">pruning_measure</span><span class="p">,</span></tt>
             </div>
             <div id="l277"
-               class="code sev- "><tt><i>277</i>             <span class="n">max_uncovered_fraction</span><span class="o">=</span><span class="n">max_uncovered_fraction</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>277</i>             <span class="n">voting_measure</span><span class="o">=</span><span class="n">voting_measure</span><span class="p">,</span></tt>
             </div>
             <div id="l278"
-               class="code sev- "><tt><i>278</i>             <span class="n">select_best_candidate</span><span class="o">=</span><span class="n">select_best_candidate</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>278</i>             <span class="n">max_growing</span><span class="o">=</span><span class="n">max_growing</span><span class="p">,</span></tt>
             </div>
             <div id="l279"
-               class="code sev- "><tt><i>279</i>             <span class="n">complementary_conditions</span><span class="o">=</span><span class="n">complementary_conditions</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>279</i>             <span class="n">enable_pruning</span><span class="o">=</span><span class="n">enable_pruning</span><span class="p">,</span></tt>
             </div>
             <div id="l280"
-               class="code sev- "><tt><i>280</i>             <span class="n">mean_based_regression</span><span class="o">=</span><span class="n">mean_based_regression</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>280</i>             <span class="n">ignore_missing</span><span class="o">=</span><span class="n">ignore_missing</span><span class="p">,</span></tt>
             </div>
             <div id="l281"
-               class="code sev- "><tt><i>281</i>             <span class="n">max_rule_count</span><span class="o">=</span><span class="n">max_rule_count</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>281</i>             <span class="n">max_uncovered_fraction</span><span class="o">=</span><span class="n">max_uncovered_fraction</span><span class="p">,</span></tt>
             </div>
             <div id="l282"
-               class="code sev- "><tt><i>282</i>         <span class="p">)</span></tt>
+               class="code sev- "><tt><i>282</i>             <span class="n">select_best_candidate</span><span class="o">=</span><span class="n">select_best_candidate</span><span class="p">,</span></tt>
             </div>
             <div id="l283"
-               class="code sev- "><tt><i>283</i>         <span class="n">ExpertKnowledgeOperator</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span></tt>
+               class="code sev- "><tt><i>283</i>             <span class="n">complementary_conditions</span><span class="o">=</span><span class="n">complementary_conditions</span><span class="p">,</span></tt>
             </div>
             <div id="l284"
-               class="code sev- "><tt><i>284</i>             <span class="bp">self</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>284</i>             <span class="n">mean_based_regression</span><span class="o">=</span><span class="n">mean_based_regression</span><span class="p">,</span></tt>
             </div>
             <div id="l285"
-               class="code sev- "><tt><i>285</i>             <span class="n">minsupp_new</span><span class="o">=</span><span class="n">minsupp_new</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>285</i>             <span class="n">max_rule_count</span><span class="o">=</span><span class="n">max_rule_count</span><span class="p">,</span></tt>
             </div>
             <div id="l286"
-               class="code sev- "><tt><i>286</i>             <span class="n">induction_measure</span><span class="o">=</span><span class="n">induction_measure</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>286</i>         <span class="p">)</span></tt>
             </div>
             <div id="l287"
-               class="code sev- "><tt><i>287</i>             <span class="n">pruning_measure</span><span class="o">=</span><span class="n">pruning_measure</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>287</i>         <span class="n">ExpertKnowledgeOperator</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span></tt>
             </div>
             <div id="l288"
-               class="code sev- "><tt><i>288</i>             <span class="n">voting_measure</span><span class="o">=</span><span class="n">voting_measure</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>288</i>             <span class="bp">self</span><span class="p">,</span></tt>
             </div>
             <div id="l289"
-               class="code sev- "><tt><i>289</i>             <span class="n">max_growing</span><span class="o">=</span><span class="n">max_growing</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>289</i>             <span class="n">minsupp_new</span><span class="o">=</span><span class="n">minsupp_new</span><span class="p">,</span></tt>
             </div>
             <div id="l290"
-               class="code sev- "><tt><i>290</i>             <span class="n">enable_pruning</span><span class="o">=</span><span class="n">enable_pruning</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>290</i>             <span class="n">induction_measure</span><span class="o">=</span><span class="n">induction_measure</span><span class="p">,</span></tt>
             </div>
             <div id="l291"
-               class="code sev- "><tt><i>291</i>             <span class="n">ignore_missing</span><span class="o">=</span><span class="n">ignore_missing</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>291</i>             <span class="n">pruning_measure</span><span class="o">=</span><span class="n">pruning_measure</span><span class="p">,</span></tt>
             </div>
             <div id="l292"
-               class="code sev- "><tt><i>292</i>             <span class="n">max_uncovered_fraction</span><span class="o">=</span><span class="n">max_uncovered_fraction</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>292</i>             <span class="n">voting_measure</span><span class="o">=</span><span class="n">voting_measure</span><span class="p">,</span></tt>
             </div>
             <div id="l293"
-               class="code sev- "><tt><i>293</i>             <span class="n">select_best_candidate</span><span class="o">=</span><span class="n">select_best_candidate</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>293</i>             <span class="n">max_growing</span><span class="o">=</span><span class="n">max_growing</span><span class="p">,</span></tt>
             </div>
             <div id="l294"
-               class="code sev- "><tt><i>294</i>             <span class="n">extend_using_preferred</span><span class="o">=</span><span class="n">extend_using_preferred</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>294</i>             <span class="n">enable_pruning</span><span class="o">=</span><span class="n">enable_pruning</span><span class="p">,</span></tt>
             </div>
             <div id="l295"
-               class="code sev- "><tt><i>295</i>             <span class="n">extend_using_automatic</span><span class="o">=</span><span class="n">extend_using_automatic</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>295</i>             <span class="n">ignore_missing</span><span class="o">=</span><span class="n">ignore_missing</span><span class="p">,</span></tt>
             </div>
             <div id="l296"
-               class="code sev- "><tt><i>296</i>             <span class="n">induce_using_preferred</span><span class="o">=</span><span class="n">induce_using_preferred</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>296</i>             <span class="n">max_uncovered_fraction</span><span class="o">=</span><span class="n">max_uncovered_fraction</span><span class="p">,</span></tt>
             </div>
             <div id="l297"
-               class="code sev- "><tt><i>297</i>             <span class="n">induce_using_automatic</span><span class="o">=</span><span class="n">induce_using_automatic</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>297</i>             <span class="n">select_best_candidate</span><span class="o">=</span><span class="n">select_best_candidate</span><span class="p">,</span></tt>
             </div>
             <div id="l298"
-               class="code sev- "><tt><i>298</i>             <span class="n">preferred_conditions_per_rule</span><span class="o">=</span><span class="n">preferred_conditions_per_rule</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>298</i>             <span class="n">extend_using_preferred</span><span class="o">=</span><span class="n">extend_using_preferred</span><span class="p">,</span></tt>
             </div>
             <div id="l299"
-               class="code sev- "><tt><i>299</i>             <span class="n">preferred_attributes_per_rule</span><span class="o">=</span><span class="n">preferred_attributes_per_rule</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>299</i>             <span class="n">extend_using_automatic</span><span class="o">=</span><span class="n">extend_using_automatic</span><span class="p">,</span></tt>
             </div>
             <div id="l300"
-               class="code sev- "><tt><i>300</i>             <span class="n">complementary_conditions</span><span class="o">=</span><span class="n">complementary_conditions</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>300</i>             <span class="n">induce_using_preferred</span><span class="o">=</span><span class="n">induce_using_preferred</span><span class="p">,</span></tt>
             </div>
             <div id="l301"
-               class="code sev- "><tt><i>301</i>             <span class="n">mean_based_regression</span><span class="o">=</span><span class="n">mean_based_regression</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>301</i>             <span class="n">induce_using_automatic</span><span class="o">=</span><span class="n">induce_using_automatic</span><span class="p">,</span></tt>
             </div>
             <div id="l302"
-               class="code sev- "><tt><i>302</i>             <span class="n">max_rule_count</span><span class="o">=</span><span class="n">max_rule_count</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>302</i>             <span class="n">preferred_conditions_per_rule</span><span class="o">=</span><span class="n">preferred_conditions_per_rule</span><span class="p">,</span></tt>
             </div>
             <div id="l303"
-               class="code sev- "><tt><i>303</i>         <span class="p">)</span></tt>
+               class="code sev- "><tt><i>303</i>             <span class="n">preferred_attributes_per_rule</span><span class="o">=</span><span class="n">preferred_attributes_per_rule</span><span class="p">,</span></tt>
             </div>
             <div id="l304"
-               class="code sev- "><tt><i>304</i>         <span class="bp">self</span><span class="o">.</span><span class="n">model</span><span class="p">:</span> <span class="n">RuleSet</span><span class="p">[</span><span class="n">RegressionRule</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span></tt>
+               class="code sev- "><tt><i>304</i>             <span class="n">complementary_conditions</span><span class="o">=</span><span class="n">complementary_conditions</span><span class="p">,</span></tt>
             </div>
             <div id="l305"
-               class="code sev- "><tt><i>305</i> &nbsp;</tt>
+               class="code sev- "><tt><i>305</i>             <span class="n">mean_based_regression</span><span class="o">=</span><span class="n">mean_based_regression</span><span class="p">,</span></tt>
             </div>
             <div id="l306"
-               class="code sev- "><tt><i>306</i>     <span class="k">def</span> <span class="nf">fit</span><span class="p">(</span>  <span class="c1"># pylint: disable=arguments-differ,too-many-arguments</span></tt>
+               class="code sev- "><tt><i>306</i>             <span class="n">max_rule_count</span><span class="o">=</span><span class="n">max_rule_count</span><span class="p">,</span></tt>
             </div>
             <div id="l307"
-               class="code sev- "><tt><i>307</i>         <span class="bp">self</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>307</i>         <span class="p">)</span></tt>
             </div>
             <div id="l308"
-               class="code sev- "><tt><i>308</i>         <span class="n">values</span><span class="p">:</span> <span class="n">Data</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>308</i>         <span class="bp">self</span><span class="o">.</span><span class="n">model</span><span class="p">:</span> <span class="n">RuleSet</span><span class="p">[</span><span class="n">RegressionRule</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span></tt>
             </div>
             <div id="l309"
-               class="code sev- "><tt><i>309</i>         <span class="n">labels</span><span class="p">:</span> <span class="n">Data</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>309</i> &nbsp;</tt>
             </div>
             <div id="l310"
-               class="code sev- "><tt><i>310</i> &nbsp;</tt>
+               class="code sev- "><tt><i>310</i>     <span class="k">def</span> <span class="nf">fit</span><span class="p">(</span>  <span class="c1"># pylint: disable=arguments-differ,too-many-arguments</span></tt>
             </div>
             <div id="l311"
-               class="code sev- "><tt><i>311</i>         <span class="n">expert_rules</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="n">Union</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="nb">tuple</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="nb">str</span><span class="p">]]]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>311</i>         <span class="bp">self</span><span class="p">,</span></tt>
             </div>
             <div id="l312"
-               class="code sev- "><tt><i>312</i>         <span class="n">expert_preferred_conditions</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="n">Union</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="nb">tuple</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="nb">str</span><span class="p">]]]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>312</i>         <span class="n">values</span><span class="p">:</span> <span class="n">Data</span><span class="p">,</span></tt>
             </div>
             <div id="l313"
-               class="code sev- "><tt><i>313</i>         <span class="n">expert_forbidden_conditions</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="n">Union</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="nb">tuple</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="nb">str</span><span class="p">]]]</span> <span class="o">=</span> <span class="kc">None</span></tt>
+               class="code sev- "><tt><i>313</i>         <span class="n">labels</span><span class="p">:</span> <span class="n">Data</span><span class="p">,</span></tt>
             </div>
             <div id="l314"
-               class="code sev- "><tt><i>314</i>     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ExpertRuleRegressor</span><span class="p">:</span></tt>
+               class="code sev- "><tt><i>314</i>         <span class="n">expert_rules</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="n">Union</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="nb">tuple</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="nb">str</span><span class="p">]]]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span></tt>
             </div>
             <div id="l315"
-               class="code sev- "><tt><i>315</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Train model on given dataset.</span></tt>
+               class="code sev- "><tt><i>315</i>         <span class="n">expert_preferred_conditions</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="n">Union</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="nb">tuple</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="nb">str</span><span class="p">]]]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span></tt>
             </div>
             <div id="l316"
-               class="code sev- "><tt><i>316</i> &nbsp;</tt>
+               class="code sev- "><tt><i>316</i>         <span class="n">expert_forbidden_conditions</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="n">Union</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="nb">tuple</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="nb">str</span><span class="p">]]]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span></tt>
             </div>
             <div id="l317"
-               class="code sev- "><tt><i>317</i> <span class="sd">        Parameters</span></tt>
+               class="code sev- "><tt><i>317</i>     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ExpertRuleRegressor</span><span class="p">:</span></tt>
             </div>
             <div id="l318"
-               class="code sev- "><tt><i>318</i> <span class="sd">        ----------</span></tt>
+               class="code sev- "><tt><i>318</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Train model on given dataset.</span></tt>
             </div>
             <div id="l319"
-               class="code sev- "><tt><i>319</i> <span class="sd">        values : :class:`rulekit.operator.Data`</span></tt>
+               class="code sev- "><tt><i>319</i> &nbsp;</tt>
             </div>
             <div id="l320"
-               class="code sev- "><tt><i>320</i> <span class="sd">            attributes</span></tt>
+               class="code sev- "><tt><i>320</i> <span class="sd">        Parameters</span></tt>
             </div>
             <div id="l321"
-               class="code sev- "><tt><i>321</i> <span class="sd">        labels : :class:`rulekit.operator.Data`</span></tt>
+               class="code sev- "><tt><i>321</i> <span class="sd">        ----------</span></tt>
             </div>
             <div id="l322"
-               class="code sev- "><tt><i>322</i> <span class="sd">            target values</span></tt>
+               class="code sev- "><tt><i>322</i> <span class="sd">        values : :class:`rulekit.operator.Data`</span></tt>
             </div>
             <div id="l323"
-               class="code sev- "><tt><i>323</i> &nbsp;</tt>
+               class="code sev- "><tt><i>323</i> <span class="sd">            attributes</span></tt>
             </div>
-            <div id="l324"
-               class="code sev- "><tt><i>324</i> <span class="sd">        expert_rules : List[Union[str, Tuple[str, str]]]</span></tt>
-            </div>
-            <div id="l325"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (98 > 79 characters)</li>
-               
-               </ul><tt><i>325</i> <span class="sd">            set of initial rules, either passed as a list of strings representing rules or as list</span></tt>
+            <div id="l324"
+               class="code sev- "><tt><i>324</i> <span class="sd">        labels : :class:`rulekit.operator.Data`</span></tt>
+            </div>
+            <div id="l325"
+               class="code sev- "><tt><i>325</i> <span class="sd">            target values</span></tt>
             </div>
             <div id="l326"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (92 > 79 characters)</li>
-               
-               </ul><tt><i>326</i> <span class="sd">            of tuples where first element is name of the rule and second one is rule string.</span></tt>
+               class="code sev- "><tt><i>326</i> &nbsp;</tt>
             </div>
             <div id="l327"
-               class="code sev- "><tt><i>327</i> <span class="sd">        expert_preferred_conditions : List[Union[str, Tuple[str, str]]]</span></tt>
+               class="code sev- "><tt><i>327</i> <span class="sd">        expert_rules : List[Union[str, Tuple[str, str]]]</span></tt>
             </div>
             <div id="l328"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (94 > 79 characters)</li>
-               
-               </ul><tt><i>328</i> <span class="sd">            multiset of preferred conditions (used also for specifying preferred attributes by</span></tt>
+               class="code sev- "><tt><i>328</i> <span class="sd">            set of initial rules, either passed as a list of strings representing rules</span></tt>
             </div>
             <div id="l329"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (98 > 79 characters)</li>
-               
-               </ul><tt><i>329</i> <span class="sd">             using special value Any). Either passed as a list of strings representing rules or as</span></tt>
+               class="code sev- "><tt><i>329</i> <span class="sd">            or as list of tuples where first element is name of the rule and second one</span></tt>
             </div>
             <div id="l330"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (98 > 79 characters)</li>
-               
-               </ul><tt><i>330</i> <span class="sd">             list of tuples where first element is name of the rule and second one is rule string.</span></tt>
+               class="code sev- "><tt><i>330</i> <span class="sd">            is rule string.</span></tt>
             </div>
             <div id="l331"
-               class="code sev- "><tt><i>331</i> <span class="sd">        expert_forbidden_conditions : List[Union[str, Tuple[str, str]]]</span></tt>
+               class="code sev- "><tt><i>331</i> <span class="sd">        expert_preferred_conditions : List[Union[str, Tuple[str, str]]]</span></tt>
             </div>
             <div id="l332"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (95 > 79 characters)</li>
-               
-               </ul><tt><i>332</i> <span class="sd">            set of forbidden conditions (used also for specifying forbidden attributes by using</span></tt>
+               class="code sev- "><tt><i>332</i> <span class="sd">            multiset of preferred conditions (used also for specifying preferred</span></tt>
             </div>
             <div id="l333"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (97 > 79 characters)</li>
-               
-               </ul><tt><i>333</i> <span class="sd">             special valye Any). Either passed as a list of strings representing rules or as list</span></tt>
+               class="code sev- "><tt><i>333</i> <span class="sd">            attributes by using special value Any). Either passed as a list of strings</span></tt>
             </div>
             <div id="l334"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (93 > 79 characters)</li>
-               
-               </ul><tt><i>334</i> <span class="sd">             of tuples where first element is name of the rule and second one is rule string.</span></tt>
+               class="code sev- "><tt><i>334</i> <span class="sd">            representing rules or as list of tuples where first element is name of the</span></tt>
             </div>
             <div id="l335"
-               class="code sev- "><tt><i>335</i> <span class="sd">        Returns</span></tt>
+               class="code sev- "><tt><i>335</i> <span class="sd">            rule and second one is rule string.</span></tt>
             </div>
             <div id="l336"
-               class="code sev- "><tt><i>336</i> <span class="sd">        -------</span></tt>
+               class="code sev- "><tt><i>336</i> <span class="sd">        expert_forbidden_conditions : List[Union[str, Tuple[str, str]]]</span></tt>
             </div>
             <div id="l337"
-               class="code sev- "><tt><i>337</i> <span class="sd">        self : ExpertRuleRegressor</span></tt>
+               class="code sev- "><tt><i>337</i> <span class="sd">            set of forbidden conditions (used also for specifying forbidden attributes</span></tt>
             </div>
             <div id="l338"
-               class="code sev- "><tt><i>338</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
+               class="code sev- "><tt><i>338</i> <span class="sd">            by using special valye Any). Either passed as a list of strings representing</span></tt>
             </div>
             <div id="l339"
-               class="code sev- "><tt><i>339</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_validate_labels</span><span class="p">(</span><span class="n">labels</span><span class="p">)</span></tt>
+               class="code sev- "><tt><i>339</i> <span class="sd">            rules or as list of tuples where first element is name of the rule and</span></tt>
             </div>
             <div id="l340"
-               class="code sev- "><tt><i>340</i>         <span class="k">return</span> <span class="n">ExpertKnowledgeOperator</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span></tt>
+               class="code sev- "><tt><i>340</i> <span class="sd">            second one is rule string.</span></tt>
             </div>
             <div id="l341"
-               class="code sev- "><tt><i>341</i>             <span class="bp">self</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>341</i> <span class="sd">        Returns</span></tt>
             </div>
             <div id="l342"
-               class="code sev- "><tt><i>342</i>             <span class="n">values</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>342</i> <span class="sd">        -------</span></tt>
             </div>
             <div id="l343"
-               class="code sev- "><tt><i>343</i>             <span class="n">labels</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>343</i> <span class="sd">        self : ExpertRuleRegressor</span></tt>
             </div>
             <div id="l344"
-               class="code sev- "><tt><i>344</i>             <span class="n">expert_rules</span><span class="o">=</span><span class="n">expert_rules</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>344</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
             </div>
             <div id="l345"
-               class="code sev- "><tt><i>345</i>             <span class="n">expert_preferred_conditions</span><span class="o">=</span><span class="n">expert_preferred_conditions</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>345</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_validate_labels</span><span class="p">(</span><span class="n">labels</span><span class="p">)</span></tt>
             </div>
             <div id="l346"
-               class="code sev- "><tt><i>346</i>             <span class="n">expert_forbidden_conditions</span><span class="o">=</span><span class="n">expert_forbidden_conditions</span></tt>
+               class="code sev- "><tt><i>346</i>         <span class="k">return</span> <span class="n">ExpertKnowledgeOperator</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span></tt>
             </div>
             <div id="l347"
-               class="code sev- "><tt><i>347</i>         <span class="p">)</span></tt>
+               class="code sev- "><tt><i>347</i>             <span class="bp">self</span><span class="p">,</span></tt>
             </div>
             <div id="l348"
-               class="code sev- "><tt><i>348</i> &nbsp;</tt>
+               class="code sev- "><tt><i>348</i>             <span class="n">values</span><span class="p">,</span></tt>
             </div>
             <div id="l349"
-               class="code sev- "><tt><i>349</i>     <span class="k">def</span> <span class="nf">predict</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">:</span> <span class="n">Data</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">:</span></tt>
+               class="code sev- "><tt><i>349</i>             <span class="n">labels</span><span class="p">,</span></tt>
             </div>
             <div id="l350"
-               class="code sev- "><tt><i>350</i>         <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_map_result</span><span class="p">(</span><span class="n">ExpertKnowledgeOperator</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">))</span></tt>
+               class="code sev- "><tt><i>350</i>             <span class="n">expert_rules</span><span class="o">=</span><span class="n">expert_rules</span><span class="p">,</span></tt>
             </div>
             <div id="l351"
-               class="code sev- "><tt><i>351</i> &nbsp;</tt>
+               class="code sev- "><tt><i>351</i>             <span class="n">expert_preferred_conditions</span><span class="o">=</span><span class="n">expert_preferred_conditions</span><span class="p">,</span></tt>
             </div>
             <div id="l352"
-               class="code sev- "><tt><i>352</i>     <span class="k">def</span> <span class="nf">_get_problem_type</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ProblemType</span><span class="p">:</span></tt>
+               class="code sev- "><tt><i>352</i>             <span class="n">expert_forbidden_conditions</span><span class="o">=</span><span class="n">expert_forbidden_conditions</span><span class="p">,</span></tt>
             </div>
             <div id="l353"
-               class="code sev- "><tt><i>353</i>         <span class="k">return</span> <span class="n">ProblemType</span><span class="o">.</span><span class="n">REGRESSION</span></tt>
+               class="code sev- "><tt><i>353</i>         <span class="p">)</span></tt>
             </div>
             <div id="l354"
                class="code sev- "><tt><i>354</i> &nbsp;</tt>
             </div>
             <div id="l355"
-               class="code sev- "><tt><i>355</i> &nbsp;</tt>
+               class="code sev- "><tt><i>355</i>     <span class="k">def</span> <span class="nf">predict</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">:</span> <span class="n">Data</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">:</span></tt>
             </div>
             <div id="l356"
-               class="code sev- "><tt><i>356</i> <span class="k">class</span> <span class="nc">ContrastSetRuleRegressor</span><span class="p">(</span><span class="n">BaseOperator</span><span class="p">):</span></tt>
+               class="code sev- "><tt><i>356</i>         <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_map_result</span><span class="p">(</span><span class="n">ExpertKnowledgeOperator</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">))</span></tt>
             </div>
             <div id="l357"
-               class="code sev- "><tt><i>357</i> <span class="w">    </span><span class="sd">&quot;&quot;&quot;Contrast set regression model.&quot;&quot;&quot;</span></tt>
+               class="code sev- "><tt><i>357</i> &nbsp;</tt>
             </div>
             <div id="l358"
-               class="code sev- "><tt><i>358</i> &nbsp;</tt>
+               class="code sev- "><tt><i>358</i>     <span class="k">def</span> <span class="nf">_get_problem_type</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ProblemType</span><span class="p">:</span></tt>
             </div>
             <div id="l359"
-               class="code sev- "><tt><i>359</i>     <span class="n">__params_class__</span> <span class="o">=</span> <span class="n">ContrastSetModelParams</span></tt>
+               class="code sev- "><tt><i>359</i>         <span class="k">return</span> <span class="n">ProblemType</span><span class="o">.</span><span class="n">REGRESSION</span></tt>
             </div>
             <div id="l360"
                class="code sev- "><tt><i>360</i> &nbsp;</tt>
             </div>
             <div id="l361"
-               class="code sev- "><tt><i>361</i>     <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span>  <span class="c1"># pylint: disable=too-many-arguments,too-many-locals</span></tt>
+               class="code sev- "><tt><i>361</i> &nbsp;</tt>
             </div>
             <div id="l362"
-               class="code sev- "><tt><i>362</i>         <span class="bp">self</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>362</i> <span class="k">class</span> <span class="nc">ContrastSetRuleRegressor</span><span class="p">(</span><span class="n">BaseOperator</span><span class="p">):</span></tt>
             </div>
             <div id="l363"
-               class="code sev- "><tt><i>363</i>         <span class="n">minsupp_all</span><span class="p">:</span> <span class="n">Tuple</span><span class="p">[</span><span class="nb">float</span><span class="p">,</span> <span class="nb">float</span><span class="p">,</span> <span class="nb">float</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>363</i> <span class="w">    </span><span class="sd">&quot;&quot;&quot;Contrast set regression model.&quot;&quot;&quot;</span></tt>
             </div>
             <div id="l364"
-               class="code sev- "><tt><i>364</i>                            <span class="nb">float</span><span class="p">]</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;minsupp_all&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>364</i> &nbsp;</tt>
             </div>
             <div id="l365"
-               class="code sev- "><tt><i>365</i>         <span class="n">max_neg2pos</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;max_neg2pos&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>365</i>     <span class="n">__params_class__</span> <span class="o">=</span> <span class="n">ContrastSetModelParams</span></tt>
             </div>
             <div id="l366"
-               class="code sev- "><tt><i>366</i>         <span class="n">max_passes_count</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;max_passes_count&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>366</i> &nbsp;</tt>
             </div>
             <div id="l367"
-               class="code sev- "><tt><i>367</i>         <span class="n">penalty_strength</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;penalty_strength&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>367</i>     <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span>  <span class="c1"># pylint: disable=too-many-arguments,too-many-locals</span></tt>
             </div>
             <div id="l368"
-               class="code sev- "><tt><i>368</i>         <span class="n">penalty_saturation</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;penalty_saturation&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>368</i>         <span class="bp">self</span><span class="p">,</span></tt>
             </div>
             <div id="l369"
-               class="code sev- "><tt><i>369</i> &nbsp;</tt>
+               class="code sev- "><tt><i>369</i>         <span class="n">minsupp_all</span><span class="p">:</span> <span class="n">Tuple</span><span class="p">[</span><span class="nb">float</span><span class="p">,</span> <span class="nb">float</span><span class="p">,</span> <span class="nb">float</span><span class="p">,</span> <span class="nb">float</span><span class="p">]</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span></tt>
             </div>
             <div id="l370"
-               class="code sev- "><tt><i>370</i>         <span class="n">minsupp_new</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;minsupp_new&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>370</i>             <span class="s2">&quot;minsupp_all&quot;</span></tt>
             </div>
             <div id="l371"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (80 > 79 characters)</li>
-               
-               </ul><tt><i>371</i>         <span class="n">induction_measure</span><span class="p">:</span> <span class="n">Measures</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;induction_measure&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>371</i>         <span class="p">],</span></tt>
             </div>
             <div id="l372"
-               class="code sev- "><tt><i>372</i>         <span class="n">pruning_measure</span><span class="p">:</span> <span class="n">Union</span><span class="p">[</span><span class="n">Measures</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>372</i>         <span class="n">max_neg2pos</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;max_neg2pos&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l373"
-               class="code sev- "><tt><i>373</i>                                <span class="nb">str</span><span class="p">]</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;pruning_measure&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>373</i>         <span class="n">max_passes_count</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;max_passes_count&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l374"
-               class="code sev- "><tt><i>374</i>         <span class="n">voting_measure</span><span class="p">:</span> <span class="n">Measures</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;voting_measure&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>374</i>         <span class="n">penalty_strength</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;penalty_strength&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l375"
-               class="code sev- "><tt><i>375</i>         <span class="n">max_growing</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;max_growing&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>375</i>         <span class="n">penalty_saturation</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;penalty_saturation&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l376"
-               class="code sev- "><tt><i>376</i>         <span class="n">enable_pruning</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;enable_pruning&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>376</i>         <span class="n">minsupp_new</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;minsupp_new&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l377"
-               class="code sev- "><tt><i>377</i>         <span class="n">ignore_missing</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;ignore_missing&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>377</i>         <span class="n">induction_measure</span><span class="p">:</span> <span class="n">Measures</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;induction_measure&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l378"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (87 > 79 characters)</li>
-               
-               </ul><tt><i>378</i>         <span class="n">max_uncovered_fraction</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;max_uncovered_fraction&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>378</i>         <span class="n">pruning_measure</span><span class="p">:</span> <span class="n">Union</span><span class="p">[</span><span class="n">Measures</span><span class="p">,</span> <span class="nb">str</span><span class="p">]</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;pruning_measure&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l379"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (84 > 79 characters)</li>
-               
-               </ul><tt><i>379</i>         <span class="n">select_best_candidate</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;select_best_candidate&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>379</i>         <span class="n">voting_measure</span><span class="p">:</span> <span class="n">Measures</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;voting_measure&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l380"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (90 > 79 characters)</li>
-               
-               </ul><tt><i>380</i>         <span class="n">complementary_conditions</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;complementary_conditions&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>380</i>         <span class="n">max_growing</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;max_growing&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l381"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (84 > 79 characters)</li>
-               
-               </ul><tt><i>381</i>         <span class="n">mean_based_regression</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;mean_based_regression&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>381</i>         <span class="n">enable_pruning</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;enable_pruning&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l382"
-               class="code sev- "><tt><i>382</i>         <span class="n">max_rule_count</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;max_rule_count&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>382</i>         <span class="n">ignore_missing</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;ignore_missing&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l383"
-               class="code sev- "><tt><i>383</i>     <span class="p">):</span></tt>
+               class="code sev- "><tt><i>383</i>         <span class="n">max_uncovered_fraction</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;max_uncovered_fraction&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l384"
-               class="code sev- "><tt><i>384</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;</span></tt>
+               class="code sev- "><tt><i>384</i>         <span class="n">select_best_candidate</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;select_best_candidate&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l385"
-               class="code sev- "><tt><i>385</i> <span class="sd">        Parameters</span></tt>
+               class="code sev- "><tt><i>385</i>         <span class="n">complementary_conditions</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span></tt>
             </div>
             <div id="l386"
-               class="code sev- "><tt><i>386</i> <span class="sd">        ----------</span></tt>
+               class="code sev- "><tt><i>386</i>             <span class="s2">&quot;complementary_conditions&quot;</span></tt>
             </div>
             <div id="l387"
-               class="code sev- "><tt><i>387</i> <span class="sd">        minsupp_all: Tuple[float, float, float, float]</span></tt>
+               class="code sev- "><tt><i>387</i>         <span class="p">],</span></tt>
             </div>
             <div id="l388"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (99 > 79 characters)</li>
-               
-               </ul><tt><i>388</i> <span class="sd">            a minimum positive support of a contrast set (p/P). When multiple values are specified,</span></tt>
+               class="code sev- "><tt><i>388</i>         <span class="n">mean_based_regression</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;mean_based_regression&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l389"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (97 > 79 characters)</li>
-               
-               </ul><tt><i>389</i> <span class="sd">            a metainduction is performed; Default and recommended sequence is: 0.8, 0.5, 0.2, 0.1</span></tt>
+               class="code sev- "><tt><i>389</i>         <span class="n">max_rule_count</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;max_rule_count&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l390"
-               class="code sev- "><tt><i>390</i> <span class="sd">        max_neg2pos: float</span></tt>
+               class="code sev- "><tt><i>390</i>     <span class="p">):</span></tt>
             </div>
             <div id="l391"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (84 > 79 characters)</li>
-               
-               </ul><tt><i>391</i> <span class="sd">            a maximum ratio of negative to positive supports (nP/pN); Default is 0.5</span></tt>
+               class="code sev- "><tt><i>391</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;</span></tt>
             </div>
             <div id="l392"
-               class="code sev- "><tt><i>392</i> <span class="sd">        max_passes_count: int</span></tt>
+               class="code sev- "><tt><i>392</i> <span class="sd">        Parameters</span></tt>
             </div>
             <div id="l393"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (97 > 79 characters)</li>
-               
-               </ul><tt><i>393</i> <span class="sd">            a maximum number of sequential covering passes for a single minsupp-all; Default is 5</span></tt>
+               class="code sev- "><tt><i>393</i> <span class="sd">        ----------</span></tt>
             </div>
             <div id="l394"
-               class="code sev- "><tt><i>394</i> <span class="sd">        penalty_strength: float</span></tt>
+               class="code sev- "><tt><i>394</i> <span class="sd">        minsupp_all: Tuple[float, float, float, float]</span></tt>
             </div>
             <div id="l395"
-               class="code sev- "><tt><i>395</i> <span class="sd">            (s) - penalty strength; Default is 0.5</span></tt>
+               class="code sev- "><tt><i>395</i> <span class="sd">            a minimum positive support of a contrast set (p/P). When multiple values are</span></tt>
             </div>
             <div id="l396"
-               class="code sev- "><tt><i>396</i> <span class="sd">        penalty_saturation: float</span></tt>
+               class="code sev- "><tt><i>396</i> <span class="sd">            specified, a metainduction is performed; Default and recommended sequence</span></tt>
             </div>
             <div id="l397"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (85 > 79 characters)</li>
-               
-               </ul><tt><i>397</i> <span class="sd">            the value of p_new / P at which penalty reward saturates; Default is 0.2.</span></tt>
+               class="code sev- "><tt><i>397</i> <span class="sd">            is: 0.8, 0.5, 0.2, 0.1</span></tt>
             </div>
             <div id="l398"
-               class="code sev- "><tt><i>398</i> <span class="sd">        minsupp_new : float = 5.0</span></tt>
+               class="code sev- "><tt><i>398</i> <span class="sd">        max_neg2pos: float</span></tt>
             </div>
             <div id="l399"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (91 > 79 characters)</li>
-               
-               </ul><tt><i>399</i> <span class="sd">            a minimum number (or fraction, if value &lt; 1.0) of previously uncovered examples</span></tt>
+               class="code sev- "><tt><i>399</i> <span class="sd">            a maximum ratio of negative to positive supports (nP/pN); Default is 0.5</span></tt>
             </div>
             <div id="l400"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (101 > 79 characters)</li>
-               
-               </ul><tt><i>400</i> <span class="sd">             to be covered by a new rule (positive examples for classification problems); default: 5,</span></tt>
+               class="code sev- "><tt><i>400</i> <span class="sd">        max_passes_count: int</span></tt>
             </div>
             <div id="l401"
-               class="code sev- "><tt><i>401</i> <span class="sd">        induction_measure : :class:`rulekit.params.Measures` = \</span></tt>
+               class="code sev- "><tt><i>401</i> <span class="sd">            a maximum number of sequential covering passes for a single minsupp-all;</span></tt>
             </div>
             <div id="l402"
-               class="code sev- "><tt><i>402</i> <span class="sd">            :class:`rulekit.params.Measures.Correlation`</span></tt>
+               class="code sev- "><tt><i>402</i> <span class="sd">            Default is 5</span></tt>
             </div>
             <div id="l403"
-               class="code sev- "><tt><i>403</i> <span class="sd">            measure used during induction; default measure is correlation</span></tt>
+               class="code sev- "><tt><i>403</i> <span class="sd">        penalty_strength: float</span></tt>
             </div>
             <div id="l404"
-               class="code sev- "><tt><i>404</i> <span class="sd">        pruning_measure : Union[:class:`rulekit.params.Measures`, str] = \</span></tt>
+               class="code sev- "><tt><i>404</i> <span class="sd">            (s) - penalty strength; Default is 0.5</span></tt>
             </div>
             <div id="l405"
-               class="code sev- "><tt><i>405</i> <span class="sd">            :class:`rulekit.params.Measures.Correlation`</span></tt>
+               class="code sev- "><tt><i>405</i> <span class="sd">        penalty_saturation: float</span></tt>
             </div>
             <div id="l406"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (84 > 79 characters)</li>
-               
-               </ul><tt><i>406</i> <span class="sd">            measure used during pruning. Could be user defined (string), for example</span></tt>
+               class="code sev- "><tt><i>406</i> <span class="sd">            the value of p_new / P at which penalty reward saturates; Default is 0.2.</span></tt>
             </div>
             <div id="l407"
-               class="code sev- "><tt><i>407</i> <span class="sd">            :code:`2 * p / n`; default measure is correlation</span></tt>
+               class="code sev- "><tt><i>407</i> <span class="sd">        minsupp_new : float = 5.0</span></tt>
             </div>
             <div id="l408"
-               class="code sev- "><tt><i>408</i> <span class="sd">        voting_measure : :class:`rulekit.params.Measures` = \</span></tt>
+               class="code sev- "><tt><i>408</i> <span class="sd">            a minimum number (or fraction, if value &lt; 1.0) of previously uncovered</span></tt>
             </div>
             <div id="l409"
-               class="code sev- "><tt><i>409</i> <span class="sd">            :class:`rulekit.params.Measures.Correlation`</span></tt>
+               class="code sev- "><tt><i>409</i> <span class="sd">            examples to be covered by a new rule (positive examples for classification</span></tt>
             </div>
             <div id="l410"
-               class="code sev- "><tt><i>410</i> <span class="sd">            measure used during voting; default measure is correlation</span></tt>
+               class="code sev- "><tt><i>410</i> <span class="sd">            problems); default: 5,</span></tt>
             </div>
             <div id="l411"
-               class="code sev- "><tt><i>411</i> <span class="sd">        max_growing : int = 0.0</span></tt>
+               class="code sev- "><tt><i>411</i> <span class="sd">        induction_measure : :class:`rulekit.params.Measures` = \</span></tt>
             </div>
             <div id="l412"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (96 > 79 characters)</li>
-               
-               </ul><tt><i>412</i> <span class="sd">            non-negative integer representing maximum number of conditions which can be added to</span></tt>
+               class="code sev- "><tt><i>412</i> <span class="sd">            :class:`rulekit.params.Measures.Correlation`</span></tt>
             </div>
             <div id="l413"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (98 > 79 characters)</li>
-               
-               </ul><tt><i>413</i> <span class="sd">            the rule in the growing phase (use this parameter for large datasets if execution time</span></tt>
+               class="code sev- "><tt><i>413</i> <span class="sd">            measure used during induction; default measure is correlation</span></tt>
             </div>
             <div id="l414"
-               class="code sev- "><tt><i>414</i> <span class="sd">            is prohibitive); 0 indicates no limit; default: 0,</span></tt>
+               class="code sev- "><tt><i>414</i> <span class="sd">        pruning_measure : Union[:class:`rulekit.params.Measures`, str] = \</span></tt>
             </div>
             <div id="l415"
-               class="code sev- "><tt><i>415</i> <span class="sd">        enable_pruning : bool = True</span></tt>
+               class="code sev- "><tt><i>415</i> <span class="sd">            :class:`rulekit.params.Measures.Correlation`</span></tt>
             </div>
             <div id="l416"
-               class="code sev- "><tt><i>416</i> <span class="sd">            enable or disable pruning, default is True.</span></tt>
+               class="code sev- "><tt><i>416</i> <span class="sd">            measure used during pruning. Could be user defined (string), for example</span></tt>
             </div>
             <div id="l417"
-               class="code sev- "><tt><i>417</i> <span class="sd">        ignore_missing : bool = False</span></tt>
+               class="code sev- "><tt><i>417</i> <span class="sd">            :code:`2 * p / n`; default measure is correlation</span></tt>
             </div>
             <div id="l418"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (97 > 79 characters)</li>
-               
-               </ul><tt><i>418</i> <span class="sd">            boolean telling whether missing values should be ignored (by default, a missing value</span></tt>
+               class="code sev- "><tt><i>418</i> <span class="sd">        voting_measure : :class:`rulekit.params.Measures` = \</span></tt>
             </div>
             <div id="l419"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (100 > 79 characters)</li>
-               
-               </ul><tt><i>419</i> <span class="sd">             of given attribute is always considered as not fulfilling the condition build upon that</span></tt>
+               class="code sev- "><tt><i>419</i> <span class="sd">            :class:`rulekit.params.Measures.Correlation`</span></tt>
             </div>
             <div id="l420"
-               class="code sev- "><tt><i>420</i> <span class="sd">            attribute); default: False.</span></tt>
+               class="code sev- "><tt><i>420</i> <span class="sd">            measure used during voting; default measure is correlation</span></tt>
             </div>
             <div id="l421"
-               class="code sev- "><tt><i>421</i> <span class="sd">        max_uncovered_fraction : float = 0.0</span></tt>
+               class="code sev- "><tt><i>421</i> <span class="sd">        max_growing : int = 0.0</span></tt>
             </div>
             <div id="l422"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (95 > 79 characters)</li>
-               
-               </ul><tt><i>422</i> <span class="sd">            Floating-point number from [0,1] interval representing maximum fraction of examples</span></tt>
+               class="code sev- "><tt><i>422</i> <span class="sd">            non-negative integer representing maximum number of conditions which can be</span></tt>
             </div>
             <div id="l423"
-               class="code sev- "><tt><i>423</i> <span class="sd">            that may remain uncovered by the rule set, default: 0.0.</span></tt>
+               class="code sev- "><tt><i>423</i> <span class="sd">            added to the rule in the growing phase (use this parameter for large</span></tt>
             </div>
             <div id="l424"
-               class="code sev- "><tt><i>424</i> <span class="sd">        select_best_candidate : bool = False</span></tt>
+               class="code sev- "><tt><i>424</i> <span class="sd">            datasets if execution time is prohibitive); 0 indicates no limit; default: 0</span></tt>
             </div>
             <div id="l425"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (85 > 79 characters)</li>
-               
-               </ul><tt><i>425</i> <span class="sd">            Flag determining if best candidate should be selected from growing phase;</span></tt>
+               class="code sev- "><tt><i>425</i> <span class="sd">        enable_pruning : bool = True</span></tt>
             </div>
             <div id="l426"
-               class="code sev- "><tt><i>426</i> <span class="sd">            default: False.</span></tt>
+               class="code sev- "><tt><i>426</i> <span class="sd">            enable or disable pruning, default is True.</span></tt>
             </div>
             <div id="l427"
-               class="code sev- "><tt><i>427</i> <span class="sd">        complementary_conditions : bool = False</span></tt>
+               class="code sev- "><tt><i>427</i> <span class="sd">        ignore_missing : bool = False</span></tt>
             </div>
             <div id="l428"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (96 > 79 characters)</li>
-               
-               </ul><tt><i>428</i> <span class="sd">            If enabled, complementary conditions in the form a = !{value} for nominal attributes</span></tt>
+               class="code sev- "><tt><i>428</i> <span class="sd">            boolean telling whether missing values should be ignored (by default, a</span></tt>
             </div>
             <div id="l429"
-               class="code sev- "><tt><i>429</i> <span class="sd">            are supported.</span></tt>
+               class="code sev- "><tt><i>429</i> <span class="sd">            missing value of given attribute is always considered as not fulfilling the</span></tt>
             </div>
             <div id="l430"
-               class="code sev- "><tt><i>430</i> <span class="sd">        mean_based_regression : bool = True</span></tt>
+               class="code sev- "><tt><i>430</i> <span class="sd">            condition build upon that attribute); default: False.</span></tt>
             </div>
             <div id="l431"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (97 > 79 characters)</li>
-               
-               </ul><tt><i>431</i> <span class="sd">            Enable fast induction of mean-based regression rules instead of default median-based.</span></tt>
+               class="code sev- "><tt><i>431</i> <span class="sd">        max_uncovered_fraction : float = 0.0</span></tt>
             </div>
             <div id="l432"
-               class="code sev- "><tt><i>432</i> <span class="sd">        max_rule_count : int = 0</span></tt>
+               class="code sev- "><tt><i>432</i> <span class="sd">            Floating-point number from [0,1] interval representing maximum fraction of</span></tt>
             </div>
             <div id="l433"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (92 > 79 characters)</li>
-               
-               </ul><tt><i>433</i> <span class="sd">            Maximum number of rules to be generated (for classification data sets it applies</span></tt>
+               class="code sev- "><tt><i>433</i> <span class="sd">            examples that may remain uncovered by the rule set, default: 0.0.</span></tt>
             </div>
             <div id="l434"
-               class="code sev- "><tt><i>434</i> <span class="sd">             to a single class); 0 indicates no limit.</span></tt>
+               class="code sev- "><tt><i>434</i> <span class="sd">        select_best_candidate : bool = False</span></tt>
             </div>
             <div id="l435"
-               class="code sev- "><tt><i>435</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
+               class="code sev- "><tt><i>435</i> <span class="sd">            Flag determining if best candidate should be selected from growing phase;</span></tt>
             </div>
             <div id="l436"
-               class="code sev- "><tt><i>436</i>         <span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span></tt>
+               class="code sev- "><tt><i>436</i> <span class="sd">            default: False.</span></tt>
             </div>
             <div id="l437"
-               class="code sev- "><tt><i>437</i>             <span class="n">minsupp_all</span><span class="o">=</span><span class="n">minsupp_all</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>437</i> <span class="sd">        complementary_conditions : bool = False</span></tt>
             </div>
             <div id="l438"
-               class="code sev- "><tt><i>438</i>             <span class="n">max_neg2pos</span><span class="o">=</span><span class="n">max_neg2pos</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>438</i> <span class="sd">            If enabled, complementary conditions in the form a = !{value} for nominal</span></tt>
             </div>
             <div id="l439"
-               class="code sev- "><tt><i>439</i>             <span class="n">max_passes_count</span><span class="o">=</span><span class="n">max_passes_count</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>439</i> <span class="sd">            attributes are supported.</span></tt>
             </div>
             <div id="l440"
-               class="code sev- "><tt><i>440</i>             <span class="n">penalty_strength</span><span class="o">=</span><span class="n">penalty_strength</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>440</i> <span class="sd">        mean_based_regression : bool = True</span></tt>
             </div>
             <div id="l441"
-               class="code sev- "><tt><i>441</i>             <span class="n">penalty_saturation</span><span class="o">=</span><span class="n">penalty_saturation</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>441</i> <span class="sd">            Enable fast induction of mean-based regression rules instead of default</span></tt>
             </div>
             <div id="l442"
-               class="code sev- "><tt><i>442</i>             <span class="n">minsupp_new</span><span class="o">=</span><span class="n">minsupp_new</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>442</i> <span class="sd">            median-based.</span></tt>
             </div>
             <div id="l443"
-               class="code sev- "><tt><i>443</i>             <span class="n">induction_measure</span><span class="o">=</span><span class="n">induction_measure</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>443</i> <span class="sd">        max_rule_count : int = 0</span></tt>
             </div>
             <div id="l444"
-               class="code sev- "><tt><i>444</i>             <span class="n">pruning_measure</span><span class="o">=</span><span class="n">pruning_measure</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>444</i> <span class="sd">            Maximum number of rules to be generated; 0 indicates no limit.</span></tt>
             </div>
             <div id="l445"
-               class="code sev- "><tt><i>445</i>             <span class="n">voting_measure</span><span class="o">=</span><span class="n">voting_measure</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>445</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
             </div>
             <div id="l446"
-               class="code sev- "><tt><i>446</i>             <span class="n">max_growing</span><span class="o">=</span><span class="n">max_growing</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>446</i>         <span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span></tt>
             </div>
             <div id="l447"
-               class="code sev- "><tt><i>447</i>             <span class="n">enable_pruning</span><span class="o">=</span><span class="n">enable_pruning</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>447</i>             <span class="n">minsupp_all</span><span class="o">=</span><span class="n">minsupp_all</span><span class="p">,</span></tt>
             </div>
             <div id="l448"
-               class="code sev- "><tt><i>448</i>             <span class="n">ignore_missing</span><span class="o">=</span><span class="n">ignore_missing</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>448</i>             <span class="n">max_neg2pos</span><span class="o">=</span><span class="n">max_neg2pos</span><span class="p">,</span></tt>
             </div>
             <div id="l449"
-               class="code sev- "><tt><i>449</i>             <span class="n">max_uncovered_fraction</span><span class="o">=</span><span class="n">max_uncovered_fraction</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>449</i>             <span class="n">max_passes_count</span><span class="o">=</span><span class="n">max_passes_count</span><span class="p">,</span></tt>
             </div>
             <div id="l450"
-               class="code sev- "><tt><i>450</i>             <span class="n">select_best_candidate</span><span class="o">=</span><span class="n">select_best_candidate</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>450</i>             <span class="n">penalty_strength</span><span class="o">=</span><span class="n">penalty_strength</span><span class="p">,</span></tt>
             </div>
             <div id="l451"
-               class="code sev- "><tt><i>451</i>             <span class="n">complementary_conditions</span><span class="o">=</span><span class="n">complementary_conditions</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>451</i>             <span class="n">penalty_saturation</span><span class="o">=</span><span class="n">penalty_saturation</span><span class="p">,</span></tt>
             </div>
             <div id="l452"
-               class="code sev- "><tt><i>452</i>             <span class="n">mean_based_regression</span><span class="o">=</span><span class="n">mean_based_regression</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>452</i>             <span class="n">minsupp_new</span><span class="o">=</span><span class="n">minsupp_new</span><span class="p">,</span></tt>
             </div>
             <div id="l453"
-               class="code sev- "><tt><i>453</i>             <span class="n">max_rule_count</span><span class="o">=</span><span class="n">max_rule_count</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>453</i>             <span class="n">induction_measure</span><span class="o">=</span><span class="n">induction_measure</span><span class="p">,</span></tt>
             </div>
             <div id="l454"
-               class="code sev- "><tt><i>454</i>         <span class="p">)</span></tt>
+               class="code sev- "><tt><i>454</i>             <span class="n">pruning_measure</span><span class="o">=</span><span class="n">pruning_measure</span><span class="p">,</span></tt>
             </div>
             <div id="l455"
-               class="code sev- "><tt><i>455</i>         <span class="bp">self</span><span class="o">.</span><span class="n">contrast_attribute</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="kc">None</span></tt>
+               class="code sev- "><tt><i>455</i>             <span class="n">voting_measure</span><span class="o">=</span><span class="n">voting_measure</span><span class="p">,</span></tt>
             </div>
             <div id="l456"
-               class="code sev- "><tt><i>456</i>         <span class="bp">self</span><span class="o">.</span><span class="n">model</span><span class="p">:</span> <span class="n">RuleSet</span><span class="p">[</span><span class="n">RegressionRule</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span></tt>
+               class="code sev- "><tt><i>456</i>             <span class="n">max_growing</span><span class="o">=</span><span class="n">max_growing</span><span class="p">,</span></tt>
             </div>
             <div id="l457"
-               class="code sev- "><tt><i>457</i> &nbsp;</tt>
+               class="code sev- "><tt><i>457</i>             <span class="n">enable_pruning</span><span class="o">=</span><span class="n">enable_pruning</span><span class="p">,</span></tt>
             </div>
             <div id="l458"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (135 > 79 characters)</li>
-               
-               </ul><tt><i>458</i>     <span class="k">def</span> <span class="nf">fit</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">:</span> <span class="n">Data</span><span class="p">,</span> <span class="n">labels</span><span class="p">:</span> <span class="n">Data</span><span class="p">,</span> <span class="n">contrast_attribute</span><span class="p">:</span> <span class="nb">str</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ContrastSetRuleRegressor</span><span class="p">:</span>  <span class="c1"># pylint: disable=arguments-differ</span></tt>
+               class="code sev- "><tt><i>458</i>             <span class="n">ignore_missing</span><span class="o">=</span><span class="n">ignore_missing</span><span class="p">,</span></tt>
             </div>
             <div id="l459"
-               class="code sev- "><tt><i>459</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Train model on given dataset.</span></tt>
+               class="code sev- "><tt><i>459</i>             <span class="n">max_uncovered_fraction</span><span class="o">=</span><span class="n">max_uncovered_fraction</span><span class="p">,</span></tt>
             </div>
             <div id="l460"
-               class="code sev- "><tt><i>460</i> &nbsp;</tt>
+               class="code sev- "><tt><i>460</i>             <span class="n">select_best_candidate</span><span class="o">=</span><span class="n">select_best_candidate</span><span class="p">,</span></tt>
             </div>
             <div id="l461"
-               class="code sev- "><tt><i>461</i> <span class="sd">        Parameters</span></tt>
+               class="code sev- "><tt><i>461</i>             <span class="n">complementary_conditions</span><span class="o">=</span><span class="n">complementary_conditions</span><span class="p">,</span></tt>
             </div>
             <div id="l462"
-               class="code sev- "><tt><i>462</i> <span class="sd">        ----------</span></tt>
+               class="code sev- "><tt><i>462</i>             <span class="n">mean_based_regression</span><span class="o">=</span><span class="n">mean_based_regression</span><span class="p">,</span></tt>
             </div>
             <div id="l463"
-               class="code sev- "><tt><i>463</i> <span class="sd">        values : :class:`rulekit.operator.Data`</span></tt>
+               class="code sev- "><tt><i>463</i>             <span class="n">max_rule_count</span><span class="o">=</span><span class="n">max_rule_count</span><span class="p">,</span></tt>
             </div>
             <div id="l464"
-               class="code sev- "><tt><i>464</i> <span class="sd">            attributes</span></tt>
+               class="code sev- "><tt><i>464</i>         <span class="p">)</span></tt>
             </div>
             <div id="l465"
-               class="code sev- "><tt><i>465</i> <span class="sd">        labels : :class:`rulekit.operator.Data`</span></tt>
+               class="code sev- "><tt><i>465</i>         <span class="bp">self</span><span class="o">.</span><span class="n">contrast_attribute</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="kc">None</span></tt>
             </div>
             <div id="l466"
-               class="code sev- "><tt><i>466</i> <span class="sd">            target values</span></tt>
+               class="code sev- "><tt><i>466</i>         <span class="bp">self</span><span class="o">.</span><span class="n">model</span><span class="p">:</span> <span class="n">RuleSet</span><span class="p">[</span><span class="n">RegressionRule</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span></tt>
             </div>
             <div id="l467"
-               class="code sev- "><tt><i>467</i> <span class="sd">        contrast_attribute: str</span></tt>
+               class="code sev- "><tt><i>467</i> &nbsp;</tt>
             </div>
             <div id="l468"
-               class="code sev- "><tt><i>468</i> <span class="sd">            group attribute</span></tt>
+               class="code sev- "><tt><i>468</i>     <span class="k">def</span> <span class="nf">fit</span><span class="p">(</span></tt>
             </div>
             <div id="l469"
-               class="code sev- "><tt><i>469</i> <span class="sd">        Returns</span></tt>
+               class="code sev- "><tt><i>469</i>         <span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">:</span> <span class="n">Data</span><span class="p">,</span> <span class="n">labels</span><span class="p">:</span> <span class="n">Data</span><span class="p">,</span> <span class="n">contrast_attribute</span><span class="p">:</span> <span class="nb">str</span></tt>
             </div>
             <div id="l470"
-               class="code sev- "><tt><i>470</i> <span class="sd">        -------</span></tt>
+               class="code sev- "><tt><i>470</i>     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ContrastSetRuleRegressor</span><span class="p">:</span>  <span class="c1"># pylint: disable=arguments-differ</span></tt>
             </div>
             <div id="l471"
-               class="code sev- "><tt><i>471</i> <span class="sd">        self : ContrastSetRuleRegressor</span></tt>
+               class="code sev- "><tt><i>471</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Train model on given dataset.</span></tt>
             </div>
             <div id="l472"
-               class="code sev- "><tt><i>472</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
+               class="code sev- "><tt><i>472</i> &nbsp;</tt>
             </div>
             <div id="l473"
-               class="code sev- "><tt><i>473</i>         <span class="n">RuleRegressor</span><span class="o">.</span><span class="n">_validate_labels</span><span class="p">(</span>  <span class="c1"># pylint: disable=protected-access</span></tt>
+               class="code sev- "><tt><i>473</i> <span class="sd">        Parameters</span></tt>
             </div>
             <div id="l474"
-               class="code sev- "><tt><i>474</i>             <span class="bp">self</span><span class="p">,</span> <span class="n">labels</span></tt>
+               class="code sev- "><tt><i>474</i> <span class="sd">        ----------</span></tt>
             </div>
             <div id="l475"
-               class="code sev- "><tt><i>475</i>         <span class="p">)</span></tt>
+               class="code sev- "><tt><i>475</i> <span class="sd">        values : :class:`rulekit.operator.Data`</span></tt>
             </div>
             <div id="l476"
-               class="code sev- "><tt><i>476</i>         <span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">values</span><span class="p">,</span> <span class="n">labels</span><span class="p">,</span> <span class="n">contrast_attribute</span><span class="o">=</span><span class="n">contrast_attribute</span><span class="p">)</span></tt>
+               class="code sev- "><tt><i>476</i> <span class="sd">            attributes</span></tt>
             </div>
             <div id="l477"
-               class="code sev- "><tt><i>477</i>         <span class="bp">self</span><span class="o">.</span><span class="n">contrast_attribute</span> <span class="o">=</span> <span class="n">contrast_attribute</span></tt>
+               class="code sev- "><tt><i>477</i> <span class="sd">        labels : :class:`rulekit.operator.Data`</span></tt>
             </div>
             <div id="l478"
-               class="code sev- "><tt><i>478</i>         <span class="k">return</span> <span class="bp">self</span></tt>
+               class="code sev- "><tt><i>478</i> <span class="sd">            target values</span></tt>
             </div>
             <div id="l479"
-               class="code sev- "><tt><i>479</i> &nbsp;</tt>
+               class="code sev- "><tt><i>479</i> <span class="sd">        contrast_attribute: str</span></tt>
             </div>
             <div id="l480"
-               class="code sev- "><tt><i>480</i>     <span class="k">def</span> <span class="nf">predict</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">:</span> <span class="n">Data</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">:</span></tt>
+               class="code sev- "><tt><i>480</i> <span class="sd">            group attribute</span></tt>
             </div>
             <div id="l481"
-               class="code sev- "><tt><i>481</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Perform prediction and returns predicted values.</span></tt>
+               class="code sev- "><tt><i>481</i> <span class="sd">        Returns</span></tt>
             </div>
             <div id="l482"
-               class="code sev- "><tt><i>482</i> &nbsp;</tt>
+               class="code sev- "><tt><i>482</i> <span class="sd">        -------</span></tt>
             </div>
             <div id="l483"
-               class="code sev- "><tt><i>483</i> <span class="sd">        Parameters</span></tt>
+               class="code sev- "><tt><i>483</i> <span class="sd">        self : ContrastSetRuleRegressor</span></tt>
             </div>
             <div id="l484"
-               class="code sev- "><tt><i>484</i> <span class="sd">        ----------</span></tt>
+               class="code sev- "><tt><i>484</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
             </div>
             <div id="l485"
-               class="code sev- "><tt><i>485</i> <span class="sd">        values : :class:`rulekit.operator.Data`</span></tt>
+               class="code sev- "><tt><i>485</i>         <span class="n">RuleRegressor</span><span class="o">.</span><span class="n">_validate_labels</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">labels</span><span class="p">)</span>  <span class="c1"># pylint: disable=protected-access</span></tt>
             </div>
             <div id="l486"
-               class="code sev- "><tt><i>486</i> <span class="sd">            attributes</span></tt>
+               class="code sev- "><tt><i>486</i>         <span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">values</span><span class="p">,</span> <span class="n">labels</span><span class="p">,</span> <span class="n">contrast_attribute</span><span class="o">=</span><span class="n">contrast_attribute</span><span class="p">)</span></tt>
             </div>
             <div id="l487"
-               class="code sev- "><tt><i>487</i> &nbsp;</tt>
+               class="code sev- "><tt><i>487</i>         <span class="bp">self</span><span class="o">.</span><span class="n">contrast_attribute</span> <span class="o">=</span> <span class="n">contrast_attribute</span></tt>
             </div>
             <div id="l488"
-               class="code sev- "><tt><i>488</i> <span class="sd">        Returns</span></tt>
+               class="code sev- "><tt><i>488</i>         <span class="k">return</span> <span class="bp">self</span></tt>
             </div>
             <div id="l489"
-               class="code sev- "><tt><i>489</i> <span class="sd">        -------</span></tt>
+               class="code sev- "><tt><i>489</i> &nbsp;</tt>
             </div>
             <div id="l490"
-               class="code sev- "><tt><i>490</i> <span class="sd">        result : np.ndarray</span></tt>
+               class="code sev- "><tt><i>490</i>     <span class="k">def</span> <span class="nf">predict</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">:</span> <span class="n">Data</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">:</span></tt>
             </div>
             <div id="l491"
-               class="code sev- "><tt><i>491</i> <span class="sd">            predicted values</span></tt>
+               class="code sev- "><tt><i>491</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Perform prediction and returns predicted values.</span></tt>
             </div>
             <div id="l492"
-               class="code sev- "><tt><i>492</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
+               class="code sev- "><tt><i>492</i> &nbsp;</tt>
             </div>
             <div id="l493"
-               class="code sev- "><tt><i>493</i>         <span class="k">return</span> <span class="n">RuleRegressor</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">)</span></tt>
+               class="code sev- "><tt><i>493</i> <span class="sd">        Parameters</span></tt>
             </div>
             <div id="l494"
-               class="code sev- "><tt><i>494</i> &nbsp;</tt>
+               class="code sev- "><tt><i>494</i> <span class="sd">        ----------</span></tt>
             </div>
             <div id="l495"
-               class="code sev- "><tt><i>495</i>     <span class="k">def</span> <span class="nf">score</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">:</span> <span class="n">Data</span><span class="p">,</span> <span class="n">labels</span><span class="p">:</span> <span class="n">Data</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">float</span><span class="p">:</span></tt>
+               class="code sev- "><tt><i>495</i> <span class="sd">        values : :class:`rulekit.operator.Data`</span></tt>
             </div>
             <div id="l496"
-               class="code sev- "><tt><i>496</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Return the coefficient of determination R2 of the prediction</span></tt>
+               class="code sev- "><tt><i>496</i> <span class="sd">            attributes</span></tt>
             </div>
             <div id="l497"
                class="code sev- "><tt><i>497</i> &nbsp;</tt>
             </div>
             <div id="l498"
-               class="code sev- "><tt><i>498</i> <span class="sd">        Parameters</span></tt>
+               class="code sev- "><tt><i>498</i> <span class="sd">        Returns</span></tt>
             </div>
             <div id="l499"
-               class="code sev- "><tt><i>499</i> <span class="sd">        ----------</span></tt>
+               class="code sev- "><tt><i>499</i> <span class="sd">        -------</span></tt>
             </div>
             <div id="l500"
-               class="code sev- "><tt><i>500</i> <span class="sd">        values : :class:`rulekit.operator.Data`</span></tt>
+               class="code sev- "><tt><i>500</i> <span class="sd">        result : np.ndarray</span></tt>
             </div>
             <div id="l501"
-               class="code sev- "><tt><i>501</i> <span class="sd">            attributes</span></tt>
+               class="code sev- "><tt><i>501</i> <span class="sd">            predicted values</span></tt>
             </div>
             <div id="l502"
-               class="code sev- "><tt><i>502</i> <span class="sd">        labels : :class:`rulekit.operator.Data`</span></tt>
+               class="code sev- "><tt><i>502</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
             </div>
             <div id="l503"
-               class="code sev- "><tt><i>503</i> <span class="sd">            true target values</span></tt>
+               class="code sev- "><tt><i>503</i>         <span class="k">return</span> <span class="n">RuleRegressor</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">)</span></tt>
             </div>
             <div id="l504"
                class="code sev- "><tt><i>504</i> &nbsp;</tt>
             </div>
             <div id="l505"
-               class="code sev- "><tt><i>505</i> <span class="sd">        Returns</span></tt>
+               class="code sev- "><tt><i>505</i>     <span class="k">def</span> <span class="nf">score</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">:</span> <span class="n">Data</span><span class="p">,</span> <span class="n">labels</span><span class="p">:</span> <span class="n">Data</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">float</span><span class="p">:</span></tt>
             </div>
             <div id="l506"
-               class="code sev- "><tt><i>506</i> <span class="sd">        -------</span></tt>
+               class="code sev- "><tt><i>506</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Return the coefficient of determination R2 of the prediction</span></tt>
             </div>
             <div id="l507"
-               class="code sev- "><tt><i>507</i> <span class="sd">        score : float</span></tt>
+               class="code sev- "><tt><i>507</i> &nbsp;</tt>
             </div>
             <div id="l508"
-               class="code sev- "><tt><i>508</i> <span class="sd">            R2 of self.predict(values) wrt. labels.</span></tt>
+               class="code sev- "><tt><i>508</i> <span class="sd">        Parameters</span></tt>
             </div>
             <div id="l509"
-               class="code sev- "><tt><i>509</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
+               class="code sev- "><tt><i>509</i> <span class="sd">        ----------</span></tt>
             </div>
             <div id="l510"
-               class="code sev- "><tt><i>510</i>         <span class="k">return</span> <span class="n">RuleRegressor</span><span class="o">.</span><span class="n">score</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">,</span> <span class="n">labels</span><span class="p">)</span></tt>
+               class="code sev- "><tt><i>510</i> <span class="sd">        values : :class:`rulekit.operator.Data`</span></tt>
             </div>
             <div id="l511"
-               class="code sev- "><tt><i>511</i> &nbsp;</tt>
+               class="code sev- "><tt><i>511</i> <span class="sd">            attributes</span></tt>
             </div>
             <div id="l512"
-               class="code sev- "><tt><i>512</i>     <span class="k">def</span> <span class="nf">__getstate__</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">dict</span><span class="p">:</span></tt>
+               class="code sev- "><tt><i>512</i> <span class="sd">        labels : :class:`rulekit.operator.Data`</span></tt>
             </div>
             <div id="l513"
-               class="code sev- "><tt><i>513</i>         <span class="k">return</span> <span class="p">{</span><span class="o">**</span><span class="n">BaseOperator</span><span class="o">.</span><span class="n">__getstate__</span><span class="p">(</span><span class="bp">self</span><span class="p">),</span> <span class="o">**</span><span class="p">{</span></tt>
+               class="code sev- "><tt><i>513</i> <span class="sd">            true target values</span></tt>
             </div>
             <div id="l514"
-               class="code sev- "><tt><i>514</i>             <span class="s1">&#39;contrast_attribute&#39;</span><span class="p">:</span> <span class="bp">self</span><span class="o">.</span><span class="n">contrast_attribute</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>514</i> &nbsp;</tt>
             </div>
             <div id="l515"
-               class="code sev- "><tt><i>515</i>         <span class="p">}}</span></tt>
+               class="code sev- "><tt><i>515</i> <span class="sd">        Returns</span></tt>
             </div>
             <div id="l516"
-               class="code sev- "><tt><i>516</i> &nbsp;</tt>
+               class="code sev- "><tt><i>516</i> <span class="sd">        -------</span></tt>
             </div>
             <div id="l517"
-               class="code sev- "><tt><i>517</i>     <span class="k">def</span> <span class="nf">__setstate__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">state</span><span class="p">:</span> <span class="nb">dict</span><span class="p">):</span></tt>
+               class="code sev- "><tt><i>517</i> <span class="sd">        score : float</span></tt>
             </div>
             <div id="l518"
-               class="code sev- "><tt><i>518</i>         <span class="n">BaseOperator</span><span class="o">.</span><span class="n">__setstate__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">state</span><span class="p">)</span></tt>
+               class="code sev- "><tt><i>518</i> <span class="sd">            R2 of self.predict(values) wrt. labels.</span></tt>
             </div>
             <div id="l519"
-               class="code sev- "><tt><i>519</i>         <span class="bp">self</span><span class="o">.</span><span class="n">contrast_attribute</span> <span class="o">=</span> <span class="n">state</span><span class="p">[</span><span class="s1">&#39;contrast_attribute&#39;</span><span class="p">]</span></tt>
+               class="code sev- "><tt><i>519</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
             </div>
             <div id="l520"
-               class="code sev- "><tt><i>520</i> &nbsp;</tt>
+               class="code sev- "><tt><i>520</i>         <span class="k">return</span> <span class="n">RuleRegressor</span><span class="o">.</span><span class="n">score</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">,</span> <span class="n">labels</span><span class="p">)</span></tt>
             </div>
             <div id="l521"
-               class="code sev- "><tt><i>521</i>     <span class="k">def</span> <span class="nf">_get_problem_type</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ProblemType</span><span class="p">:</span></tt>
+               class="code sev- "><tt><i>521</i> &nbsp;</tt>
             </div>
             <div id="l522"
-               class="code sev- "><tt><i>522</i>         <span class="k">return</span> <span class="n">ProblemType</span><span class="o">.</span><span class="n">CONTRAST_REGRESSION</span></tt>
+               class="code sev- "><tt><i>522</i>     <span class="k">def</span> <span class="nf">__getstate__</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">dict</span><span class="p">:</span></tt>
+            </div>
+            <div id="l523"
+               class="code sev- "><tt><i>523</i>         <span class="k">return</span> <span class="p">{</span></tt>
+            </div>
+            <div id="l524"
+               class="code sev- "><tt><i>524</i>             <span class="o">**</span><span class="n">BaseOperator</span><span class="o">.</span><span class="n">__getstate__</span><span class="p">(</span><span class="bp">self</span><span class="p">),</span></tt>
+            </div>
+            <div id="l525"
+               class="code sev- "><tt><i>525</i>             <span class="o">**</span><span class="p">{</span></tt>
+            </div>
+            <div id="l526"
+               class="code sev- "><tt><i>526</i>                 <span class="s2">&quot;contrast_attribute&quot;</span><span class="p">:</span> <span class="bp">self</span><span class="o">.</span><span class="n">contrast_attribute</span><span class="p">,</span></tt>
+            </div>
+            <div id="l527"
+               class="code sev- "><tt><i>527</i>             <span class="p">},</span></tt>
+            </div>
+            <div id="l528"
+               class="code sev- "><tt><i>528</i>         <span class="p">}</span></tt>
+            </div>
+            <div id="l529"
+               class="code sev- "><tt><i>529</i> &nbsp;</tt>
+            </div>
+            <div id="l530"
+               class="code sev- "><tt><i>530</i>     <span class="k">def</span> <span class="nf">__setstate__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">state</span><span class="p">:</span> <span class="nb">dict</span><span class="p">):</span></tt>
+            </div>
+            <div id="l531"
+               class="code sev- "><tt><i>531</i>         <span class="n">BaseOperator</span><span class="o">.</span><span class="n">__setstate__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">state</span><span class="p">)</span></tt>
+            </div>
+            <div id="l532"
+               class="code sev- "><tt><i>532</i>         <span class="bp">self</span><span class="o">.</span><span class="n">contrast_attribute</span> <span class="o">=</span> <span class="n">state</span><span class="p">[</span><span class="s2">&quot;contrast_attribute&quot;</span><span class="p">]</span></tt>
+            </div>
+            <div id="l533"
+               class="code sev- "><tt><i>533</i> &nbsp;</tt>
+            </div>
+            <div id="l534"
+               class="code sev- "><tt><i>534</i>     <span class="k">def</span> <span class="nf">_get_problem_type</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ProblemType</span><span class="p">:</span></tt>
+            </div>
+            <div id="l535"
+               class="code sev- "><tt><i>535</i>         <span class="k">return</span> <span class="n">ProblemType</span><span class="o">.</span><span class="n">CONTRAST_REGRESSION</span></tt>
             </div>
             
          </div>
diff --git a/docs/reports/flake8/rulekit.rules.report.html b/docs/reports/flake8/rulekit.rules.report.html
deleted file mode 100644
index 060a32c..0000000
--- a/docs/reports/flake8/rulekit.rules.report.html
+++ /dev/null
@@ -1,147 +0,0 @@
-<!DOCTYPE html>
-<html>
-   <head>
-      <title>flake8 violations: rulekit\rules.py</title>
-      <meta http-equiv="Content-Type" value="text/html; charset=UTF-8">
-      <link rel="stylesheet" href="styles.css">
-<script>
-function bindHandler(link) {
-   var code = link.getAttribute('data-code');
-   var key = location.pathname + '#' + code;
-
-   var ul = link.parentNode.querySelector('.details');
-   if (sessionStorage[key] != 'open') {
-      ul.style.display = 'none';
-   }
-   link.addEventListener('click', function (event) {
-      if (!ul.style.display || ul.style.display == 'none') {
-         ul.style.display = 'block';
-         sessionStorage[key] = 'open';
-      } else {
-         ul.style.display = 'none';
-         sessionStorage[key] = 'closed';
-      }
-   });
-}
-
-window.addEventListener('DOMContentLoaded', function () {
-   var links = document.querySelectorAll('#index > li > a');
-   for (var i = 0; i < links.length; i++) {
-      bindHandler(links[i]);
-   }
-});
-</script>
-   </head>
-   <body>
-      <div id="masthead" class="sev-2"></div>
-      <div id="page">
-         <p id="srclink">
-            <a title="View full annotated source"
-               href="rulekit.rules.source.html">
-               <img src="file.svg" alt="&#x2261;">
-            </a></p>
-         <h1>
-            <a href="index.html">
-               <img src="back.svg" alt="&#x2B05;">
-               rulekit\rules.py
-            </a>
-         </h1>
-
-         <ul id="index">
-         
-         <li>
-            <a data-code="E501">
-               <span class="count sev-2">
-                  11
-               </span>
-               <strong>E501:</strong> line too long (96 > 79 characters)
-               
-                  (and 9 similar)
-               
-            </a>
-            <ul class="details">
-            <li>
-               
-               <p>Line too long (96 > 79 characters):</p>
-               
-               <a href="rulekit.rules.source.html#l24">
-                  <tt><i>24</i>         <span class="bp">self</span><span class="o">.</span><span class="n">maximum_uncovered_fraction</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_java_object</span><span class="o">.</span><span class="n">getMaximumUncoveredFraction</span><span class="p">()</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (87 > 79 characters):</p>
-               
-               <a href="rulekit.rules.source.html#l27">
-                  <tt><i>27</i>         <span class="bp">self</span><span class="o">.</span><span class="n">max_growing_condition</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_java_object</span><span class="o">.</span><span class="n">getMaxGrowingConditions</span><span class="p">()</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (92 > 79 characters):</p>
-               
-               <a href="rulekit.rules.source.html#l35">
-                  <tt><i>35</i>         <span class="k">return</span> <span class="n">InductionParameters</span><span class="o">.</span><span class="n">_get_measure_str</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_java_object</span><span class="o">.</span><span class="n">getInductionMeasure</span><span class="p">())</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (90 > 79 characters):</p>
-               
-               <a href="rulekit.rules.source.html#l43">
-                  <tt><i>43</i>         <span class="k">return</span> <span class="n">InductionParameters</span><span class="o">.</span><span class="n">_get_measure_str</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_java_object</span><span class="o">.</span><span class="n">getPruningMeasure</span><span class="p">())</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (89 > 79 characters):</p>
-               
-               <a href="rulekit.rules.source.html#l51">
-                  <tt><i>51</i>         <span class="k">return</span> <span class="n">InductionParameters</span><span class="o">.</span><span class="n">_get_measure_str</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_java_object</span><span class="o">.</span><span class="n">getVotingMeasure</span><span class="p">())</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (82 > 79 characters):</p>
-               
-               <a href="rulekit.rules.source.html#l173">
-                  <tt><i>173</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_kaplan_meier_estimator</span><span class="p">:</span> <span class="n">KaplanMeierEstimator</span> <span class="o">=</span> <span class="n">KaplanMeierEstimator</span><span class="p">(</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (99 > 79 characters):</p>
-               
-               <a href="rulekit.rules.source.html#l240">
-                  <tt><i>240</i>             <span class="n">covering_info</span> <span class="o">=</span> <span class="n">rule</span><span class="o">.</span><span class="n">_java_object</span><span class="o">.</span><span class="n">coversUnlabelled</span><span class="p">(</span>  <span class="c1"># pylint: disable=protected-access</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (98 > 79 characters):</p>
-               
-               <a href="rulekit.rules.source.html#l323">
-                  <tt><i>323</i> <span class="sd">            Significance of the rule set with false discovery rate correction. Dictionary contains</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (91 > 79 characters):</p>
-               
-               <a href="rulekit.rules.source.html#l324">
-                  <tt><i>324</i> <span class="sd">            two fields: *fraction* (fraction of rules significant at assumed level) and *p*</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (92 > 79 characters):</p>
-               
-               <a href="rulekit.rules.source.html#l338">
-                  <tt><i>338</i> <span class="sd">            Significance of the rule set with familiy-wise error rate correction. Dictionary</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (93 > 79 characters):</p>
-               
-               <a href="rulekit.rules.source.html#l339">
-                  <tt><i>339</i> <span class="sd">             contains two fields: *fraction* (fraction of rules significant at assumed level)</span></tt>
-               </a>
-            </li>
-            </ul>
-         </li>
-         
-         </ul>
-      </div>
-   </body>
-</html>
\ No newline at end of file
diff --git a/docs/reports/flake8/rulekit.rules.source.html b/docs/reports/flake8/rulekit.rules.source.html
deleted file mode 100644
index ab29a44..0000000
--- a/docs/reports/flake8/rulekit.rules.source.html
+++ /dev/null
@@ -1,1172 +0,0 @@
-<!DOCTYPE html>
-<html>
-   <head>
-      <title>rulekit\rules.py - flake8 annotated source</title>
-      <meta http-equiv="Content-Type" value="text/html; charset=UTF-8">
-      <link rel="stylesheet" href="styles.css">
-   </head>
-   <body>
-      <div id="masthead" class="sev-2"></div>
-      <div id="page">
-         <h1>
-            <a href="rulekit.rules.report.html">
-               <img src="back.svg" alt="&#x2B05;">
-               rulekit\rules.py source
-            </a>
-         </h1>
-
-         <div id="doc">
-            <div id="l1"
-               class="code sev- "><tt><i>1</i> <span class="sd">&quot;&quot;&quot;Contains classes representing rules and rulesets.</span></tt>
-            </div>
-            <div id="l2"
-               class="code sev- "><tt><i>2</i> <span class="sd">&quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l3"
-               class="code sev- "><tt><i>3</i> <span class="kn">from</span> <span class="nn">typing</span> <span class="kn">import</span> <span class="n">Generic</span></tt>
-            </div>
-            <div id="l4"
-               class="code sev- "><tt><i>4</i> <span class="kn">from</span> <span class="nn">typing</span> <span class="kn">import</span> <span class="n">TypeVar</span></tt>
-            </div>
-            <div id="l5"
-               class="code sev- "><tt><i>5</i> <span class="kn">from</span> <span class="nn">typing</span> <span class="kn">import</span> <span class="n">Union</span></tt>
-            </div>
-            <div id="l6"
-               class="code sev- "><tt><i>6</i> &nbsp;</tt>
-            </div>
-            <div id="l7"
-               class="code sev- "><tt><i>7</i> <span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span></tt>
-            </div>
-            <div id="l8"
-               class="code sev- "><tt><i>8</i> <span class="kn">from</span> <span class="nn">jpype</span> <span class="kn">import</span> <span class="n">JObject</span></tt>
-            </div>
-            <div id="l9"
-               class="code sev- "><tt><i>9</i> &nbsp;</tt>
-            </div>
-            <div id="l10"
-               class="code sev- "><tt><i>10</i> <span class="kn">from</span> <span class="nn">rulekit.kaplan_meier</span> <span class="kn">import</span> <span class="n">KaplanMeierEstimator</span></tt>
-            </div>
-            <div id="l11"
-               class="code sev- "><tt><i>11</i> <span class="kn">from</span> <span class="nn">rulekit.params</span> <span class="kn">import</span> <span class="n">Measures</span></tt>
-            </div>
-            <div id="l12"
-               class="code sev- "><tt><i>12</i> <span class="kn">from</span> <span class="nn">rulekit.stats</span> <span class="kn">import</span> <span class="n">RuleSetStatistics</span></tt>
-            </div>
-            <div id="l13"
-               class="code sev- "><tt><i>13</i> <span class="kn">from</span> <span class="nn">rulekit.stats</span> <span class="kn">import</span> <span class="n">RuleStatistics</span></tt>
-            </div>
-            <div id="l14"
-               class="code sev- "><tt><i>14</i> &nbsp;</tt>
-            </div>
-            <div id="l15"
-               class="code sev- "><tt><i>15</i> &nbsp;</tt>
-            </div>
-            <div id="l16"
-               class="code sev- "><tt><i>16</i> <span class="k">class</span> <span class="nc">InductionParameters</span><span class="p">:</span></tt>
-            </div>
-            <div id="l17"
-               class="code sev- "><tt><i>17</i> <span class="w">    </span><span class="sd">&quot;&quot;&quot;Induction parameters.</span></tt>
-            </div>
-            <div id="l18"
-               class="code sev- "><tt><i>18</i> <span class="sd">    &quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l19"
-               class="code sev- "><tt><i>19</i> &nbsp;</tt>
-            </div>
-            <div id="l20"
-               class="code sev- "><tt><i>20</i>     <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">java_object</span><span class="p">):</span></tt>
-            </div>
-            <div id="l21"
-               class="code sev- "><tt><i>21</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_java_object</span> <span class="o">=</span> <span class="n">java_object</span></tt>
-            </div>
-            <div id="l22"
-               class="code sev- "><tt><i>22</i> &nbsp;</tt>
-            </div>
-            <div id="l23"
-               class="code sev- "><tt><i>23</i>         <span class="bp">self</span><span class="o">.</span><span class="n">minimum_covered</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_java_object</span><span class="o">.</span><span class="n">getMinimumCovered</span><span class="p">()</span></tt>
-            </div>
-            <div id="l24"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (96 > 79 characters)</li>
-               
-               </ul><tt><i>24</i>         <span class="bp">self</span><span class="o">.</span><span class="n">maximum_uncovered_fraction</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_java_object</span><span class="o">.</span><span class="n">getMaximumUncoveredFraction</span><span class="p">()</span></tt>
-            </div>
-            <div id="l25"
-               class="code sev- "><tt><i>25</i>         <span class="bp">self</span><span class="o">.</span><span class="n">ignore_missing</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_java_object</span><span class="o">.</span><span class="n">isIgnoreMissing</span><span class="p">()</span></tt>
-            </div>
-            <div id="l26"
-               class="code sev- "><tt><i>26</i>         <span class="bp">self</span><span class="o">.</span><span class="n">pruning_enabled</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_java_object</span><span class="o">.</span><span class="n">isPruningEnabled</span><span class="p">()</span></tt>
-            </div>
-            <div id="l27"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (87 > 79 characters)</li>
-               
-               </ul><tt><i>27</i>         <span class="bp">self</span><span class="o">.</span><span class="n">max_growing_condition</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_java_object</span><span class="o">.</span><span class="n">getMaxGrowingConditions</span><span class="p">()</span></tt>
-            </div>
-            <div id="l28"
-               class="code sev- "><tt><i>28</i> &nbsp;</tt>
-            </div>
-            <div id="l29"
-               class="code sev- "><tt><i>29</i>     <span class="nd">@property</span></tt>
-            </div>
-            <div id="l30"
-               class="code sev- "><tt><i>30</i>     <span class="k">def</span> <span class="nf">induction_measure</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Union</span><span class="p">[</span><span class="n">Measures</span><span class="p">,</span> <span class="nb">str</span><span class="p">]:</span></tt>
-            </div>
-            <div id="l31"
-               class="code sev- "><tt><i>31</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l32"
-               class="code sev- "><tt><i>32</i> <span class="sd">        Returns:</span></tt>
-            </div>
-            <div id="l33"
-               class="code sev- "><tt><i>33</i> <span class="sd">            Union[Measures, str]: Measure used for induction</span></tt>
-            </div>
-            <div id="l34"
-               class="code sev- "><tt><i>34</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l35"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (92 > 79 characters)</li>
-               
-               </ul><tt><i>35</i>         <span class="k">return</span> <span class="n">InductionParameters</span><span class="o">.</span><span class="n">_get_measure_str</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_java_object</span><span class="o">.</span><span class="n">getInductionMeasure</span><span class="p">())</span></tt>
-            </div>
-            <div id="l36"
-               class="code sev- "><tt><i>36</i> &nbsp;</tt>
-            </div>
-            <div id="l37"
-               class="code sev- "><tt><i>37</i>     <span class="nd">@property</span></tt>
-            </div>
-            <div id="l38"
-               class="code sev- "><tt><i>38</i>     <span class="k">def</span> <span class="nf">pruning_measure</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Union</span><span class="p">[</span><span class="n">Measures</span><span class="p">,</span> <span class="nb">str</span><span class="p">]:</span></tt>
-            </div>
-            <div id="l39"
-               class="code sev- "><tt><i>39</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l40"
-               class="code sev- "><tt><i>40</i> <span class="sd">        Returns:</span></tt>
-            </div>
-            <div id="l41"
-               class="code sev- "><tt><i>41</i> <span class="sd">            Union[Measures, str]: Measure used for pruning</span></tt>
-            </div>
-            <div id="l42"
-               class="code sev- "><tt><i>42</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l43"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (90 > 79 characters)</li>
-               
-               </ul><tt><i>43</i>         <span class="k">return</span> <span class="n">InductionParameters</span><span class="o">.</span><span class="n">_get_measure_str</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_java_object</span><span class="o">.</span><span class="n">getPruningMeasure</span><span class="p">())</span></tt>
-            </div>
-            <div id="l44"
-               class="code sev- "><tt><i>44</i> &nbsp;</tt>
-            </div>
-            <div id="l45"
-               class="code sev- "><tt><i>45</i>     <span class="nd">@property</span></tt>
-            </div>
-            <div id="l46"
-               class="code sev- "><tt><i>46</i>     <span class="k">def</span> <span class="nf">voting_measure</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Union</span><span class="p">[</span><span class="n">Measures</span><span class="p">,</span> <span class="nb">str</span><span class="p">]:</span></tt>
-            </div>
-            <div id="l47"
-               class="code sev- "><tt><i>47</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l48"
-               class="code sev- "><tt><i>48</i> <span class="sd">        Returns:</span></tt>
-            </div>
-            <div id="l49"
-               class="code sev- "><tt><i>49</i> <span class="sd">            Union[Measures, str]: Measure used for voting</span></tt>
-            </div>
-            <div id="l50"
-               class="code sev- "><tt><i>50</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l51"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (89 > 79 characters)</li>
-               
-               </ul><tt><i>51</i>         <span class="k">return</span> <span class="n">InductionParameters</span><span class="o">.</span><span class="n">_get_measure_str</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_java_object</span><span class="o">.</span><span class="n">getVotingMeasure</span><span class="p">())</span></tt>
-            </div>
-            <div id="l52"
-               class="code sev- "><tt><i>52</i> &nbsp;</tt>
-            </div>
-            <div id="l53"
-               class="code sev- "><tt><i>53</i>     <span class="nd">@staticmethod</span></tt>
-            </div>
-            <div id="l54"
-               class="code sev- "><tt><i>54</i>     <span class="k">def</span> <span class="nf">_get_measure_str</span><span class="p">(</span><span class="n">measure</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Union</span><span class="p">[</span><span class="n">Measures</span><span class="p">,</span> <span class="nb">str</span><span class="p">]:</span></tt>
-            </div>
-            <div id="l55"
-               class="code sev- "><tt><i>55</i>         <span class="n">name</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="n">measure</span><span class="o">.</span><span class="n">getName</span><span class="p">()</span></tt>
-            </div>
-            <div id="l56"
-               class="code sev- "><tt><i>56</i>         <span class="k">if</span> <span class="n">name</span> <span class="o">==</span> <span class="s1">&#39;UserDefined&#39;</span><span class="p">:</span></tt>
-            </div>
-            <div id="l57"
-               class="code sev- "><tt><i>57</i>             <span class="k">return</span> <span class="s1">&#39;UserDefined&#39;</span></tt>
-            </div>
-            <div id="l58"
-               class="code sev- "><tt><i>58</i>         <span class="k">return</span> <span class="n">Measures</span><span class="p">[</span><span class="n">name</span><span class="p">]</span></tt>
-            </div>
-            <div id="l59"
-               class="code sev- "><tt><i>59</i> &nbsp;</tt>
-            </div>
-            <div id="l60"
-               class="code sev- "><tt><i>60</i>     <span class="k">def</span> <span class="fm">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span></tt>
-            </div>
-            <div id="l61"
-               class="code sev- "><tt><i>61</i>         <span class="k">return</span> <span class="nb">str</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_java_object</span><span class="o">.</span><span class="n">toString</span><span class="p">())</span></tt>
-            </div>
-            <div id="l62"
-               class="code sev- "><tt><i>62</i> &nbsp;</tt>
-            </div>
-            <div id="l63"
-               class="code sev- "><tt><i>63</i> &nbsp;</tt>
-            </div>
-            <div id="l64"
-               class="code sev- "><tt><i>64</i> <span class="k">class</span> <span class="nc">BaseRule</span><span class="p">:</span></tt>
-            </div>
-            <div id="l65"
-               class="code sev- "><tt><i>65</i> <span class="w">    </span><span class="sd">&quot;&quot;&quot;Base class representing single rule.&quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l66"
-               class="code sev- "><tt><i>66</i> &nbsp;</tt>
-            </div>
-            <div id="l67"
-               class="code sev- "><tt><i>67</i>     <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">java_object</span><span class="p">):</span></tt>
-            </div>
-            <div id="l68"
-               class="code sev- "><tt><i>68</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;:meta private:&quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l69"
-               class="code sev- "><tt><i>69</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_java_object</span> <span class="o">=</span> <span class="n">java_object</span></tt>
-            </div>
-            <div id="l70"
-               class="code sev- "><tt><i>70</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_stats</span><span class="p">:</span> <span class="n">RuleStatistics</span> <span class="o">=</span> <span class="kc">None</span></tt>
-            </div>
-            <div id="l71"
-               class="code sev- "><tt><i>71</i> &nbsp;</tt>
-            </div>
-            <div id="l72"
-               class="code sev- "><tt><i>72</i>     <span class="nd">@property</span></tt>
-            </div>
-            <div id="l73"
-               class="code sev- "><tt><i>73</i>     <span class="k">def</span> <span class="nf">weight</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">float</span><span class="p">:</span></tt>
-            </div>
-            <div id="l74"
-               class="code sev- "><tt><i>74</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Rule weight&quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l75"
-               class="code sev- "><tt><i>75</i>         <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_java_object</span><span class="o">.</span><span class="n">getWeight</span><span class="p">()</span></tt>
-            </div>
-            <div id="l76"
-               class="code sev- "><tt><i>76</i> &nbsp;</tt>
-            </div>
-            <div id="l77"
-               class="code sev- "><tt><i>77</i>     <span class="nd">@property</span></tt>
-            </div>
-            <div id="l78"
-               class="code sev- "><tt><i>78</i>     <span class="k">def</span> <span class="nf">weighted_p</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">float</span><span class="p">:</span></tt>
-            </div>
-            <div id="l79"
-               class="code sev- "><tt><i>79</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Number of positives covered by the rule (accounting weights).&quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l80"
-               class="code sev- "><tt><i>80</i>         <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_java_object</span><span class="o">.</span><span class="n">getWeighted_p</span><span class="p">()</span></tt>
-            </div>
-            <div id="l81"
-               class="code sev- "><tt><i>81</i> &nbsp;</tt>
-            </div>
-            <div id="l82"
-               class="code sev- "><tt><i>82</i>     <span class="nd">@property</span></tt>
-            </div>
-            <div id="l83"
-               class="code sev- "><tt><i>83</i>     <span class="k">def</span> <span class="nf">weighted_n</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">float</span><span class="p">:</span></tt>
-            </div>
-            <div id="l84"
-               class="code sev- "><tt><i>84</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Number of negatives covered by the rule (accounting weights).&quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l85"
-               class="code sev- "><tt><i>85</i>         <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_java_object</span><span class="o">.</span><span class="n">getWeighted_n</span><span class="p">()</span></tt>
-            </div>
-            <div id="l86"
-               class="code sev- "><tt><i>86</i> &nbsp;</tt>
-            </div>
-            <div id="l87"
-               class="code sev- "><tt><i>87</i>     <span class="nd">@property</span></tt>
-            </div>
-            <div id="l88"
-               class="code sev- "><tt><i>88</i>     <span class="k">def</span> <span class="nf">weighted_P</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">float</span><span class="p">:</span>  <span class="c1"># pylint: disable=invalid-name</span></tt>
-            </div>
-            <div id="l89"
-               class="code sev- "><tt><i>89</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Number of positives in the training set (accounting weights).&quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l90"
-               class="code sev- "><tt><i>90</i>         <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_java_object</span><span class="o">.</span><span class="n">getWeighted_P</span><span class="p">()</span></tt>
-            </div>
-            <div id="l91"
-               class="code sev- "><tt><i>91</i> &nbsp;</tt>
-            </div>
-            <div id="l92"
-               class="code sev- "><tt><i>92</i>     <span class="nd">@property</span></tt>
-            </div>
-            <div id="l93"
-               class="code sev- "><tt><i>93</i>     <span class="k">def</span> <span class="nf">weighted_N</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">float</span><span class="p">:</span>  <span class="c1"># pylint: disable=invalid-name</span></tt>
-            </div>
-            <div id="l94"
-               class="code sev- "><tt><i>94</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Number of negatives in the training set (accounting weights).&quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l95"
-               class="code sev- "><tt><i>95</i>         <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_java_object</span><span class="o">.</span><span class="n">getWeighted_N</span><span class="p">()</span></tt>
-            </div>
-            <div id="l96"
-               class="code sev- "><tt><i>96</i> &nbsp;</tt>
-            </div>
-            <div id="l97"
-               class="code sev- "><tt><i>97</i>     <span class="nd">@property</span></tt>
-            </div>
-            <div id="l98"
-               class="code sev- "><tt><i>98</i>     <span class="k">def</span> <span class="nf">pvalue</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">float</span><span class="p">:</span></tt>
-            </div>
-            <div id="l99"
-               class="code sev- "><tt><i>99</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Rule significance.&quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l100"
-               class="code sev- "><tt><i>100</i>         <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_java_object</span><span class="o">.</span><span class="n">getPValue</span><span class="p">()</span></tt>
-            </div>
-            <div id="l101"
-               class="code sev- "><tt><i>101</i> &nbsp;</tt>
-            </div>
-            <div id="l102"
-               class="code sev- "><tt><i>102</i>     <span class="nd">@property</span></tt>
-            </div>
-            <div id="l103"
-               class="code sev- "><tt><i>103</i>     <span class="k">def</span> <span class="nf">stats</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">RuleStatistics</span><span class="p">:</span></tt>
-            </div>
-            <div id="l104"
-               class="code sev- "><tt><i>104</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Rule statistics.&quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l105"
-               class="code sev- "><tt><i>105</i>         <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">_stats</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span></tt>
-            </div>
-            <div id="l106"
-               class="code sev- "><tt><i>106</i>             <span class="bp">self</span><span class="o">.</span><span class="n">_stats</span> <span class="o">=</span> <span class="n">RuleStatistics</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span></tt>
-            </div>
-            <div id="l107"
-               class="code sev- "><tt><i>107</i>         <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_stats</span></tt>
-            </div>
-            <div id="l108"
-               class="code sev- "><tt><i>108</i> &nbsp;</tt>
-            </div>
-            <div id="l109"
-               class="code sev- "><tt><i>109</i>     <span class="k">def</span> <span class="nf">get_covering_information</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">dict</span><span class="p">:</span></tt>
-            </div>
-            <div id="l110"
-               class="code sev- "><tt><i>110</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Returns information about rule covering</span></tt>
-            </div>
-            <div id="l111"
-               class="code sev- "><tt><i>111</i> &nbsp;</tt>
-            </div>
-            <div id="l112"
-               class="code sev- "><tt><i>112</i> <span class="sd">        Returns</span></tt>
-            </div>
-            <div id="l113"
-               class="code sev- "><tt><i>113</i> <span class="sd">        -------</span></tt>
-            </div>
-            <div id="l114"
-               class="code sev- "><tt><i>114</i> <span class="sd">        covering_data : dict</span></tt>
-            </div>
-            <div id="l115"
-               class="code sev- "><tt><i>115</i> <span class="sd">            Dictionary containing covering information.</span></tt>
-            </div>
-            <div id="l116"
-               class="code sev- "><tt><i>116</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l117"
-               class="code sev- "><tt><i>117</i>         <span class="k">return</span> <span class="p">{</span></tt>
-            </div>
-            <div id="l118"
-               class="code sev- "><tt><i>118</i>             <span class="s1">&#39;weighted_n&#39;</span><span class="p">:</span> <span class="bp">self</span><span class="o">.</span><span class="n">weighted_n</span><span class="p">,</span></tt>
-            </div>
-            <div id="l119"
-               class="code sev- "><tt><i>119</i>             <span class="s1">&#39;weighted_p&#39;</span><span class="p">:</span> <span class="bp">self</span><span class="o">.</span><span class="n">weighted_p</span><span class="p">,</span></tt>
-            </div>
-            <div id="l120"
-               class="code sev- "><tt><i>120</i>             <span class="s1">&#39;weighted_N&#39;</span><span class="p">:</span> <span class="bp">self</span><span class="o">.</span><span class="n">weighted_N</span><span class="p">,</span></tt>
-            </div>
-            <div id="l121"
-               class="code sev- "><tt><i>121</i>             <span class="s1">&#39;weighted_P&#39;</span><span class="p">:</span> <span class="bp">self</span><span class="o">.</span><span class="n">weighted_P</span><span class="p">,</span></tt>
-            </div>
-            <div id="l122"
-               class="code sev- "><tt><i>122</i>         <span class="p">}</span></tt>
-            </div>
-            <div id="l123"
-               class="code sev- "><tt><i>123</i> &nbsp;</tt>
-            </div>
-            <div id="l124"
-               class="code sev- "><tt><i>124</i>     <span class="k">def</span> <span class="nf">print_stats</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span></tt>
-            </div>
-            <div id="l125"
-               class="code sev- "><tt><i>125</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Prints rule statistics as formatted text.&quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l126"
-               class="code sev- "><tt><i>126</i>         <span class="nb">print</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">stats</span><span class="p">)</span></tt>
-            </div>
-            <div id="l127"
-               class="code sev- "><tt><i>127</i> &nbsp;</tt>
-            </div>
-            <div id="l128"
-               class="code sev- "><tt><i>128</i>     <span class="k">def</span> <span class="fm">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span></tt>
-            </div>
-            <div id="l129"
-               class="code sev- "><tt><i>129</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Returns string representation of the rule.&quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l130"
-               class="code sev- "><tt><i>130</i>         <span class="k">return</span> <span class="nb">str</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_java_object</span><span class="o">.</span><span class="n">toString</span><span class="p">())</span></tt>
-            </div>
-            <div id="l131"
-               class="code sev- "><tt><i>131</i> &nbsp;</tt>
-            </div>
-            <div id="l132"
-               class="code sev- "><tt><i>132</i> &nbsp;</tt>
-            </div>
-            <div id="l133"
-               class="code sev- "><tt><i>133</i> <span class="k">class</span> <span class="nc">ClassificationRule</span><span class="p">(</span><span class="n">BaseRule</span><span class="p">):</span></tt>
-            </div>
-            <div id="l134"
-               class="code sev- "><tt><i>134</i> <span class="w">    </span><span class="sd">&quot;&quot;&quot;Class representing classification rule</span></tt>
-            </div>
-            <div id="l135"
-               class="code sev- "><tt><i>135</i> <span class="sd">    &quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l136"
-               class="code sev- "><tt><i>136</i> &nbsp;</tt>
-            </div>
-            <div id="l137"
-               class="code sev- "><tt><i>137</i>     <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">java_object</span><span class="p">):</span></tt>
-            </div>
-            <div id="l138"
-               class="code sev- "><tt><i>138</i>         <span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">java_object</span><span class="p">)</span></tt>
-            </div>
-            <div id="l139"
-               class="code sev- "><tt><i>139</i> &nbsp;</tt>
-            </div>
-            <div id="l140"
-               class="code sev- "><tt><i>140</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_decision_class</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="nb">str</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_java_object</span><span class="o">.</span><span class="n">getClassLabel</span><span class="p">())</span></tt>
-            </div>
-            <div id="l141"
-               class="code sev- "><tt><i>141</i> &nbsp;</tt>
-            </div>
-            <div id="l142"
-               class="code sev- "><tt><i>142</i>     <span class="nd">@property</span></tt>
-            </div>
-            <div id="l143"
-               class="code sev- "><tt><i>143</i>     <span class="k">def</span> <span class="nf">decision_class</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">str</span><span class="p">:</span></tt>
-            </div>
-            <div id="l144"
-               class="code sev- "><tt><i>144</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Decision class of the rule</span></tt>
-            </div>
-            <div id="l145"
-               class="code sev- "><tt><i>145</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l146"
-               class="code sev- "><tt><i>146</i>         <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_decision_class</span></tt>
-            </div>
-            <div id="l147"
-               class="code sev- "><tt><i>147</i> &nbsp;</tt>
-            </div>
-            <div id="l148"
-               class="code sev- "><tt><i>148</i> &nbsp;</tt>
-            </div>
-            <div id="l149"
-               class="code sev- "><tt><i>149</i> <span class="k">class</span> <span class="nc">RegressionRule</span><span class="p">(</span><span class="n">BaseRule</span><span class="p">):</span></tt>
-            </div>
-            <div id="l150"
-               class="code sev- "><tt><i>150</i> <span class="w">    </span><span class="sd">&quot;&quot;&quot;Class representing regression rule</span></tt>
-            </div>
-            <div id="l151"
-               class="code sev- "><tt><i>151</i> <span class="sd">    &quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l152"
-               class="code sev- "><tt><i>152</i> &nbsp;</tt>
-            </div>
-            <div id="l153"
-               class="code sev- "><tt><i>153</i>     <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">java_object</span><span class="p">):</span></tt>
-            </div>
-            <div id="l154"
-               class="code sev- "><tt><i>154</i>         <span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">java_object</span><span class="p">)</span></tt>
-            </div>
-            <div id="l155"
-               class="code sev- "><tt><i>155</i> &nbsp;</tt>
-            </div>
-            <div id="l156"
-               class="code sev- "><tt><i>156</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_conclusion_value</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="nb">float</span><span class="p">(</span></tt>
-            </div>
-            <div id="l157"
-               class="code sev- "><tt><i>157</i>             <span class="bp">self</span><span class="o">.</span><span class="n">_java_object</span><span class="o">.</span><span class="n">getConsequenceValue</span><span class="p">())</span></tt>
-            </div>
-            <div id="l158"
-               class="code sev- "><tt><i>158</i> &nbsp;</tt>
-            </div>
-            <div id="l159"
-               class="code sev- "><tt><i>159</i>     <span class="nd">@property</span></tt>
-            </div>
-            <div id="l160"
-               class="code sev- "><tt><i>160</i>     <span class="k">def</span> <span class="nf">conclusion_value</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">float</span><span class="p">:</span></tt>
-            </div>
-            <div id="l161"
-               class="code sev- "><tt><i>161</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Value from the rule&#39;s conclusion</span></tt>
-            </div>
-            <div id="l162"
-               class="code sev- "><tt><i>162</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l163"
-               class="code sev- "><tt><i>163</i>         <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_conclusion_value</span></tt>
-            </div>
-            <div id="l164"
-               class="code sev- "><tt><i>164</i> &nbsp;</tt>
-            </div>
-            <div id="l165"
-               class="code sev- "><tt><i>165</i> &nbsp;</tt>
-            </div>
-            <div id="l166"
-               class="code sev- "><tt><i>166</i> <span class="k">class</span> <span class="nc">SurvivalRule</span><span class="p">(</span><span class="n">BaseRule</span><span class="p">):</span></tt>
-            </div>
-            <div id="l167"
-               class="code sev- "><tt><i>167</i> <span class="w">    </span><span class="sd">&quot;&quot;&quot;Class representing survival rule</span></tt>
-            </div>
-            <div id="l168"
-               class="code sev- "><tt><i>168</i> <span class="sd">    &quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l169"
-               class="code sev- "><tt><i>169</i> &nbsp;</tt>
-            </div>
-            <div id="l170"
-               class="code sev- "><tt><i>170</i>     <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">java_object</span><span class="p">):</span></tt>
-            </div>
-            <div id="l171"
-               class="code sev- "><tt><i>171</i>         <span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">java_object</span><span class="p">)</span></tt>
-            </div>
-            <div id="l172"
-               class="code sev- "><tt><i>172</i> &nbsp;</tt>
-            </div>
-            <div id="l173"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (82 > 79 characters)</li>
-               
-               </ul><tt><i>173</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_kaplan_meier_estimator</span><span class="p">:</span> <span class="n">KaplanMeierEstimator</span> <span class="o">=</span> <span class="n">KaplanMeierEstimator</span><span class="p">(</span></tt>
-            </div>
-            <div id="l174"
-               class="code sev- "><tt><i>174</i>             <span class="n">java_object</span><span class="o">.</span><span class="n">getEstimator</span><span class="p">()</span></tt>
-            </div>
-            <div id="l175"
-               class="code sev- "><tt><i>175</i>         <span class="p">)</span></tt>
-            </div>
-            <div id="l176"
-               class="code sev- "><tt><i>176</i> &nbsp;</tt>
-            </div>
-            <div id="l177"
-               class="code sev- "><tt><i>177</i>     <span class="nd">@property</span></tt>
-            </div>
-            <div id="l178"
-               class="code sev- "><tt><i>178</i>     <span class="k">def</span> <span class="nf">kaplan_meier_estimator</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">KaplanMeierEstimator</span><span class="p">:</span></tt>
-            </div>
-            <div id="l179"
-               class="code sev- "><tt><i>179</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Kaplan-Meier estimator from the rule concslusion</span></tt>
-            </div>
-            <div id="l180"
-               class="code sev- "><tt><i>180</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l181"
-               class="code sev- "><tt><i>181</i>         <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_kaplan_meier_estimator</span></tt>
-            </div>
-            <div id="l182"
-               class="code sev- "><tt><i>182</i> &nbsp;</tt>
-            </div>
-            <div id="l183"
-               class="code sev- "><tt><i>183</i> &nbsp;</tt>
-            </div>
-            <div id="l184"
-               class="code sev- "><tt><i>184</i> <span class="k">def</span> <span class="nf">_rule_factory</span><span class="p">(</span><span class="n">java_object</span><span class="p">:</span> <span class="n">JObject</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">BaseRule</span><span class="p">:</span></tt>
-            </div>
-            <div id="l185"
-               class="code sev- "><tt><i>185</i>     <span class="n">class_name</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="nb">str</span><span class="p">(</span><span class="n">java_object</span><span class="o">.</span><span class="n">getClass</span><span class="p">()</span><span class="o">.</span><span class="n">getName</span><span class="p">())</span><span class="o">.</span><span class="n">lower</span><span class="p">()</span></tt>
-            </div>
-            <div id="l186"
-               class="code sev- "><tt><i>186</i>     <span class="k">if</span> <span class="s1">&#39;regression&#39;</span> <span class="ow">in</span> <span class="n">class_name</span><span class="p">:</span></tt>
-            </div>
-            <div id="l187"
-               class="code sev- "><tt><i>187</i>         <span class="k">return</span> <span class="n">RegressionRule</span><span class="p">(</span><span class="n">java_object</span><span class="p">)</span></tt>
-            </div>
-            <div id="l188"
-               class="code sev- "><tt><i>188</i>     <span class="k">elif</span> <span class="s1">&#39;survival&#39;</span> <span class="ow">in</span> <span class="n">class_name</span><span class="p">:</span></tt>
-            </div>
-            <div id="l189"
-               class="code sev- "><tt><i>189</i>         <span class="k">return</span> <span class="n">SurvivalRule</span><span class="p">(</span><span class="n">java_object</span><span class="p">)</span></tt>
-            </div>
-            <div id="l190"
-               class="code sev- "><tt><i>190</i>     <span class="k">return</span> <span class="n">ClassificationRule</span><span class="p">(</span><span class="n">java_object</span><span class="p">)</span></tt>
-            </div>
-            <div id="l191"
-               class="code sev- "><tt><i>191</i> &nbsp;</tt>
-            </div>
-            <div id="l192"
-               class="code sev- "><tt><i>192</i> &nbsp;</tt>
-            </div>
-            <div id="l193"
-               class="code sev- "><tt><i>193</i> <span class="n">T</span> <span class="o">=</span> <span class="n">TypeVar</span><span class="p">(</span><span class="s1">&#39;T&#39;</span><span class="p">)</span></tt>
-            </div>
-            <div id="l194"
-               class="code sev- "><tt><i>194</i> &nbsp;</tt>
-            </div>
-            <div id="l195"
-               class="code sev- "><tt><i>195</i> &nbsp;</tt>
-            </div>
-            <div id="l196"
-               class="code sev- "><tt><i>196</i> <span class="k">class</span> <span class="nc">RuleSet</span><span class="p">(</span><span class="n">Generic</span><span class="p">[</span><span class="n">T</span><span class="p">]):</span></tt>
-            </div>
-            <div id="l197"
-               class="code sev- "><tt><i>197</i> <span class="w">    </span><span class="sd">&quot;&quot;&quot;Class representing ruleset.&quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l198"
-               class="code sev- "><tt><i>198</i> &nbsp;</tt>
-            </div>
-            <div id="l199"
-               class="code sev- "><tt><i>199</i>     <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">java_object</span><span class="p">):</span></tt>
-            </div>
-            <div id="l200"
-               class="code sev- "><tt><i>200</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;:meta private:&quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l201"
-               class="code sev- "><tt><i>201</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_java_object</span> <span class="o">=</span> <span class="n">java_object</span></tt>
-            </div>
-            <div id="l202"
-               class="code sev- "><tt><i>202</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_stats</span><span class="p">:</span> <span class="n">RuleSetStatistics</span> <span class="o">=</span> <span class="kc">None</span></tt>
-            </div>
-            <div id="l203"
-               class="code sev- "><tt><i>203</i> &nbsp;</tt>
-            </div>
-            <div id="l204"
-               class="code sev- "><tt><i>204</i>     <span class="nd">@property</span></tt>
-            </div>
-            <div id="l205"
-               class="code sev- "><tt><i>205</i>     <span class="k">def</span> <span class="nf">total_time</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">float</span><span class="p">:</span></tt>
-            </div>
-            <div id="l206"
-               class="code sev- "><tt><i>206</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Time of constructing the rule set in seconds&quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l207"
-               class="code sev- "><tt><i>207</i>         <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_java_object</span><span class="o">.</span><span class="n">getTotalTime</span><span class="p">()</span></tt>
-            </div>
-            <div id="l208"
-               class="code sev- "><tt><i>208</i> &nbsp;</tt>
-            </div>
-            <div id="l209"
-               class="code sev- "><tt><i>209</i>     <span class="nd">@property</span></tt>
-            </div>
-            <div id="l210"
-               class="code sev- "><tt><i>210</i>     <span class="k">def</span> <span class="nf">growing_time</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">float</span><span class="p">:</span></tt>
-            </div>
-            <div id="l211"
-               class="code sev- "><tt><i>211</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Time of growing in seconds&quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l212"
-               class="code sev- "><tt><i>212</i>         <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_java_object</span><span class="o">.</span><span class="n">getGrowingTime</span><span class="p">()</span></tt>
-            </div>
-            <div id="l213"
-               class="code sev- "><tt><i>213</i> &nbsp;</tt>
-            </div>
-            <div id="l214"
-               class="code sev- "><tt><i>214</i>     <span class="nd">@property</span></tt>
-            </div>
-            <div id="l215"
-               class="code sev- "><tt><i>215</i>     <span class="k">def</span> <span class="nf">pruning_time</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">float</span><span class="p">:</span></tt>
-            </div>
-            <div id="l216"
-               class="code sev- "><tt><i>216</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Time of pruning in seconds&quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l217"
-               class="code sev- "><tt><i>217</i>         <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_java_object</span><span class="o">.</span><span class="n">getPruningTime</span><span class="p">()</span></tt>
-            </div>
-            <div id="l218"
-               class="code sev- "><tt><i>218</i> &nbsp;</tt>
-            </div>
-            <div id="l219"
-               class="code sev- "><tt><i>219</i>     <span class="nd">@property</span></tt>
-            </div>
-            <div id="l220"
-               class="code sev- "><tt><i>220</i>     <span class="k">def</span> <span class="nf">is_voting</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">bool</span><span class="p">:</span></tt>
-            </div>
-            <div id="l221"
-               class="code sev- "><tt><i>221</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Value indicating whether rules are voting.&quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l222"
-               class="code sev- "><tt><i>222</i>         <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_java_object</span><span class="o">.</span><span class="n">getIsVoting</span><span class="p">()</span></tt>
-            </div>
-            <div id="l223"
-               class="code sev- "><tt><i>223</i> &nbsp;</tt>
-            </div>
-            <div id="l224"
-               class="code sev- "><tt><i>224</i>     <span class="nd">@property</span></tt>
-            </div>
-            <div id="l225"
-               class="code sev- "><tt><i>225</i>     <span class="k">def</span> <span class="nf">parameters</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">object</span><span class="p">:</span></tt>
-            </div>
-            <div id="l226"
-               class="code sev- "><tt><i>226</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Parameters used during rule set induction.&quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l227"
-               class="code sev- "><tt><i>227</i>         <span class="k">return</span> <span class="n">InductionParameters</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_java_object</span><span class="o">.</span><span class="n">getParams</span><span class="p">())</span></tt>
-            </div>
-            <div id="l228"
-               class="code sev- "><tt><i>228</i> &nbsp;</tt>
-            </div>
-            <div id="l229"
-               class="code sev- "><tt><i>229</i>     <span class="nd">@property</span></tt>
-            </div>
-            <div id="l230"
-               class="code sev- "><tt><i>230</i>     <span class="k">def</span> <span class="nf">stats</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">RuleSetStatistics</span><span class="p">:</span></tt>
-            </div>
-            <div id="l231"
-               class="code sev- "><tt><i>231</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Rule set statistics.&quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l232"
-               class="code sev- "><tt><i>232</i>         <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">_stats</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span></tt>
-            </div>
-            <div id="l233"
-               class="code sev- "><tt><i>233</i>             <span class="bp">self</span><span class="o">.</span><span class="n">_stats</span> <span class="o">=</span> <span class="n">RuleSetStatistics</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span></tt>
-            </div>
-            <div id="l234"
-               class="code sev- "><tt><i>234</i>         <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_stats</span></tt>
-            </div>
-            <div id="l235"
-               class="code sev- "><tt><i>235</i> &nbsp;</tt>
-            </div>
-            <div id="l236"
-               class="code sev- "><tt><i>236</i>     <span class="k">def</span> <span class="nf">covering</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">example_set</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">:</span></tt>
-            </div>
-            <div id="l237"
-               class="code sev- "><tt><i>237</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;:meta private:&quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l238"
-               class="code sev- "><tt><i>238</i>         <span class="n">res</span> <span class="o">=</span> <span class="p">[]</span></tt>
-            </div>
-            <div id="l239"
-               class="code sev- "><tt><i>239</i>         <span class="k">for</span> <span class="n">rule</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">rules</span><span class="p">:</span></tt>
-            </div>
-            <div id="l240"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (99 > 79 characters)</li>
-               
-               </ul><tt><i>240</i>             <span class="n">covering_info</span> <span class="o">=</span> <span class="n">rule</span><span class="o">.</span><span class="n">_java_object</span><span class="o">.</span><span class="n">coversUnlabelled</span><span class="p">(</span>  <span class="c1"># pylint: disable=protected-access</span></tt>
-            </div>
-            <div id="l241"
-               class="code sev- "><tt><i>241</i>                 <span class="n">example_set</span></tt>
-            </div>
-            <div id="l242"
-               class="code sev- "><tt><i>242</i>             <span class="p">)</span></tt>
-            </div>
-            <div id="l243"
-               class="code sev- "><tt><i>243</i>             <span class="n">covered_examples_indexes</span> <span class="o">=</span> <span class="p">[]</span></tt>
-            </div>
-            <div id="l244"
-               class="code sev- "><tt><i>244</i>             <span class="n">covered_examples_indexes</span> <span class="o">+=</span> <span class="n">covering_info</span></tt>
-            </div>
-            <div id="l245"
-               class="code sev- "><tt><i>245</i>             <span class="n">res</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">covered_examples_indexes</span><span class="p">)</span></tt>
-            </div>
-            <div id="l246"
-               class="code sev- "><tt><i>246</i>         <span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">res</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="nb">object</span><span class="p">)</span></tt>
-            </div>
-            <div id="l247"
-               class="code sev- "><tt><i>247</i> &nbsp;</tt>
-            </div>
-            <div id="l248"
-               class="code sev- "><tt><i>248</i>     <span class="nd">@property</span></tt>
-            </div>
-            <div id="l249"
-               class="code sev- "><tt><i>249</i>     <span class="k">def</span> <span class="nf">rules</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">list</span><span class="p">[</span><span class="n">T</span><span class="p">]:</span></tt>
-            </div>
-            <div id="l250"
-               class="code sev- "><tt><i>250</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;List of rules objects.&quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l251"
-               class="code sev- "><tt><i>251</i>         <span class="k">return</span> <span class="p">[</span></tt>
-            </div>
-            <div id="l252"
-               class="code sev- "><tt><i>252</i>             <span class="n">_rule_factory</span><span class="p">(</span><span class="n">java_rule</span><span class="p">)</span></tt>
-            </div>
-            <div id="l253"
-               class="code sev- "><tt><i>253</i>             <span class="k">for</span> <span class="n">java_rule</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">_java_object</span><span class="o">.</span><span class="n">getRules</span><span class="p">()</span></tt>
-            </div>
-            <div id="l254"
-               class="code sev- "><tt><i>254</i>         <span class="p">]</span></tt>
-            </div>
-            <div id="l255"
-               class="code sev- "><tt><i>255</i> &nbsp;</tt>
-            </div>
-            <div id="l256"
-               class="code sev- "><tt><i>256</i>     <span class="k">def</span> <span class="nf">calculate_conditions_count</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">float</span><span class="p">:</span></tt>
-            </div>
-            <div id="l257"
-               class="code sev- "><tt><i>257</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l258"
-               class="code sev- "><tt><i>258</i> <span class="sd">        Returns</span></tt>
-            </div>
-            <div id="l259"
-               class="code sev- "><tt><i>259</i> <span class="sd">        -------</span></tt>
-            </div>
-            <div id="l260"
-               class="code sev- "><tt><i>260</i> <span class="sd">        count: float</span></tt>
-            </div>
-            <div id="l261"
-               class="code sev- "><tt><i>261</i> <span class="sd">            Number of conditions.</span></tt>
-            </div>
-            <div id="l262"
-               class="code sev- "><tt><i>262</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l263"
-               class="code sev- "><tt><i>263</i>         <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_java_object</span><span class="o">.</span><span class="n">calculateConditionsCount</span><span class="p">()</span></tt>
-            </div>
-            <div id="l264"
-               class="code sev- "><tt><i>264</i> &nbsp;</tt>
-            </div>
-            <div id="l265"
-               class="code sev- "><tt><i>265</i>     <span class="k">def</span> <span class="nf">calculate_induced_conditions_count</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">float</span><span class="p">:</span></tt>
-            </div>
-            <div id="l266"
-               class="code sev- "><tt><i>266</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l267"
-               class="code sev- "><tt><i>267</i> <span class="sd">        Returns</span></tt>
-            </div>
-            <div id="l268"
-               class="code sev- "><tt><i>268</i> <span class="sd">        -------</span></tt>
-            </div>
-            <div id="l269"
-               class="code sev- "><tt><i>269</i> <span class="sd">        count: float</span></tt>
-            </div>
-            <div id="l270"
-               class="code sev- "><tt><i>270</i> <span class="sd">            Number of induced conditions.</span></tt>
-            </div>
-            <div id="l271"
-               class="code sev- "><tt><i>271</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l272"
-               class="code sev- "><tt><i>272</i>         <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_java_object</span><span class="o">.</span><span class="n">calculateInducedCondtionsCount</span><span class="p">()</span></tt>
-            </div>
-            <div id="l273"
-               class="code sev- "><tt><i>273</i> &nbsp;</tt>
-            </div>
-            <div id="l274"
-               class="code sev- "><tt><i>274</i>     <span class="k">def</span> <span class="nf">calculate_avg_rule_coverage</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">float</span><span class="p">:</span></tt>
-            </div>
-            <div id="l275"
-               class="code sev- "><tt><i>275</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l276"
-               class="code sev- "><tt><i>276</i> <span class="sd">        Returns</span></tt>
-            </div>
-            <div id="l277"
-               class="code sev- "><tt><i>277</i> <span class="sd">        -------</span></tt>
-            </div>
-            <div id="l278"
-               class="code sev- "><tt><i>278</i> <span class="sd">        count: float</span></tt>
-            </div>
-            <div id="l279"
-               class="code sev- "><tt><i>279</i> <span class="sd">            Average rule coverage.</span></tt>
-            </div>
-            <div id="l280"
-               class="code sev- "><tt><i>280</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l281"
-               class="code sev- "><tt><i>281</i>         <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_java_object</span><span class="o">.</span><span class="n">calculateAvgRuleCoverage</span><span class="p">()</span></tt>
-            </div>
-            <div id="l282"
-               class="code sev- "><tt><i>282</i> &nbsp;</tt>
-            </div>
-            <div id="l283"
-               class="code sev- "><tt><i>283</i>     <span class="k">def</span> <span class="nf">calculate_avg_rule_precision</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">float</span><span class="p">:</span></tt>
-            </div>
-            <div id="l284"
-               class="code sev- "><tt><i>284</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l285"
-               class="code sev- "><tt><i>285</i> <span class="sd">        Returns</span></tt>
-            </div>
-            <div id="l286"
-               class="code sev- "><tt><i>286</i> <span class="sd">        -------</span></tt>
-            </div>
-            <div id="l287"
-               class="code sev- "><tt><i>287</i> <span class="sd">        count: float</span></tt>
-            </div>
-            <div id="l288"
-               class="code sev- "><tt><i>288</i> <span class="sd">            Average rule precision.</span></tt>
-            </div>
-            <div id="l289"
-               class="code sev- "><tt><i>289</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l290"
-               class="code sev- "><tt><i>290</i>         <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_java_object</span><span class="o">.</span><span class="n">calculateAvgRulePrecision</span><span class="p">()</span></tt>
-            </div>
-            <div id="l291"
-               class="code sev- "><tt><i>291</i> &nbsp;</tt>
-            </div>
-            <div id="l292"
-               class="code sev- "><tt><i>292</i>     <span class="k">def</span> <span class="nf">calculate_avg_rule_quality</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">float</span><span class="p">:</span></tt>
-            </div>
-            <div id="l293"
-               class="code sev- "><tt><i>293</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l294"
-               class="code sev- "><tt><i>294</i> <span class="sd">        Returns</span></tt>
-            </div>
-            <div id="l295"
-               class="code sev- "><tt><i>295</i> <span class="sd">        -------</span></tt>
-            </div>
-            <div id="l296"
-               class="code sev- "><tt><i>296</i> <span class="sd">        count: float</span></tt>
-            </div>
-            <div id="l297"
-               class="code sev- "><tt><i>297</i> <span class="sd">            Average rule quality.</span></tt>
-            </div>
-            <div id="l298"
-               class="code sev- "><tt><i>298</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l299"
-               class="code sev- "><tt><i>299</i>         <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_java_object</span><span class="o">.</span><span class="n">calculateAvgRuleQuality</span><span class="p">()</span></tt>
-            </div>
-            <div id="l300"
-               class="code sev- "><tt><i>300</i> &nbsp;</tt>
-            </div>
-            <div id="l301"
-               class="code sev- "><tt><i>301</i>     <span class="k">def</span> <span class="nf">calculate_significance</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">alpha</span><span class="p">:</span> <span class="nb">float</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">dict</span><span class="p">:</span></tt>
-            </div>
-            <div id="l302"
-               class="code sev- "><tt><i>302</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l303"
-               class="code sev- "><tt><i>303</i> <span class="sd">        Parameters</span></tt>
-            </div>
-            <div id="l304"
-               class="code sev- "><tt><i>304</i> <span class="sd">        ----------</span></tt>
-            </div>
-            <div id="l305"
-               class="code sev- "><tt><i>305</i> <span class="sd">        alpha : float</span></tt>
-            </div>
-            <div id="l306"
-               class="code sev- "><tt><i>306</i> &nbsp;</tt>
-            </div>
-            <div id="l307"
-               class="code sev- "><tt><i>307</i> <span class="sd">        Returns</span></tt>
-            </div>
-            <div id="l308"
-               class="code sev- "><tt><i>308</i> <span class="sd">        -------</span></tt>
-            </div>
-            <div id="l309"
-               class="code sev- "><tt><i>309</i> <span class="sd">        count: float</span></tt>
-            </div>
-            <div id="l310"
-               class="code sev- "><tt><i>310</i> <span class="sd">            Significance of the rule set.</span></tt>
-            </div>
-            <div id="l311"
-               class="code sev- "><tt><i>311</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l312"
-               class="code sev- "><tt><i>312</i>         <span class="n">significance</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_java_object</span><span class="o">.</span><span class="n">calculateSignificance</span><span class="p">(</span><span class="n">alpha</span><span class="p">)</span></tt>
-            </div>
-            <div id="l313"
-               class="code sev- "><tt><i>313</i>         <span class="k">return</span> <span class="p">{</span></tt>
-            </div>
-            <div id="l314"
-               class="code sev- "><tt><i>314</i>             <span class="s1">&#39;p&#39;</span><span class="p">:</span> <span class="n">significance</span><span class="o">.</span><span class="n">p</span><span class="p">,</span></tt>
-            </div>
-            <div id="l315"
-               class="code sev- "><tt><i>315</i>             <span class="s1">&#39;fraction&#39;</span><span class="p">:</span> <span class="n">significance</span><span class="o">.</span><span class="n">fraction</span></tt>
-            </div>
-            <div id="l316"
-               class="code sev- "><tt><i>316</i>         <span class="p">}</span></tt>
-            </div>
-            <div id="l317"
-               class="code sev- "><tt><i>317</i> &nbsp;</tt>
-            </div>
-            <div id="l318"
-               class="code sev- "><tt><i>318</i>     <span class="k">def</span> <span class="nf">calculate_significance_fdr</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">alpha</span><span class="p">:</span> <span class="nb">float</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">dict</span><span class="p">:</span></tt>
-            </div>
-            <div id="l319"
-               class="code sev- "><tt><i>319</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l320"
-               class="code sev- "><tt><i>320</i> <span class="sd">        Returns</span></tt>
-            </div>
-            <div id="l321"
-               class="code sev- "><tt><i>321</i> <span class="sd">        -------</span></tt>
-            </div>
-            <div id="l322"
-               class="code sev- "><tt><i>322</i> <span class="sd">        count: dict</span></tt>
-            </div>
-            <div id="l323"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (98 > 79 characters)</li>
-               
-               </ul><tt><i>323</i> <span class="sd">            Significance of the rule set with false discovery rate correction. Dictionary contains</span></tt>
-            </div>
-            <div id="l324"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (91 > 79 characters)</li>
-               
-               </ul><tt><i>324</i> <span class="sd">            two fields: *fraction* (fraction of rules significant at assumed level) and *p*</span></tt>
-            </div>
-            <div id="l325"
-               class="code sev- "><tt><i>325</i> <span class="sd">             (average p-value of all rules).</span></tt>
-            </div>
-            <div id="l326"
-               class="code sev- "><tt><i>326</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l327"
-               class="code sev- "><tt><i>327</i>         <span class="n">significance</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_java_object</span><span class="o">.</span><span class="n">calculateSignificanceFDR</span><span class="p">(</span><span class="n">alpha</span><span class="p">)</span></tt>
-            </div>
-            <div id="l328"
-               class="code sev- "><tt><i>328</i>         <span class="k">return</span> <span class="p">{</span></tt>
-            </div>
-            <div id="l329"
-               class="code sev- "><tt><i>329</i>             <span class="s1">&#39;p&#39;</span><span class="p">:</span> <span class="n">significance</span><span class="o">.</span><span class="n">p</span><span class="p">,</span></tt>
-            </div>
-            <div id="l330"
-               class="code sev- "><tt><i>330</i>             <span class="s1">&#39;fraction&#39;</span><span class="p">:</span> <span class="n">significance</span><span class="o">.</span><span class="n">fraction</span></tt>
-            </div>
-            <div id="l331"
-               class="code sev- "><tt><i>331</i>         <span class="p">}</span></tt>
-            </div>
-            <div id="l332"
-               class="code sev- "><tt><i>332</i> &nbsp;</tt>
-            </div>
-            <div id="l333"
-               class="code sev- "><tt><i>333</i>     <span class="k">def</span> <span class="nf">calculate_significance_fwer</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">alpha</span><span class="p">:</span> <span class="nb">float</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">dict</span><span class="p">:</span></tt>
-            </div>
-            <div id="l334"
-               class="code sev- "><tt><i>334</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l335"
-               class="code sev- "><tt><i>335</i> <span class="sd">        Returns</span></tt>
-            </div>
-            <div id="l336"
-               class="code sev- "><tt><i>336</i> <span class="sd">        -------</span></tt>
-            </div>
-            <div id="l337"
-               class="code sev- "><tt><i>337</i> <span class="sd">        count: dict</span></tt>
-            </div>
-            <div id="l338"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (92 > 79 characters)</li>
-               
-               </ul><tt><i>338</i> <span class="sd">            Significance of the rule set with familiy-wise error rate correction. Dictionary</span></tt>
-            </div>
-            <div id="l339"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (93 > 79 characters)</li>
-               
-               </ul><tt><i>339</i> <span class="sd">             contains two fields: *fraction* (fraction of rules significant at assumed level)</span></tt>
-            </div>
-            <div id="l340"
-               class="code sev- "><tt><i>340</i> <span class="sd">             and *p* (average p-value of all rules).</span></tt>
-            </div>
-            <div id="l341"
-               class="code sev- "><tt><i>341</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l342"
-               class="code sev- "><tt><i>342</i>         <span class="n">significance</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_java_object</span><span class="o">.</span><span class="n">calculateSignificanceFWER</span><span class="p">(</span><span class="n">alpha</span><span class="p">)</span></tt>
-            </div>
-            <div id="l343"
-               class="code sev- "><tt><i>343</i>         <span class="k">return</span> <span class="p">{</span></tt>
-            </div>
-            <div id="l344"
-               class="code sev- "><tt><i>344</i>             <span class="s1">&#39;p&#39;</span><span class="p">:</span> <span class="n">significance</span><span class="o">.</span><span class="n">p</span><span class="p">,</span></tt>
-            </div>
-            <div id="l345"
-               class="code sev- "><tt><i>345</i>             <span class="s1">&#39;fraction&#39;</span><span class="p">:</span> <span class="n">significance</span><span class="o">.</span><span class="n">fraction</span></tt>
-            </div>
-            <div id="l346"
-               class="code sev- "><tt><i>346</i>         <span class="p">}</span></tt>
-            </div>
-            <div id="l347"
-               class="code sev- "><tt><i>347</i> &nbsp;</tt>
-            </div>
-            <div id="l348"
-               class="code sev- "><tt><i>348</i>     <span class="k">def</span> <span class="fm">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span></tt>
-            </div>
-            <div id="l349"
-               class="code sev- "><tt><i>349</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Returns string representation of the object.&quot;&quot;&quot;</span></tt>
-            </div>
-            <div id="l350"
-               class="code sev- "><tt><i>350</i>         <span class="k">return</span> <span class="nb">str</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_java_object</span><span class="o">.</span><span class="n">toString</span><span class="p">())</span></tt>
-            </div>
-            
-         </div>
-      </div>
-   </body>
-</html>
\ No newline at end of file
diff --git a/docs/reports/flake8/rulekit.survival.report.html b/docs/reports/flake8/rulekit.survival.report.html
index 73b5fa6..0b8389f 100644
--- a/docs/reports/flake8/rulekit.survival.report.html
+++ b/docs/reports/flake8/rulekit.survival.report.html
@@ -52,699 +52,34 @@ <h1>
          <li>
             <a data-code="E501">
                <span class="count sev-2">
-                  98
+                  3
                </span>
-               <strong>E501:</strong> line too long (92 > 79 characters)
+               <strong>E501:</strong> line too long (94 > 88 characters)
                
-                  (and 19 similar)
+                  (and 2 similar)
                
             </a>
             <ul class="details">
             <li>
                
-               <p>Line too long (92 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l36">
-                  <tt><i>36</i>     <span class="n">max_uncovered_fraction</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">float</span><span class="p">]</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;max_uncovered_fraction&#39;</span><span class="p">]</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (89 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l37">
-                  <tt><i>37</i>     <span class="n">select_best_candidate</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">bool</span><span class="p">]</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;select_best_candidate&#39;</span><span class="p">]</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (95 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l38">
-                  <tt><i>38</i>     <span class="n">complementary_conditions</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">bool</span><span class="p">]</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;complementary_conditions&#39;</span><span class="p">]</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (94 > 79 characters):</p>
+               <p>Line too long (94 > 88 characters):</p>
                
                <a href="rulekit.survival.source.html#l56">
                   <tt><i>56</i>             <span class="bp">self</span><span class="o">.</span><span class="n">model</span><span class="o">.</span><span class="n">_java_object</span><span class="o">.</span><span class="n">getTrainingEstimator</span><span class="p">()</span>  <span class="c1"># pylint: disable=protected-access</span></tt>
                </a>
             </li><li>
                
-               <p>Line too long (87 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l72">
-                  <tt><i>72</i>         <span class="n">max_uncovered_fraction</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;max_uncovered_fraction&#39;</span><span class="p">],</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (84 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l73">
-                  <tt><i>73</i>         <span class="n">select_best_candidate</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;select_best_candidate&#39;</span><span class="p">],</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (90 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l74">
-                  <tt><i>74</i>         <span class="n">complementary_conditions</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;complementary_conditions&#39;</span><span class="p">],</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (97 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l81">
-                  <tt><i>81</i> <span class="sd">            name of column containing survival time data (use when data passed to model is padnas</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (91 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l84">
-                  <tt><i>84</i> <span class="sd">            a minimum number (or fraction, if value &lt; 1.0) of previously uncovered examples</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (101 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l85">
-                  <tt><i>85</i> <span class="sd">             to be covered by a new rule (positive examples for classification problems); default: 5,</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (96 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l87">
-                  <tt><i>87</i> <span class="sd">            non-negative integer representing maximum number of conditions which can be added to</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (99 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l88">
-                  <tt><i>88</i> <span class="sd">            the rule in the growing phase  (use this parameter for large datasets if execution time</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (97 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l93">
-                  <tt><i>93</i> <span class="sd">            boolean telling whether missing values should be ignored (by default, a missing value</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (100 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l94">
-                  <tt><i>94</i> <span class="sd">             of given attribute is always considered as not fulfilling the condition build upon that</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (95 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l97">
-                  <tt><i>97</i> <span class="sd">            Floating-point number from [0,1] interval representing maximum fraction of examples</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (85 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l100">
-                  <tt><i>100</i> <span class="sd">            Flag determining if best candidate should be selected from growing phase;</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (96 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l103">
-                  <tt><i>103</i> <span class="sd">            If enabled, complementary conditions in the form a = !{value} for nominal attributes</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (92 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l106">
-                  <tt><i>106</i> <span class="sd">            Maximum number of rules to be generated (for classification data sets it applies</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (84 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l130">
-                  <tt><i>130</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Set models hyperparameters. Parameters are the same as in constructor.&quot;&quot;&quot;</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (94 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l153">
-                  <tt><i>153</i>                 <span class="s1">&#39;Data values must be instance of either pandas DataFrame, numpy array or list&#39;</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (94 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l157">
-                  <tt><i>157</i>     <span class="k">def</span> <span class="nf">_prepare_survival_attribute</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">survival_time</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">Data</span><span class="p">],</span> <span class="n">values</span><span class="p">:</span> <span class="n">Data</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">str</span><span class="p">:</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (127 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l168">
-                  <tt><i>168</i>     <span class="k">def</span> <span class="nf">fit</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">:</span> <span class="n">Data</span><span class="p">,</span> <span class="n">labels</span><span class="p">:</span> <span class="n">Data</span><span class="p">,</span> <span class="n">survival_time</span><span class="p">:</span> <span class="n">Data</span> <span class="o">=</span> <span class="kc">None</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">SurvivalRules</span><span class="p">:</span>  <span class="c1"># pylint: disable=arguments-differ</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (90 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l178">
-                  <tt><i>178</i> <span class="sd">            data about survival time. Could be omitted when *survival_time_attr* parameter</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (86 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l191">
-                  <tt><i>191</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Perform prediction and return estimated survival function for each example.</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (99 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l201">
-                  <tt><i>201</i> <span class="sd">            Each row represent single example from dataset and contains estimated survival function</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (96 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l202">
-                  <tt><i>202</i> <span class="sd">            for that example. Estimated survival function is returned as a dictionary containing</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (85 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l207">
-                  <tt><i>207</i>     <span class="k">def</span> <span class="nf">score</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">:</span> <span class="n">Data</span><span class="p">,</span> <span class="n">labels</span><span class="p">:</span> <span class="n">Data</span><span class="p">,</span> <span class="n">survival_time</span><span class="p">:</span> <span class="n">Data</span> <span class="o">=</span> <span class="kc">None</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">float</span><span class="p">:</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (93 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l211">
-                  <tt><i>211</i> <span class="sd">        Integrated Brier Score (IBS) - the Brier score (BS) represents the squared difference</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (85 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l212">
-                  <tt><i>212</i> <span class="sd">         between true event status at time T and predicted event status at that time;</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (98 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l213">
-                  <tt><i>213</i> <span class="sd">         the Integrated Brier score summarizes the prediction error over all observations and over</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (94 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l223">
-                  <tt><i>223</i> <span class="sd">            data about survival time. Could be omitted when *survival_time_attr* parameter was</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (98 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l237">
-                  <tt><i>237</i>         <span class="n">predicted_example_set</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">model</span><span class="o">.</span><span class="n">_java_object</span><span class="o">.</span><span class="n">apply</span><span class="p">(</span>  <span class="c1"># pylint: disable=protected-access</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (93 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l258">
-                  <tt><i>258</i>     <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span>  <span class="c1"># pylint: disable=super-init-not-called,too-many-arguments,too-many-locals</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (87 > 79 characters):</p>
+               <p>Line too long (93 > 88 characters):</p>
                
                <a href="rulekit.survival.source.html#l265">
-                  <tt><i>265</i>         <span class="n">max_uncovered_fraction</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;max_uncovered_fraction&#39;</span><span class="p">],</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (84 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l266">
-                  <tt><i>266</i>         <span class="n">select_best_candidate</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;select_best_candidate&#39;</span><span class="p">],</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (90 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l267">
-                  <tt><i>267</i>         <span class="n">complementary_conditions</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;complementary_conditions&#39;</span><span class="p">],</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (86 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l269">
-                  <tt><i>269</i>         <span class="n">extend_using_preferred</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;extend_using_preferred&#39;</span><span class="p">],</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (86 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l270">
-                  <tt><i>270</i>         <span class="n">extend_using_automatic</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;extend_using_automatic&#39;</span><span class="p">],</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (86 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l271">
-                  <tt><i>271</i>         <span class="n">induce_using_preferred</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;induce_using_preferred&#39;</span><span class="p">],</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (86 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l272">
-                  <tt><i>272</i>         <span class="n">induce_using_automatic</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;induce_using_automatic&#39;</span><span class="p">],</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (91 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l283">
-                  <tt><i>283</i> <span class="sd">            a minimum number (or fraction, if value &lt; 1.0) of previously uncovered examples</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (101 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l284">
-                  <tt><i>284</i> <span class="sd">             to be covered by a new rule (positive examples for classification problems); default: 5,</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (97 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l286">
-                  <tt><i>286</i> <span class="sd">            name of column containing survival time data (use when data passed to model is pandas</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (96 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l289">
-                  <tt><i>289</i> <span class="sd">            non-negative integer representing maximum number of conditions which can be added to</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (98 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l290">
-                  <tt><i>290</i> <span class="sd">            the rule in the growing phase (use this parameter for large datasets if execution time</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (97 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l295">
-                  <tt><i>295</i> <span class="sd">            boolean telling whether missing values should be ignored (by default, a missing value</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (99 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l296">
-                  <tt><i>296</i> <span class="sd">            of given attribute is always considered as not fulfilling the condition build upon that</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (95 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l299">
-                  <tt><i>299</i> <span class="sd">            Floating-point number from [0,1] interval representing maximum fraction of examples</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (85 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l302">
-                  <tt><i>302</i> <span class="sd">            Flag determining if best candidate should be selected from growing phase;</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (96 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l305">
-                  <tt><i>305</i> <span class="sd">            If enabled, complementary conditions in the form a = !{value} for nominal attributes</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (92 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l308">
-                  <tt><i>308</i> <span class="sd">            Maximum number of rules to be generated (for classification data sets it applies</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (95 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l312">
-                  <tt><i>312</i> <span class="sd">            boolean indicating whether initial rules should be extended with a use of preferred</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (95 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l315">
-                  <tt><i>315</i> <span class="sd">            boolean indicating whether initial rules should be extended with a use of automatic</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (90 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l318">
-                  <tt><i>318</i> <span class="sd">            boolean indicating whether new rules should be induced with a use of preferred</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (90 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l321">
-                  <tt><i>321</i> <span class="sd">            boolean indicating whether new rules should be induced with a use of automatic</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (80 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l324">
-                  <tt><i>324</i> <span class="sd">            maximum number of preferred conditions per rule; default: unlimited,</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (80 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l326">
-                  <tt><i>326</i> <span class="sd">            maximum number of preferred attributes per rule; default: unlimited.</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (94 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l377">
-                  <tt><i>377</i> <span class="sd">            data about survival time. Could be omitted when *survival_time_attr* parameter was</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (98 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l381">
-                  <tt><i>381</i> <span class="sd">            set of initial rules, either passed as a list of strings representing rules or as list</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (94 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l385">
-                  <tt><i>385</i> <span class="sd">            multiset of preferred conditions (used also for specifying preferred attributes by</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (98 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l386">
-                  <tt><i>386</i> <span class="sd">             using special value Any). Either passed as a list of strings representing rules or as</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (97 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l387">
-                  <tt><i>387</i> <span class="sd">            list of tuples where first element is name of the rule and second one is rule string.</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (95 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l389">
-                  <tt><i>389</i> <span class="sd">            set of forbidden conditions (used also for specifying forbidden attributes by using</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (97 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l390">
-                  <tt><i>390</i> <span class="sd">             special valye Any). Either passed as a list of strings representing rules or as list</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (92 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l391">
-                  <tt><i>391</i> <span class="sd">            of tuples where first element is name of the rule and second one is rule string.</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (97 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l410">
-                  <tt><i>410</i>         <span class="k">return</span> <span class="n">PredictionResultMapper</span><span class="o">.</span><span class="n">map_survival</span><span class="p">(</span><span class="n">ExpertKnowledgeOperator</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">))</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (85 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l416">
-                  <tt><i>416</i> <span class="k">class</span> <span class="nc">_SurvivalContrastSetModelParams</span><span class="p">(</span><span class="n">ContrastSetModelParams</span><span class="p">,</span> <span class="n">_SurvivalModelsParams</span><span class="p">):</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (87 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l439">
-                  <tt><i>439</i>         <span class="n">max_uncovered_fraction</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;max_uncovered_fraction&#39;</span><span class="p">],</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (84 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l440">
-                  <tt><i>440</i>         <span class="n">select_best_candidate</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;select_best_candidate&#39;</span><span class="p">],</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (90 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l441">
-                  <tt><i>441</i>         <span class="n">complementary_conditions</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;complementary_conditions&#39;</span><span class="p">],</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (99 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l448">
-                  <tt><i>448</i> <span class="sd">            a minimum positive support of a contrast set (p/P). When multiple values are specified,</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (97 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l449">
-                  <tt><i>449</i> <span class="sd">            a metainduction is performed; Default and recommended sequence is: 0.8, 0.5, 0.2, 0.1</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (84 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l451">
-                  <tt><i>451</i> <span class="sd">            a maximum ratio of negative to positive supports (nP/pN); Default is 0.5</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (97 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l453">
-                  <tt><i>453</i> <span class="sd">            a maximum number of sequential covering passes for a single minsupp-all; Default is 5</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (85 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l457">
-                  <tt><i>457</i> <span class="sd">            the value of p_new / P at which penalty reward saturates; Default is 0.2.</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (97 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l459">
-                  <tt><i>459</i> <span class="sd">            name of column containing survival time data (use when data passed to model is pandas</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (91 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l462">
-                  <tt><i>462</i> <span class="sd">            a minimum number (or fraction, if value &lt; 1.0) of previously uncovered examples</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (101 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l463">
-                  <tt><i>463</i> <span class="sd">             to be covered by a new rule (positive examples for classification problems); default: 5,</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (96 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l465">
-                  <tt><i>465</i> <span class="sd">            non-negative integer representing maximum number of conditions which can be added to</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (99 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l466">
-                  <tt><i>466</i> <span class="sd">             the rule in the growing phase (use this parameter for large datasets if execution time</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (97 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l471">
-                  <tt><i>471</i> <span class="sd">            boolean telling whether missing values should be ignored (by default, a missing value</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (100 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l472">
-                  <tt><i>472</i> <span class="sd">             of given attribute is always considered as not fulfilling the condition build upon that</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (95 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l475">
-                  <tt><i>475</i> <span class="sd">            Floating-point number from [0,1] interval representing maximum fraction of examples</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (85 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l478">
-                  <tt><i>478</i> <span class="sd">            Flag determining if best candidate should be selected from growing phase;</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (96 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l481">
-                  <tt><i>481</i> <span class="sd">            If enabled, complementary conditions in the form a = !{value} for nominal attributes</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (92 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l484">
-                  <tt><i>484</i> <span class="sd">            Maximum number of rules to be generated (for classification data sets it applies</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (84 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l511">
-                  <tt><i>511</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Set models hyperparameters. Parameters are the same as in constructor.&quot;&quot;&quot;</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (90 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l534">
-                  <tt><i>534</i> <span class="sd">            data about survival time. Could be omitted when *survival_time_attr* parameter</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (112 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l541">
-                  <tt><i>541</i>         <span class="n">survival_time_attribute</span> <span class="o">=</span> <span class="n">SurvivalRules</span><span class="o">.</span><span class="n">_prepare_survival_attribute</span><span class="p">(</span>  <span class="c1"># pylint: disable=protected-access</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (86 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l551">
-                  <tt><i>551</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Perform prediction and return estimated survival function for each example.</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (99 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l561">
-                  <tt><i>561</i> <span class="sd">            Each row represent single example from dataset and contains estimated survival function</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (96 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l562">
-                  <tt><i>562</i> <span class="sd">            for that example. Estimated survival function is returned as a dictionary containing</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (85 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l567">
-                  <tt><i>567</i>     <span class="k">def</span> <span class="nf">score</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">:</span> <span class="n">Data</span><span class="p">,</span> <span class="n">labels</span><span class="p">:</span> <span class="n">Data</span><span class="p">,</span> <span class="n">survival_time</span><span class="p">:</span> <span class="n">Data</span> <span class="o">=</span> <span class="kc">None</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">float</span><span class="p">:</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (93 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l571">
-                  <tt><i>571</i> <span class="sd">        Integrated Brier Score (IBS) - the Brier score (BS) represents the squared difference</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (84 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l572">
-                  <tt><i>572</i> <span class="sd">        between true event status at time T and predicted event status at that time;</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (93 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l573">
-                  <tt><i>573</i> <span class="sd">         the Integrated Brier score summarizes the prediction error over all observations and</span></tt>
-               </a>
-            </li><li>
-               
-               <p>Line too long (94 > 79 characters):</p>
-               
-               <a href="rulekit.survival.source.html#l583">
-                  <tt><i>583</i> <span class="sd">            data about survival time. Could be omitted when *survival_time_attr* parameter was</span></tt>
+                  <tt><i>265</i>     <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span>  <span class="c1"># pylint: disable=super-init-not-called,too-many-arguments,too-many-locals</span></tt>
                </a>
             </li><li>
                
-               <p>Line too long (85 > 79 characters):</p>
+               <p>Line too long (112 > 88 characters):</p>
                
-               <a href="rulekit.survival.source.html#l591">
-                  <tt><i>591</i>         <span class="k">return</span> <span class="n">SurvivalRules</span><span class="o">.</span><span class="n">score</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">,</span> <span class="n">labels</span><span class="p">,</span> <span class="n">survival_time</span><span class="o">=</span><span class="n">survival_time</span><span class="p">)</span></tt>
+               <a href="rulekit.survival.source.html#l557">
+                  <tt><i>557</i>         <span class="n">survival_time_attribute</span> <span class="o">=</span> <span class="n">SurvivalRules</span><span class="o">.</span><span class="n">_prepare_survival_attribute</span><span class="p">(</span>  <span class="c1"># pylint: disable=protected-access</span></tt>
                </a>
             </li>
             </ul>
diff --git a/docs/reports/flake8/rulekit.survival.source.html b/docs/reports/flake8/rulekit.survival.source.html
index 69187b3..84e748d 100644
--- a/docs/reports/flake8/rulekit.survival.source.html
+++ b/docs/reports/flake8/rulekit.survival.source.html
@@ -23,139 +23,112 @@ <h1>
                class="code sev- "><tt><i>2</i> <span class="sd">&quot;&quot;&quot;</span></tt>
             </div>
             <div id="l3"
-               class="code sev- "><tt><i>3</i> <span class="kn">from</span> <span class="nn">__future__</span> <span class="kn">import</span> <span class="n">annotations</span></tt>
+               class="code sev- "><tt><i>3</i> &nbsp;</tt>
             </div>
             <div id="l4"
-               class="code sev- "><tt><i>4</i> &nbsp;</tt>
+               class="code sev- "><tt><i>4</i> <span class="kn">from</span> <span class="nn">__future__</span> <span class="kn">import</span> <span class="n">annotations</span></tt>
             </div>
             <div id="l5"
-               class="code sev- "><tt><i>5</i> <span class="kn">from</span> <span class="nn">typing</span> <span class="kn">import</span> <span class="n">Optional</span></tt>
+               class="code sev- "><tt><i>5</i> &nbsp;</tt>
             </div>
             <div id="l6"
-               class="code sev- "><tt><i>6</i> <span class="kn">from</span> <span class="nn">typing</span> <span class="kn">import</span> <span class="n">Tuple</span></tt>
+               class="code sev- "><tt><i>6</i> <span class="kn">from</span> <span class="nn">typing</span> <span class="kn">import</span> <span class="n">Optional</span><span class="p">,</span> <span class="n">Tuple</span><span class="p">,</span> <span class="n">Union</span></tt>
             </div>
             <div id="l7"
-               class="code sev- "><tt><i>7</i> <span class="kn">from</span> <span class="nn">typing</span> <span class="kn">import</span> <span class="n">Union</span></tt>
+               class="code sev- "><tt><i>7</i> &nbsp;</tt>
             </div>
             <div id="l8"
-               class="code sev- "><tt><i>8</i> &nbsp;</tt>
+               class="code sev- "><tt><i>8</i> <span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span></tt>
             </div>
             <div id="l9"
-               class="code sev- "><tt><i>9</i> <span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span></tt>
+               class="code sev- "><tt><i>9</i> <span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span></tt>
             </div>
             <div id="l10"
-               class="code sev- "><tt><i>10</i> <span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span></tt>
+               class="code sev- "><tt><i>10</i> <span class="kn">from</span> <span class="nn">jpype</span> <span class="kn">import</span> <span class="n">JClass</span></tt>
             </div>
             <div id="l11"
-               class="code sev- "><tt><i>11</i> <span class="kn">from</span> <span class="nn">jpype</span> <span class="kn">import</span> <span class="n">JClass</span></tt>
+               class="code sev- "><tt><i>11</i> <span class="kn">from</span> <span class="nn">pydantic</span> <span class="kn">import</span> <span class="n">BaseModel</span>  <span class="c1"># pylint: disable=no-name-in-module</span></tt>
             </div>
             <div id="l12"
-               class="code sev- "><tt><i>12</i> <span class="kn">from</span> <span class="nn">pydantic</span> <span class="kn">import</span> <span class="n">BaseModel</span>  <span class="c1"># pylint: disable=no-name-in-module</span></tt>
+               class="code sev- "><tt><i>12</i> &nbsp;</tt>
             </div>
             <div id="l13"
-               class="code sev- "><tt><i>13</i> &nbsp;</tt>
+               class="code sev- "><tt><i>13</i> <span class="kn">from</span> <span class="nn">rulekit._helpers</span> <span class="kn">import</span> <span class="n">ExampleSetFactory</span><span class="p">,</span> <span class="n">PredictionResultMapper</span></tt>
             </div>
             <div id="l14"
-               class="code sev- "><tt><i>14</i> <span class="kn">from</span> <span class="nn">rulekit._helpers</span> <span class="kn">import</span> <span class="n">ExampleSetFactory</span></tt>
+               class="code sev- "><tt><i>14</i> <span class="kn">from</span> <span class="nn">rulekit._operator</span> <span class="kn">import</span> <span class="n">BaseOperator</span><span class="p">,</span> <span class="n">Data</span><span class="p">,</span> <span class="n">ExpertKnowledgeOperator</span></tt>
             </div>
             <div id="l15"
-               class="code sev- "><tt><i>15</i> <span class="kn">from</span> <span class="nn">rulekit._helpers</span> <span class="kn">import</span> <span class="n">PredictionResultMapper</span></tt>
+               class="code sev- "><tt><i>15</i> <span class="kn">from</span> <span class="nn">rulekit._problem_types</span> <span class="kn">import</span> <span class="n">ProblemType</span></tt>
             </div>
             <div id="l16"
-               class="code sev- "><tt><i>16</i> <span class="kn">from</span> <span class="nn">rulekit._operator</span> <span class="kn">import</span> <span class="n">BaseOperator</span></tt>
+               class="code sev- "><tt><i>16</i> <span class="kn">from</span> <span class="nn">rulekit.kaplan_meier</span> <span class="kn">import</span> <span class="n">KaplanMeierEstimator</span></tt>
             </div>
             <div id="l17"
-               class="code sev- "><tt><i>17</i> <span class="kn">from</span> <span class="nn">rulekit._operator</span> <span class="kn">import</span> <span class="n">Data</span></tt>
+               class="code sev- "><tt><i>17</i> <span class="kn">from</span> <span class="nn">rulekit.params</span> <span class="kn">import</span> <span class="p">(</span><span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">,</span> <span class="n">ContrastSetModelParams</span><span class="p">,</span></tt>
             </div>
             <div id="l18"
-               class="code sev- "><tt><i>18</i> <span class="kn">from</span> <span class="nn">rulekit._operator</span> <span class="kn">import</span> <span class="n">ExpertKnowledgeOperator</span></tt>
+               class="code sev- "><tt><i>18</i>                             <span class="n">ExpertModelParams</span><span class="p">)</span></tt>
             </div>
             <div id="l19"
-               class="code sev- "><tt><i>19</i> <span class="kn">from</span> <span class="nn">rulekit._problem_types</span> <span class="kn">import</span> <span class="n">ProblemType</span></tt>
+               class="code sev- "><tt><i>19</i> <span class="kn">from</span> <span class="nn">rulekit.rules</span> <span class="kn">import</span> <span class="n">RuleSet</span><span class="p">,</span> <span class="n">SurvivalRule</span></tt>
             </div>
             <div id="l20"
-               class="code sev- "><tt><i>20</i> <span class="kn">from</span> <span class="nn">rulekit.kaplan_meier</span> <span class="kn">import</span> <span class="n">KaplanMeierEstimator</span></tt>
+               class="code sev- "><tt><i>20</i> &nbsp;</tt>
             </div>
             <div id="l21"
-               class="code sev- "><tt><i>21</i> <span class="kn">from</span> <span class="nn">rulekit.params</span> <span class="kn">import</span> <span class="n">ContrastSetModelParams</span></tt>
+               class="code sev- "><tt><i>21</i> <span class="n">_DEFAULT_SURVIVAL_TIME_ATTR</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="s2">&quot;survival_time&quot;</span></tt>
             </div>
             <div id="l22"
-               class="code sev- "><tt><i>22</i> <span class="kn">from</span> <span class="nn">rulekit.params</span> <span class="kn">import</span> <span class="n">DEFAULT_PARAMS_VALUE</span></tt>
+               class="code sev- "><tt><i>22</i> &nbsp;</tt>
             </div>
             <div id="l23"
-               class="code sev- "><tt><i>23</i> <span class="kn">from</span> <span class="nn">rulekit.params</span> <span class="kn">import</span> <span class="n">ExpertModelParams</span></tt>
+               class="code sev- "><tt><i>23</i> &nbsp;</tt>
             </div>
             <div id="l24"
-               class="code sev- "><tt><i>24</i> <span class="kn">from</span> <span class="nn">rulekit.rules</span> <span class="kn">import</span> <span class="n">RuleSet</span></tt>
+               class="code sev- "><tt><i>24</i> <span class="k">class</span> <span class="nc">_SurvivalModelsParams</span><span class="p">(</span><span class="n">BaseModel</span><span class="p">):</span></tt>
             </div>
             <div id="l25"
-               class="code sev- "><tt><i>25</i> <span class="kn">from</span> <span class="nn">rulekit.rules</span> <span class="kn">import</span> <span class="n">SurvivalRule</span></tt>
+               class="code sev- "><tt><i>25</i>     <span class="n">survival_time_attr</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">str</span><span class="p">]</span></tt>
             </div>
             <div id="l26"
-               class="code sev- "><tt><i>26</i> &nbsp;</tt>
+               class="code sev- "><tt><i>26</i>     <span class="n">minsupp_new</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">float</span><span class="p">]</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;minsupp_new&quot;</span><span class="p">]</span></tt>
             </div>
             <div id="l27"
-               class="code sev- "><tt><i>27</i> <span class="n">_DEFAULT_SURVIVAL_TIME_ATTR</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="s1">&#39;survival_time&#39;</span></tt>
+               class="code sev- "><tt><i>27</i>     <span class="n">max_growing</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">float</span><span class="p">]</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;max_growing&quot;</span><span class="p">]</span></tt>
             </div>
             <div id="l28"
-               class="code sev- "><tt><i>28</i> &nbsp;</tt>
+               class="code sev- "><tt><i>28</i>     <span class="n">enable_pruning</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">bool</span><span class="p">]</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;enable_pruning&quot;</span><span class="p">]</span></tt>
             </div>
             <div id="l29"
-               class="code sev- "><tt><i>29</i> &nbsp;</tt>
+               class="code sev- "><tt><i>29</i>     <span class="n">ignore_missing</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">bool</span><span class="p">]</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;ignore_missing&quot;</span><span class="p">]</span></tt>
             </div>
             <div id="l30"
-               class="code sev- "><tt><i>30</i> <span class="k">class</span> <span class="nc">_SurvivalModelsParams</span><span class="p">(</span><span class="n">BaseModel</span><span class="p">):</span></tt>
+               class="code sev- "><tt><i>30</i>     <span class="n">max_uncovered_fraction</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">float</span><span class="p">]</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span></tt>
             </div>
             <div id="l31"
-               class="code sev- "><tt><i>31</i>     <span class="n">survival_time_attr</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">str</span><span class="p">]</span></tt>
+               class="code sev- "><tt><i>31</i>         <span class="s2">&quot;max_uncovered_fraction&quot;</span></tt>
             </div>
             <div id="l32"
-               class="code sev- "><tt><i>32</i>     <span class="n">minsupp_new</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">float</span><span class="p">]</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;minsupp_new&#39;</span><span class="p">]</span></tt>
+               class="code sev- "><tt><i>32</i>     <span class="p">]</span></tt>
             </div>
             <div id="l33"
-               class="code sev- "><tt><i>33</i>     <span class="n">max_growing</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">float</span><span class="p">]</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;max_growing&#39;</span><span class="p">]</span></tt>
+               class="code sev- "><tt><i>33</i>     <span class="n">select_best_candidate</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">bool</span><span class="p">]</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span></tt>
             </div>
             <div id="l34"
-               class="code sev- "><tt><i>34</i>     <span class="n">enable_pruning</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">bool</span><span class="p">]</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;enable_pruning&#39;</span><span class="p">]</span></tt>
+               class="code sev- "><tt><i>34</i>         <span class="s2">&quot;select_best_candidate&quot;</span></tt>
             </div>
             <div id="l35"
-               class="code sev- "><tt><i>35</i>     <span class="n">ignore_missing</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">bool</span><span class="p">]</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;ignore_missing&#39;</span><span class="p">]</span></tt>
+               class="code sev- "><tt><i>35</i>     <span class="p">]</span></tt>
             </div>
             <div id="l36"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (92 > 79 characters)</li>
-               
-               </ul><tt><i>36</i>     <span class="n">max_uncovered_fraction</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">float</span><span class="p">]</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;max_uncovered_fraction&#39;</span><span class="p">]</span></tt>
+               class="code sev- "><tt><i>36</i>     <span class="n">complementary_conditions</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">bool</span><span class="p">]</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span></tt>
             </div>
             <div id="l37"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (89 > 79 characters)</li>
-               
-               </ul><tt><i>37</i>     <span class="n">select_best_candidate</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">bool</span><span class="p">]</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;select_best_candidate&#39;</span><span class="p">]</span></tt>
+               class="code sev- "><tt><i>37</i>         <span class="s2">&quot;complementary_conditions&quot;</span></tt>
             </div>
             <div id="l38"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (95 > 79 characters)</li>
-               
-               </ul><tt><i>38</i>     <span class="n">complementary_conditions</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">bool</span><span class="p">]</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;complementary_conditions&#39;</span><span class="p">]</span></tt>
+               class="code sev- "><tt><i>38</i>     <span class="p">]</span></tt>
             </div>
             <div id="l39"
                class="code sev- "><tt><i>39</i> &nbsp;</tt>
@@ -216,7 +189,7 @@ <h1>
                      <span class="count sev-2">
                         E501
                      </span>
-                     Line too long (94 > 79 characters)</li>
+                     Line too long (94 > 88 characters)</li>
                
                </ul><tt><i>56</i>             <span class="bp">self</span><span class="o">.</span><span class="n">model</span><span class="o">.</span><span class="n">_java_object</span><span class="o">.</span><span class="n">getTrainingEstimator</span><span class="p">()</span>  <span class="c1"># pylint: disable=protected-access</span></tt>
             </div>
@@ -254,331 +227,196 @@ <h1>
                class="code sev- "><tt><i>67</i>         <span class="n">survival_time_attr</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span></tt>
             </div>
             <div id="l68"
-               class="code sev- "><tt><i>68</i>         <span class="n">minsupp_new</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;minsupp_new&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>68</i>         <span class="n">minsupp_new</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;minsupp_new&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l69"
-               class="code sev- "><tt><i>69</i>         <span class="n">max_growing</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;max_growing&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>69</i>         <span class="n">max_growing</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;max_growing&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l70"
-               class="code sev- "><tt><i>70</i>         <span class="n">enable_pruning</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;enable_pruning&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>70</i>         <span class="n">enable_pruning</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;enable_pruning&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l71"
-               class="code sev- "><tt><i>71</i>         <span class="n">ignore_missing</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;ignore_missing&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>71</i>         <span class="n">ignore_missing</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;ignore_missing&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l72"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (87 > 79 characters)</li>
-               
-               </ul><tt><i>72</i>         <span class="n">max_uncovered_fraction</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;max_uncovered_fraction&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>72</i>         <span class="n">max_uncovered_fraction</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;max_uncovered_fraction&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l73"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (84 > 79 characters)</li>
-               
-               </ul><tt><i>73</i>         <span class="n">select_best_candidate</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;select_best_candidate&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>73</i>         <span class="n">select_best_candidate</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;select_best_candidate&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l74"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (90 > 79 characters)</li>
-               
-               </ul><tt><i>74</i>         <span class="n">complementary_conditions</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;complementary_conditions&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>74</i>         <span class="n">complementary_conditions</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span></tt>
             </div>
             <div id="l75"
-               class="code sev- "><tt><i>75</i>         <span class="n">max_rule_count</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;max_rule_count&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>75</i>             <span class="s2">&quot;complementary_conditions&quot;</span></tt>
             </div>
             <div id="l76"
-               class="code sev- "><tt><i>76</i>     <span class="p">):</span></tt>
+               class="code sev- "><tt><i>76</i>         <span class="p">],</span></tt>
             </div>
             <div id="l77"
-               class="code sev- "><tt><i>77</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;</span></tt>
+               class="code sev- "><tt><i>77</i>         <span class="n">max_rule_count</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;max_rule_count&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l78"
-               class="code sev- "><tt><i>78</i> <span class="sd">        Parameters</span></tt>
+               class="code sev- "><tt><i>78</i>     <span class="p">):</span></tt>
             </div>
             <div id="l79"
-               class="code sev- "><tt><i>79</i> <span class="sd">        ----------</span></tt>
+               class="code sev- "><tt><i>79</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;</span></tt>
             </div>
             <div id="l80"
-               class="code sev- "><tt><i>80</i> <span class="sd">        survival_time_attr : str</span></tt>
+               class="code sev- "><tt><i>80</i> <span class="sd">        Parameters</span></tt>
             </div>
             <div id="l81"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (97 > 79 characters)</li>
-               
-               </ul><tt><i>81</i> <span class="sd">            name of column containing survival time data (use when data passed to model is padnas</span></tt>
+               class="code sev- "><tt><i>81</i> <span class="sd">        ----------</span></tt>
             </div>
             <div id="l82"
-               class="code sev- "><tt><i>82</i> <span class="sd">            dataframe).</span></tt>
+               class="code sev- "><tt><i>82</i> <span class="sd">        survival_time_attr : str</span></tt>
             </div>
             <div id="l83"
-               class="code sev- "><tt><i>83</i> <span class="sd">        minsupp_new : float = 5.0</span></tt>
+               class="code sev- "><tt><i>83</i> <span class="sd">            name of column containing survival time data (use when data passed to model</span></tt>
             </div>
             <div id="l84"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (91 > 79 characters)</li>
-               
-               </ul><tt><i>84</i> <span class="sd">            a minimum number (or fraction, if value &lt; 1.0) of previously uncovered examples</span></tt>
+               class="code sev- "><tt><i>84</i> <span class="sd">            is padnas dataframe).</span></tt>
             </div>
             <div id="l85"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (101 > 79 characters)</li>
-               
-               </ul><tt><i>85</i> <span class="sd">             to be covered by a new rule (positive examples for classification problems); default: 5,</span></tt>
+               class="code sev- "><tt><i>85</i> <span class="sd">        minsupp_new : float = 5.0</span></tt>
             </div>
             <div id="l86"
-               class="code sev- "><tt><i>86</i> <span class="sd">        max_growing : int = 0.0</span></tt>
+               class="code sev- "><tt><i>86</i> <span class="sd">            a minimum number (or fraction, if value &lt; 1.0) of previously uncovered</span></tt>
             </div>
             <div id="l87"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (96 > 79 characters)</li>
-               
-               </ul><tt><i>87</i> <span class="sd">            non-negative integer representing maximum number of conditions which can be added to</span></tt>
+               class="code sev- "><tt><i>87</i> <span class="sd">            examples to be covered by a new rule (positive examples for classification</span></tt>
             </div>
             <div id="l88"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (99 > 79 characters)</li>
-               
-               </ul><tt><i>88</i> <span class="sd">            the rule in the growing phase  (use this parameter for large datasets if execution time</span></tt>
+               class="code sev- "><tt><i>88</i> <span class="sd">            problems); default: 5,</span></tt>
             </div>
             <div id="l89"
-               class="code sev- "><tt><i>89</i> <span class="sd">            is prohibitive); 0 indicates no limit; default: 0,</span></tt>
+               class="code sev- "><tt><i>89</i> <span class="sd">        max_growing : int = 0.0</span></tt>
             </div>
             <div id="l90"
-               class="code sev- "><tt><i>90</i> <span class="sd">        enable_pruning : bool = True</span></tt>
+               class="code sev- "><tt><i>90</i> <span class="sd">            non-negative integer representing maximum number of conditions which can be</span></tt>
             </div>
             <div id="l91"
-               class="code sev- "><tt><i>91</i> <span class="sd">            enable or disable pruning, default is True.</span></tt>
+               class="code sev- "><tt><i>91</i> <span class="sd">            added to the rule in the growing phase  (use this parameter for large</span></tt>
             </div>
             <div id="l92"
-               class="code sev- "><tt><i>92</i> <span class="sd">        ignore_missing : bool = False</span></tt>
+               class="code sev- "><tt><i>92</i> <span class="sd">            datasets if execution time is prohibitive); 0 indicates no limit; default: 0</span></tt>
             </div>
             <div id="l93"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (97 > 79 characters)</li>
-               
-               </ul><tt><i>93</i> <span class="sd">            boolean telling whether missing values should be ignored (by default, a missing value</span></tt>
+               class="code sev- "><tt><i>93</i> <span class="sd">        enable_pruning : bool = True</span></tt>
             </div>
             <div id="l94"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (100 > 79 characters)</li>
-               
-               </ul><tt><i>94</i> <span class="sd">             of given attribute is always considered as not fulfilling the condition build upon that</span></tt>
+               class="code sev- "><tt><i>94</i> <span class="sd">            enable or disable pruning, default is True.</span></tt>
             </div>
             <div id="l95"
-               class="code sev- "><tt><i>95</i> <span class="sd">            attribute); default: False.</span></tt>
+               class="code sev- "><tt><i>95</i> <span class="sd">        ignore_missing : bool = False</span></tt>
             </div>
             <div id="l96"
-               class="code sev- "><tt><i>96</i> <span class="sd">        max_uncovered_fraction : float = 0.0</span></tt>
+               class="code sev- "><tt><i>96</i> <span class="sd">            boolean telling whether missing values should be ignored (by default, a</span></tt>
             </div>
             <div id="l97"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (95 > 79 characters)</li>
-               
-               </ul><tt><i>97</i> <span class="sd">            Floating-point number from [0,1] interval representing maximum fraction of examples</span></tt>
+               class="code sev- "><tt><i>97</i> <span class="sd">            missing value of given attribute is always considered as not fulfilling the</span></tt>
             </div>
             <div id="l98"
-               class="code sev- "><tt><i>98</i> <span class="sd">             that may remain uncovered by the rule set, default: 0.0.</span></tt>
+               class="code sev- "><tt><i>98</i> <span class="sd">            condition build upon that attribute); default: False.</span></tt>
             </div>
             <div id="l99"
-               class="code sev- "><tt><i>99</i> <span class="sd">        select_best_candidate : bool = False</span></tt>
+               class="code sev- "><tt><i>99</i> <span class="sd">        max_uncovered_fraction : float = 0.0</span></tt>
             </div>
             <div id="l100"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (85 > 79 characters)</li>
-               
-               </ul><tt><i>100</i> <span class="sd">            Flag determining if best candidate should be selected from growing phase;</span></tt>
+               class="code sev- "><tt><i>100</i> <span class="sd">            Floating-point number from [0,1] interval representing maximum fraction of</span></tt>
             </div>
             <div id="l101"
-               class="code sev- "><tt><i>101</i> <span class="sd">             default: False.</span></tt>
+               class="code sev- "><tt><i>101</i> <span class="sd">            examples that may remain uncovered by the rule set, default: 0.0.</span></tt>
             </div>
             <div id="l102"
-               class="code sev- "><tt><i>102</i> <span class="sd">        complementary_conditions : bool = False</span></tt>
+               class="code sev- "><tt><i>102</i> <span class="sd">        select_best_candidate : bool = False</span></tt>
             </div>
             <div id="l103"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (96 > 79 characters)</li>
-               
-               </ul><tt><i>103</i> <span class="sd">            If enabled, complementary conditions in the form a = !{value} for nominal attributes</span></tt>
+               class="code sev- "><tt><i>103</i> <span class="sd">            Flag determining if best candidate should be selected from growing phase;</span></tt>
             </div>
             <div id="l104"
-               class="code sev- "><tt><i>104</i> <span class="sd">            are supported.</span></tt>
+               class="code sev- "><tt><i>104</i> <span class="sd">             default: False.</span></tt>
             </div>
             <div id="l105"
-               class="code sev- "><tt><i>105</i> <span class="sd">        max_rule_count : int = 0</span></tt>
+               class="code sev- "><tt><i>105</i> <span class="sd">        complementary_conditions : bool = False</span></tt>
             </div>
             <div id="l106"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (92 > 79 characters)</li>
-               
-               </ul><tt><i>106</i> <span class="sd">            Maximum number of rules to be generated (for classification data sets it applies</span></tt>
+               class="code sev- "><tt><i>106</i> <span class="sd">            If enabled, complementary conditions in the form a = !{value} for nominal</span></tt>
             </div>
             <div id="l107"
-               class="code sev- "><tt><i>107</i> <span class="sd">             to a single class); 0 indicates no limit.</span></tt>
+               class="code sev- "><tt><i>107</i> <span class="sd">            attributes are supported.</span></tt>
             </div>
             <div id="l108"
-               class="code sev- "><tt><i>108</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
+               class="code sev- "><tt><i>108</i> <span class="sd">        max_rule_count : int = 0</span></tt>
             </div>
             <div id="l109"
-               class="code sev- "><tt><i>109</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_params</span> <span class="o">=</span> <span class="kc">None</span></tt>
+               class="code sev- "><tt><i>109</i> <span class="sd">            Maximum number of rules to be generated (for classification data sets it</span></tt>
             </div>
             <div id="l110"
-               class="code sev- "><tt><i>110</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_rule_generator</span> <span class="o">=</span> <span class="kc">None</span></tt>
+               class="code sev- "><tt><i>110</i> <span class="sd">            applies to a single class); 0 indicates no limit.</span></tt>
             </div>
             <div id="l111"
-               class="code sev- "><tt><i>111</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_configurator</span> <span class="o">=</span> <span class="kc">None</span></tt>
+               class="code sev- "><tt><i>111</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
             </div>
             <div id="l112"
-               class="code sev- "><tt><i>112</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_initialize_rulekit</span><span class="p">()</span></tt>
+               class="code sev- "><tt><i>112</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_params</span> <span class="o">=</span> <span class="kc">None</span></tt>
             </div>
             <div id="l113"
-               class="code sev- "><tt><i>113</i>         <span class="bp">self</span><span class="o">.</span><span class="n">set_params</span><span class="p">(</span></tt>
+               class="code sev- "><tt><i>113</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_rule_generator</span> <span class="o">=</span> <span class="kc">None</span></tt>
             </div>
             <div id="l114"
-               class="code sev- "><tt><i>114</i>             <span class="n">survival_time_attr</span><span class="o">=</span><span class="n">survival_time_attr</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>114</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_configurator</span> <span class="o">=</span> <span class="kc">None</span></tt>
             </div>
             <div id="l115"
-               class="code sev- "><tt><i>115</i>             <span class="n">minsupp_new</span><span class="o">=</span><span class="n">minsupp_new</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>115</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_initialize_rulekit</span><span class="p">()</span></tt>
             </div>
             <div id="l116"
-               class="code sev- "><tt><i>116</i>             <span class="n">max_growing</span><span class="o">=</span><span class="n">max_growing</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>116</i>         <span class="bp">self</span><span class="o">.</span><span class="n">set_params</span><span class="p">(</span></tt>
             </div>
             <div id="l117"
-               class="code sev- "><tt><i>117</i>             <span class="n">enable_pruning</span><span class="o">=</span><span class="n">enable_pruning</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>117</i>             <span class="n">survival_time_attr</span><span class="o">=</span><span class="n">survival_time_attr</span><span class="p">,</span></tt>
             </div>
             <div id="l118"
-               class="code sev- "><tt><i>118</i>             <span class="n">ignore_missing</span><span class="o">=</span><span class="n">ignore_missing</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>118</i>             <span class="n">minsupp_new</span><span class="o">=</span><span class="n">minsupp_new</span><span class="p">,</span></tt>
             </div>
             <div id="l119"
-               class="code sev- "><tt><i>119</i>             <span class="n">max_uncovered_fraction</span><span class="o">=</span><span class="n">max_uncovered_fraction</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>119</i>             <span class="n">max_growing</span><span class="o">=</span><span class="n">max_growing</span><span class="p">,</span></tt>
             </div>
             <div id="l120"
-               class="code sev- "><tt><i>120</i>             <span class="n">select_best_candidate</span><span class="o">=</span><span class="n">select_best_candidate</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>120</i>             <span class="n">enable_pruning</span><span class="o">=</span><span class="n">enable_pruning</span><span class="p">,</span></tt>
             </div>
             <div id="l121"
-               class="code sev- "><tt><i>121</i>             <span class="n">complementary_conditions</span><span class="o">=</span><span class="n">complementary_conditions</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>121</i>             <span class="n">ignore_missing</span><span class="o">=</span><span class="n">ignore_missing</span><span class="p">,</span></tt>
             </div>
             <div id="l122"
-               class="code sev- "><tt><i>122</i>             <span class="n">max_rule_count</span><span class="o">=</span><span class="n">max_rule_count</span></tt>
+               class="code sev- "><tt><i>122</i>             <span class="n">max_uncovered_fraction</span><span class="o">=</span><span class="n">max_uncovered_fraction</span><span class="p">,</span></tt>
             </div>
             <div id="l123"
-               class="code sev- "><tt><i>123</i>         <span class="p">)</span></tt>
+               class="code sev- "><tt><i>123</i>             <span class="n">select_best_candidate</span><span class="o">=</span><span class="n">select_best_candidate</span><span class="p">,</span></tt>
             </div>
             <div id="l124"
-               class="code sev- "><tt><i>124</i>         <span class="bp">self</span><span class="o">.</span><span class="n">model</span><span class="p">:</span> <span class="n">RuleSet</span><span class="p">[</span><span class="n">SurvivalRule</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span></tt>
+               class="code sev- "><tt><i>124</i>             <span class="n">complementary_conditions</span><span class="o">=</span><span class="n">complementary_conditions</span><span class="p">,</span></tt>
             </div>
             <div id="l125"
-               class="code sev- "><tt><i>125</i> &nbsp;</tt>
+               class="code sev- "><tt><i>125</i>             <span class="n">max_rule_count</span><span class="o">=</span><span class="n">max_rule_count</span><span class="p">,</span></tt>
             </div>
             <div id="l126"
-               class="code sev- "><tt><i>126</i>     <span class="k">def</span> <span class="nf">set_params</span><span class="p">(</span></tt>
+               class="code sev- "><tt><i>126</i>         <span class="p">)</span></tt>
             </div>
             <div id="l127"
-               class="code sev- "><tt><i>127</i>         <span class="bp">self</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>127</i>         <span class="bp">self</span><span class="o">.</span><span class="n">model</span><span class="p">:</span> <span class="n">RuleSet</span><span class="p">[</span><span class="n">SurvivalRule</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span></tt>
             </div>
             <div id="l128"
-               class="code sev- "><tt><i>128</i>         <span class="o">**</span><span class="n">kwargs</span></tt>
+               class="code sev- "><tt><i>128</i> &nbsp;</tt>
             </div>
             <div id="l129"
-               class="code sev- "><tt><i>129</i>     <span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">object</span><span class="p">:</span></tt>
+               class="code sev- "><tt><i>129</i>     <span class="k">def</span> <span class="nf">set_params</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">object</span><span class="p">:</span></tt>
             </div>
             <div id="l130"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (84 > 79 characters)</li>
-               
-               </ul><tt><i>130</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Set models hyperparameters. Parameters are the same as in constructor.&quot;&quot;&quot;</span></tt>
+               class="code sev- "><tt><i>130</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Set models hyperparameters. Parameters are the same as in constructor.&quot;&quot;&quot;</span></tt>
             </div>
             <div id="l131"
-               class="code sev- "><tt><i>131</i>         <span class="bp">self</span><span class="o">.</span><span class="n">survival_time_attr</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;survival_time_attr&#39;</span><span class="p">)</span></tt>
+               class="code sev- "><tt><i>131</i>         <span class="bp">self</span><span class="o">.</span><span class="n">survival_time_attr</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">&quot;survival_time_attr&quot;</span><span class="p">)</span></tt>
             </div>
             <div id="l132"
                class="code sev- "><tt><i>132</i>         <span class="k">return</span> <span class="n">BaseOperator</span><span class="o">.</span><span class="n">set_params</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></tt>
@@ -593,67 +431,58 @@ <h1>
                class="code sev- "><tt><i>135</i>     <span class="k">def</span> <span class="nf">_append_survival_time_columns</span><span class="p">(</span></tt>
             </div>
             <div id="l136"
-               class="code sev- "><tt><i>136</i>         <span class="n">values</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>136</i>         <span class="n">values</span><span class="p">,</span> <span class="n">survival_time</span><span class="p">:</span> <span class="n">Union</span><span class="p">[</span><span class="n">pd</span><span class="o">.</span><span class="n">Series</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">,</span> <span class="nb">list</span><span class="p">]</span></tt>
             </div>
             <div id="l137"
-               class="code sev- "><tt><i>137</i>         <span class="n">survival_time</span><span class="p">:</span> <span class="n">Union</span><span class="p">[</span><span class="n">pd</span><span class="o">.</span><span class="n">Series</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">,</span> <span class="nb">list</span><span class="p">]</span></tt>
+               class="code sev- "><tt><i>137</i>     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">str</span><span class="p">]:</span></tt>
             </div>
             <div id="l138"
-               class="code sev- "><tt><i>138</i>     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">str</span><span class="p">]:</span></tt>
+               class="code sev- "><tt><i>138</i>         <span class="n">survival_time_attr</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="n">_DEFAULT_SURVIVAL_TIME_ATTR</span></tt>
             </div>
             <div id="l139"
-               class="code sev- "><tt><i>139</i>         <span class="n">survival_time_attr</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="n">_DEFAULT_SURVIVAL_TIME_ATTR</span></tt>
+               class="code sev- "><tt><i>139</i>         <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">survival_time</span><span class="p">,</span> <span class="n">pd</span><span class="o">.</span><span class="n">Series</span><span class="p">):</span></tt>
             </div>
             <div id="l140"
-               class="code sev- "><tt><i>140</i>         <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">values</span><span class="p">,</span> <span class="n">pd</span><span class="o">.</span><span class="n">Series</span><span class="p">):</span></tt>
+               class="code sev- "><tt><i>140</i>             <span class="k">if</span> <span class="n">survival_time</span><span class="o">.</span><span class="n">name</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span></tt>
             </div>
             <div id="l141"
-               class="code sev- "><tt><i>141</i>             <span class="k">if</span> <span class="n">survival_time</span><span class="o">.</span><span class="n">name</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span></tt>
+               class="code sev- "><tt><i>141</i>                 <span class="n">survival_time</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="n">survival_time_attr</span></tt>
             </div>
             <div id="l142"
-               class="code sev- "><tt><i>142</i>                 <span class="n">survival_time</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="n">survival_time_attr</span></tt>
+               class="code sev- "><tt><i>142</i>             <span class="k">else</span><span class="p">:</span></tt>
             </div>
             <div id="l143"
-               class="code sev- "><tt><i>143</i>             <span class="k">else</span><span class="p">:</span></tt>
+               class="code sev- "><tt><i>143</i>                 <span class="n">survival_time_attr</span> <span class="o">=</span> <span class="n">survival_time</span><span class="o">.</span><span class="n">name</span></tt>
             </div>
             <div id="l144"
-               class="code sev- "><tt><i>144</i>                 <span class="n">survival_time_attr</span> <span class="o">=</span> <span class="n">survival_time</span><span class="o">.</span><span class="n">name</span></tt>
+               class="code sev- "><tt><i>144</i>             <span class="n">values</span><span class="p">[</span><span class="n">survival_time</span><span class="o">.</span><span class="n">name</span><span class="p">]</span> <span class="o">=</span> <span class="n">survival_time</span></tt>
             </div>
             <div id="l145"
-               class="code sev- "><tt><i>145</i>             <span class="n">values</span><span class="p">[</span><span class="n">survival_time</span><span class="o">.</span><span class="n">name</span><span class="p">]</span> <span class="o">=</span> <span class="n">survival_time</span></tt>
+               class="code sev- "><tt><i>145</i>         <span class="k">elif</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">survival_time</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">):</span></tt>
             </div>
             <div id="l146"
-               class="code sev- "><tt><i>146</i>         <span class="k">elif</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">values</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">):</span></tt>
+               class="code sev- "><tt><i>146</i>             <span class="n">np</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">values</span><span class="p">,</span> <span class="n">survival_time</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span></tt>
             </div>
             <div id="l147"
-               class="code sev- "><tt><i>147</i>             <span class="n">np</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">values</span><span class="p">,</span> <span class="n">survival_time</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span></tt>
+               class="code sev- "><tt><i>147</i>         <span class="k">elif</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">survival_time</span><span class="p">,</span> <span class="nb">list</span><span class="p">):</span></tt>
             </div>
             <div id="l148"
-               class="code sev- "><tt><i>148</i>         <span class="k">elif</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">values</span><span class="p">,</span> <span class="nb">list</span><span class="p">):</span></tt>
+               class="code sev- "><tt><i>148</i>             <span class="k">for</span> <span class="n">index</span><span class="p">,</span> <span class="n">row</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">values</span><span class="p">):</span></tt>
             </div>
             <div id="l149"
-               class="code sev- "><tt><i>149</i>             <span class="k">for</span> <span class="n">index</span><span class="p">,</span> <span class="n">row</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">values</span><span class="p">):</span></tt>
+               class="code sev- "><tt><i>149</i>                 <span class="n">row</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">survival_time</span><span class="p">[</span><span class="n">index</span><span class="p">])</span></tt>
             </div>
             <div id="l150"
-               class="code sev- "><tt><i>150</i>                 <span class="n">row</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">survival_time</span><span class="p">[</span><span class="n">index</span><span class="p">])</span></tt>
+               class="code sev- "><tt><i>150</i>         <span class="k">else</span><span class="p">:</span></tt>
             </div>
             <div id="l151"
-               class="code sev- "><tt><i>151</i>         <span class="k">else</span><span class="p">:</span></tt>
+               class="code sev- "><tt><i>151</i>             <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span></tt>
             </div>
             <div id="l152"
-               class="code sev- "><tt><i>152</i>             <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span></tt>
+               class="code sev- "><tt><i>152</i>                 <span class="s2">&quot;Data values must be instance of either pandas DataFrame, numpy array&quot;</span></tt>
             </div>
             <div id="l153"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (94 > 79 characters)</li>
-               
-               </ul><tt><i>153</i>                 <span class="s1">&#39;Data values must be instance of either pandas DataFrame, numpy array or list&#39;</span></tt>
+               class="code sev- "><tt><i>153</i>                 <span class="s2">&quot; or list&quot;</span></tt>
             </div>
             <div id="l154"
                class="code sev- "><tt><i>154</i>             <span class="p">)</span></tt>
@@ -665,445 +494,328 @@ <h1>
                class="code sev- "><tt><i>156</i> &nbsp;</tt>
             </div>
             <div id="l157"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (94 > 79 characters)</li>
-               
-               </ul><tt><i>157</i>     <span class="k">def</span> <span class="nf">_prepare_survival_attribute</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">survival_time</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">Data</span><span class="p">],</span> <span class="n">values</span><span class="p">:</span> <span class="n">Data</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">str</span><span class="p">:</span></tt>
+               class="code sev- "><tt><i>157</i>     <span class="k">def</span> <span class="nf">_prepare_survival_attribute</span><span class="p">(</span></tt>
             </div>
             <div id="l158"
-               class="code sev- "><tt><i>158</i>         <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">survival_time_attr</span> <span class="ow">is</span> <span class="kc">None</span> <span class="ow">and</span> <span class="n">survival_time</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span></tt>
+               class="code sev- "><tt><i>158</i>         <span class="bp">self</span><span class="p">,</span> <span class="n">survival_time</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">Data</span><span class="p">],</span> <span class="n">values</span><span class="p">:</span> <span class="n">Data</span></tt>
             </div>
             <div id="l159"
-               class="code sev- "><tt><i>159</i>             <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span></tt>
+               class="code sev- "><tt><i>159</i>     <span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">str</span><span class="p">:</span></tt>
             </div>
             <div id="l160"
-               class="code sev- "><tt><i>160</i>                 <span class="s1">&#39;No &quot;survival_time&quot; attribute name was specified. &#39;</span> <span class="o">+</span></tt>
+               class="code sev- "><tt><i>160</i>         <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">survival_time_attr</span> <span class="ow">is</span> <span class="kc">None</span> <span class="ow">and</span> <span class="n">survival_time</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span></tt>
             </div>
             <div id="l161"
-               class="code sev- "><tt><i>161</i>                 <span class="s1">&#39;Specify it using method set_params&#39;</span></tt>
+               class="code sev- "><tt><i>161</i>             <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span></tt>
             </div>
             <div id="l162"
-               class="code sev- "><tt><i>162</i>             <span class="p">)</span></tt>
+               class="code sev- "><tt><i>162</i>                 <span class="s1">&#39;No &quot;survival_time&quot; attribute name was specified. &#39;</span></tt>
             </div>
             <div id="l163"
-               class="code sev- "><tt><i>163</i>         <span class="k">if</span> <span class="n">survival_time</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span></tt>
+               class="code sev- "><tt><i>163</i>                 <span class="o">+</span> <span class="s2">&quot;Specify it using method set_params&quot;</span></tt>
             </div>
             <div id="l164"
-               class="code sev- "><tt><i>164</i>             <span class="k">return</span> <span class="n">SurvivalRules</span><span class="o">.</span><span class="n">_append_survival_time_columns</span><span class="p">(</span></tt>
+               class="code sev- "><tt><i>164</i>             <span class="p">)</span></tt>
             </div>
             <div id="l165"
-               class="code sev- "><tt><i>165</i>                 <span class="n">values</span><span class="p">,</span> <span class="n">survival_time</span><span class="p">)</span></tt>
+               class="code sev- "><tt><i>165</i>         <span class="k">if</span> <span class="n">survival_time</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span></tt>
             </div>
             <div id="l166"
-               class="code sev- "><tt><i>166</i>         <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">survival_time_attr</span></tt>
+               class="code sev- "><tt><i>166</i>             <span class="k">return</span> <span class="n">SurvivalRules</span><span class="o">.</span><span class="n">_append_survival_time_columns</span><span class="p">(</span><span class="n">values</span><span class="p">,</span> <span class="n">survival_time</span><span class="p">)</span></tt>
             </div>
             <div id="l167"
-               class="code sev- "><tt><i>167</i> &nbsp;</tt>
+               class="code sev- "><tt><i>167</i>         <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">survival_time_attr</span></tt>
             </div>
             <div id="l168"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (127 > 79 characters)</li>
-               
-               </ul><tt><i>168</i>     <span class="k">def</span> <span class="nf">fit</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">:</span> <span class="n">Data</span><span class="p">,</span> <span class="n">labels</span><span class="p">:</span> <span class="n">Data</span><span class="p">,</span> <span class="n">survival_time</span><span class="p">:</span> <span class="n">Data</span> <span class="o">=</span> <span class="kc">None</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">SurvivalRules</span><span class="p">:</span>  <span class="c1"># pylint: disable=arguments-differ</span></tt>
+               class="code sev- "><tt><i>168</i> &nbsp;</tt>
             </div>
             <div id="l169"
-               class="code sev- "><tt><i>169</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Train model on given dataset.</span></tt>
+               class="code sev- "><tt><i>169</i>     <span class="k">def</span> <span class="nf">fit</span><span class="p">(</span></tt>
             </div>
             <div id="l170"
-               class="code sev- "><tt><i>170</i> &nbsp;</tt>
+               class="code sev- "><tt><i>170</i>         <span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">:</span> <span class="n">Data</span><span class="p">,</span> <span class="n">labels</span><span class="p">:</span> <span class="n">Data</span><span class="p">,</span> <span class="n">survival_time</span><span class="p">:</span> <span class="n">Data</span> <span class="o">=</span> <span class="kc">None</span></tt>
             </div>
             <div id="l171"
-               class="code sev- "><tt><i>171</i> <span class="sd">        Parameters</span></tt>
+               class="code sev- "><tt><i>171</i>     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">SurvivalRules</span><span class="p">:</span>  <span class="c1"># pylint: disable=arguments-differ</span></tt>
             </div>
             <div id="l172"
-               class="code sev- "><tt><i>172</i> <span class="sd">        ----------</span></tt>
+               class="code sev- "><tt><i>172</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Train model on given dataset.</span></tt>
             </div>
             <div id="l173"
-               class="code sev- "><tt><i>173</i> <span class="sd">        values : :class:`rulekit.operator.Data`</span></tt>
+               class="code sev- "><tt><i>173</i> &nbsp;</tt>
             </div>
             <div id="l174"
-               class="code sev- "><tt><i>174</i> <span class="sd">            attributes</span></tt>
+               class="code sev- "><tt><i>174</i> <span class="sd">        Parameters</span></tt>
             </div>
             <div id="l175"
-               class="code sev- "><tt><i>175</i> <span class="sd">        labels : :class:`rulekit.operator.Data`</span></tt>
+               class="code sev- "><tt><i>175</i> <span class="sd">        ----------</span></tt>
             </div>
             <div id="l176"
-               class="code sev- "><tt><i>176</i> <span class="sd">            survival status</span></tt>
+               class="code sev- "><tt><i>176</i> <span class="sd">        values : :class:`rulekit.operator.Data`</span></tt>
             </div>
             <div id="l177"
-               class="code sev- "><tt><i>177</i> <span class="sd">        survival_time: :class:`rulekit.operator.Data`</span></tt>
+               class="code sev- "><tt><i>177</i> <span class="sd">            attributes</span></tt>
             </div>
             <div id="l178"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (90 > 79 characters)</li>
-               
-               </ul><tt><i>178</i> <span class="sd">            data about survival time. Could be omitted when *survival_time_attr* parameter</span></tt>
+               class="code sev- "><tt><i>178</i> <span class="sd">        labels : :class:`rulekit.operator.Data`</span></tt>
             </div>
             <div id="l179"
-               class="code sev- "><tt><i>179</i> <span class="sd">             was specified.</span></tt>
+               class="code sev- "><tt><i>179</i> <span class="sd">            survival status</span></tt>
             </div>
             <div id="l180"
-               class="code sev- "><tt><i>180</i> &nbsp;</tt>
+               class="code sev- "><tt><i>180</i> <span class="sd">        survival_time: :class:`rulekit.operator.Data`</span></tt>
             </div>
             <div id="l181"
-               class="code sev- "><tt><i>181</i> <span class="sd">        Returns</span></tt>
+               class="code sev- "><tt><i>181</i> <span class="sd">            data about survival time. Could be omitted when *survival_time_attr*</span></tt>
             </div>
             <div id="l182"
-               class="code sev- "><tt><i>182</i> <span class="sd">        -------</span></tt>
+               class="code sev- "><tt><i>182</i> <span class="sd">            parameter was specified.</span></tt>
             </div>
             <div id="l183"
-               class="code sev- "><tt><i>183</i> <span class="sd">        self : SurvivalRules</span></tt>
+               class="code sev- "><tt><i>183</i> &nbsp;</tt>
             </div>
             <div id="l184"
-               class="code sev- "><tt><i>184</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
+               class="code sev- "><tt><i>184</i> <span class="sd">        Returns</span></tt>
             </div>
             <div id="l185"
-               class="code sev- "><tt><i>185</i>         <span class="n">survival_time_attribute</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_prepare_survival_attribute</span><span class="p">(</span></tt>
+               class="code sev- "><tt><i>185</i> <span class="sd">        -------</span></tt>
             </div>
             <div id="l186"
-               class="code sev- "><tt><i>186</i>             <span class="n">survival_time</span><span class="p">,</span> <span class="n">values</span><span class="p">)</span></tt>
+               class="code sev- "><tt><i>186</i> <span class="sd">        self : SurvivalRules</span></tt>
             </div>
             <div id="l187"
-               class="code sev- "><tt><i>187</i>         <span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">values</span><span class="p">,</span> <span class="n">labels</span><span class="p">,</span> <span class="n">survival_time_attribute</span><span class="p">)</span></tt>
+               class="code sev- "><tt><i>187</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
             </div>
             <div id="l188"
-               class="code sev- "><tt><i>188</i>         <span class="k">return</span> <span class="bp">self</span></tt>
+               class="code sev- "><tt><i>188</i>         <span class="n">survival_time_attribute</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_prepare_survival_attribute</span><span class="p">(</span></tt>
             </div>
             <div id="l189"
-               class="code sev- "><tt><i>189</i> &nbsp;</tt>
+               class="code sev- "><tt><i>189</i>             <span class="n">survival_time</span><span class="p">,</span> <span class="n">values</span></tt>
             </div>
             <div id="l190"
-               class="code sev- "><tt><i>190</i>     <span class="k">def</span> <span class="nf">predict</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">:</span> <span class="n">Data</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">:</span></tt>
+               class="code sev- "><tt><i>190</i>         <span class="p">)</span></tt>
             </div>
             <div id="l191"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (86 > 79 characters)</li>
-               
-               </ul><tt><i>191</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Perform prediction and return estimated survival function for each example.</span></tt>
+               class="code sev- "><tt><i>191</i>         <span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">values</span><span class="p">,</span> <span class="n">labels</span><span class="p">,</span> <span class="n">survival_time_attribute</span><span class="p">)</span></tt>
             </div>
             <div id="l192"
-               class="code sev- "><tt><i>192</i> &nbsp;</tt>
+               class="code sev- "><tt><i>192</i>         <span class="k">return</span> <span class="bp">self</span></tt>
             </div>
             <div id="l193"
-               class="code sev- "><tt><i>193</i> <span class="sd">        Parameters</span></tt>
+               class="code sev- "><tt><i>193</i> &nbsp;</tt>
             </div>
             <div id="l194"
-               class="code sev- "><tt><i>194</i> <span class="sd">        ----------</span></tt>
+               class="code sev- "><tt><i>194</i>     <span class="k">def</span> <span class="nf">predict</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">:</span> <span class="n">Data</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">:</span></tt>
             </div>
             <div id="l195"
-               class="code sev- "><tt><i>195</i> <span class="sd">        values : :class:`rulekit.operator.Data`</span></tt>
+               class="code sev- "><tt><i>195</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Perform prediction and return estimated survival function for each example.</span></tt>
             </div>
             <div id="l196"
-               class="code sev- "><tt><i>196</i> <span class="sd">            attributes</span></tt>
+               class="code sev- "><tt><i>196</i> &nbsp;</tt>
             </div>
             <div id="l197"
-               class="code sev- "><tt><i>197</i> &nbsp;</tt>
+               class="code sev- "><tt><i>197</i> <span class="sd">        Parameters</span></tt>
             </div>
             <div id="l198"
-               class="code sev- "><tt><i>198</i> <span class="sd">        Returns</span></tt>
+               class="code sev- "><tt><i>198</i> <span class="sd">        ----------</span></tt>
             </div>
             <div id="l199"
-               class="code sev- "><tt><i>199</i> <span class="sd">        -------</span></tt>
+               class="code sev- "><tt><i>199</i> <span class="sd">        values : :class:`rulekit.operator.Data`</span></tt>
             </div>
             <div id="l200"
-               class="code sev- "><tt><i>200</i> <span class="sd">        result : np.ndarray</span></tt>
+               class="code sev- "><tt><i>200</i> <span class="sd">            attributes</span></tt>
             </div>
             <div id="l201"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (99 > 79 characters)</li>
-               
-               </ul><tt><i>201</i> <span class="sd">            Each row represent single example from dataset and contains estimated survival function</span></tt>
+               class="code sev- "><tt><i>201</i> &nbsp;</tt>
             </div>
             <div id="l202"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (96 > 79 characters)</li>
-               
-               </ul><tt><i>202</i> <span class="sd">            for that example. Estimated survival function is returned as a dictionary containing</span></tt>
+               class="code sev- "><tt><i>202</i> <span class="sd">        Returns</span></tt>
             </div>
             <div id="l203"
-               class="code sev- "><tt><i>203</i> <span class="sd">             times and corresponding probabilities.</span></tt>
+               class="code sev- "><tt><i>203</i> <span class="sd">        -------</span></tt>
             </div>
             <div id="l204"
-               class="code sev- "><tt><i>204</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
+               class="code sev- "><tt><i>204</i> <span class="sd">        result : np.ndarray</span></tt>
             </div>
             <div id="l205"
-               class="code sev- "><tt><i>205</i>         <span class="k">return</span> <span class="n">PredictionResultMapper</span><span class="o">.</span><span class="n">map_survival</span><span class="p">(</span><span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">values</span><span class="p">))</span></tt>
+               class="code sev- "><tt><i>205</i> <span class="sd">            Each row represent single example from dataset and contains estimated</span></tt>
             </div>
             <div id="l206"
-               class="code sev- "><tt><i>206</i> &nbsp;</tt>
+               class="code sev- "><tt><i>206</i> <span class="sd">            survival function for that example. Estimated survival function is returned</span></tt>
             </div>
             <div id="l207"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (85 > 79 characters)</li>
-               
-               </ul><tt><i>207</i>     <span class="k">def</span> <span class="nf">score</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">:</span> <span class="n">Data</span><span class="p">,</span> <span class="n">labels</span><span class="p">:</span> <span class="n">Data</span><span class="p">,</span> <span class="n">survival_time</span><span class="p">:</span> <span class="n">Data</span> <span class="o">=</span> <span class="kc">None</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">float</span><span class="p">:</span></tt>
+               class="code sev- "><tt><i>207</i> <span class="sd">            as a dictionary containing times and corresponding probabilities.</span></tt>
             </div>
             <div id="l208"
-               class="code sev- "><tt><i>208</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Return the Integrated Brier Score on the given dataset and labels</span></tt>
+               class="code sev- "><tt><i>208</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
             </div>
             <div id="l209"
-               class="code sev- "><tt><i>209</i> <span class="sd">         (event status indicator).</span></tt>
+               class="code sev- "><tt><i>209</i>         <span class="k">return</span> <span class="n">PredictionResultMapper</span><span class="o">.</span><span class="n">map_survival</span><span class="p">(</span><span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">values</span><span class="p">))</span></tt>
             </div>
             <div id="l210"
                class="code sev- "><tt><i>210</i> &nbsp;</tt>
             </div>
             <div id="l211"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (93 > 79 characters)</li>
-               
-               </ul><tt><i>211</i> <span class="sd">        Integrated Brier Score (IBS) - the Brier score (BS) represents the squared difference</span></tt>
+               class="code sev- "><tt><i>211</i>     <span class="k">def</span> <span class="nf">score</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">:</span> <span class="n">Data</span><span class="p">,</span> <span class="n">labels</span><span class="p">:</span> <span class="n">Data</span><span class="p">,</span> <span class="n">survival_time</span><span class="p">:</span> <span class="n">Data</span> <span class="o">=</span> <span class="kc">None</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">float</span><span class="p">:</span></tt>
             </div>
             <div id="l212"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (85 > 79 characters)</li>
-               
-               </ul><tt><i>212</i> <span class="sd">         between true event status at time T and predicted event status at that time;</span></tt>
+               class="code sev- "><tt><i>212</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Return the Integrated Brier Score on the given dataset and labels</span></tt>
             </div>
             <div id="l213"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (98 > 79 characters)</li>
-               
-               </ul><tt><i>213</i> <span class="sd">         the Integrated Brier score summarizes the prediction error over all observations and over</span></tt>
+               class="code sev- "><tt><i>213</i> <span class="sd">         (event status indicator).</span></tt>
             </div>
             <div id="l214"
-               class="code sev- "><tt><i>214</i> <span class="sd">         all times in a test set.</span></tt>
+               class="code sev- "><tt><i>214</i> &nbsp;</tt>
             </div>
             <div id="l215"
-               class="code sev- "><tt><i>215</i> &nbsp;</tt>
+               class="code sev- "><tt><i>215</i> <span class="sd">        Integrated Brier Score (IBS) - the Brier score (BS) represents the squared</span></tt>
             </div>
             <div id="l216"
-               class="code sev- "><tt><i>216</i> <span class="sd">        Parameters</span></tt>
+               class="code sev- "><tt><i>216</i> <span class="sd">        difference between true event status at time T and predicted event status at</span></tt>
             </div>
             <div id="l217"
-               class="code sev- "><tt><i>217</i> <span class="sd">        ----------</span></tt>
+               class="code sev- "><tt><i>217</i> <span class="sd">        that time; the Integrated Brier score summarizes the prediction error over all</span></tt>
             </div>
             <div id="l218"
-               class="code sev- "><tt><i>218</i> <span class="sd">        values : :class:`rulekit.operator.Data`</span></tt>
+               class="code sev- "><tt><i>218</i> <span class="sd">        observations and over all times in a test set.</span></tt>
             </div>
             <div id="l219"
-               class="code sev- "><tt><i>219</i> <span class="sd">            attributes</span></tt>
+               class="code sev- "><tt><i>219</i> &nbsp;</tt>
             </div>
             <div id="l220"
-               class="code sev- "><tt><i>220</i> <span class="sd">        labels : :class:`rulekit.operator.Data`</span></tt>
+               class="code sev- "><tt><i>220</i> <span class="sd">        Parameters</span></tt>
             </div>
             <div id="l221"
-               class="code sev- "><tt><i>221</i> <span class="sd">            survival status</span></tt>
+               class="code sev- "><tt><i>221</i> <span class="sd">        ----------</span></tt>
             </div>
             <div id="l222"
-               class="code sev- "><tt><i>222</i> <span class="sd">        survival_time: :class:`rulekit.operator.Data`</span></tt>
+               class="code sev- "><tt><i>222</i> <span class="sd">        values : :class:`rulekit.operator.Data`</span></tt>
             </div>
             <div id="l223"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (94 > 79 characters)</li>
-               
-               </ul><tt><i>223</i> <span class="sd">            data about survival time. Could be omitted when *survival_time_attr* parameter was</span></tt>
+               class="code sev- "><tt><i>223</i> <span class="sd">            attributes</span></tt>
             </div>
             <div id="l224"
-               class="code sev- "><tt><i>224</i> <span class="sd">            specified</span></tt>
+               class="code sev- "><tt><i>224</i> <span class="sd">        labels : :class:`rulekit.operator.Data`</span></tt>
             </div>
             <div id="l225"
-               class="code sev- "><tt><i>225</i> &nbsp;</tt>
+               class="code sev- "><tt><i>225</i> <span class="sd">            survival status</span></tt>
             </div>
             <div id="l226"
-               class="code sev- "><tt><i>226</i> <span class="sd">        Returns</span></tt>
+               class="code sev- "><tt><i>226</i> <span class="sd">        survival_time: :class:`rulekit.operator.Data`</span></tt>
             </div>
             <div id="l227"
-               class="code sev- "><tt><i>227</i> <span class="sd">        -------</span></tt>
+               class="code sev- "><tt><i>227</i> <span class="sd">            data about survival time. Could be omitted when *survival_time_attr*</span></tt>
             </div>
             <div id="l228"
-               class="code sev- "><tt><i>228</i> <span class="sd">        score : float</span></tt>
+               class="code sev- "><tt><i>228</i> <span class="sd">            parameter was specified</span></tt>
             </div>
             <div id="l229"
-               class="code sev- "><tt><i>229</i> <span class="sd">            Integrated Brier Score of self.predict(values) wrt. labels.</span></tt>
+               class="code sev- "><tt><i>229</i> &nbsp;</tt>
             </div>
             <div id="l230"
-               class="code sev- "><tt><i>230</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
+               class="code sev- "><tt><i>230</i> <span class="sd">        Returns</span></tt>
             </div>
             <div id="l231"
-               class="code sev- "><tt><i>231</i> &nbsp;</tt>
+               class="code sev- "><tt><i>231</i> <span class="sd">        -------</span></tt>
             </div>
             <div id="l232"
-               class="code sev- "><tt><i>232</i>         <span class="n">survival_time_attribute</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_prepare_survival_attribute</span><span class="p">(</span></tt>
+               class="code sev- "><tt><i>232</i> <span class="sd">        score : float</span></tt>
             </div>
             <div id="l233"
-               class="code sev- "><tt><i>233</i>             <span class="n">survival_time</span><span class="p">,</span> <span class="n">values</span><span class="p">)</span></tt>
+               class="code sev- "><tt><i>233</i> <span class="sd">            Integrated Brier Score of self.predict(values) wrt. labels.</span></tt>
             </div>
             <div id="l234"
-               class="code sev- "><tt><i>234</i>         <span class="n">example_set</span> <span class="o">=</span> <span class="n">ExampleSetFactory</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_get_problem_type</span><span class="p">())</span><span class="o">.</span><span class="n">make</span><span class="p">(</span></tt>
+               class="code sev- "><tt><i>234</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
             </div>
             <div id="l235"
-               class="code sev- "><tt><i>235</i>             <span class="n">values</span><span class="p">,</span> <span class="n">labels</span><span class="p">,</span> <span class="n">survival_time_attribute</span><span class="o">=</span><span class="n">survival_time_attribute</span><span class="p">)</span></tt>
+               class="code sev- "><tt><i>235</i> &nbsp;</tt>
             </div>
             <div id="l236"
-               class="code sev- "><tt><i>236</i> &nbsp;</tt>
+               class="code sev- "><tt><i>236</i>         <span class="n">survival_time_attribute</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_prepare_survival_attribute</span><span class="p">(</span></tt>
             </div>
             <div id="l237"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (98 > 79 characters)</li>
-               
-               </ul><tt><i>237</i>         <span class="n">predicted_example_set</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">model</span><span class="o">.</span><span class="n">_java_object</span><span class="o">.</span><span class="n">apply</span><span class="p">(</span>  <span class="c1"># pylint: disable=protected-access</span></tt>
+               class="code sev- "><tt><i>237</i>             <span class="n">survival_time</span><span class="p">,</span> <span class="n">values</span></tt>
             </div>
             <div id="l238"
-               class="code sev- "><tt><i>238</i>             <span class="n">example_set</span></tt>
+               class="code sev- "><tt><i>238</i>         <span class="p">)</span></tt>
             </div>
             <div id="l239"
-               class="code sev- "><tt><i>239</i>         <span class="p">)</span></tt>
+               class="code sev- "><tt><i>239</i>         <span class="n">example_set</span> <span class="o">=</span> <span class="n">ExampleSetFactory</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_get_problem_type</span><span class="p">())</span><span class="o">.</span><span class="n">make</span><span class="p">(</span></tt>
             </div>
             <div id="l240"
-               class="code sev- "><tt><i>240</i> &nbsp;</tt>
+               class="code sev- "><tt><i>240</i>             <span class="n">values</span><span class="p">,</span> <span class="n">labels</span><span class="p">,</span> <span class="n">survival_time_attribute</span><span class="o">=</span><span class="n">survival_time_attribute</span></tt>
             </div>
             <div id="l241"
-               class="code sev- "><tt><i>241</i>         <span class="n">IntegratedBrierScore</span> <span class="o">=</span> <span class="n">JClass</span><span class="p">(</span>  <span class="c1"># pylint: disable=invalid-name</span></tt>
+               class="code sev- "><tt><i>241</i>         <span class="p">)</span></tt>
             </div>
             <div id="l242"
-               class="code sev- "><tt><i>242</i>             <span class="s1">&#39;adaa.analytics.rules.logic.performance.IntegratedBrierScore&#39;</span></tt>
+               class="code sev- "><tt><i>242</i> &nbsp;</tt>
             </div>
             <div id="l243"
-               class="code sev- "><tt><i>243</i>         <span class="p">)</span></tt>
+               class="code sev- "><tt><i>243</i>         <span class="n">predicted_example_set</span> <span class="o">=</span> <span class="p">(</span></tt>
             </div>
             <div id="l244"
-               class="code sev- "><tt><i>244</i>         <span class="n">integrated_brier_score</span> <span class="o">=</span> <span class="n">IntegratedBrierScore</span><span class="p">()</span></tt>
+               class="code sev- "><tt><i>244</i>             <span class="bp">self</span><span class="o">.</span><span class="n">model</span><span class="o">.</span><span class="n">_java_object</span><span class="o">.</span><span class="n">apply</span><span class="p">(</span>  <span class="c1"># pylint: disable=protected-access</span></tt>
             </div>
             <div id="l245"
-               class="code sev- "><tt><i>245</i>         <span class="n">ibs</span> <span class="o">=</span> <span class="n">integrated_brier_score</span><span class="o">.</span><span class="n">countExample</span><span class="p">(</span></tt>
+               class="code sev- "><tt><i>245</i>                 <span class="n">example_set</span></tt>
             </div>
             <div id="l246"
-               class="code sev- "><tt><i>246</i>             <span class="n">predicted_example_set</span><span class="p">)</span><span class="o">.</span><span class="n">getValue</span><span class="p">()</span></tt>
+               class="code sev- "><tt><i>246</i>             <span class="p">)</span></tt>
             </div>
             <div id="l247"
-               class="code sev- "><tt><i>247</i>         <span class="k">return</span> <span class="nb">float</span><span class="p">(</span><span class="n">ibs</span><span class="p">)</span></tt>
+               class="code sev- "><tt><i>247</i>         <span class="p">)</span></tt>
             </div>
             <div id="l248"
                class="code sev- "><tt><i>248</i> &nbsp;</tt>
             </div>
             <div id="l249"
-               class="code sev- "><tt><i>249</i>     <span class="k">def</span> <span class="nf">_get_problem_type</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ProblemType</span><span class="p">:</span></tt>
+               class="code sev- "><tt><i>249</i>         <span class="n">IntegratedBrierScore</span> <span class="o">=</span> <span class="n">JClass</span><span class="p">(</span>  <span class="c1"># pylint: disable=invalid-name</span></tt>
             </div>
             <div id="l250"
-               class="code sev- "><tt><i>250</i>         <span class="k">return</span> <span class="n">ProblemType</span><span class="o">.</span><span class="n">SURVIVAL</span></tt>
+               class="code sev- "><tt><i>250</i>             <span class="s2">&quot;adaa.analytics.rules.logic.performance.IntegratedBrierScore&quot;</span></tt>
             </div>
             <div id="l251"
-               class="code sev- "><tt><i>251</i> &nbsp;</tt>
+               class="code sev- "><tt><i>251</i>         <span class="p">)</span></tt>
             </div>
             <div id="l252"
-               class="code sev- "><tt><i>252</i> &nbsp;</tt>
+               class="code sev- "><tt><i>252</i>         <span class="n">integrated_brier_score</span> <span class="o">=</span> <span class="n">IntegratedBrierScore</span><span class="p">()</span></tt>
             </div>
             <div id="l253"
-               class="code sev- "><tt><i>253</i> <span class="k">class</span> <span class="nc">ExpertSurvivalRules</span><span class="p">(</span><span class="n">ExpertKnowledgeOperator</span><span class="p">,</span> <span class="n">SurvivalRules</span><span class="p">):</span></tt>
+               class="code sev- "><tt><i>253</i>         <span class="n">ibs</span> <span class="o">=</span> <span class="n">integrated_brier_score</span><span class="o">.</span><span class="n">countExample</span><span class="p">(</span><span class="n">predicted_example_set</span><span class="p">)</span><span class="o">.</span><span class="n">getValue</span><span class="p">()</span></tt>
             </div>
             <div id="l254"
-               class="code sev- "><tt><i>254</i> <span class="w">    </span><span class="sd">&quot;&quot;&quot;Expert Survival model.&quot;&quot;&quot;</span></tt>
+               class="code sev- "><tt><i>254</i>         <span class="k">return</span> <span class="nb">float</span><span class="p">(</span><span class="n">ibs</span><span class="p">)</span></tt>
             </div>
             <div id="l255"
                class="code sev- "><tt><i>255</i> &nbsp;</tt>
             </div>
             <div id="l256"
-               class="code sev- "><tt><i>256</i>     <span class="n">__params_class__</span> <span class="o">=</span> <span class="n">_SurvivalExpertModelParams</span></tt>
+               class="code sev- "><tt><i>256</i>     <span class="k">def</span> <span class="nf">_get_problem_type</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ProblemType</span><span class="p">:</span></tt>
             </div>
             <div id="l257"
-               class="code sev- "><tt><i>257</i> &nbsp;</tt>
+               class="code sev- "><tt><i>257</i>         <span class="k">return</span> <span class="n">ProblemType</span><span class="o">.</span><span class="n">SURVIVAL</span></tt>
             </div>
             <div id="l258"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (93 > 79 characters)</li>
-               
-               </ul><tt><i>258</i>     <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span>  <span class="c1"># pylint: disable=super-init-not-called,too-many-arguments,too-many-locals</span></tt>
+               class="code sev- "><tt><i>258</i> &nbsp;</tt>
             </div>
             <div id="l259"
-               class="code sev- "><tt><i>259</i>         <span class="bp">self</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>259</i> &nbsp;</tt>
             </div>
             <div id="l260"
-               class="code sev- "><tt><i>260</i>         <span class="n">survival_time_attr</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>260</i> <span class="k">class</span> <span class="nc">ExpertSurvivalRules</span><span class="p">(</span><span class="n">ExpertKnowledgeOperator</span><span class="p">,</span> <span class="n">SurvivalRules</span><span class="p">):</span></tt>
             </div>
             <div id="l261"
-               class="code sev- "><tt><i>261</i>         <span class="n">minsupp_new</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;minsupp_new&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>261</i> <span class="w">    </span><span class="sd">&quot;&quot;&quot;Expert Survival model.&quot;&quot;&quot;</span></tt>
             </div>
             <div id="l262"
-               class="code sev- "><tt><i>262</i>         <span class="n">max_growing</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;max_growing&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>262</i> &nbsp;</tt>
             </div>
             <div id="l263"
-               class="code sev- "><tt><i>263</i>         <span class="n">enable_pruning</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;enable_pruning&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>263</i>     <span class="n">__params_class__</span> <span class="o">=</span> <span class="n">_SurvivalExpertModelParams</span></tt>
             </div>
             <div id="l264"
-               class="code sev- "><tt><i>264</i>         <span class="n">ignore_missing</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;ignore_missing&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>264</i> &nbsp;</tt>
             </div>
             <div id="l265"
                class="code sev-2  le">
@@ -1113,1400 +825,884 @@ <h1>
                      <span class="count sev-2">
                         E501
                      </span>
-                     Line too long (87 > 79 characters)</li>
+                     Line too long (93 > 88 characters)</li>
                
-               </ul><tt><i>265</i>         <span class="n">max_uncovered_fraction</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;max_uncovered_fraction&#39;</span><span class="p">],</span></tt>
+               </ul><tt><i>265</i>     <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span>  <span class="c1"># pylint: disable=super-init-not-called,too-many-arguments,too-many-locals</span></tt>
             </div>
             <div id="l266"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (84 > 79 characters)</li>
-               
-               </ul><tt><i>266</i>         <span class="n">select_best_candidate</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;select_best_candidate&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>266</i>         <span class="bp">self</span><span class="p">,</span></tt>
             </div>
             <div id="l267"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (90 > 79 characters)</li>
-               
-               </ul><tt><i>267</i>         <span class="n">complementary_conditions</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;complementary_conditions&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>267</i>         <span class="n">survival_time_attr</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span></tt>
             </div>
             <div id="l268"
-               class="code sev- "><tt><i>268</i> &nbsp;</tt>
+               class="code sev- "><tt><i>268</i>         <span class="n">minsupp_new</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;minsupp_new&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l269"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (86 > 79 characters)</li>
-               
-               </ul><tt><i>269</i>         <span class="n">extend_using_preferred</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;extend_using_preferred&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>269</i>         <span class="n">max_growing</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;max_growing&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l270"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (86 > 79 characters)</li>
-               
-               </ul><tt><i>270</i>         <span class="n">extend_using_automatic</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;extend_using_automatic&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>270</i>         <span class="n">enable_pruning</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;enable_pruning&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l271"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (86 > 79 characters)</li>
-               
-               </ul><tt><i>271</i>         <span class="n">induce_using_preferred</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;induce_using_preferred&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>271</i>         <span class="n">ignore_missing</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;ignore_missing&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l272"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (86 > 79 characters)</li>
-               
-               </ul><tt><i>272</i>         <span class="n">induce_using_automatic</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;induce_using_automatic&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>272</i>         <span class="n">max_uncovered_fraction</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;max_uncovered_fraction&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l273"
-               class="code sev- "><tt><i>273</i>         <span class="n">preferred_conditions_per_rule</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span></tt>
+               class="code sev- "><tt><i>273</i>         <span class="n">select_best_candidate</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;select_best_candidate&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l274"
-               class="code sev- "><tt><i>274</i>             <span class="s1">&#39;preferred_conditions_per_rule&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>274</i>         <span class="n">complementary_conditions</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span></tt>
             </div>
             <div id="l275"
-               class="code sev- "><tt><i>275</i>         <span class="n">preferred_attributes_per_rule</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span></tt>
+               class="code sev- "><tt><i>275</i>             <span class="s2">&quot;complementary_conditions&quot;</span></tt>
             </div>
             <div id="l276"
-               class="code sev- "><tt><i>276</i>             <span class="s1">&#39;preferred_attributes_per_rule&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>276</i>         <span class="p">],</span></tt>
             </div>
             <div id="l277"
-               class="code sev- "><tt><i>277</i>         <span class="n">max_rule_count</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;max_rule_count&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>277</i>         <span class="n">extend_using_preferred</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;extend_using_preferred&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l278"
-               class="code sev- "><tt><i>278</i>     <span class="p">):</span></tt>
+               class="code sev- "><tt><i>278</i>         <span class="n">extend_using_automatic</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;extend_using_automatic&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l279"
-               class="code sev- "><tt><i>279</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;</span></tt>
+               class="code sev- "><tt><i>279</i>         <span class="n">induce_using_preferred</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;induce_using_preferred&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l280"
-               class="code sev- "><tt><i>280</i> <span class="sd">        Parameters</span></tt>
+               class="code sev- "><tt><i>280</i>         <span class="n">induce_using_automatic</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;induce_using_automatic&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l281"
-               class="code sev- "><tt><i>281</i> <span class="sd">        ----------</span></tt>
+               class="code sev- "><tt><i>281</i>         <span class="n">preferred_conditions_per_rule</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span></tt>
             </div>
             <div id="l282"
-               class="code sev- "><tt><i>282</i> <span class="sd">        minsupp_new : float = 5.0</span></tt>
+               class="code sev- "><tt><i>282</i>             <span class="s2">&quot;preferred_conditions_per_rule&quot;</span></tt>
             </div>
             <div id="l283"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (91 > 79 characters)</li>
-               
-               </ul><tt><i>283</i> <span class="sd">            a minimum number (or fraction, if value &lt; 1.0) of previously uncovered examples</span></tt>
+               class="code sev- "><tt><i>283</i>         <span class="p">],</span></tt>
             </div>
             <div id="l284"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (101 > 79 characters)</li>
-               
-               </ul><tt><i>284</i> <span class="sd">             to be covered by a new rule (positive examples for classification problems); default: 5,</span></tt>
+               class="code sev- "><tt><i>284</i>         <span class="n">preferred_attributes_per_rule</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span></tt>
             </div>
             <div id="l285"
-               class="code sev- "><tt><i>285</i> <span class="sd">        survival_time_attr : str</span></tt>
+               class="code sev- "><tt><i>285</i>             <span class="s2">&quot;preferred_attributes_per_rule&quot;</span></tt>
             </div>
             <div id="l286"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (97 > 79 characters)</li>
-               
-               </ul><tt><i>286</i> <span class="sd">            name of column containing survival time data (use when data passed to model is pandas</span></tt>
+               class="code sev- "><tt><i>286</i>         <span class="p">],</span></tt>
             </div>
             <div id="l287"
-               class="code sev- "><tt><i>287</i> <span class="sd">            dataframe).</span></tt>
+               class="code sev- "><tt><i>287</i>         <span class="n">max_rule_count</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;max_rule_count&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l288"
-               class="code sev- "><tt><i>288</i> <span class="sd">        max_growing : int = 0.0</span></tt>
+               class="code sev- "><tt><i>288</i>     <span class="p">):</span></tt>
             </div>
             <div id="l289"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (96 > 79 characters)</li>
-               
-               </ul><tt><i>289</i> <span class="sd">            non-negative integer representing maximum number of conditions which can be added to</span></tt>
+               class="code sev- "><tt><i>289</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;</span></tt>
             </div>
             <div id="l290"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (98 > 79 characters)</li>
-               
-               </ul><tt><i>290</i> <span class="sd">            the rule in the growing phase (use this parameter for large datasets if execution time</span></tt>
+               class="code sev- "><tt><i>290</i> <span class="sd">        Parameters</span></tt>
             </div>
             <div id="l291"
-               class="code sev- "><tt><i>291</i> <span class="sd">            is prohibitive); 0 indicates no limit; default: 0,</span></tt>
+               class="code sev- "><tt><i>291</i> <span class="sd">        ----------</span></tt>
             </div>
             <div id="l292"
-               class="code sev- "><tt><i>292</i> <span class="sd">        enable_pruning : bool = True</span></tt>
+               class="code sev- "><tt><i>292</i> <span class="sd">        minsupp_new : float = 5.0</span></tt>
             </div>
             <div id="l293"
-               class="code sev- "><tt><i>293</i> <span class="sd">            enable or disable pruning, default is True.</span></tt>
+               class="code sev- "><tt><i>293</i> <span class="sd">            a minimum number (or fraction, if value &lt; 1.0) of previously uncovered</span></tt>
             </div>
             <div id="l294"
-               class="code sev- "><tt><i>294</i> <span class="sd">        ignore_missing : bool = False</span></tt>
+               class="code sev- "><tt><i>294</i> <span class="sd">            examples to be covered by a new rule (positive examples for classification</span></tt>
             </div>
             <div id="l295"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (97 > 79 characters)</li>
-               
-               </ul><tt><i>295</i> <span class="sd">            boolean telling whether missing values should be ignored (by default, a missing value</span></tt>
+               class="code sev- "><tt><i>295</i> <span class="sd">            problems); default: 5,</span></tt>
             </div>
             <div id="l296"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (99 > 79 characters)</li>
-               
-               </ul><tt><i>296</i> <span class="sd">            of given attribute is always considered as not fulfilling the condition build upon that</span></tt>
+               class="code sev- "><tt><i>296</i> <span class="sd">        survival_time_attr : str</span></tt>
             </div>
             <div id="l297"
-               class="code sev- "><tt><i>297</i> <span class="sd">            attribute); default: False.</span></tt>
+               class="code sev- "><tt><i>297</i> <span class="sd">            name of column containing survival time data (use when data passed to model</span></tt>
             </div>
             <div id="l298"
-               class="code sev- "><tt><i>298</i> <span class="sd">        max_uncovered_fraction : float = 0.0</span></tt>
+               class="code sev- "><tt><i>298</i> <span class="sd">            is pandas dataframe).</span></tt>
             </div>
             <div id="l299"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (95 > 79 characters)</li>
-               
-               </ul><tt><i>299</i> <span class="sd">            Floating-point number from [0,1] interval representing maximum fraction of examples</span></tt>
+               class="code sev- "><tt><i>299</i> <span class="sd">        max_growing : int = 0.0</span></tt>
             </div>
             <div id="l300"
-               class="code sev- "><tt><i>300</i> <span class="sd">             that may remain uncovered by the rule set, default: 0.0.</span></tt>
+               class="code sev- "><tt><i>300</i> <span class="sd">            non-negative integer representing maximum number of conditions which can be</span></tt>
             </div>
             <div id="l301"
-               class="code sev- "><tt><i>301</i> <span class="sd">        select_best_candidate : bool = False</span></tt>
+               class="code sev- "><tt><i>301</i> <span class="sd">            added to the rule in the growing phase (use this parameter for large</span></tt>
             </div>
             <div id="l302"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (85 > 79 characters)</li>
-               
-               </ul><tt><i>302</i> <span class="sd">            Flag determining if best candidate should be selected from growing phase;</span></tt>
+               class="code sev- "><tt><i>302</i> <span class="sd">            datasets if execution time is prohibitive); 0 indicates no limit; default: 0</span></tt>
             </div>
             <div id="l303"
-               class="code sev- "><tt><i>303</i> <span class="sd">             default: False.</span></tt>
+               class="code sev- "><tt><i>303</i> <span class="sd">        enable_pruning : bool = True</span></tt>
             </div>
             <div id="l304"
-               class="code sev- "><tt><i>304</i> <span class="sd">        complementary_conditions : bool = False</span></tt>
+               class="code sev- "><tt><i>304</i> <span class="sd">            enable or disable pruning, default is True.</span></tt>
             </div>
             <div id="l305"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (96 > 79 characters)</li>
-               
-               </ul><tt><i>305</i> <span class="sd">            If enabled, complementary conditions in the form a = !{value} for nominal attributes</span></tt>
+               class="code sev- "><tt><i>305</i> <span class="sd">        ignore_missing : bool = False</span></tt>
             </div>
             <div id="l306"
-               class="code sev- "><tt><i>306</i> <span class="sd">            are supported.</span></tt>
+               class="code sev- "><tt><i>306</i> <span class="sd">            boolean telling whether missing values should be ignored (by default, a</span></tt>
             </div>
             <div id="l307"
-               class="code sev- "><tt><i>307</i> <span class="sd">        max_rule_count : int = 0</span></tt>
+               class="code sev- "><tt><i>307</i> <span class="sd">            missing value of given attribute is always considered as not fulfilling the</span></tt>
             </div>
             <div id="l308"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (92 > 79 characters)</li>
-               
-               </ul><tt><i>308</i> <span class="sd">            Maximum number of rules to be generated (for classification data sets it applies</span></tt>
+               class="code sev- "><tt><i>308</i> <span class="sd">            condition build upon that attribute); default: False.</span></tt>
             </div>
             <div id="l309"
-               class="code sev- "><tt><i>309</i> <span class="sd">             to a single class); 0 indicates no limit.</span></tt>
+               class="code sev- "><tt><i>309</i> <span class="sd">        max_uncovered_fraction : float = 0.0</span></tt>
             </div>
             <div id="l310"
-               class="code sev- "><tt><i>310</i> &nbsp;</tt>
+               class="code sev- "><tt><i>310</i> <span class="sd">            Floating-point number from [0,1] interval representing maximum fraction of</span></tt>
             </div>
             <div id="l311"
-               class="code sev- "><tt><i>311</i> <span class="sd">        extend_using_preferred : bool = False</span></tt>
+               class="code sev- "><tt><i>311</i> <span class="sd">            examples that may remain uncovered by the rule set, default: 0.0.</span></tt>
             </div>
             <div id="l312"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (95 > 79 characters)</li>
-               
-               </ul><tt><i>312</i> <span class="sd">            boolean indicating whether initial rules should be extended with a use of preferred</span></tt>
+               class="code sev- "><tt><i>312</i> <span class="sd">        select_best_candidate : bool = False</span></tt>
             </div>
             <div id="l313"
-               class="code sev- "><tt><i>313</i> <span class="sd">            conditions and attributes; default is False</span></tt>
+               class="code sev- "><tt><i>313</i> <span class="sd">            Flag determining if best candidate should be selected from growing phase;</span></tt>
             </div>
             <div id="l314"
-               class="code sev- "><tt><i>314</i> <span class="sd">        extend_using_automatic : bool = False</span></tt>
+               class="code sev- "><tt><i>314</i> <span class="sd">             default: False.</span></tt>
             </div>
             <div id="l315"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (95 > 79 characters)</li>
-               
-               </ul><tt><i>315</i> <span class="sd">            boolean indicating whether initial rules should be extended with a use of automatic</span></tt>
+               class="code sev- "><tt><i>315</i> <span class="sd">        complementary_conditions : bool = False</span></tt>
             </div>
             <div id="l316"
-               class="code sev- "><tt><i>316</i> <span class="sd">            conditions and attributes; default is False</span></tt>
+               class="code sev- "><tt><i>316</i> <span class="sd">            If enabled, complementary conditions in the form a = !{value} for nominal</span></tt>
             </div>
             <div id="l317"
-               class="code sev- "><tt><i>317</i> <span class="sd">        induce_using_preferred : bool = False</span></tt>
+               class="code sev- "><tt><i>317</i> <span class="sd">            attributes are supported.</span></tt>
             </div>
             <div id="l318"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (90 > 79 characters)</li>
-               
-               </ul><tt><i>318</i> <span class="sd">            boolean indicating whether new rules should be induced with a use of preferred</span></tt>
+               class="code sev- "><tt><i>318</i> <span class="sd">        max_rule_count : int = 0</span></tt>
             </div>
             <div id="l319"
-               class="code sev- "><tt><i>319</i> <span class="sd">             conditions and attributes; default is False</span></tt>
+               class="code sev- "><tt><i>319</i> <span class="sd">            Maximum number of rules to be generated (for classification data sets it</span></tt>
             </div>
             <div id="l320"
-               class="code sev- "><tt><i>320</i> <span class="sd">        induce_using_automatic : bool = False</span></tt>
+               class="code sev- "><tt><i>320</i> <span class="sd">            applies to a single class); 0 indicates no limit.</span></tt>
             </div>
             <div id="l321"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (90 > 79 characters)</li>
-               
-               </ul><tt><i>321</i> <span class="sd">            boolean indicating whether new rules should be induced with a use of automatic</span></tt>
+               class="code sev- "><tt><i>321</i> &nbsp;</tt>
             </div>
             <div id="l322"
-               class="code sev- "><tt><i>322</i> <span class="sd">             conditions and attributes; default is False</span></tt>
+               class="code sev- "><tt><i>322</i> <span class="sd">        extend_using_preferred : bool = False</span></tt>
             </div>
             <div id="l323"
-               class="code sev- "><tt><i>323</i> <span class="sd">        preferred_conditions_per_rule : int = None</span></tt>
+               class="code sev- "><tt><i>323</i> <span class="sd">            boolean indicating whether initial rules should be extended with a use of</span></tt>
             </div>
             <div id="l324"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (80 > 79 characters)</li>
-               
-               </ul><tt><i>324</i> <span class="sd">            maximum number of preferred conditions per rule; default: unlimited,</span></tt>
+               class="code sev- "><tt><i>324</i> <span class="sd">            preferred conditions and attributes; default is False</span></tt>
             </div>
             <div id="l325"
-               class="code sev- "><tt><i>325</i> <span class="sd">        preferred_attributes_per_rule : int = None</span></tt>
+               class="code sev- "><tt><i>325</i> <span class="sd">        extend_using_automatic : bool = False</span></tt>
             </div>
             <div id="l326"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (80 > 79 characters)</li>
-               
-               </ul><tt><i>326</i> <span class="sd">            maximum number of preferred attributes per rule; default: unlimited.</span></tt>
+               class="code sev- "><tt><i>326</i> <span class="sd">            boolean indicating whether initial rules should be extended with a use of</span></tt>
             </div>
             <div id="l327"
-               class="code sev- "><tt><i>327</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
+               class="code sev- "><tt><i>327</i> <span class="sd">            automatic conditions and attributes; default is False</span></tt>
             </div>
             <div id="l328"
-               class="code sev- "><tt><i>328</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_params</span> <span class="o">=</span> <span class="kc">None</span></tt>
+               class="code sev- "><tt><i>328</i> <span class="sd">        induce_using_preferred : bool = False</span></tt>
             </div>
             <div id="l329"
-               class="code sev- "><tt><i>329</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_rule_generator</span> <span class="o">=</span> <span class="kc">None</span></tt>
+               class="code sev- "><tt><i>329</i> <span class="sd">            boolean indicating whether new rules should be induced with a use of</span></tt>
             </div>
             <div id="l330"
-               class="code sev- "><tt><i>330</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_configurator</span> <span class="o">=</span> <span class="kc">None</span></tt>
+               class="code sev- "><tt><i>330</i> <span class="sd">            preferred conditions and attributes; default is False</span></tt>
             </div>
             <div id="l331"
-               class="code sev- "><tt><i>331</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_initialize_rulekit</span><span class="p">()</span></tt>
+               class="code sev- "><tt><i>331</i> <span class="sd">        induce_using_automatic : bool = False</span></tt>
             </div>
             <div id="l332"
-               class="code sev- "><tt><i>332</i>         <span class="bp">self</span><span class="o">.</span><span class="n">set_params</span><span class="p">(</span></tt>
+               class="code sev- "><tt><i>332</i> <span class="sd">            boolean indicating whether new rules should be induced with a use of</span></tt>
             </div>
             <div id="l333"
-               class="code sev- "><tt><i>333</i>             <span class="n">survival_time_attr</span><span class="o">=</span><span class="n">survival_time_attr</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>333</i> <span class="sd">            automatic conditions and attributes; default is False</span></tt>
             </div>
             <div id="l334"
-               class="code sev- "><tt><i>334</i>             <span class="n">minsupp_new</span><span class="o">=</span><span class="n">minsupp_new</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>334</i> <span class="sd">        preferred_conditions_per_rule : int = None</span></tt>
             </div>
             <div id="l335"
-               class="code sev- "><tt><i>335</i>             <span class="n">max_growing</span><span class="o">=</span><span class="n">max_growing</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>335</i> <span class="sd">            maximum number of preferred conditions per rule; default: unlimited,</span></tt>
             </div>
             <div id="l336"
-               class="code sev- "><tt><i>336</i>             <span class="n">enable_pruning</span><span class="o">=</span><span class="n">enable_pruning</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>336</i> <span class="sd">        preferred_attributes_per_rule : int = None</span></tt>
             </div>
             <div id="l337"
-               class="code sev- "><tt><i>337</i>             <span class="n">ignore_missing</span><span class="o">=</span><span class="n">ignore_missing</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>337</i> <span class="sd">            maximum number of preferred attributes per rule; default: unlimited.</span></tt>
             </div>
             <div id="l338"
-               class="code sev- "><tt><i>338</i>             <span class="n">max_uncovered_fraction</span><span class="o">=</span><span class="n">max_uncovered_fraction</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>338</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
             </div>
             <div id="l339"
-               class="code sev- "><tt><i>339</i>             <span class="n">select_best_candidate</span><span class="o">=</span><span class="n">select_best_candidate</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>339</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_params</span> <span class="o">=</span> <span class="kc">None</span></tt>
             </div>
             <div id="l340"
-               class="code sev- "><tt><i>340</i>             <span class="n">extend_using_preferred</span><span class="o">=</span><span class="n">extend_using_preferred</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>340</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_rule_generator</span> <span class="o">=</span> <span class="kc">None</span></tt>
             </div>
             <div id="l341"
-               class="code sev- "><tt><i>341</i>             <span class="n">extend_using_automatic</span><span class="o">=</span><span class="n">extend_using_automatic</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>341</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_configurator</span> <span class="o">=</span> <span class="kc">None</span></tt>
             </div>
             <div id="l342"
-               class="code sev- "><tt><i>342</i>             <span class="n">induce_using_preferred</span><span class="o">=</span><span class="n">induce_using_preferred</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>342</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_initialize_rulekit</span><span class="p">()</span></tt>
             </div>
             <div id="l343"
-               class="code sev- "><tt><i>343</i>             <span class="n">induce_using_automatic</span><span class="o">=</span><span class="n">induce_using_automatic</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>343</i>         <span class="bp">self</span><span class="o">.</span><span class="n">set_params</span><span class="p">(</span></tt>
             </div>
             <div id="l344"
-               class="code sev- "><tt><i>344</i>             <span class="n">preferred_conditions_per_rule</span><span class="o">=</span><span class="n">preferred_conditions_per_rule</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>344</i>             <span class="n">survival_time_attr</span><span class="o">=</span><span class="n">survival_time_attr</span><span class="p">,</span></tt>
             </div>
             <div id="l345"
-               class="code sev- "><tt><i>345</i>             <span class="n">preferred_attributes_per_rule</span><span class="o">=</span><span class="n">preferred_attributes_per_rule</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>345</i>             <span class="n">minsupp_new</span><span class="o">=</span><span class="n">minsupp_new</span><span class="p">,</span></tt>
             </div>
             <div id="l346"
-               class="code sev- "><tt><i>346</i>             <span class="n">complementary_conditions</span><span class="o">=</span><span class="n">complementary_conditions</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>346</i>             <span class="n">max_growing</span><span class="o">=</span><span class="n">max_growing</span><span class="p">,</span></tt>
             </div>
             <div id="l347"
-               class="code sev- "><tt><i>347</i>             <span class="n">max_rule_count</span><span class="o">=</span><span class="n">max_rule_count</span></tt>
+               class="code sev- "><tt><i>347</i>             <span class="n">enable_pruning</span><span class="o">=</span><span class="n">enable_pruning</span><span class="p">,</span></tt>
             </div>
             <div id="l348"
-               class="code sev- "><tt><i>348</i>         <span class="p">)</span></tt>
+               class="code sev- "><tt><i>348</i>             <span class="n">ignore_missing</span><span class="o">=</span><span class="n">ignore_missing</span><span class="p">,</span></tt>
             </div>
             <div id="l349"
-               class="code sev- "><tt><i>349</i>         <span class="bp">self</span><span class="o">.</span><span class="n">model</span><span class="p">:</span> <span class="n">RuleSet</span><span class="p">[</span><span class="n">SurvivalRule</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span></tt>
+               class="code sev- "><tt><i>349</i>             <span class="n">max_uncovered_fraction</span><span class="o">=</span><span class="n">max_uncovered_fraction</span><span class="p">,</span></tt>
             </div>
             <div id="l350"
-               class="code sev- "><tt><i>350</i> &nbsp;</tt>
+               class="code sev- "><tt><i>350</i>             <span class="n">select_best_candidate</span><span class="o">=</span><span class="n">select_best_candidate</span><span class="p">,</span></tt>
             </div>
             <div id="l351"
-               class="code sev- "><tt><i>351</i>     <span class="k">def</span> <span class="nf">set_params</span><span class="p">(</span>  <span class="c1"># pylint: disable=arguments-differ</span></tt>
+               class="code sev- "><tt><i>351</i>             <span class="n">extend_using_preferred</span><span class="o">=</span><span class="n">extend_using_preferred</span><span class="p">,</span></tt>
             </div>
             <div id="l352"
-               class="code sev- "><tt><i>352</i>         <span class="bp">self</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>352</i>             <span class="n">extend_using_automatic</span><span class="o">=</span><span class="n">extend_using_automatic</span><span class="p">,</span></tt>
             </div>
             <div id="l353"
-               class="code sev- "><tt><i>353</i>         <span class="o">**</span><span class="n">kwargs</span></tt>
+               class="code sev- "><tt><i>353</i>             <span class="n">induce_using_preferred</span><span class="o">=</span><span class="n">induce_using_preferred</span><span class="p">,</span></tt>
             </div>
             <div id="l354"
-               class="code sev- "><tt><i>354</i>     <span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">object</span><span class="p">:</span></tt>
+               class="code sev- "><tt><i>354</i>             <span class="n">induce_using_automatic</span><span class="o">=</span><span class="n">induce_using_automatic</span><span class="p">,</span></tt>
             </div>
             <div id="l355"
-               class="code sev- "><tt><i>355</i>         <span class="bp">self</span><span class="o">.</span><span class="n">survival_time_attr</span> <span class="o">=</span> <span class="n">kwargs</span><span class="p">[</span><span class="s1">&#39;survival_time_attr&#39;</span><span class="p">]</span></tt>
+               class="code sev- "><tt><i>355</i>             <span class="n">preferred_conditions_per_rule</span><span class="o">=</span><span class="n">preferred_conditions_per_rule</span><span class="p">,</span></tt>
             </div>
             <div id="l356"
-               class="code sev- "><tt><i>356</i>         <span class="k">return</span> <span class="n">ExpertKnowledgeOperator</span><span class="o">.</span><span class="n">set_params</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></tt>
+               class="code sev- "><tt><i>356</i>             <span class="n">preferred_attributes_per_rule</span><span class="o">=</span><span class="n">preferred_attributes_per_rule</span><span class="p">,</span></tt>
             </div>
             <div id="l357"
-               class="code sev- "><tt><i>357</i> &nbsp;</tt>
+               class="code sev- "><tt><i>357</i>             <span class="n">complementary_conditions</span><span class="o">=</span><span class="n">complementary_conditions</span><span class="p">,</span></tt>
             </div>
             <div id="l358"
-               class="code sev- "><tt><i>358</i>     <span class="k">def</span> <span class="nf">fit</span><span class="p">(</span>  <span class="c1"># pylint: disable=arguments-differ,too-many-arguments</span></tt>
+               class="code sev- "><tt><i>358</i>             <span class="n">max_rule_count</span><span class="o">=</span><span class="n">max_rule_count</span><span class="p">,</span></tt>
             </div>
             <div id="l359"
-               class="code sev- "><tt><i>359</i>         <span class="bp">self</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>359</i>         <span class="p">)</span></tt>
             </div>
             <div id="l360"
-               class="code sev- "><tt><i>360</i>         <span class="n">values</span><span class="p">:</span> <span class="n">Data</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>360</i>         <span class="bp">self</span><span class="o">.</span><span class="n">model</span><span class="p">:</span> <span class="n">RuleSet</span><span class="p">[</span><span class="n">SurvivalRule</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span></tt>
             </div>
             <div id="l361"
-               class="code sev- "><tt><i>361</i>         <span class="n">labels</span><span class="p">:</span> <span class="n">Data</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>361</i> &nbsp;</tt>
             </div>
             <div id="l362"
-               class="code sev- "><tt><i>362</i>         <span class="n">survival_time</span><span class="p">:</span> <span class="n">Data</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>362</i>     <span class="k">def</span> <span class="nf">set_params</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">object</span><span class="p">:</span>  <span class="c1"># pylint: disable=arguments-differ</span></tt>
             </div>
             <div id="l363"
-               class="code sev- "><tt><i>363</i> &nbsp;</tt>
+               class="code sev- "><tt><i>363</i>         <span class="bp">self</span><span class="o">.</span><span class="n">survival_time_attr</span> <span class="o">=</span> <span class="n">kwargs</span><span class="p">[</span><span class="s2">&quot;survival_time_attr&quot;</span><span class="p">]</span></tt>
             </div>
             <div id="l364"
-               class="code sev- "><tt><i>364</i>         <span class="n">expert_rules</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="n">Union</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="nb">tuple</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="nb">str</span><span class="p">]]]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>364</i>         <span class="k">return</span> <span class="n">ExpertKnowledgeOperator</span><span class="o">.</span><span class="n">set_params</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></tt>
             </div>
             <div id="l365"
-               class="code sev- "><tt><i>365</i>         <span class="n">expert_preferred_conditions</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="n">Union</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="nb">tuple</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="nb">str</span><span class="p">]]]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>365</i> &nbsp;</tt>
             </div>
             <div id="l366"
-               class="code sev- "><tt><i>366</i>         <span class="n">expert_forbidden_conditions</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="n">Union</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="nb">tuple</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="nb">str</span><span class="p">]]]</span> <span class="o">=</span> <span class="kc">None</span></tt>
+               class="code sev- "><tt><i>366</i>     <span class="k">def</span> <span class="nf">fit</span><span class="p">(</span>  <span class="c1"># pylint: disable=arguments-differ,too-many-arguments</span></tt>
             </div>
             <div id="l367"
-               class="code sev- "><tt><i>367</i>     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ExpertSurvivalRules</span><span class="p">:</span></tt>
+               class="code sev- "><tt><i>367</i>         <span class="bp">self</span><span class="p">,</span></tt>
             </div>
             <div id="l368"
-               class="code sev- "><tt><i>368</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Train model on given dataset.</span></tt>
+               class="code sev- "><tt><i>368</i>         <span class="n">values</span><span class="p">:</span> <span class="n">Data</span><span class="p">,</span></tt>
             </div>
             <div id="l369"
-               class="code sev- "><tt><i>369</i> &nbsp;</tt>
+               class="code sev- "><tt><i>369</i>         <span class="n">labels</span><span class="p">:</span> <span class="n">Data</span><span class="p">,</span></tt>
             </div>
             <div id="l370"
-               class="code sev- "><tt><i>370</i> <span class="sd">        Parameters</span></tt>
+               class="code sev- "><tt><i>370</i>         <span class="n">survival_time</span><span class="p">:</span> <span class="n">Data</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span></tt>
             </div>
             <div id="l371"
-               class="code sev- "><tt><i>371</i> <span class="sd">        ----------</span></tt>
+               class="code sev- "><tt><i>371</i>         <span class="n">expert_rules</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="n">Union</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="nb">tuple</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="nb">str</span><span class="p">]]]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span></tt>
             </div>
             <div id="l372"
-               class="code sev- "><tt><i>372</i> <span class="sd">        values : :class:`rulekit.operator.Data`</span></tt>
+               class="code sev- "><tt><i>372</i>         <span class="n">expert_preferred_conditions</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="n">Union</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="nb">tuple</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="nb">str</span><span class="p">]]]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span></tt>
             </div>
             <div id="l373"
-               class="code sev- "><tt><i>373</i> <span class="sd">            attributes</span></tt>
+               class="code sev- "><tt><i>373</i>         <span class="n">expert_forbidden_conditions</span><span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="n">Union</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="nb">tuple</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="nb">str</span><span class="p">]]]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span></tt>
             </div>
             <div id="l374"
-               class="code sev- "><tt><i>374</i> <span class="sd">        labels : Data</span></tt>
+               class="code sev- "><tt><i>374</i>     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ExpertSurvivalRules</span><span class="p">:</span></tt>
             </div>
             <div id="l375"
-               class="code sev- "><tt><i>375</i> <span class="sd">            survival status</span></tt>
+               class="code sev- "><tt><i>375</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Train model on given dataset.</span></tt>
             </div>
             <div id="l376"
-               class="code sev- "><tt><i>376</i> <span class="sd">        survival_time: :class:`rulekit.operator.Data`</span></tt>
+               class="code sev- "><tt><i>376</i> &nbsp;</tt>
             </div>
             <div id="l377"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (94 > 79 characters)</li>
-               
-               </ul><tt><i>377</i> <span class="sd">            data about survival time. Could be omitted when *survival_time_attr* parameter was</span></tt>
+               class="code sev- "><tt><i>377</i> <span class="sd">        Parameters</span></tt>
             </div>
             <div id="l378"
-               class="code sev- "><tt><i>378</i> <span class="sd">            specified.</span></tt>
+               class="code sev- "><tt><i>378</i> <span class="sd">        ----------</span></tt>
             </div>
             <div id="l379"
-               class="code sev- "><tt><i>379</i> &nbsp;</tt>
+               class="code sev- "><tt><i>379</i> <span class="sd">        values : :class:`rulekit.operator.Data`</span></tt>
             </div>
             <div id="l380"
-               class="code sev- "><tt><i>380</i> <span class="sd">        expert_rules : List[Union[str, Tuple[str, str]]]</span></tt>
+               class="code sev- "><tt><i>380</i> <span class="sd">            attributes</span></tt>
             </div>
             <div id="l381"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (98 > 79 characters)</li>
-               
-               </ul><tt><i>381</i> <span class="sd">            set of initial rules, either passed as a list of strings representing rules or as list</span></tt>
+               class="code sev- "><tt><i>381</i> <span class="sd">        labels : Data</span></tt>
             </div>
             <div id="l382"
-               class="code sev- "><tt><i>382</i> <span class="sd">            of tuples where first</span></tt>
+               class="code sev- "><tt><i>382</i> <span class="sd">            survival status</span></tt>
             </div>
             <div id="l383"
-               class="code sev- "><tt><i>383</i> <span class="sd">            element is name of the rule and second one is rule string.</span></tt>
+               class="code sev- "><tt><i>383</i> <span class="sd">        survival_time: :class:`rulekit.operator.Data`</span></tt>
             </div>
             <div id="l384"
-               class="code sev- "><tt><i>384</i> <span class="sd">        expert_preferred_conditions : List[Union[str, Tuple[str, str]]]</span></tt>
+               class="code sev- "><tt><i>384</i> <span class="sd">            data about survival time. Could be omitted when *survival_time_attr*</span></tt>
             </div>
             <div id="l385"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (94 > 79 characters)</li>
-               
-               </ul><tt><i>385</i> <span class="sd">            multiset of preferred conditions (used also for specifying preferred attributes by</span></tt>
+               class="code sev- "><tt><i>385</i> <span class="sd">            parameter was specified.</span></tt>
             </div>
             <div id="l386"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (98 > 79 characters)</li>
-               
-               </ul><tt><i>386</i> <span class="sd">             using special value Any). Either passed as a list of strings representing rules or as</span></tt>
+               class="code sev- "><tt><i>386</i> <span class="sd">        expert_rules : List[Union[str, Tuple[str, str]]]</span></tt>
             </div>
             <div id="l387"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (97 > 79 characters)</li>
-               
-               </ul><tt><i>387</i> <span class="sd">            list of tuples where first element is name of the rule and second one is rule string.</span></tt>
+               class="code sev- "><tt><i>387</i> <span class="sd">            set of initial rules, either passed as a list of strings representing rules</span></tt>
             </div>
             <div id="l388"
-               class="code sev- "><tt><i>388</i> <span class="sd">        expert_forbidden_conditions : List[Union[str, Tuple[str, str]]]</span></tt>
+               class="code sev- "><tt><i>388</i> <span class="sd">            or as list of tuples where first element is name of the rule and second one</span></tt>
             </div>
             <div id="l389"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (95 > 79 characters)</li>
-               
-               </ul><tt><i>389</i> <span class="sd">            set of forbidden conditions (used also for specifying forbidden attributes by using</span></tt>
+               class="code sev- "><tt><i>389</i> <span class="sd">            is rule string.</span></tt>
             </div>
             <div id="l390"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (97 > 79 characters)</li>
-               
-               </ul><tt><i>390</i> <span class="sd">             special valye Any). Either passed as a list of strings representing rules or as list</span></tt>
+               class="code sev- "><tt><i>390</i> <span class="sd">        expert_preferred_conditions : List[Union[str, Tuple[str, str]]]</span></tt>
             </div>
             <div id="l391"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (92 > 79 characters)</li>
-               
-               </ul><tt><i>391</i> <span class="sd">            of tuples where first element is name of the rule and second one is rule string.</span></tt>
+               class="code sev- "><tt><i>391</i> <span class="sd">            multiset of preferred conditions (used also for specifying preferred</span></tt>
             </div>
             <div id="l392"
-               class="code sev- "><tt><i>392</i> &nbsp;</tt>
+               class="code sev- "><tt><i>392</i> <span class="sd">            attributes by using special value Any). Either passed as a list of strings</span></tt>
             </div>
             <div id="l393"
-               class="code sev- "><tt><i>393</i> <span class="sd">        Returns</span></tt>
+               class="code sev- "><tt><i>393</i> <span class="sd">            representing rules or as list of tuples where first element is name of the</span></tt>
             </div>
             <div id="l394"
-               class="code sev- "><tt><i>394</i> <span class="sd">        -------</span></tt>
+               class="code sev- "><tt><i>394</i> <span class="sd">            rule and second one is rule string.</span></tt>
             </div>
             <div id="l395"
-               class="code sev- "><tt><i>395</i> <span class="sd">        self : ExpertSurvivalRules</span></tt>
+               class="code sev- "><tt><i>395</i> <span class="sd">        expert_forbidden_conditions : List[Union[str, Tuple[str, str]]]</span></tt>
             </div>
             <div id="l396"
-               class="code sev- "><tt><i>396</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
+               class="code sev- "><tt><i>396</i> <span class="sd">            set of forbidden conditions (used also for specifying forbidden attributes</span></tt>
             </div>
             <div id="l397"
-               class="code sev- "><tt><i>397</i>         <span class="n">survival_time_attribute</span> <span class="o">=</span> <span class="n">SurvivalRules</span><span class="o">.</span><span class="n">_prepare_survival_attribute</span><span class="p">(</span></tt>
+               class="code sev- "><tt><i>397</i> <span class="sd">            by using special valye Any). Either passed as a list of strings representing</span></tt>
             </div>
             <div id="l398"
-               class="code sev- "><tt><i>398</i>             <span class="bp">self</span><span class="p">,</span> <span class="n">survival_time</span><span class="p">,</span> <span class="n">values</span><span class="p">)</span></tt>
+               class="code sev- "><tt><i>398</i> <span class="sd">            rules or as list of tuples where first element is name of the rule and</span></tt>
             </div>
             <div id="l399"
-               class="code sev- "><tt><i>399</i>         <span class="k">return</span> <span class="n">ExpertKnowledgeOperator</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span></tt>
+               class="code sev- "><tt><i>399</i> <span class="sd">            second one is rule string.</span></tt>
             </div>
             <div id="l400"
-               class="code sev- "><tt><i>400</i>             <span class="bp">self</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>400</i> &nbsp;</tt>
             </div>
             <div id="l401"
-               class="code sev- "><tt><i>401</i>             <span class="n">values</span><span class="o">=</span><span class="n">values</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>401</i> <span class="sd">        Returns</span></tt>
             </div>
             <div id="l402"
-               class="code sev- "><tt><i>402</i>             <span class="n">labels</span><span class="o">=</span><span class="n">labels</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>402</i> <span class="sd">        -------</span></tt>
             </div>
             <div id="l403"
-               class="code sev- "><tt><i>403</i>             <span class="n">survival_time_attribute</span><span class="o">=</span><span class="n">survival_time_attribute</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>403</i> <span class="sd">        self : ExpertSurvivalRules</span></tt>
             </div>
             <div id="l404"
-               class="code sev- "><tt><i>404</i>             <span class="n">expert_rules</span><span class="o">=</span><span class="n">expert_rules</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>404</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
             </div>
             <div id="l405"
-               class="code sev- "><tt><i>405</i>             <span class="n">expert_preferred_conditions</span><span class="o">=</span><span class="n">expert_preferred_conditions</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>405</i>         <span class="n">survival_time_attribute</span> <span class="o">=</span> <span class="n">SurvivalRules</span><span class="o">.</span><span class="n">_prepare_survival_attribute</span><span class="p">(</span></tt>
             </div>
             <div id="l406"
-               class="code sev- "><tt><i>406</i>             <span class="n">expert_forbidden_conditions</span><span class="o">=</span><span class="n">expert_forbidden_conditions</span></tt>
+               class="code sev- "><tt><i>406</i>             <span class="bp">self</span><span class="p">,</span> <span class="n">survival_time</span><span class="p">,</span> <span class="n">values</span></tt>
             </div>
             <div id="l407"
                class="code sev- "><tt><i>407</i>         <span class="p">)</span></tt>
             </div>
             <div id="l408"
-               class="code sev- "><tt><i>408</i> &nbsp;</tt>
+               class="code sev- "><tt><i>408</i>         <span class="k">return</span> <span class="n">ExpertKnowledgeOperator</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span></tt>
             </div>
             <div id="l409"
-               class="code sev- "><tt><i>409</i>     <span class="k">def</span> <span class="nf">predict</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">:</span> <span class="n">Data</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">:</span></tt>
+               class="code sev- "><tt><i>409</i>             <span class="bp">self</span><span class="p">,</span></tt>
             </div>
             <div id="l410"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (97 > 79 characters)</li>
-               
-               </ul><tt><i>410</i>         <span class="k">return</span> <span class="n">PredictionResultMapper</span><span class="o">.</span><span class="n">map_survival</span><span class="p">(</span><span class="n">ExpertKnowledgeOperator</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">))</span></tt>
+               class="code sev- "><tt><i>410</i>             <span class="n">values</span><span class="o">=</span><span class="n">values</span><span class="p">,</span></tt>
             </div>
             <div id="l411"
-               class="code sev- "><tt><i>411</i> &nbsp;</tt>
+               class="code sev- "><tt><i>411</i>             <span class="n">labels</span><span class="o">=</span><span class="n">labels</span><span class="p">,</span></tt>
             </div>
             <div id="l412"
-               class="code sev- "><tt><i>412</i>     <span class="k">def</span> <span class="nf">_get_problem_type</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ProblemType</span><span class="p">:</span></tt>
+               class="code sev- "><tt><i>412</i>             <span class="n">survival_time_attribute</span><span class="o">=</span><span class="n">survival_time_attribute</span><span class="p">,</span></tt>
             </div>
             <div id="l413"
-               class="code sev- "><tt><i>413</i>         <span class="k">return</span> <span class="n">ProblemType</span><span class="o">.</span><span class="n">SURVIVAL</span></tt>
+               class="code sev- "><tt><i>413</i>             <span class="n">expert_rules</span><span class="o">=</span><span class="n">expert_rules</span><span class="p">,</span></tt>
             </div>
             <div id="l414"
-               class="code sev- "><tt><i>414</i> &nbsp;</tt>
+               class="code sev- "><tt><i>414</i>             <span class="n">expert_preferred_conditions</span><span class="o">=</span><span class="n">expert_preferred_conditions</span><span class="p">,</span></tt>
             </div>
             <div id="l415"
-               class="code sev- "><tt><i>415</i> &nbsp;</tt>
+               class="code sev- "><tt><i>415</i>             <span class="n">expert_forbidden_conditions</span><span class="o">=</span><span class="n">expert_forbidden_conditions</span><span class="p">,</span></tt>
             </div>
             <div id="l416"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (85 > 79 characters)</li>
-               
-               </ul><tt><i>416</i> <span class="k">class</span> <span class="nc">_SurvivalContrastSetModelParams</span><span class="p">(</span><span class="n">ContrastSetModelParams</span><span class="p">,</span> <span class="n">_SurvivalModelsParams</span><span class="p">):</span></tt>
+               class="code sev- "><tt><i>416</i>         <span class="p">)</span></tt>
             </div>
             <div id="l417"
-               class="code sev- "><tt><i>417</i>     <span class="k">pass</span></tt>
+               class="code sev- "><tt><i>417</i> &nbsp;</tt>
             </div>
             <div id="l418"
-               class="code sev- "><tt><i>418</i> &nbsp;</tt>
+               class="code sev- "><tt><i>418</i>     <span class="k">def</span> <span class="nf">predict</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">:</span> <span class="n">Data</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">:</span></tt>
             </div>
             <div id="l419"
-               class="code sev- "><tt><i>419</i> &nbsp;</tt>
+               class="code sev- "><tt><i>419</i>         <span class="k">return</span> <span class="n">PredictionResultMapper</span><span class="o">.</span><span class="n">map_survival</span><span class="p">(</span></tt>
             </div>
             <div id="l420"
-               class="code sev- "><tt><i>420</i> <span class="k">class</span> <span class="nc">ContrastSetSurvivalRules</span><span class="p">(</span><span class="n">BaseOperator</span><span class="p">,</span> <span class="n">_BaseSurvivalRulesModel</span><span class="p">):</span></tt>
+               class="code sev- "><tt><i>420</i>             <span class="n">ExpertKnowledgeOperator</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">)</span></tt>
             </div>
             <div id="l421"
-               class="code sev- "><tt><i>421</i> <span class="w">    </span><span class="sd">&quot;&quot;&quot;Contrast set survival model.&quot;&quot;&quot;</span></tt>
+               class="code sev- "><tt><i>421</i>         <span class="p">)</span></tt>
             </div>
             <div id="l422"
                class="code sev- "><tt><i>422</i> &nbsp;</tt>
             </div>
             <div id="l423"
-               class="code sev- "><tt><i>423</i>     <span class="n">__params_class__</span> <span class="o">=</span> <span class="n">_SurvivalContrastSetModelParams</span></tt>
+               class="code sev- "><tt><i>423</i>     <span class="k">def</span> <span class="nf">_get_problem_type</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ProblemType</span><span class="p">:</span></tt>
             </div>
             <div id="l424"
-               class="code sev- "><tt><i>424</i> &nbsp;</tt>
+               class="code sev- "><tt><i>424</i>         <span class="k">return</span> <span class="n">ProblemType</span><span class="o">.</span><span class="n">SURVIVAL</span></tt>
             </div>
             <div id="l425"
-               class="code sev- "><tt><i>425</i>     <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span>  <span class="c1"># pylint: disable=super-init-not-called,too-many-arguments</span></tt>
+               class="code sev- "><tt><i>425</i> &nbsp;</tt>
             </div>
             <div id="l426"
-               class="code sev- "><tt><i>426</i>         <span class="bp">self</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>426</i> &nbsp;</tt>
             </div>
             <div id="l427"
-               class="code sev- "><tt><i>427</i>         <span class="n">minsupp_all</span><span class="p">:</span> <span class="n">Tuple</span><span class="p">[</span><span class="nb">float</span><span class="p">,</span> <span class="nb">float</span><span class="p">,</span> <span class="nb">float</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>427</i> <span class="k">class</span> <span class="nc">_SurvivalContrastSetModelParams</span><span class="p">(</span><span class="n">ContrastSetModelParams</span><span class="p">,</span> <span class="n">_SurvivalModelsParams</span><span class="p">):</span></tt>
             </div>
             <div id="l428"
-               class="code sev- "><tt><i>428</i>                            <span class="nb">float</span><span class="p">]</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;minsupp_all&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>428</i>     <span class="k">pass</span></tt>
             </div>
             <div id="l429"
-               class="code sev- "><tt><i>429</i>         <span class="n">max_neg2pos</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;max_neg2pos&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>429</i> &nbsp;</tt>
             </div>
             <div id="l430"
-               class="code sev- "><tt><i>430</i>         <span class="n">max_passes_count</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;max_passes_count&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>430</i> &nbsp;</tt>
             </div>
             <div id="l431"
-               class="code sev- "><tt><i>431</i>         <span class="n">penalty_strength</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;penalty_strength&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>431</i> <span class="k">class</span> <span class="nc">ContrastSetSurvivalRules</span><span class="p">(</span><span class="n">BaseOperator</span><span class="p">,</span> <span class="n">_BaseSurvivalRulesModel</span><span class="p">):</span></tt>
             </div>
             <div id="l432"
-               class="code sev- "><tt><i>432</i>         <span class="n">penalty_saturation</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;penalty_saturation&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>432</i> <span class="w">    </span><span class="sd">&quot;&quot;&quot;Contrast set survival model.&quot;&quot;&quot;</span></tt>
             </div>
             <div id="l433"
                class="code sev- "><tt><i>433</i> &nbsp;</tt>
             </div>
             <div id="l434"
-               class="code sev- "><tt><i>434</i>         <span class="n">survival_time_attr</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>434</i>     <span class="n">__params_class__</span> <span class="o">=</span> <span class="n">_SurvivalContrastSetModelParams</span></tt>
             </div>
             <div id="l435"
-               class="code sev- "><tt><i>435</i>         <span class="n">minsupp_new</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;minsupp_new&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>435</i> &nbsp;</tt>
             </div>
             <div id="l436"
-               class="code sev- "><tt><i>436</i>         <span class="n">max_growing</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;max_growing&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>436</i>     <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span>  <span class="c1"># pylint: disable=super-init-not-called,too-many-arguments</span></tt>
             </div>
             <div id="l437"
-               class="code sev- "><tt><i>437</i>         <span class="n">enable_pruning</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;enable_pruning&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>437</i>         <span class="bp">self</span><span class="p">,</span></tt>
             </div>
             <div id="l438"
-               class="code sev- "><tt><i>438</i>         <span class="n">ignore_missing</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;ignore_missing&#39;</span><span class="p">],</span></tt>
-            </div>
-            <div id="l439"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (87 > 79 characters)</li>
-               
-               </ul><tt><i>439</i>         <span class="n">max_uncovered_fraction</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;max_uncovered_fraction&#39;</span><span class="p">],</span></tt>
-            </div>
-            <div id="l440"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (84 > 79 characters)</li>
-               
-               </ul><tt><i>440</i>         <span class="n">select_best_candidate</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;select_best_candidate&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>438</i>         <span class="n">minsupp_all</span><span class="p">:</span> <span class="n">Tuple</span><span class="p">[</span><span class="nb">float</span><span class="p">,</span> <span class="nb">float</span><span class="p">,</span> <span class="nb">float</span><span class="p">,</span> <span class="nb">float</span><span class="p">]</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span></tt>
             </div>
-            <div id="l441"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (90 > 79 characters)</li>
-               
-               </ul><tt><i>441</i>         <span class="n">complementary_conditions</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;complementary_conditions&#39;</span><span class="p">],</span></tt>
+            <div id="l439"
+               class="code sev- "><tt><i>439</i>             <span class="s2">&quot;minsupp_all&quot;</span></tt>
+            </div>
+            <div id="l440"
+               class="code sev- "><tt><i>440</i>         <span class="p">],</span></tt>
+            </div>
+            <div id="l441"
+               class="code sev- "><tt><i>441</i>         <span class="n">max_neg2pos</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;max_neg2pos&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l442"
-               class="code sev- "><tt><i>442</i>         <span class="n">max_rule_count</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s1">&#39;max_rule_count&#39;</span><span class="p">],</span></tt>
+               class="code sev- "><tt><i>442</i>         <span class="n">max_passes_count</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;max_passes_count&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l443"
-               class="code sev- "><tt><i>443</i>     <span class="p">):</span></tt>
+               class="code sev- "><tt><i>443</i>         <span class="n">penalty_strength</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;penalty_strength&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l444"
-               class="code sev- "><tt><i>444</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;</span></tt>
+               class="code sev- "><tt><i>444</i>         <span class="n">penalty_saturation</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;penalty_saturation&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l445"
-               class="code sev- "><tt><i>445</i> <span class="sd">        Parameters</span></tt>
+               class="code sev- "><tt><i>445</i>         <span class="n">survival_time_attr</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span></tt>
             </div>
             <div id="l446"
-               class="code sev- "><tt><i>446</i> <span class="sd">        ----------</span></tt>
+               class="code sev- "><tt><i>446</i>         <span class="n">minsupp_new</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;minsupp_new&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l447"
-               class="code sev- "><tt><i>447</i> <span class="sd">        minsupp_all: Tuple[float, float, float, float]</span></tt>
+               class="code sev- "><tt><i>447</i>         <span class="n">max_growing</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;max_growing&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l448"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (99 > 79 characters)</li>
-               
-               </ul><tt><i>448</i> <span class="sd">            a minimum positive support of a contrast set (p/P). When multiple values are specified,</span></tt>
+               class="code sev- "><tt><i>448</i>         <span class="n">enable_pruning</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;enable_pruning&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l449"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (97 > 79 characters)</li>
-               
-               </ul><tt><i>449</i> <span class="sd">            a metainduction is performed; Default and recommended sequence is: 0.8, 0.5, 0.2, 0.1</span></tt>
+               class="code sev- "><tt><i>449</i>         <span class="n">ignore_missing</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;ignore_missing&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l450"
-               class="code sev- "><tt><i>450</i> <span class="sd">        max_neg2pos: float</span></tt>
+               class="code sev- "><tt><i>450</i>         <span class="n">max_uncovered_fraction</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;max_uncovered_fraction&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l451"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (84 > 79 characters)</li>
-               
-               </ul><tt><i>451</i> <span class="sd">            a maximum ratio of negative to positive supports (nP/pN); Default is 0.5</span></tt>
+               class="code sev- "><tt><i>451</i>         <span class="n">select_best_candidate</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;select_best_candidate&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l452"
-               class="code sev- "><tt><i>452</i> <span class="sd">        max_passes_count: int</span></tt>
+               class="code sev- "><tt><i>452</i>         <span class="n">complementary_conditions</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span></tt>
             </div>
             <div id="l453"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (97 > 79 characters)</li>
-               
-               </ul><tt><i>453</i> <span class="sd">            a maximum number of sequential covering passes for a single minsupp-all; Default is 5</span></tt>
+               class="code sev- "><tt><i>453</i>             <span class="s2">&quot;complementary_conditions&quot;</span></tt>
             </div>
             <div id="l454"
-               class="code sev- "><tt><i>454</i> <span class="sd">        penalty_strength: float</span></tt>
+               class="code sev- "><tt><i>454</i>         <span class="p">],</span></tt>
             </div>
             <div id="l455"
-               class="code sev- "><tt><i>455</i> <span class="sd">            (s) - penalty strength; Default is 0.5</span></tt>
+               class="code sev- "><tt><i>455</i>         <span class="n">max_rule_count</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="n">DEFAULT_PARAMS_VALUE</span><span class="p">[</span><span class="s2">&quot;max_rule_count&quot;</span><span class="p">],</span></tt>
             </div>
             <div id="l456"
-               class="code sev- "><tt><i>456</i> <span class="sd">        penalty_saturation: float</span></tt>
+               class="code sev- "><tt><i>456</i>     <span class="p">):</span></tt>
             </div>
             <div id="l457"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (85 > 79 characters)</li>
-               
-               </ul><tt><i>457</i> <span class="sd">            the value of p_new / P at which penalty reward saturates; Default is 0.2.</span></tt>
+               class="code sev- "><tt><i>457</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;</span></tt>
             </div>
             <div id="l458"
-               class="code sev- "><tt><i>458</i> <span class="sd">        survival_time_attr : str</span></tt>
+               class="code sev- "><tt><i>458</i> <span class="sd">        Parameters</span></tt>
             </div>
             <div id="l459"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (97 > 79 characters)</li>
-               
-               </ul><tt><i>459</i> <span class="sd">            name of column containing survival time data (use when data passed to model is pandas</span></tt>
+               class="code sev- "><tt><i>459</i> <span class="sd">        ----------</span></tt>
             </div>
             <div id="l460"
-               class="code sev- "><tt><i>460</i> <span class="sd">            dataframe).</span></tt>
+               class="code sev- "><tt><i>460</i> <span class="sd">        minsupp_all: Tuple[float, float, float, float]</span></tt>
             </div>
             <div id="l461"
-               class="code sev- "><tt><i>461</i> <span class="sd">        minsupp_new : float = 5.0</span></tt>
+               class="code sev- "><tt><i>461</i> <span class="sd">            a minimum positive support of a contrast set (p/P). When multiple values are</span></tt>
             </div>
             <div id="l462"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (91 > 79 characters)</li>
-               
-               </ul><tt><i>462</i> <span class="sd">            a minimum number (or fraction, if value &lt; 1.0) of previously uncovered examples</span></tt>
+               class="code sev- "><tt><i>462</i> <span class="sd">            specified, a metainduction is performed; Default and recommended sequence</span></tt>
             </div>
             <div id="l463"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (101 > 79 characters)</li>
-               
-               </ul><tt><i>463</i> <span class="sd">             to be covered by a new rule (positive examples for classification problems); default: 5,</span></tt>
+               class="code sev- "><tt><i>463</i> <span class="sd">            is: 0.8, 0.5, 0.2, 0.1</span></tt>
             </div>
             <div id="l464"
-               class="code sev- "><tt><i>464</i> <span class="sd">        max_growing : int = 0.0</span></tt>
+               class="code sev- "><tt><i>464</i> <span class="sd">        max_neg2pos: float</span></tt>
             </div>
             <div id="l465"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (96 > 79 characters)</li>
-               
-               </ul><tt><i>465</i> <span class="sd">            non-negative integer representing maximum number of conditions which can be added to</span></tt>
+               class="code sev- "><tt><i>465</i> <span class="sd">            a maximum ratio of negative to positive supports (nP/pN); Default is 0.5</span></tt>
             </div>
             <div id="l466"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (99 > 79 characters)</li>
-               
-               </ul><tt><i>466</i> <span class="sd">             the rule in the growing phase (use this parameter for large datasets if execution time</span></tt>
+               class="code sev- "><tt><i>466</i> <span class="sd">        max_passes_count: int</span></tt>
             </div>
             <div id="l467"
-               class="code sev- "><tt><i>467</i> <span class="sd">            is prohibitive); 0 indicates no limit; default: 0,</span></tt>
+               class="code sev- "><tt><i>467</i> <span class="sd">            a maximum number of sequential covering passes for a single minsupp-all;</span></tt>
             </div>
             <div id="l468"
-               class="code sev- "><tt><i>468</i> <span class="sd">        enable_pruning : bool = True</span></tt>
+               class="code sev- "><tt><i>468</i> <span class="sd">            Default is 5</span></tt>
             </div>
             <div id="l469"
-               class="code sev- "><tt><i>469</i> <span class="sd">            enable or disable pruning, default is True.</span></tt>
+               class="code sev- "><tt><i>469</i> <span class="sd">        penalty_strength: float</span></tt>
             </div>
             <div id="l470"
-               class="code sev- "><tt><i>470</i> <span class="sd">        ignore_missing : bool = False</span></tt>
+               class="code sev- "><tt><i>470</i> <span class="sd">            (s) - penalty strength; Default is 0.5</span></tt>
             </div>
             <div id="l471"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (97 > 79 characters)</li>
-               
-               </ul><tt><i>471</i> <span class="sd">            boolean telling whether missing values should be ignored (by default, a missing value</span></tt>
+               class="code sev- "><tt><i>471</i> <span class="sd">        penalty_saturation: float</span></tt>
             </div>
             <div id="l472"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (100 > 79 characters)</li>
-               
-               </ul><tt><i>472</i> <span class="sd">             of given attribute is always considered as not fulfilling the condition build upon that</span></tt>
+               class="code sev- "><tt><i>472</i> <span class="sd">            the value of p_new / P at which penalty reward saturates; Default is 0.2.</span></tt>
             </div>
             <div id="l473"
-               class="code sev- "><tt><i>473</i> <span class="sd">            attribute); default: False.</span></tt>
+               class="code sev- "><tt><i>473</i> <span class="sd">        survival_time_attr : str</span></tt>
             </div>
             <div id="l474"
-               class="code sev- "><tt><i>474</i> <span class="sd">        max_uncovered_fraction : float = 0.0</span></tt>
+               class="code sev- "><tt><i>474</i> <span class="sd">            name of column containing survival time data (use when data passed to model</span></tt>
             </div>
             <div id="l475"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (95 > 79 characters)</li>
-               
-               </ul><tt><i>475</i> <span class="sd">            Floating-point number from [0,1] interval representing maximum fraction of examples</span></tt>
+               class="code sev- "><tt><i>475</i> <span class="sd">            is pandas dataframe).</span></tt>
             </div>
             <div id="l476"
-               class="code sev- "><tt><i>476</i> <span class="sd">             that may remain uncovered by the rule set, default: 0.0.</span></tt>
+               class="code sev- "><tt><i>476</i> <span class="sd">        minsupp_new : float = 5.0</span></tt>
             </div>
             <div id="l477"
-               class="code sev- "><tt><i>477</i> <span class="sd">        select_best_candidate : bool = False</span></tt>
+               class="code sev- "><tt><i>477</i> <span class="sd">            a minimum number (or fraction, if value &lt; 1.0) of previously uncovered</span></tt>
             </div>
             <div id="l478"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (85 > 79 characters)</li>
-               
-               </ul><tt><i>478</i> <span class="sd">            Flag determining if best candidate should be selected from growing phase;</span></tt>
+               class="code sev- "><tt><i>478</i> <span class="sd">            examples to be covered by a new rule (positive examples for classification</span></tt>
             </div>
             <div id="l479"
-               class="code sev- "><tt><i>479</i> <span class="sd">            default: False.</span></tt>
+               class="code sev- "><tt><i>479</i> <span class="sd">            problems); default: 5,</span></tt>
             </div>
             <div id="l480"
-               class="code sev- "><tt><i>480</i> <span class="sd">        complementary_conditions : bool = False</span></tt>
+               class="code sev- "><tt><i>480</i> <span class="sd">        max_growing : int = 0.0</span></tt>
             </div>
             <div id="l481"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (96 > 79 characters)</li>
-               
-               </ul><tt><i>481</i> <span class="sd">            If enabled, complementary conditions in the form a = !{value} for nominal attributes</span></tt>
+               class="code sev- "><tt><i>481</i> <span class="sd">            non-negative integer representing maximum number of conditions which can be</span></tt>
             </div>
             <div id="l482"
-               class="code sev- "><tt><i>482</i> <span class="sd">            are supported.</span></tt>
+               class="code sev- "><tt><i>482</i> <span class="sd">            added to the rule in the growing phase (use this parameter for large</span></tt>
             </div>
             <div id="l483"
-               class="code sev- "><tt><i>483</i> <span class="sd">        max_rule_count : int = 0</span></tt>
+               class="code sev- "><tt><i>483</i> <span class="sd">            datasets if execution time is prohibitive); 0 indicates no limit; default: 0</span></tt>
             </div>
             <div id="l484"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (92 > 79 characters)</li>
-               
-               </ul><tt><i>484</i> <span class="sd">            Maximum number of rules to be generated (for classification data sets it applies</span></tt>
+               class="code sev- "><tt><i>484</i> <span class="sd">        enable_pruning : bool = True</span></tt>
             </div>
             <div id="l485"
-               class="code sev- "><tt><i>485</i> <span class="sd">             to a single class); 0 indicates no limit.</span></tt>
+               class="code sev- "><tt><i>485</i> <span class="sd">            enable or disable pruning, default is True.</span></tt>
             </div>
             <div id="l486"
-               class="code sev- "><tt><i>486</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
+               class="code sev- "><tt><i>486</i> <span class="sd">        ignore_missing : bool = False</span></tt>
             </div>
             <div id="l487"
-               class="code sev- "><tt><i>487</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_params</span> <span class="o">=</span> <span class="kc">None</span></tt>
+               class="code sev- "><tt><i>487</i> <span class="sd">            boolean telling whether missing values should be ignored (by default, a</span></tt>
             </div>
             <div id="l488"
-               class="code sev- "><tt><i>488</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_rule_generator</span> <span class="o">=</span> <span class="kc">None</span></tt>
+               class="code sev- "><tt><i>488</i> <span class="sd">            missing value of given attribute is always considered as not fulfilling the</span></tt>
             </div>
             <div id="l489"
-               class="code sev- "><tt><i>489</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_configurator</span> <span class="o">=</span> <span class="kc">None</span></tt>
+               class="code sev- "><tt><i>489</i> <span class="sd">            condition build upon that attribute); default: False.</span></tt>
             </div>
             <div id="l490"
-               class="code sev- "><tt><i>490</i>         <span class="bp">self</span><span class="o">.</span><span class="n">contrast_attribute</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="kc">None</span></tt>
+               class="code sev- "><tt><i>490</i> <span class="sd">        max_uncovered_fraction : float = 0.0</span></tt>
             </div>
             <div id="l491"
-               class="code sev- "><tt><i>491</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_initialize_rulekit</span><span class="p">()</span></tt>
+               class="code sev- "><tt><i>491</i> <span class="sd">            Floating-point number from [0,1] interval representing maximum fraction of</span></tt>
             </div>
             <div id="l492"
-               class="code sev- "><tt><i>492</i>         <span class="bp">self</span><span class="o">.</span><span class="n">set_params</span><span class="p">(</span></tt>
+               class="code sev- "><tt><i>492</i> <span class="sd">            examples that may remain uncovered by the rule set, default: 0.0.</span></tt>
             </div>
             <div id="l493"
-               class="code sev- "><tt><i>493</i>             <span class="n">minsupp_all</span><span class="o">=</span><span class="n">minsupp_all</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>493</i> <span class="sd">        select_best_candidate : bool = False</span></tt>
             </div>
             <div id="l494"
-               class="code sev- "><tt><i>494</i>             <span class="n">max_neg2pos</span><span class="o">=</span><span class="n">max_neg2pos</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>494</i> <span class="sd">            Flag determining if best candidate should be selected from growing phase;</span></tt>
             </div>
             <div id="l495"
-               class="code sev- "><tt><i>495</i>             <span class="n">max_passes_count</span><span class="o">=</span><span class="n">max_passes_count</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>495</i> <span class="sd">            default: False.</span></tt>
             </div>
             <div id="l496"
-               class="code sev- "><tt><i>496</i>             <span class="n">penalty_strength</span><span class="o">=</span><span class="n">penalty_strength</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>496</i> <span class="sd">        complementary_conditions : bool = False</span></tt>
             </div>
             <div id="l497"
-               class="code sev- "><tt><i>497</i>             <span class="n">penalty_saturation</span><span class="o">=</span><span class="n">penalty_saturation</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>497</i> <span class="sd">            If enabled, complementary conditions in the form a = !{value} for nominal</span></tt>
             </div>
             <div id="l498"
-               class="code sev- "><tt><i>498</i>             <span class="n">survival_time_attr</span><span class="o">=</span><span class="n">survival_time_attr</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>498</i> <span class="sd">            attributes are supported.</span></tt>
             </div>
             <div id="l499"
-               class="code sev- "><tt><i>499</i>             <span class="n">minsupp_new</span><span class="o">=</span><span class="n">minsupp_new</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>499</i> <span class="sd">        max_rule_count : int = 0</span></tt>
             </div>
             <div id="l500"
-               class="code sev- "><tt><i>500</i>             <span class="n">max_growing</span><span class="o">=</span><span class="n">max_growing</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>500</i> <span class="sd">            Maximum number of rules to be generated (for classification data sets it</span></tt>
             </div>
             <div id="l501"
-               class="code sev- "><tt><i>501</i>             <span class="n">enable_pruning</span><span class="o">=</span><span class="n">enable_pruning</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>501</i> <span class="sd">            applies to a single class); 0 indicates no limit.</span></tt>
             </div>
             <div id="l502"
-               class="code sev- "><tt><i>502</i>             <span class="n">ignore_missing</span><span class="o">=</span><span class="n">ignore_missing</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>502</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
             </div>
             <div id="l503"
-               class="code sev- "><tt><i>503</i>             <span class="n">max_uncovered_fraction</span><span class="o">=</span><span class="n">max_uncovered_fraction</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>503</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_params</span> <span class="o">=</span> <span class="kc">None</span></tt>
             </div>
             <div id="l504"
-               class="code sev- "><tt><i>504</i>             <span class="n">select_best_candidate</span><span class="o">=</span><span class="n">select_best_candidate</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>504</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_rule_generator</span> <span class="o">=</span> <span class="kc">None</span></tt>
             </div>
             <div id="l505"
-               class="code sev- "><tt><i>505</i>             <span class="n">complementary_conditions</span><span class="o">=</span><span class="n">complementary_conditions</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>505</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_configurator</span> <span class="o">=</span> <span class="kc">None</span></tt>
             </div>
             <div id="l506"
-               class="code sev- "><tt><i>506</i>             <span class="n">max_rule_count</span><span class="o">=</span><span class="n">max_rule_count</span></tt>
+               class="code sev- "><tt><i>506</i>         <span class="bp">self</span><span class="o">.</span><span class="n">contrast_attribute</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="kc">None</span></tt>
             </div>
             <div id="l507"
-               class="code sev- "><tt><i>507</i>         <span class="p">)</span></tt>
+               class="code sev- "><tt><i>507</i>         <span class="bp">self</span><span class="o">.</span><span class="n">_initialize_rulekit</span><span class="p">()</span></tt>
             </div>
             <div id="l508"
-               class="code sev- "><tt><i>508</i>         <span class="bp">self</span><span class="o">.</span><span class="n">model</span><span class="p">:</span> <span class="n">RuleSet</span><span class="p">[</span><span class="n">SurvivalRule</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span></tt>
+               class="code sev- "><tt><i>508</i>         <span class="bp">self</span><span class="o">.</span><span class="n">set_params</span><span class="p">(</span></tt>
             </div>
             <div id="l509"
-               class="code sev- "><tt><i>509</i> &nbsp;</tt>
+               class="code sev- "><tt><i>509</i>             <span class="n">minsupp_all</span><span class="o">=</span><span class="n">minsupp_all</span><span class="p">,</span></tt>
             </div>
             <div id="l510"
-               class="code sev- "><tt><i>510</i>     <span class="k">def</span> <span class="nf">set_params</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">object</span><span class="p">:</span></tt>
+               class="code sev- "><tt><i>510</i>             <span class="n">max_neg2pos</span><span class="o">=</span><span class="n">max_neg2pos</span><span class="p">,</span></tt>
             </div>
             <div id="l511"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (84 > 79 characters)</li>
-               
-               </ul><tt><i>511</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Set models hyperparameters. Parameters are the same as in constructor.&quot;&quot;&quot;</span></tt>
+               class="code sev- "><tt><i>511</i>             <span class="n">max_passes_count</span><span class="o">=</span><span class="n">max_passes_count</span><span class="p">,</span></tt>
             </div>
             <div id="l512"
-               class="code sev- "><tt><i>512</i>         <span class="c1"># params validation</span></tt>
+               class="code sev- "><tt><i>512</i>             <span class="n">penalty_strength</span><span class="o">=</span><span class="n">penalty_strength</span><span class="p">,</span></tt>
             </div>
             <div id="l513"
-               class="code sev- "><tt><i>513</i>         <span class="bp">self</span><span class="o">.</span><span class="n">survival_time_attr</span> <span class="o">=</span> <span class="n">kwargs</span><span class="p">[</span><span class="s1">&#39;survival_time_attr&#39;</span><span class="p">]</span></tt>
+               class="code sev- "><tt><i>513</i>             <span class="n">penalty_saturation</span><span class="o">=</span><span class="n">penalty_saturation</span><span class="p">,</span></tt>
             </div>
             <div id="l514"
-               class="code sev- "><tt><i>514</i>         <span class="k">return</span> <span class="n">BaseOperator</span><span class="o">.</span><span class="n">set_params</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></tt>
+               class="code sev- "><tt><i>514</i>             <span class="n">survival_time_attr</span><span class="o">=</span><span class="n">survival_time_attr</span><span class="p">,</span></tt>
             </div>
             <div id="l515"
-               class="code sev- "><tt><i>515</i> &nbsp;</tt>
+               class="code sev- "><tt><i>515</i>             <span class="n">minsupp_new</span><span class="o">=</span><span class="n">minsupp_new</span><span class="p">,</span></tt>
             </div>
             <div id="l516"
-               class="code sev- "><tt><i>516</i>     <span class="k">def</span> <span class="nf">fit</span><span class="p">(</span>  <span class="c1"># pylint: disable=arguments-renamed</span></tt>
+               class="code sev- "><tt><i>516</i>             <span class="n">max_growing</span><span class="o">=</span><span class="n">max_growing</span><span class="p">,</span></tt>
             </div>
             <div id="l517"
-               class="code sev- "><tt><i>517</i>         <span class="bp">self</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>517</i>             <span class="n">enable_pruning</span><span class="o">=</span><span class="n">enable_pruning</span><span class="p">,</span></tt>
             </div>
             <div id="l518"
-               class="code sev- "><tt><i>518</i>         <span class="n">values</span><span class="p">:</span> <span class="n">Data</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>518</i>             <span class="n">ignore_missing</span><span class="o">=</span><span class="n">ignore_missing</span><span class="p">,</span></tt>
             </div>
             <div id="l519"
-               class="code sev- "><tt><i>519</i>         <span class="n">labels</span><span class="p">:</span> <span class="n">Data</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>519</i>             <span class="n">max_uncovered_fraction</span><span class="o">=</span><span class="n">max_uncovered_fraction</span><span class="p">,</span></tt>
             </div>
             <div id="l520"
-               class="code sev- "><tt><i>520</i>         <span class="n">contrast_attribute</span><span class="p">:</span> <span class="nb">str</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>520</i>             <span class="n">select_best_candidate</span><span class="o">=</span><span class="n">select_best_candidate</span><span class="p">,</span></tt>
             </div>
             <div id="l521"
-               class="code sev- "><tt><i>521</i>         <span class="n">survival_time</span><span class="p">:</span> <span class="n">Data</span> <span class="o">=</span> <span class="kc">None</span></tt>
+               class="code sev- "><tt><i>521</i>             <span class="n">complementary_conditions</span><span class="o">=</span><span class="n">complementary_conditions</span><span class="p">,</span></tt>
             </div>
             <div id="l522"
-               class="code sev- "><tt><i>522</i>     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ContrastSetSurvivalRules</span><span class="p">:</span></tt>
+               class="code sev- "><tt><i>522</i>             <span class="n">max_rule_count</span><span class="o">=</span><span class="n">max_rule_count</span><span class="p">,</span></tt>
             </div>
             <div id="l523"
-               class="code sev- "><tt><i>523</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Train model on given dataset.</span></tt>
+               class="code sev- "><tt><i>523</i>         <span class="p">)</span></tt>
             </div>
             <div id="l524"
-               class="code sev- "><tt><i>524</i> &nbsp;</tt>
+               class="code sev- "><tt><i>524</i>         <span class="bp">self</span><span class="o">.</span><span class="n">model</span><span class="p">:</span> <span class="n">RuleSet</span><span class="p">[</span><span class="n">SurvivalRule</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span></tt>
             </div>
             <div id="l525"
-               class="code sev- "><tt><i>525</i> <span class="sd">        Parameters</span></tt>
+               class="code sev- "><tt><i>525</i> &nbsp;</tt>
             </div>
             <div id="l526"
-               class="code sev- "><tt><i>526</i> <span class="sd">        ----------</span></tt>
+               class="code sev- "><tt><i>526</i>     <span class="k">def</span> <span class="nf">set_params</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">object</span><span class="p">:</span></tt>
             </div>
             <div id="l527"
-               class="code sev- "><tt><i>527</i> <span class="sd">        values : :class:`rulekit.operator.Data`</span></tt>
+               class="code sev- "><tt><i>527</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Set models hyperparameters. Parameters are the same as in constructor.&quot;&quot;&quot;</span></tt>
             </div>
             <div id="l528"
-               class="code sev- "><tt><i>528</i> <span class="sd">            attributes</span></tt>
+               class="code sev- "><tt><i>528</i>         <span class="c1"># params validation</span></tt>
             </div>
             <div id="l529"
-               class="code sev- "><tt><i>529</i> <span class="sd">        labels : :class:`rulekit.operator.Data`</span></tt>
+               class="code sev- "><tt><i>529</i>         <span class="bp">self</span><span class="o">.</span><span class="n">survival_time_attr</span> <span class="o">=</span> <span class="n">kwargs</span><span class="p">[</span><span class="s2">&quot;survival_time_attr&quot;</span><span class="p">]</span></tt>
             </div>
             <div id="l530"
-               class="code sev- "><tt><i>530</i> <span class="sd">            survival status</span></tt>
+               class="code sev- "><tt><i>530</i>         <span class="k">return</span> <span class="n">BaseOperator</span><span class="o">.</span><span class="n">set_params</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></tt>
             </div>
             <div id="l531"
-               class="code sev- "><tt><i>531</i> <span class="sd">        contrast_attribute: str</span></tt>
+               class="code sev- "><tt><i>531</i> &nbsp;</tt>
             </div>
             <div id="l532"
-               class="code sev- "><tt><i>532</i> <span class="sd">            group attribute</span></tt>
+               class="code sev- "><tt><i>532</i>     <span class="k">def</span> <span class="nf">fit</span><span class="p">(</span>  <span class="c1"># pylint: disable=arguments-renamed</span></tt>
             </div>
             <div id="l533"
-               class="code sev- "><tt><i>533</i> <span class="sd">        survival_time: :class:`rulekit.operator.Data`</span></tt>
+               class="code sev- "><tt><i>533</i>         <span class="bp">self</span><span class="p">,</span></tt>
             </div>
             <div id="l534"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (90 > 79 characters)</li>
-               
-               </ul><tt><i>534</i> <span class="sd">            data about survival time. Could be omitted when *survival_time_attr* parameter</span></tt>
+               class="code sev- "><tt><i>534</i>         <span class="n">values</span><span class="p">:</span> <span class="n">Data</span><span class="p">,</span></tt>
             </div>
             <div id="l535"
-               class="code sev- "><tt><i>535</i> <span class="sd">             was specified.</span></tt>
+               class="code sev- "><tt><i>535</i>         <span class="n">labels</span><span class="p">:</span> <span class="n">Data</span><span class="p">,</span></tt>
             </div>
             <div id="l536"
-               class="code sev- "><tt><i>536</i> &nbsp;</tt>
+               class="code sev- "><tt><i>536</i>         <span class="n">contrast_attribute</span><span class="p">:</span> <span class="nb">str</span><span class="p">,</span></tt>
             </div>
             <div id="l537"
-               class="code sev- "><tt><i>537</i> <span class="sd">        Returns</span></tt>
+               class="code sev- "><tt><i>537</i>         <span class="n">survival_time</span><span class="p">:</span> <span class="n">Data</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span></tt>
             </div>
             <div id="l538"
-               class="code sev- "><tt><i>538</i> <span class="sd">        -------</span></tt>
+               class="code sev- "><tt><i>538</i>     <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ContrastSetSurvivalRules</span><span class="p">:</span></tt>
             </div>
             <div id="l539"
-               class="code sev- "><tt><i>539</i> <span class="sd">        self : ContrastSetSurvivalRules</span></tt>
+               class="code sev- "><tt><i>539</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Train model on given dataset.</span></tt>
             </div>
             <div id="l540"
-               class="code sev- "><tt><i>540</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
+               class="code sev- "><tt><i>540</i> &nbsp;</tt>
             </div>
             <div id="l541"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (112 > 79 characters)</li>
-               
-               </ul><tt><i>541</i>         <span class="n">survival_time_attribute</span> <span class="o">=</span> <span class="n">SurvivalRules</span><span class="o">.</span><span class="n">_prepare_survival_attribute</span><span class="p">(</span>  <span class="c1"># pylint: disable=protected-access</span></tt>
+               class="code sev- "><tt><i>541</i> <span class="sd">        Parameters</span></tt>
             </div>
             <div id="l542"
-               class="code sev- "><tt><i>542</i>             <span class="bp">self</span><span class="p">,</span> <span class="n">survival_time</span><span class="p">,</span> <span class="n">values</span><span class="p">)</span></tt>
+               class="code sev- "><tt><i>542</i> <span class="sd">        ----------</span></tt>
             </div>
             <div id="l543"
-               class="code sev- "><tt><i>543</i>         <span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span></tt>
+               class="code sev- "><tt><i>543</i> <span class="sd">        values : :class:`rulekit.operator.Data`</span></tt>
             </div>
             <div id="l544"
-               class="code sev- "><tt><i>544</i>             <span class="n">values</span><span class="p">,</span> <span class="n">labels</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>544</i> <span class="sd">            attributes</span></tt>
             </div>
             <div id="l545"
-               class="code sev- "><tt><i>545</i>             <span class="n">survival_time_attribute</span><span class="o">=</span><span class="n">survival_time_attribute</span><span class="p">,</span></tt>
+               class="code sev- "><tt><i>545</i> <span class="sd">        labels : :class:`rulekit.operator.Data`</span></tt>
             </div>
             <div id="l546"
-               class="code sev- "><tt><i>546</i>             <span class="n">contrast_attribute</span><span class="o">=</span><span class="n">contrast_attribute</span><span class="p">)</span></tt>
+               class="code sev- "><tt><i>546</i> <span class="sd">            survival status</span></tt>
             </div>
             <div id="l547"
-               class="code sev- "><tt><i>547</i>         <span class="bp">self</span><span class="o">.</span><span class="n">contrast_attribute</span> <span class="o">=</span> <span class="n">contrast_attribute</span></tt>
+               class="code sev- "><tt><i>547</i> <span class="sd">        contrast_attribute: str</span></tt>
             </div>
             <div id="l548"
-               class="code sev- "><tt><i>548</i>         <span class="k">return</span> <span class="bp">self</span></tt>
+               class="code sev- "><tt><i>548</i> <span class="sd">            group attribute</span></tt>
             </div>
             <div id="l549"
-               class="code sev- "><tt><i>549</i> &nbsp;</tt>
+               class="code sev- "><tt><i>549</i> <span class="sd">        survival_time: :class:`rulekit.operator.Data`</span></tt>
             </div>
             <div id="l550"
-               class="code sev- "><tt><i>550</i>     <span class="k">def</span> <span class="nf">predict</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">:</span> <span class="n">Data</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">:</span></tt>
+               class="code sev- "><tt><i>550</i> <span class="sd">            data about survival time. Could be omitted when *survival_time_attr*</span></tt>
             </div>
             <div id="l551"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (86 > 79 characters)</li>
-               
-               </ul><tt><i>551</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Perform prediction and return estimated survival function for each example.</span></tt>
+               class="code sev- "><tt><i>551</i> <span class="sd">            parameter was specified.</span></tt>
             </div>
             <div id="l552"
                class="code sev- "><tt><i>552</i> &nbsp;</tt>
             </div>
             <div id="l553"
-               class="code sev- "><tt><i>553</i> <span class="sd">        Parameters</span></tt>
+               class="code sev- "><tt><i>553</i> <span class="sd">        Returns</span></tt>
             </div>
             <div id="l554"
-               class="code sev- "><tt><i>554</i> <span class="sd">        ----------</span></tt>
+               class="code sev- "><tt><i>554</i> <span class="sd">        -------</span></tt>
             </div>
             <div id="l555"
-               class="code sev- "><tt><i>555</i> <span class="sd">        values : :class:`rulekit.operator.Data`</span></tt>
+               class="code sev- "><tt><i>555</i> <span class="sd">        self : ContrastSetSurvivalRules</span></tt>
             </div>
             <div id="l556"
-               class="code sev- "><tt><i>556</i> <span class="sd">            attributes</span></tt>
+               class="code sev- "><tt><i>556</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
             </div>
             <div id="l557"
-               class="code sev- "><tt><i>557</i> &nbsp;</tt>
-            </div>
-            <div id="l558"
-               class="code sev- "><tt><i>558</i> <span class="sd">        Returns</span></tt>
-            </div>
-            <div id="l559"
-               class="code sev- "><tt><i>559</i> <span class="sd">        -------</span></tt>
-            </div>
-            <div id="l560"
-               class="code sev- "><tt><i>560</i> <span class="sd">        result : np.ndarray</span></tt>
-            </div>
-            <div id="l561"
                class="code sev-2  le">
                <ul class="violations">
                
@@ -2514,171 +1710,177 @@ <h1>
                      <span class="count sev-2">
                         E501
                      </span>
-                     Line too long (99 > 79 characters)</li>
+                     Line too long (112 > 88 characters)</li>
                
-               </ul><tt><i>561</i> <span class="sd">            Each row represent single example from dataset and contains estimated survival function</span></tt>
+               </ul><tt><i>557</i>         <span class="n">survival_time_attribute</span> <span class="o">=</span> <span class="n">SurvivalRules</span><span class="o">.</span><span class="n">_prepare_survival_attribute</span><span class="p">(</span>  <span class="c1"># pylint: disable=protected-access</span></tt>
+            </div>
+            <div id="l558"
+               class="code sev- "><tt><i>558</i>             <span class="bp">self</span><span class="p">,</span> <span class="n">survival_time</span><span class="p">,</span> <span class="n">values</span></tt>
+            </div>
+            <div id="l559"
+               class="code sev- "><tt><i>559</i>         <span class="p">)</span></tt>
+            </div>
+            <div id="l560"
+               class="code sev- "><tt><i>560</i>         <span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span></tt>
+            </div>
+            <div id="l561"
+               class="code sev- "><tt><i>561</i>             <span class="n">values</span><span class="p">,</span></tt>
             </div>
             <div id="l562"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (96 > 79 characters)</li>
-               
-               </ul><tt><i>562</i> <span class="sd">            for that example. Estimated survival function is returned as a dictionary containing</span></tt>
+               class="code sev- "><tt><i>562</i>             <span class="n">labels</span><span class="p">,</span></tt>
             </div>
             <div id="l563"
-               class="code sev- "><tt><i>563</i> <span class="sd">             times and corresponding probabilities.</span></tt>
+               class="code sev- "><tt><i>563</i>             <span class="n">survival_time_attribute</span><span class="o">=</span><span class="n">survival_time_attribute</span><span class="p">,</span></tt>
             </div>
             <div id="l564"
-               class="code sev- "><tt><i>564</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
+               class="code sev- "><tt><i>564</i>             <span class="n">contrast_attribute</span><span class="o">=</span><span class="n">contrast_attribute</span><span class="p">,</span></tt>
             </div>
             <div id="l565"
-               class="code sev- "><tt><i>565</i>         <span class="k">return</span> <span class="n">PredictionResultMapper</span><span class="o">.</span><span class="n">map_survival</span><span class="p">(</span><span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">values</span><span class="p">))</span></tt>
+               class="code sev- "><tt><i>565</i>         <span class="p">)</span></tt>
             </div>
             <div id="l566"
-               class="code sev- "><tt><i>566</i> &nbsp;</tt>
+               class="code sev- "><tt><i>566</i>         <span class="bp">self</span><span class="o">.</span><span class="n">contrast_attribute</span> <span class="o">=</span> <span class="n">contrast_attribute</span></tt>
             </div>
             <div id="l567"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (85 > 79 characters)</li>
-               
-               </ul><tt><i>567</i>     <span class="k">def</span> <span class="nf">score</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">:</span> <span class="n">Data</span><span class="p">,</span> <span class="n">labels</span><span class="p">:</span> <span class="n">Data</span><span class="p">,</span> <span class="n">survival_time</span><span class="p">:</span> <span class="n">Data</span> <span class="o">=</span> <span class="kc">None</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">float</span><span class="p">:</span></tt>
+               class="code sev- "><tt><i>567</i>         <span class="k">return</span> <span class="bp">self</span></tt>
             </div>
             <div id="l568"
-               class="code sev- "><tt><i>568</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Return the Integrated Brier Score on the given dataset and</span></tt>
+               class="code sev- "><tt><i>568</i> &nbsp;</tt>
             </div>
             <div id="l569"
-               class="code sev- "><tt><i>569</i> <span class="sd">         labels(event status indicator).</span></tt>
+               class="code sev- "><tt><i>569</i>     <span class="k">def</span> <span class="nf">predict</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">:</span> <span class="n">Data</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">:</span></tt>
             </div>
             <div id="l570"
-               class="code sev- "><tt><i>570</i> &nbsp;</tt>
+               class="code sev- "><tt><i>570</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Perform prediction and return estimated survival function for each example.</span></tt>
             </div>
             <div id="l571"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (93 > 79 characters)</li>
-               
-               </ul><tt><i>571</i> <span class="sd">        Integrated Brier Score (IBS) - the Brier score (BS) represents the squared difference</span></tt>
+               class="code sev- "><tt><i>571</i> &nbsp;</tt>
             </div>
             <div id="l572"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (84 > 79 characters)</li>
-               
-               </ul><tt><i>572</i> <span class="sd">        between true event status at time T and predicted event status at that time;</span></tt>
+               class="code sev- "><tt><i>572</i> <span class="sd">        Parameters</span></tt>
             </div>
             <div id="l573"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (93 > 79 characters)</li>
-               
-               </ul><tt><i>573</i> <span class="sd">         the Integrated Brier score summarizes the prediction error over all observations and</span></tt>
+               class="code sev- "><tt><i>573</i> <span class="sd">        ----------</span></tt>
             </div>
             <div id="l574"
-               class="code sev- "><tt><i>574</i> <span class="sd">         over all times in a test set.</span></tt>
+               class="code sev- "><tt><i>574</i> <span class="sd">        values : :class:`rulekit.operator.Data`</span></tt>
             </div>
             <div id="l575"
-               class="code sev- "><tt><i>575</i> &nbsp;</tt>
+               class="code sev- "><tt><i>575</i> <span class="sd">            attributes</span></tt>
             </div>
             <div id="l576"
-               class="code sev- "><tt><i>576</i> <span class="sd">        Parameters</span></tt>
+               class="code sev- "><tt><i>576</i> &nbsp;</tt>
             </div>
             <div id="l577"
-               class="code sev- "><tt><i>577</i> <span class="sd">        ----------</span></tt>
+               class="code sev- "><tt><i>577</i> <span class="sd">        Returns</span></tt>
             </div>
             <div id="l578"
-               class="code sev- "><tt><i>578</i> <span class="sd">        values : :class:`rulekit.operator.Data`</span></tt>
+               class="code sev- "><tt><i>578</i> <span class="sd">        -------</span></tt>
             </div>
             <div id="l579"
-               class="code sev- "><tt><i>579</i> <span class="sd">            attributes</span></tt>
+               class="code sev- "><tt><i>579</i> <span class="sd">        result : np.ndarray</span></tt>
             </div>
             <div id="l580"
-               class="code sev- "><tt><i>580</i> <span class="sd">        labels : :class:`rulekit.operator.Data`</span></tt>
+               class="code sev- "><tt><i>580</i> <span class="sd">            Each row represent single example from dataset and contains estimated</span></tt>
             </div>
             <div id="l581"
-               class="code sev- "><tt><i>581</i> <span class="sd">            survival status</span></tt>
+               class="code sev- "><tt><i>581</i> <span class="sd">            survival function for that example. Estimated survival function is returned</span></tt>
             </div>
             <div id="l582"
-               class="code sev- "><tt><i>582</i> <span class="sd">        survival_time: :class:`rulekit.operator.Data`</span></tt>
+               class="code sev- "><tt><i>582</i> <span class="sd">            as a dictionary containing times and corresponding probabilities.</span></tt>
             </div>
             <div id="l583"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (94 > 79 characters)</li>
-               
-               </ul><tt><i>583</i> <span class="sd">            data about survival time. Could be omitted when *survival_time_attr* parameter was</span></tt>
+               class="code sev- "><tt><i>583</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
             </div>
             <div id="l584"
-               class="code sev- "><tt><i>584</i> <span class="sd">            specified</span></tt>
+               class="code sev- "><tt><i>584</i>         <span class="k">return</span> <span class="n">PredictionResultMapper</span><span class="o">.</span><span class="n">map_survival</span><span class="p">(</span><span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">values</span><span class="p">))</span></tt>
             </div>
             <div id="l585"
                class="code sev- "><tt><i>585</i> &nbsp;</tt>
             </div>
             <div id="l586"
-               class="code sev- "><tt><i>586</i> <span class="sd">        Returns</span></tt>
+               class="code sev- "><tt><i>586</i>     <span class="k">def</span> <span class="nf">score</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">:</span> <span class="n">Data</span><span class="p">,</span> <span class="n">labels</span><span class="p">:</span> <span class="n">Data</span><span class="p">,</span> <span class="n">survival_time</span><span class="p">:</span> <span class="n">Data</span> <span class="o">=</span> <span class="kc">None</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">float</span><span class="p">:</span></tt>
             </div>
             <div id="l587"
-               class="code sev- "><tt><i>587</i> <span class="sd">        -------</span></tt>
+               class="code sev- "><tt><i>587</i> <span class="w">        </span><span class="sd">&quot;&quot;&quot;Return the Integrated Brier Score on the given dataset and</span></tt>
             </div>
             <div id="l588"
-               class="code sev- "><tt><i>588</i> <span class="sd">        score : float</span></tt>
+               class="code sev- "><tt><i>588</i> <span class="sd">         labels(event status indicator).</span></tt>
             </div>
             <div id="l589"
-               class="code sev- "><tt><i>589</i> <span class="sd">            Integrated Brier Score of self.predict(values) wrt. labels.</span></tt>
+               class="code sev- "><tt><i>589</i> &nbsp;</tt>
             </div>
             <div id="l590"
-               class="code sev- "><tt><i>590</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
+               class="code sev- "><tt><i>590</i> <span class="sd">        Integrated Brier Score (IBS) - the Brier score (BS) represents the squared</span></tt>
             </div>
             <div id="l591"
-               class="code sev-2  le">
-               <ul class="violations">
-               
-                  <li>
-                     <span class="count sev-2">
-                        E501
-                     </span>
-                     Line too long (85 > 79 characters)</li>
-               
-               </ul><tt><i>591</i>         <span class="k">return</span> <span class="n">SurvivalRules</span><span class="o">.</span><span class="n">score</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">,</span> <span class="n">labels</span><span class="p">,</span> <span class="n">survival_time</span><span class="o">=</span><span class="n">survival_time</span><span class="p">)</span></tt>
+               class="code sev- "><tt><i>591</i> <span class="sd">        differencebetween true event status at time T and predicted event status at that</span></tt>
             </div>
             <div id="l592"
-               class="code sev- "><tt><i>592</i> &nbsp;</tt>
+               class="code sev- "><tt><i>592</i> <span class="sd">        time; the Integrated Brier score summarizes the prediction error over all</span></tt>
             </div>
             <div id="l593"
-               class="code sev- "><tt><i>593</i>     <span class="k">def</span> <span class="nf">_get_problem_type</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ProblemType</span><span class="p">:</span></tt>
+               class="code sev- "><tt><i>593</i> <span class="sd">        observations and over all times in a test set.</span></tt>
             </div>
             <div id="l594"
-               class="code sev- "><tt><i>594</i>         <span class="k">return</span> <span class="n">ProblemType</span><span class="o">.</span><span class="n">CONTRAST_SURVIVAL</span></tt>
+               class="code sev- "><tt><i>594</i> &nbsp;</tt>
+            </div>
+            <div id="l595"
+               class="code sev- "><tt><i>595</i> <span class="sd">        Parameters</span></tt>
+            </div>
+            <div id="l596"
+               class="code sev- "><tt><i>596</i> <span class="sd">        ----------</span></tt>
+            </div>
+            <div id="l597"
+               class="code sev- "><tt><i>597</i> <span class="sd">        values : :class:`rulekit.operator.Data`</span></tt>
+            </div>
+            <div id="l598"
+               class="code sev- "><tt><i>598</i> <span class="sd">            attributes</span></tt>
+            </div>
+            <div id="l599"
+               class="code sev- "><tt><i>599</i> <span class="sd">        labels : :class:`rulekit.operator.Data`</span></tt>
+            </div>
+            <div id="l600"
+               class="code sev- "><tt><i>600</i> <span class="sd">            survival status</span></tt>
+            </div>
+            <div id="l601"
+               class="code sev- "><tt><i>601</i> <span class="sd">        survival_time: :class:`rulekit.operator.Data`</span></tt>
+            </div>
+            <div id="l602"
+               class="code sev- "><tt><i>602</i> <span class="sd">            data about survival time. Could be omitted when *survival_time_attr*</span></tt>
+            </div>
+            <div id="l603"
+               class="code sev- "><tt><i>603</i> <span class="sd">            parameter was specified</span></tt>
+            </div>
+            <div id="l604"
+               class="code sev- "><tt><i>604</i> &nbsp;</tt>
+            </div>
+            <div id="l605"
+               class="code sev- "><tt><i>605</i> <span class="sd">        Returns</span></tt>
+            </div>
+            <div id="l606"
+               class="code sev- "><tt><i>606</i> <span class="sd">        -------</span></tt>
+            </div>
+            <div id="l607"
+               class="code sev- "><tt><i>607</i> <span class="sd">        score : float</span></tt>
+            </div>
+            <div id="l608"
+               class="code sev- "><tt><i>608</i> <span class="sd">            Integrated Brier Score of self.predict(values) wrt. labels.</span></tt>
+            </div>
+            <div id="l609"
+               class="code sev- "><tt><i>609</i> <span class="sd">        &quot;&quot;&quot;</span></tt>
+            </div>
+            <div id="l610"
+               class="code sev- "><tt><i>610</i>         <span class="k">return</span> <span class="n">SurvivalRules</span><span class="o">.</span><span class="n">score</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">,</span> <span class="n">labels</span><span class="p">,</span> <span class="n">survival_time</span><span class="o">=</span><span class="n">survival_time</span><span class="p">)</span></tt>
+            </div>
+            <div id="l611"
+               class="code sev- "><tt><i>611</i> &nbsp;</tt>
+            </div>
+            <div id="l612"
+               class="code sev- "><tt><i>612</i>     <span class="k">def</span> <span class="nf">_get_problem_type</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ProblemType</span><span class="p">:</span></tt>
+            </div>
+            <div id="l613"
+               class="code sev- "><tt><i>613</i>         <span class="k">return</span> <span class="n">ProblemType</span><span class="o">.</span><span class="n">CONTRAST_SURVIVAL</span></tt>
             </div>
             
          </div>
diff --git a/docs/reports/junit/report.html b/docs/reports/junit/report.html
index 72dbf32..3c44db4 100644
--- a/docs/reports/junit/report.html
+++ b/docs/reports/junit/report.html
@@ -260,25 +260,29 @@ <h1>
                 <li>tests.test_classifier.TestClassifier
                 <ul>
                     
-                    <li class="outcome outcome-passed"><a href="#45700207-d130-4e7f-a2bd-aaa01a8a60ca">test_classification_accuracy_on_iris</a></li>
+                    <li class="outcome outcome-passed"><a href="#23b626ac-f7e9-45b1-8812-9856ef94acdb">test_classification_accuracy_on_iris</a></li>
                     
-                    <li class="outcome outcome-passed"><a href="#eaaab67a-da58-4cdb-bfa5-6c57a7ea258b">test_classification_metrics</a></li>
+                    <li class="outcome outcome-passed"><a href="#3bc3f839-b9c3-42fb-a21e-da28f4ed748d">test_classification_metrics</a></li>
                     
-                    <li class="outcome outcome-passed"><a href="#80521b77-184b-4a98-a577-3c70f0f985cf">test_classification_predict_proba</a></li>
+                    <li class="outcome outcome-passed"><a href="#8f277da6-cdb1-40d9-8548-e710e4a21152">test_classification_predict_proba</a></li>
                     
-                    <li class="outcome outcome-passed"><a href="#1e232482-e037-42a7-b37a-e126b2cf1a83">test_compare_with_java_results</a></li>
+                    <li class="outcome outcome-passed"><a href="#90838ced-0df9-4bc0-85a3-81db7211bd01">test_compare_with_java_results</a></li>
                     
-                    <li class="outcome outcome-passed"><a href="#74b3f13b-d14e-4618-8454-d6d9b36112fa">test_fit_and_predict_on_boolean_columns</a></li>
+                    <li class="outcome outcome-passed"><a href="#452478a0-7d05-4189-a3e3-6157a43d34cd">test_fit_and_predict_on_boolean_columns</a></li>
                     
-                    <li class="outcome outcome-passed"><a href="#9c6a2b2f-bad6-4cf2-9617-1c098f2dc78d">test_getting_examples_coverage</a></li>
+                    <li class="outcome outcome-passed"><a href="#3dc61c52-e239-4067-9ced-4ff68d51b09b">test_fit_on_integer_labels</a></li>
                     
-                    <li class="outcome outcome-passed"><a href="#edfaacda-f22a-4d14-9475-b9033dcefd23">test_induction_progress_listener</a></li>
+                    <li class="outcome outcome-passed"><a href="#8a9f1c1b-59de-427c-a468-da4d66a01695">test_getting_examples_coverage</a></li>
                     
-                    <li class="outcome outcome-passed"><a href="#f2ca82fa-1854-4c97-8b2e-6f813afaf5a2">test_predict_proba</a></li>
+                    <li class="outcome outcome-passed"><a href="#485377b6-f3e8-40b9-a7d4-6eb7ab83fc44">test_induction_progress_listener</a></li>
                     
-                    <li class="outcome outcome-passed"><a href="#50cd88a3-76b0-4f56-964e-3fab65bedfcf">test_prediction_on_nominal_values</a></li>
+                    <li class="outcome outcome-passed"><a href="#925322a8-506e-4cc3-9cb7-9d193b71068c">test_predict_proba</a></li>
                     
-                    <li class="outcome outcome-passed"><a href="#3961d83c-a985-429e-8e2f-a8f9c4592cb3">test_prediction_results_mapping</a></li>
+                    <li class="outcome outcome-passed"><a href="#d1e03e61-d8fb-40c5-87d4-a195847e8f12">test_prediction_on_nominal_values</a></li>
+                    
+                    <li class="outcome outcome-passed"><a href="#77a4295c-336d-4453-9876-1f7f53e6d916">test_prediction_results_mapping</a></li>
+                    
+                    <li class="outcome outcome-passed"><a href="#d5a4e1cf-a714-4f21-bc17-0375d00b9dd4">test_score</a></li>
                     
                 </ul>
                 </li>
@@ -286,11 +290,13 @@ <h1>
                 <li>tests.test_classifier.TestExperClassifier
                 <ul>
                     
-                    <li class="outcome outcome-passed"><a href="#ce51e945-0383-4fbb-b5d2-0b36da9919f3">test_compare_with_java_results</a></li>
+                    <li class="outcome outcome-passed"><a href="#30566a6c-3b89-4a41-a4e6-4b4a82c6eb6f">test_compare_with_java_results</a></li>
+                    
+                    <li class="outcome outcome-passed"><a href="#2a784d7f-b85c-4c51-b6e4-5b6858d2455f">test_left_open_intervals_in_expert_induction</a></li>
                     
-                    <li class="outcome outcome-passed"><a href="#c4ed1753-c3f9-47cf-b549-5399b84d51e9">test_left_open_intervals_in_expert_induction</a></li>
+                    <li class="outcome outcome-passed"><a href="#f2c61ac0-47bd-49bf-bebd-fe68e5924f1b">test_predict_proba</a></li>
                     
-                    <li class="outcome outcome-passed"><a href="#9e20c63a-75a6-42cb-abfc-8f97f5b8d571">test_predict_proba</a></li>
+                    <li class="outcome outcome-passed"><a href="#fbac7b47-4255-4568-b456-1714c5e36b5d">test_refining_conditions_for_nominal_attributes</a></li>
                     
                 </ul>
                 </li>
@@ -298,7 +304,11 @@ <h1>
                 <li>tests.test_regression.TestExpertRegressor
                 <ul>
                     
-                    <li class="outcome outcome-passed"><a href="#67706f15-4bb6-4c25-ac1f-88c095b6d145">test_compare_with_java_results</a></li>
+                    <li class="outcome outcome-passed"><a href="#ca929297-c2a5-4651-8973-4755b0cd73bd">test_compare_with_java_results</a></li>
+                    
+                    <li class="outcome outcome-passed"><a href="#21eea713-d27e-49c0-a96f-486409efc9b0">test_legacy_expert_rules_format</a></li>
+                    
+                    <li class="outcome outcome-passed"><a href="#d0dfe80c-9743-4c62-ae72-4f284b6d2634">test_refining_conditions_for_nominal_attributes</a></li>
                     
                 </ul>
                 </li>
@@ -306,13 +316,13 @@ <h1>
                 <li>tests.test_regression.TestRegressor
                 <ul>
                     
-                    <li class="outcome outcome-passed"><a href="#f55dafa2-7651-4239-a7d5-fd4bf7aebdea">test_cholesterol</a></li>
+                    <li class="outcome outcome-passed"><a href="#561ca3f1-a2fb-425d-83c2-10e9dfd7e4e5">test_cholesterol</a></li>
                     
-                    <li class="outcome outcome-passed"><a href="#6374d293-9d14-45c6-b0e4-f87116ceaecf">test_compare_with_java_results</a></li>
+                    <li class="outcome outcome-passed"><a href="#3d6b1d91-200b-4c73-b242-e0f05503e70a">test_compare_with_java_results</a></li>
                     
-                    <li class="outcome outcome-passed"><a href="#f9045c64-0abc-41aa-bfae-8f01be910aeb">test_fit_and_predict_on_boolean_columns</a></li>
+                    <li class="outcome outcome-passed"><a href="#22987d4b-0089-41e1-903d-e2779546ade7">test_fit_and_predict_on_boolean_columns</a></li>
                     
-                    <li class="outcome outcome-passed"><a href="#aa2636b7-d888-479d-8745-1e6021fdb7dd">test_induction_progress_listener</a></li>
+                    <li class="outcome outcome-passed"><a href="#ee811432-8207-4d9a-9531-44bff7efe42f">test_induction_progress_listener</a></li>
                     
                 </ul>
                 </li>
@@ -320,9 +330,9 @@ <h1>
                 <li>tests.test_rulekit.TestRuleKitMainClass
                 <ul>
                     
-                    <li class="outcome outcome-passed"><a href="#e0858de9-06f8-49ca-a83b-7e23640b3a74">test_loading_rulekit_class</a></li>
+                    <li class="outcome outcome-passed"><a href="#6748cab2-d3b0-43e3-940f-6f101332f561">test_loading_rulekit_class</a></li>
                     
-                    <li class="outcome outcome-passed"><a href="#9a6a3f89-6872-450a-aafd-f75a4aaa3fb9">test_reading_version</a></li>
+                    <li class="outcome outcome-passed"><a href="#cc51e809-4b94-485a-adf3-285a19c56538">test_reading_version</a></li>
                     
                 </ul>
                 </li>
@@ -330,19 +340,19 @@ <h1>
                 <li>tests.test_serialization.TestModelSerialization
                 <ul>
                     
-                    <li class="outcome outcome-passed"><a href="#02e3bf3d-ab29-46c1-a629-2e3af90f42a7">test_classifier_serialization</a></li>
+                    <li class="outcome outcome-passed"><a href="#cb68228f-07b9-4e8e-9ec5-8bdd51f863da">test_classifier_serialization</a></li>
                     
-                    <li class="outcome outcome-passed"><a href="#3b9637fc-1344-40df-af45-b5256fd364b7">test_expert_classifier_serialization</a></li>
+                    <li class="outcome outcome-passed"><a href="#cebf1221-1eca-44a3-8f6d-14777ad6b3d9">test_expert_classifier_serialization</a></li>
                     
-                    <li class="outcome outcome-passed"><a href="#18a93913-5df9-4eb9-95ee-8ae82715404b">test_expert_regressor_serialization</a></li>
+                    <li class="outcome outcome-passed"><a href="#d98bbd9f-ebad-4f19-bbe9-fb584ca08bc3">test_expert_regressor_serialization</a></li>
                     
-                    <li class="outcome outcome-passed"><a href="#03766557-8a03-4af8-99ba-1a3ced3b6d03">test_expert_survival_serialization</a></li>
+                    <li class="outcome outcome-passed"><a href="#7259c60f-e3ff-4048-a431-8c35869eb136">test_expert_survival_serialization</a></li>
                     
-                    <li class="outcome outcome-passed"><a href="#20907f68-d183-45b4-b60d-996f6cd39373">test_multiple_serialization</a></li>
+                    <li class="outcome outcome-passed"><a href="#975fa674-3404-4f18-ac7a-fe4ea0d367dd">test_multiple_serialization</a></li>
                     
-                    <li class="outcome outcome-passed"><a href="#c68265b7-56e0-465b-a9c1-7ab0e7822448">test_regressor_serialization</a></li>
+                    <li class="outcome outcome-passed"><a href="#ca8c8208-89a9-4ed4-a24f-a783ec132978">test_regressor_serialization</a></li>
                     
-                    <li class="outcome outcome-passed"><a href="#b03d2c41-adec-46c4-bb4a-78eb634ea18e">test_survival_serialization</a></li>
+                    <li class="outcome outcome-passed"><a href="#a2490ba6-83fe-437f-8281-641b434213e5">test_survival_serialization</a></li>
                     
                 </ul>
                 </li>
@@ -350,7 +360,7 @@ <h1>
                 <li>tests.test_sklearn_metrics.TestMetrics
                 <ul>
                     
-                    <li class="outcome outcome-passed"><a href="#8519a856-27e4-437b-9992-02eda010164f">test_classification_accuracy_on_iris</a></li>
+                    <li class="outcome outcome-passed"><a href="#37071817-5710-4c03-ab48-c537c7cfbaa2">test_classification_accuracy_on_iris</a></li>
                     
                 </ul>
                 </li>
@@ -358,15 +368,17 @@ <h1>
                 <li>tests.test_statistics.TestRuleClassifier
                 <ul>
                     
-                    <li class="outcome outcome-passed"><a href="#1c2f8996-e0a3-4b13-90c9-285eb94d5459">test_classification_accuracy_on_iris</a></li>
+                    <li class="outcome outcome-passed"><a href="#b2e8ae66-ca38-4825-9970-a8c4bbceef7c">test_classification_accuracy_on_iris</a></li>
                     
                 </ul>
                 </li>
                 
-                <li>tests.test_survival.TestExpertSurvivalLogRankTree
+                <li>tests.test_survival.TestExpertSurvivalRules
                 <ul>
                     
-                    <li class="outcome outcome-passed"><a href="#59de910f-061d-4429-ad4e-beb9d863b3fd">test_compare_with_java_results</a></li>
+                    <li class="outcome outcome-passed"><a href="#834a815a-8059-4782-a623-6fe164bfd834">test_compare_with_java_results</a></li>
+                    
+                    <li class="outcome outcome-passed"><a href="#b1518405-5417-405b-9acf-5504576b187a">test_refining_conditions_for_nominal_attributes</a></li>
                     
                 </ul>
                 </li>
@@ -374,11 +386,11 @@ <h1>
                 <li>tests.test_survival.TestKaplanMeierEstimator
                 <ul>
                     
-                    <li class="outcome outcome-passed"><a href="#41dbd1e3-1758-43fd-a8c4-4db032aaea29">test_accessing_at_risk_count</a></li>
+                    <li class="outcome outcome-passed"><a href="#fb203089-6070-4569-991e-c59c7f44ad02">test_accessing_at_risk_count</a></li>
                     
-                    <li class="outcome outcome-passed"><a href="#7fc1f45c-6f83-45b1-a486-87151df5f55f">test_accessing_events_count</a></li>
+                    <li class="outcome outcome-passed"><a href="#a9f3b308-e0c2-420a-8140-6f02675ad52f">test_accessing_events_count</a></li>
                     
-                    <li class="outcome outcome-passed"><a href="#2703f2ed-3b53-4f95-8d8b-f82c6953593d">test_accessing_probabilities</a></li>
+                    <li class="outcome outcome-passed"><a href="#cbcee1e6-1a63-4ee9-bd4e-10e719ec4fd7">test_accessing_probabilities</a></li>
                     
                 </ul>
                 </li>
@@ -386,11 +398,17 @@ <h1>
                 <li>tests.test_survival.TestSurvivalRules
                 <ul>
                     
-                    <li class="outcome outcome-passed"><a href="#5586df64-7e3d-4ce5-8c8f-03131f8489ba">test_compare_with_java_results</a></li>
+                    <li class="outcome outcome-passed"><a href="#9b70f4c3-e5b9-4d31-9b13-67b1295841e8">test_compare_with_java_results</a></li>
                     
-                    <li class="outcome outcome-passed"><a href="#ddea1596-fd51-49cb-b830-12cc045b9785">test_fit_and_predict_on_boolean_columns</a></li>
+                    <li class="outcome outcome-passed"><a href="#d7fc3896-5868-4c68-bfb9-79f489501625">test_fit_and_predict_on_boolean_columns</a></li>
                     
-                    <li class="outcome outcome-passed"><a href="#57305227-bee5-4e02-8b4b-670fb124bff4">test_induction_progress_listener</a></li>
+                    <li class="outcome outcome-passed"><a href="#86433132-5c2a-4cf6-a812-b9903dd022db">test_getting_training_dataset_kaplan_meier_estimator</a></li>
+                    
+                    <li class="outcome outcome-passed"><a href="#afd8f98c-3dea-4d4b-8fe2-e067c823072c">test_ibs_calculation</a></li>
+                    
+                    <li class="outcome outcome-passed"><a href="#78174d15-1f48-42d8-82b6-59d86a023eb7">test_induction_progress_listener</a></li>
+                    
+                    <li class="outcome outcome-passed"><a href="#cd3d9d79-3b58-4a41-8664-6b9b2d067a55">test_passing_survival_time_column_to_fit_method</a></li>
                     
                 </ul>
                 </li>
@@ -423,6 +441,10 @@ <h1>
                     
                     
                     
+                    
+                    
+                    
+                    
                 
                     
                     
@@ -431,10 +453,16 @@ <h1>
                     
                     
                     
+                    
+                    
                 
                     
                     
                     
+                    
+                    
+                    
+                    
                 
                     
                     
@@ -479,6 +507,8 @@ <h1>
                     
                     
                     
+                    
+                    
                 
                     
                     
@@ -488,6 +518,12 @@ <h1>
                     
                     
                 
+                    
+                    
+                    
+                    
+                    
+                    
                     
                     
                     
@@ -506,16 +542,16 @@ <h1>
 
     <div class="testsuite">
         <h2>Test Suite: </h2>
-        <a id="074b8e69-f29d-4f11-9c8f-11af3939f721"></a>
+        <a id="5bd10191-53f7-43be-9bd7-a18e0f864e68"></a>
         
         
         <h3>Results</h3>
         <table class="proplist">
             <tr>
-                <th>Duration</th><td>21.825 sec</td>
+                <th>Duration</th><td>30.906 sec</td>
             </tr>
             <tr>
-                <th>Tests</th><td>36</td>
+                <th>Tests</th><td>45</td>
             </tr>
             <tr>
                 <th>Failures</th><td>0</td>
@@ -530,11 +566,11 @@ <h4>tests.test_classifier.TestClassifier</h4>
                 <div class="testcases">
                 
                     <div class="test outcome outcome-passed">
-                        <a id="45700207-d130-4e7f-a2bd-aaa01a8a60ca"></a>
+                        <a id="23b626ac-f7e9-45b1-8812-9856ef94acdb"></a>
                         <table class="proplist">
                             <tr><th>Test case:</th><td><b>test_classification_accuracy_on_iris</b></td></tr>
                             <tr><th>Outcome:</th><td>Passed</td></tr>
-                            <tr><th>Duration:</th><td>0.982 sec</td></tr>
+                            <tr><th>Duration:</th><td>0.974 sec</td></tr>
                         
                         
                         </table>
@@ -548,11 +584,11 @@ <h4>tests.test_classifier.TestClassifier</h4>
                     </div>
                 
                     <div class="test outcome outcome-passed">
-                        <a id="eaaab67a-da58-4cdb-bfa5-6c57a7ea258b"></a>
+                        <a id="3bc3f839-b9c3-42fb-a21e-da28f4ed748d"></a>
                         <table class="proplist">
                             <tr><th>Test case:</th><td><b>test_classification_metrics</b></td></tr>
                             <tr><th>Outcome:</th><td>Passed</td></tr>
-                            <tr><th>Duration:</th><td>0.027 sec</td></tr>
+                            <tr><th>Duration:</th><td>0.028 sec</td></tr>
                         
                         
                         </table>
@@ -566,11 +602,11 @@ <h4>tests.test_classifier.TestClassifier</h4>
                     </div>
                 
                     <div class="test outcome outcome-passed">
-                        <a id="80521b77-184b-4a98-a577-3c70f0f985cf"></a>
+                        <a id="8f277da6-cdb1-40d9-8548-e710e4a21152"></a>
                         <table class="proplist">
                             <tr><th>Test case:</th><td><b>test_classification_predict_proba</b></td></tr>
                             <tr><th>Outcome:</th><td>Passed</td></tr>
-                            <tr><th>Duration:</th><td>0.02 sec</td></tr>
+                            <tr><th>Duration:</th><td>0.021 sec</td></tr>
                         
                         
                         </table>
@@ -584,11 +620,11 @@ <h4>tests.test_classifier.TestClassifier</h4>
                     </div>
                 
                     <div class="test outcome outcome-passed">
-                        <a id="1e232482-e037-42a7-b37a-e126b2cf1a83"></a>
+                        <a id="90838ced-0df9-4bc0-85a3-81db7211bd01"></a>
                         <table class="proplist">
                             <tr><th>Test case:</th><td><b>test_compare_with_java_results</b></td></tr>
                             <tr><th>Outcome:</th><td>Passed</td></tr>
-                            <tr><th>Duration:</th><td>0.395 sec</td></tr>
+                            <tr><th>Duration:</th><td>0.374 sec</td></tr>
                         
                         
                         </table>
@@ -602,11 +638,29 @@ <h4>tests.test_classifier.TestClassifier</h4>
                     </div>
                 
                     <div class="test outcome outcome-passed">
-                        <a id="74b3f13b-d14e-4618-8454-d6d9b36112fa"></a>
+                        <a id="452478a0-7d05-4189-a3e3-6157a43d34cd"></a>
                         <table class="proplist">
                             <tr><th>Test case:</th><td><b>test_fit_and_predict_on_boolean_columns</b></td></tr>
                             <tr><th>Outcome:</th><td>Passed</td></tr>
-                            <tr><th>Duration:</th><td>0.187 sec</td></tr>
+                            <tr><th>Duration:</th><td>0.157 sec</td></tr>
+                        
+                        
+                        </table>
+
+                        
+                        
+
+                        
+                        
+                        
+                    </div>
+                
+                    <div class="test outcome outcome-passed">
+                        <a id="3dc61c52-e239-4067-9ced-4ff68d51b09b"></a>
+                        <table class="proplist">
+                            <tr><th>Test case:</th><td><b>test_fit_on_integer_labels</b></td></tr>
+                            <tr><th>Outcome:</th><td>Passed</td></tr>
+                            <tr><th>Duration:</th><td>0.09 sec</td></tr>
                         
                         
                         </table>
@@ -620,11 +674,11 @@ <h4>tests.test_classifier.TestClassifier</h4>
                     </div>
                 
                     <div class="test outcome outcome-passed">
-                        <a id="9c6a2b2f-bad6-4cf2-9617-1c098f2dc78d"></a>
+                        <a id="8a9f1c1b-59de-427c-a468-da4d66a01695"></a>
                         <table class="proplist">
                             <tr><th>Test case:</th><td><b>test_getting_examples_coverage</b></td></tr>
                             <tr><th>Outcome:</th><td>Passed</td></tr>
-                            <tr><th>Duration:</th><td>0.073 sec</td></tr>
+                            <tr><th>Duration:</th><td>0.017 sec</td></tr>
                         
                         
                         </table>
@@ -638,11 +692,11 @@ <h4>tests.test_classifier.TestClassifier</h4>
                     </div>
                 
                     <div class="test outcome outcome-passed">
-                        <a id="edfaacda-f22a-4d14-9475-b9033dcefd23"></a>
+                        <a id="485377b6-f3e8-40b9-a7d4-6eb7ab83fc44"></a>
                         <table class="proplist">
                             <tr><th>Test case:</th><td><b>test_induction_progress_listener</b></td></tr>
                             <tr><th>Outcome:</th><td>Passed</td></tr>
-                            <tr><th>Duration:</th><td>0.077 sec</td></tr>
+                            <tr><th>Duration:</th><td>0.065 sec</td></tr>
                         
                         
                         </table>
@@ -656,11 +710,11 @@ <h4>tests.test_classifier.TestClassifier</h4>
                     </div>
                 
                     <div class="test outcome outcome-passed">
-                        <a id="f2ca82fa-1854-4c97-8b2e-6f813afaf5a2"></a>
+                        <a id="925322a8-506e-4cc3-9cb7-9d193b71068c"></a>
                         <table class="proplist">
                             <tr><th>Test case:</th><td><b>test_predict_proba</b></td></tr>
                             <tr><th>Outcome:</th><td>Passed</td></tr>
-                            <tr><th>Duration:</th><td>0.094 sec</td></tr>
+                            <tr><th>Duration:</th><td>0.155 sec</td></tr>
                         
                         
                         </table>
@@ -674,11 +728,11 @@ <h4>tests.test_classifier.TestClassifier</h4>
                     </div>
                 
                     <div class="test outcome outcome-passed">
-                        <a id="50cd88a3-76b0-4f56-964e-3fab65bedfcf"></a>
+                        <a id="d1e03e61-d8fb-40c5-87d4-a195847e8f12"></a>
                         <table class="proplist">
                             <tr><th>Test case:</th><td><b>test_prediction_on_nominal_values</b></td></tr>
                             <tr><th>Outcome:</th><td>Passed</td></tr>
-                            <tr><th>Duration:</th><td>0.006 sec</td></tr>
+                            <tr><th>Duration:</th><td>0.004 sec</td></tr>
                         
                         
                         </table>
@@ -692,11 +746,29 @@ <h4>tests.test_classifier.TestClassifier</h4>
                     </div>
                 
                     <div class="test outcome outcome-passed">
-                        <a id="3961d83c-a985-429e-8e2f-a8f9c4592cb3"></a>
+                        <a id="77a4295c-336d-4453-9876-1f7f53e6d916"></a>
                         <table class="proplist">
                             <tr><th>Test case:</th><td><b>test_prediction_results_mapping</b></td></tr>
                             <tr><th>Outcome:</th><td>Passed</td></tr>
-                            <tr><th>Duration:</th><td>0.005 sec</td></tr>
+                            <tr><th>Duration:</th><td>0.003 sec</td></tr>
+                        
+                        
+                        </table>
+
+                        
+                        
+
+                        
+                        
+                        
+                    </div>
+                
+                    <div class="test outcome outcome-passed">
+                        <a id="d5a4e1cf-a714-4f21-bc17-0375d00b9dd4"></a>
+                        <table class="proplist">
+                            <tr><th>Test case:</th><td><b>test_score</b></td></tr>
+                            <tr><th>Outcome:</th><td>Passed</td></tr>
+                            <tr><th>Duration:</th><td>0.015 sec</td></tr>
                         
                         
                         </table>
@@ -717,11 +789,11 @@ <h4>tests.test_classifier.TestExperClassifier</h4>
                 <div class="testcases">
                 
                     <div class="test outcome outcome-passed">
-                        <a id="ce51e945-0383-4fbb-b5d2-0b36da9919f3"></a>
+                        <a id="30566a6c-3b89-4a41-a4e6-4b4a82c6eb6f"></a>
                         <table class="proplist">
                             <tr><th>Test case:</th><td><b>test_compare_with_java_results</b></td></tr>
                             <tr><th>Outcome:</th><td>Passed</td></tr>
-                            <tr><th>Duration:</th><td>0.737 sec</td></tr>
+                            <tr><th>Duration:</th><td>0.795 sec</td></tr>
                         
                         
                         </table>
@@ -735,11 +807,11 @@ <h4>tests.test_classifier.TestExperClassifier</h4>
                     </div>
                 
                     <div class="test outcome outcome-passed">
-                        <a id="c4ed1753-c3f9-47cf-b549-5399b84d51e9"></a>
+                        <a id="2a784d7f-b85c-4c51-b6e4-5b6858d2455f"></a>
                         <table class="proplist">
                             <tr><th>Test case:</th><td><b>test_left_open_intervals_in_expert_induction</b></td></tr>
                             <tr><th>Outcome:</th><td>Passed</td></tr>
-                            <tr><th>Duration:</th><td>0.047 sec</td></tr>
+                            <tr><th>Duration:</th><td>0.073 sec</td></tr>
                         
                         
                         </table>
@@ -753,11 +825,29 @@ <h4>tests.test_classifier.TestExperClassifier</h4>
                     </div>
                 
                     <div class="test outcome outcome-passed">
-                        <a id="9e20c63a-75a6-42cb-abfc-8f97f5b8d571"></a>
+                        <a id="f2c61ac0-47bd-49bf-bebd-fe68e5924f1b"></a>
                         <table class="proplist">
                             <tr><th>Test case:</th><td><b>test_predict_proba</b></td></tr>
                             <tr><th>Outcome:</th><td>Passed</td></tr>
-                            <tr><th>Duration:</th><td>0.14 sec</td></tr>
+                            <tr><th>Duration:</th><td>0.047 sec</td></tr>
+                        
+                        
+                        </table>
+
+                        
+                        
+
+                        
+                        
+                        
+                    </div>
+                
+                    <div class="test outcome outcome-passed">
+                        <a id="fbac7b47-4255-4568-b456-1714c5e36b5d"></a>
+                        <table class="proplist">
+                            <tr><th>Test case:</th><td><b>test_refining_conditions_for_nominal_attributes</b></td></tr>
+                            <tr><th>Outcome:</th><td>Passed</td></tr>
+                            <tr><th>Duration:</th><td>0.534 sec</td></tr>
                         
                         
                         </table>
@@ -778,11 +868,47 @@ <h4>tests.test_regression.TestExpertRegressor</h4>
                 <div class="testcases">
                 
                     <div class="test outcome outcome-passed">
-                        <a id="67706f15-4bb6-4c25-ac1f-88c095b6d145"></a>
+                        <a id="ca929297-c2a5-4651-8973-4755b0cd73bd"></a>
                         <table class="proplist">
                             <tr><th>Test case:</th><td><b>test_compare_with_java_results</b></td></tr>
                             <tr><th>Outcome:</th><td>Passed</td></tr>
-                            <tr><th>Duration:</th><td>1.144 sec</td></tr>
+                            <tr><th>Duration:</th><td>1.196 sec</td></tr>
+                        
+                        
+                        </table>
+
+                        
+                        
+
+                        
+                        
+                        
+                    </div>
+                
+                    <div class="test outcome outcome-passed">
+                        <a id="21eea713-d27e-49c0-a96f-486409efc9b0"></a>
+                        <table class="proplist">
+                            <tr><th>Test case:</th><td><b>test_legacy_expert_rules_format</b></td></tr>
+                            <tr><th>Outcome:</th><td>Passed</td></tr>
+                            <tr><th>Duration:</th><td>0.033 sec</td></tr>
+                        
+                        
+                        </table>
+
+                        
+                        
+
+                        
+                        
+                        
+                    </div>
+                
+                    <div class="test outcome outcome-passed">
+                        <a id="d0dfe80c-9743-4c62-ae72-4f284b6d2634"></a>
+                        <table class="proplist">
+                            <tr><th>Test case:</th><td><b>test_refining_conditions_for_nominal_attributes</b></td></tr>
+                            <tr><th>Outcome:</th><td>Passed</td></tr>
+                            <tr><th>Duration:</th><td>0.038 sec</td></tr>
                         
                         
                         </table>
@@ -803,11 +929,11 @@ <h4>tests.test_regression.TestRegressor</h4>
                 <div class="testcases">
                 
                     <div class="test outcome outcome-passed">
-                        <a id="f55dafa2-7651-4239-a7d5-fd4bf7aebdea"></a>
+                        <a id="561ca3f1-a2fb-425d-83c2-10e9dfd7e4e5"></a>
                         <table class="proplist">
                             <tr><th>Test case:</th><td><b>test_cholesterol</b></td></tr>
                             <tr><th>Outcome:</th><td>Passed</td></tr>
-                            <tr><th>Duration:</th><td>3.422 sec</td></tr>
+                            <tr><th>Duration:</th><td>3.309 sec</td></tr>
                         
                         
                         </table>
@@ -821,11 +947,11 @@ <h4>tests.test_regression.TestRegressor</h4>
                     </div>
                 
                     <div class="test outcome outcome-passed">
-                        <a id="6374d293-9d14-45c6-b0e4-f87116ceaecf"></a>
+                        <a id="3d6b1d91-200b-4c73-b242-e0f05503e70a"></a>
                         <table class="proplist">
                             <tr><th>Test case:</th><td><b>test_compare_with_java_results</b></td></tr>
                             <tr><th>Outcome:</th><td>Passed</td></tr>
-                            <tr><th>Duration:</th><td>0.278 sec</td></tr>
+                            <tr><th>Duration:</th><td>0.271 sec</td></tr>
                         
                         
                         </table>
@@ -839,11 +965,11 @@ <h4>tests.test_regression.TestRegressor</h4>
                     </div>
                 
                     <div class="test outcome outcome-passed">
-                        <a id="f9045c64-0abc-41aa-bfae-8f01be910aeb"></a>
+                        <a id="22987d4b-0089-41e1-903d-e2779546ade7"></a>
                         <table class="proplist">
                             <tr><th>Test case:</th><td><b>test_fit_and_predict_on_boolean_columns</b></td></tr>
                             <tr><th>Outcome:</th><td>Passed</td></tr>
-                            <tr><th>Duration:</th><td>0.543 sec</td></tr>
+                            <tr><th>Duration:</th><td>0.495 sec</td></tr>
                         
                         
                         </table>
@@ -857,11 +983,11 @@ <h4>tests.test_regression.TestRegressor</h4>
                     </div>
                 
                     <div class="test outcome outcome-passed">
-                        <a id="aa2636b7-d888-479d-8745-1e6021fdb7dd"></a>
+                        <a id="ee811432-8207-4d9a-9531-44bff7efe42f"></a>
                         <table class="proplist">
                             <tr><th>Test case:</th><td><b>test_induction_progress_listener</b></td></tr>
                             <tr><th>Outcome:</th><td>Passed</td></tr>
-                            <tr><th>Duration:</th><td>0.032 sec</td></tr>
+                            <tr><th>Duration:</th><td>0.03 sec</td></tr>
                         
                         
                         </table>
@@ -882,7 +1008,7 @@ <h4>tests.test_rulekit.TestRuleKitMainClass</h4>
                 <div class="testcases">
                 
                     <div class="test outcome outcome-passed">
-                        <a id="e0858de9-06f8-49ca-a83b-7e23640b3a74"></a>
+                        <a id="6748cab2-d3b0-43e3-940f-6f101332f561"></a>
                         <table class="proplist">
                             <tr><th>Test case:</th><td><b>test_loading_rulekit_class</b></td></tr>
                             <tr><th>Outcome:</th><td>Passed</td></tr>
@@ -900,7 +1026,7 @@ <h4>tests.test_rulekit.TestRuleKitMainClass</h4>
                     </div>
                 
                     <div class="test outcome outcome-passed">
-                        <a id="9a6a3f89-6872-450a-aafd-f75a4aaa3fb9"></a>
+                        <a id="cc51e809-4b94-485a-adf3-285a19c56538"></a>
                         <table class="proplist">
                             <tr><th>Test case:</th><td><b>test_reading_version</b></td></tr>
                             <tr><th>Outcome:</th><td>Passed</td></tr>
@@ -925,11 +1051,11 @@ <h4>tests.test_serialization.TestModelSerialization</h4>
                 <div class="testcases">
                 
                     <div class="test outcome outcome-passed">
-                        <a id="02e3bf3d-ab29-46c1-a629-2e3af90f42a7"></a>
+                        <a id="cb68228f-07b9-4e8e-9ec5-8bdd51f863da"></a>
                         <table class="proplist">
                             <tr><th>Test case:</th><td><b>test_classifier_serialization</b></td></tr>
                             <tr><th>Outcome:</th><td>Passed</td></tr>
-                            <tr><th>Duration:</th><td>0.101 sec</td></tr>
+                            <tr><th>Duration:</th><td>0.085 sec</td></tr>
                         
                         
                         </table>
@@ -943,11 +1069,11 @@ <h4>tests.test_serialization.TestModelSerialization</h4>
                     </div>
                 
                     <div class="test outcome outcome-passed">
-                        <a id="3b9637fc-1344-40df-af45-b5256fd364b7"></a>
+                        <a id="cebf1221-1eca-44a3-8f6d-14777ad6b3d9"></a>
                         <table class="proplist">
                             <tr><th>Test case:</th><td><b>test_expert_classifier_serialization</b></td></tr>
                             <tr><th>Outcome:</th><td>Passed</td></tr>
-                            <tr><th>Duration:</th><td>0.02 sec</td></tr>
+                            <tr><th>Duration:</th><td>0.031 sec</td></tr>
                         
                         
                         </table>
@@ -961,11 +1087,11 @@ <h4>tests.test_serialization.TestModelSerialization</h4>
                     </div>
                 
                     <div class="test outcome outcome-passed">
-                        <a id="18a93913-5df9-4eb9-95ee-8ae82715404b"></a>
+                        <a id="d98bbd9f-ebad-4f19-bbe9-fb584ca08bc3"></a>
                         <table class="proplist">
                             <tr><th>Test case:</th><td><b>test_expert_regressor_serialization</b></td></tr>
                             <tr><th>Outcome:</th><td>Passed</td></tr>
-                            <tr><th>Duration:</th><td>0.087 sec</td></tr>
+                            <tr><th>Duration:</th><td>0.068 sec</td></tr>
                         
                         
                         </table>
@@ -979,11 +1105,11 @@ <h4>tests.test_serialization.TestModelSerialization</h4>
                     </div>
                 
                     <div class="test outcome outcome-passed">
-                        <a id="03766557-8a03-4af8-99ba-1a3ced3b6d03"></a>
+                        <a id="7259c60f-e3ff-4048-a431-8c35869eb136"></a>
                         <table class="proplist">
                             <tr><th>Test case:</th><td><b>test_expert_survival_serialization</b></td></tr>
                             <tr><th>Outcome:</th><td>Passed</td></tr>
-                            <tr><th>Duration:</th><td>0.036 sec</td></tr>
+                            <tr><th>Duration:</th><td>0.052 sec</td></tr>
                         
                         
                         </table>
@@ -997,11 +1123,11 @@ <h4>tests.test_serialization.TestModelSerialization</h4>
                     </div>
                 
                     <div class="test outcome outcome-passed">
-                        <a id="20907f68-d183-45b4-b60d-996f6cd39373"></a>
+                        <a id="975fa674-3404-4f18-ac7a-fe4ea0d367dd"></a>
                         <table class="proplist">
                             <tr><th>Test case:</th><td><b>test_multiple_serialization</b></td></tr>
                             <tr><th>Outcome:</th><td>Passed</td></tr>
-                            <tr><th>Duration:</th><td>0.024 sec</td></tr>
+                            <tr><th>Duration:</th><td>0.015 sec</td></tr>
                         
                         
                         </table>
@@ -1015,11 +1141,11 @@ <h4>tests.test_serialization.TestModelSerialization</h4>
                     </div>
                 
                     <div class="test outcome outcome-passed">
-                        <a id="c68265b7-56e0-465b-a9c1-7ab0e7822448"></a>
+                        <a id="ca8c8208-89a9-4ed4-a24f-a783ec132978"></a>
                         <table class="proplist">
                             <tr><th>Test case:</th><td><b>test_regressor_serialization</b></td></tr>
                             <tr><th>Outcome:</th><td>Passed</td></tr>
-                            <tr><th>Duration:</th><td>3.804 sec</td></tr>
+                            <tr><th>Duration:</th><td>4.265 sec</td></tr>
                         
                         
                         </table>
@@ -1033,11 +1159,11 @@ <h4>tests.test_serialization.TestModelSerialization</h4>
                     </div>
                 
                     <div class="test outcome outcome-passed">
-                        <a id="b03d2c41-adec-46c4-bb4a-78eb634ea18e"></a>
+                        <a id="a2490ba6-83fe-437f-8281-641b434213e5"></a>
                         <table class="proplist">
                             <tr><th>Test case:</th><td><b>test_survival_serialization</b></td></tr>
                             <tr><th>Outcome:</th><td>Passed</td></tr>
-                            <tr><th>Duration:</th><td>0.212 sec</td></tr>
+                            <tr><th>Duration:</th><td>0.214 sec</td></tr>
                         
                         
                         </table>
@@ -1058,11 +1184,11 @@ <h4>tests.test_sklearn_metrics.TestMetrics</h4>
                 <div class="testcases">
                 
                     <div class="test outcome outcome-passed">
-                        <a id="8519a856-27e4-437b-9992-02eda010164f"></a>
+                        <a id="37071817-5710-4c03-ab48-c537c7cfbaa2"></a>
                         <table class="proplist">
                             <tr><th>Test case:</th><td><b>test_classification_accuracy_on_iris</b></td></tr>
                             <tr><th>Outcome:</th><td>Passed</td></tr>
-                            <tr><th>Duration:</th><td>0.016 sec</td></tr>
+                            <tr><th>Duration:</th><td>0.014 sec</td></tr>
                         
                         
                         </table>
@@ -1083,11 +1209,11 @@ <h4>tests.test_statistics.TestRuleClassifier</h4>
                 <div class="testcases">
                 
                     <div class="test outcome outcome-passed">
-                        <a id="1c2f8996-e0a3-4b13-90c9-285eb94d5459"></a>
+                        <a id="b2e8ae66-ca38-4825-9970-a8c4bbceef7c"></a>
                         <table class="proplist">
                             <tr><th>Test case:</th><td><b>test_classification_accuracy_on_iris</b></td></tr>
                             <tr><th>Outcome:</th><td>Passed</td></tr>
-                            <tr><th>Duration:</th><td>0.011 sec</td></tr>
+                            <tr><th>Duration:</th><td>0.01 sec</td></tr>
                         
                         
                         </table>
@@ -1104,15 +1230,33 @@ <h4>tests.test_statistics.TestRuleClassifier</h4>
             </div>
             
             <div class="testclass">
-                <h4>tests.test_survival.TestExpertSurvivalLogRankTree</h4>
+                <h4>tests.test_survival.TestExpertSurvivalRules</h4>
                 <div class="testcases">
                 
                     <div class="test outcome outcome-passed">
-                        <a id="59de910f-061d-4429-ad4e-beb9d863b3fd"></a>
+                        <a id="834a815a-8059-4782-a623-6fe164bfd834"></a>
                         <table class="proplist">
                             <tr><th>Test case:</th><td><b>test_compare_with_java_results</b></td></tr>
                             <tr><th>Outcome:</th><td>Passed</td></tr>
-                            <tr><th>Duration:</th><td>1.34 sec</td></tr>
+                            <tr><th>Duration:</th><td>1.635 sec</td></tr>
+                        
+                        
+                        </table>
+
+                        
+                        
+
+                        
+                        
+                        
+                    </div>
+                
+                    <div class="test outcome outcome-passed">
+                        <a id="b1518405-5417-405b-9acf-5504576b187a"></a>
+                        <table class="proplist">
+                            <tr><th>Test case:</th><td><b>test_refining_conditions_for_nominal_attributes</b></td></tr>
+                            <tr><th>Outcome:</th><td>Passed</td></tr>
+                            <tr><th>Duration:</th><td>0.165 sec</td></tr>
                         
                         
                         </table>
@@ -1133,11 +1277,11 @@ <h4>tests.test_survival.TestKaplanMeierEstimator</h4>
                 <div class="testcases">
                 
                     <div class="test outcome outcome-passed">
-                        <a id="41dbd1e3-1758-43fd-a8c4-4db032aaea29"></a>
+                        <a id="fb203089-6070-4569-991e-c59c7f44ad02"></a>
                         <table class="proplist">
                             <tr><th>Test case:</th><td><b>test_accessing_at_risk_count</b></td></tr>
                             <tr><th>Outcome:</th><td>Passed</td></tr>
-                            <tr><th>Duration:</th><td>1.064 sec</td></tr>
+                            <tr><th>Duration:</th><td>1.242 sec</td></tr>
                         
                         
                         </table>
@@ -1151,11 +1295,11 @@ <h4>tests.test_survival.TestKaplanMeierEstimator</h4>
                     </div>
                 
                     <div class="test outcome outcome-passed">
-                        <a id="7fc1f45c-6f83-45b1-a486-87151df5f55f"></a>
+                        <a id="a9f3b308-e0c2-420a-8140-6f02675ad52f"></a>
                         <table class="proplist">
                             <tr><th>Test case:</th><td><b>test_accessing_events_count</b></td></tr>
                             <tr><th>Outcome:</th><td>Passed</td></tr>
-                            <tr><th>Duration:</th><td>1.021 sec</td></tr>
+                            <tr><th>Duration:</th><td>1.034 sec</td></tr>
                         
                         
                         </table>
@@ -1169,11 +1313,11 @@ <h4>tests.test_survival.TestKaplanMeierEstimator</h4>
                     </div>
                 
                     <div class="test outcome outcome-passed">
-                        <a id="2703f2ed-3b53-4f95-8d8b-f82c6953593d"></a>
+                        <a id="cbcee1e6-1a63-4ee9-bd4e-10e719ec4fd7"></a>
                         <table class="proplist">
                             <tr><th>Test case:</th><td><b>test_accessing_probabilities</b></td></tr>
                             <tr><th>Outcome:</th><td>Passed</td></tr>
-                            <tr><th>Duration:</th><td>0.873 sec</td></tr>
+                            <tr><th>Duration:</th><td>0.999 sec</td></tr>
                         
                         
                         </table>
@@ -1194,11 +1338,11 @@ <h4>tests.test_survival.TestSurvivalRules</h4>
                 <div class="testcases">
                 
                     <div class="test outcome outcome-passed">
-                        <a id="5586df64-7e3d-4ce5-8c8f-03131f8489ba"></a>
+                        <a id="9b70f4c3-e5b9-4d31-9b13-67b1295841e8"></a>
                         <table class="proplist">
                             <tr><th>Test case:</th><td><b>test_compare_with_java_results</b></td></tr>
                             <tr><th>Outcome:</th><td>Passed</td></tr>
-                            <tr><th>Duration:</th><td>1.347 sec</td></tr>
+                            <tr><th>Duration:</th><td>1.712 sec</td></tr>
                         
                         
                         </table>
@@ -1212,11 +1356,11 @@ <h4>tests.test_survival.TestSurvivalRules</h4>
                     </div>
                 
                     <div class="test outcome outcome-passed">
-                        <a id="ddea1596-fd51-49cb-b830-12cc045b9785"></a>
+                        <a id="d7fc3896-5868-4c68-bfb9-79f489501625"></a>
                         <table class="proplist">
                             <tr><th>Test case:</th><td><b>test_fit_and_predict_on_boolean_columns</b></td></tr>
                             <tr><th>Outcome:</th><td>Passed</td></tr>
-                            <tr><th>Duration:</th><td>2.792 sec</td></tr>
+                            <tr><th>Duration:</th><td>3.122 sec</td></tr>
                         
                         
                         </table>
@@ -1230,11 +1374,65 @@ <h4>tests.test_survival.TestSurvivalRules</h4>
                     </div>
                 
                     <div class="test outcome outcome-passed">
-                        <a id="57305227-bee5-4e02-8b4b-670fb124bff4"></a>
+                        <a id="86433132-5c2a-4cf6-a812-b9903dd022db"></a>
+                        <table class="proplist">
+                            <tr><th>Test case:</th><td><b>test_getting_training_dataset_kaplan_meier_estimator</b></td></tr>
+                            <tr><th>Outcome:</th><td>Passed</td></tr>
+                            <tr><th>Duration:</th><td>1.552 sec</td></tr>
+                        
+                        
+                        </table>
+
+                        
+                        
+
+                        
+                        
+                        
+                    </div>
+                
+                    <div class="test outcome outcome-passed">
+                        <a id="afd8f98c-3dea-4d4b-8fe2-e067c823072c"></a>
+                        <table class="proplist">
+                            <tr><th>Test case:</th><td><b>test_ibs_calculation</b></td></tr>
+                            <tr><th>Outcome:</th><td>Passed</td></tr>
+                            <tr><th>Duration:</th><td>1.723 sec</td></tr>
+                        
+                        
+                        </table>
+
+                        
+                        
+
+                        
+                        
+                        
+                    </div>
+                
+                    <div class="test outcome outcome-passed">
+                        <a id="78174d15-1f48-42d8-82b6-59d86a023eb7"></a>
                         <table class="proplist">
                             <tr><th>Test case:</th><td><b>test_induction_progress_listener</b></td></tr>
                             <tr><th>Outcome:</th><td>Passed</td></tr>
-                            <tr><th>Duration:</th><td>0.866 sec</td></tr>
+                            <tr><th>Duration:</th><td>1.065 sec</td></tr>
+                        
+                        
+                        </table>
+
+                        
+                        
+
+                        
+                        
+                        
+                    </div>
+                
+                    <div class="test outcome outcome-passed">
+                        <a id="cd3d9d79-3b58-4a41-8664-6b9b2d067a55"></a>
+                        <table class="proplist">
+                            <tr><th>Test case:</th><td><b>test_passing_survival_time_column_to_fit_method</b></td></tr>
+                            <tr><th>Outcome:</th><td>Passed</td></tr>
+                            <tr><th>Duration:</th><td>3.172 sec</td></tr>
                         
                         
                         </table>
diff --git a/rulekit/_helpers.py b/rulekit/_helpers.py
index 4d9a6fd..56fa4d1 100644
--- a/rulekit/_helpers.py
+++ b/rulekit/_helpers.py
@@ -35,20 +35,21 @@ def get_rule_generator(expert: bool = False) -> Any:
         Any: RuleGenerator instance
     """
     RuleGenerator = JClass(  # pylint: disable=invalid-name
-        'adaa.analytics.rules.logic.rulegenerator.RuleGenerator'
+        "adaa.analytics.rules.logic.rulegenerator.RuleGenerator"
     )
     rule_generator = RuleGenerator(expert)
     return rule_generator
 
 
 class RuleGeneratorConfigurator:
-    """Class for configuring rule induction parameters
-    """
+    """Class for configuring rule induction parameters"""
 
     _MEASURES_PARAMETERS: list[str] = [
-        'induction_measure', 'pruning_measure', 'voting_measure',
+        "induction_measure",
+        "pruning_measure",
+        "voting_measure",
     ]
-    _USER_DEFINED_MEASURE_VALUE: str = 'UserDefined'
+    _USER_DEFINED_MEASURE_VALUE: str = "UserDefined"
 
     def __init__(self, rule_generator):
         self.rule_generator = rule_generator
@@ -72,18 +73,21 @@ def _configure_expert_parameter(self, param_name: str, param_value: Any):
         if isinstance(param_value, list) and len(param_value) > 0:
             if isinstance(param_value[0], str):
                 for index, rule in enumerate(param_value):
-                    rule_name = f'{param_name[:-1]}-{index}'
+                    rule_name = f"{param_name[:-1]}-{index}"
                     rules_list.add(
-                        JObject([rule_name, rule], JArray('java.lang.String', 1)))
+                        JObject([rule_name, rule], JArray("java.lang.String", 1))
+                    )
             elif isinstance(param_value[0], BaseRule):
                 for index, rule in enumerate(param_value):
-                    rule_name = f'{param_name[:-1]}-{index}'
+                    rule_name = f"{param_name[:-1]}-{index}"
                     rules_list.add(
-                        JObject([rule_name, str(rule)], JArray('java.lang.String', 1)))
+                        JObject([rule_name, str(rule)], JArray("java.lang.String", 1))
+                    )
             elif isinstance(param_value[0], tuple):
                 for index, rule in enumerate(param_value):
                     rules_list.add(
-                        JObject([rule[0], rule[1]], JArray('java.lang.String', 1)))
+                        JObject([rule[0], rule[1]], JArray("java.lang.String", 1))
+                    )
         self.rule_generator.setListParameter(param_name, rules_list)
 
     def _configure_simple_parameter(self, param_name: str, param_value: Any):
@@ -91,39 +95,44 @@ def _configure_simple_parameter(self, param_name: str, param_value: Any):
             if isinstance(param_value, bool):
                 param_value = (str(param_value)).lower()
             elif isinstance(param_value, tuple):
-                param_value = ' '.join(list(map(str, param_value)))
+                param_value = " ".join(list(map(str, param_value)))
             elif not isinstance(param_value, str):
                 param_value = str(param_value)
             self.rule_generator.setParameter(param_name, param_value)
 
-    def _configure_measure_parameter(self, param_name: str, param_value: Union[str, Measures]):
+    def _configure_measure_parameter(
+        self, param_name: str, param_value: Union[str, Measures]
+    ):
         if param_value is not None:
             if isinstance(param_value, Measures):
-                self.rule_generator.setParameter(
-                    param_name, param_value.value)
+                self.rule_generator.setParameter(param_name, param_value.value)
             if isinstance(param_value, Callable):
-                self._configure_user_defined_measure_parameter(
-                    param_name, param_value)
+                self._configure_user_defined_measure_parameter(param_name, param_value)
 
-    def _configure_user_defined_measure_parameter(self, param_name: str, param_value: Any):
+    def _configure_user_defined_measure_parameter(
+        self, param_name: str, param_value: Any
+    ):
         from rulekit.params import _user_defined_measure_factory
+
         user_defined_measure = _user_defined_measure_factory(param_value)
         {
-            'induction_measure': self.rule_generator.setUserMeasureInductionObject,
-            'pruning_measure': self.rule_generator.setUserMeasurePurningObject,
-            'voting_measure': self.rule_generator.setUserMeasureVotingObject,
+            "induction_measure": self.rule_generator.setUserMeasureInductionObject,
+            "pruning_measure": self.rule_generator.setUserMeasurePurningObject,
+            "voting_measure": self.rule_generator.setUserMeasureVotingObject,
         }[param_name](user_defined_measure)
-        self.rule_generator.setParameter(
-            param_name, self._USER_DEFINED_MEASURE_VALUE)
+        self.rule_generator.setParameter(param_name, self._USER_DEFINED_MEASURE_VALUE)
 
     def _configure_rule_generator(self, **kwargs: dict[str, Any]):
-        if any([kwargs.get(param_name) == Measures.LogRank for param_name in self._MEASURES_PARAMETERS]):
-            self.LogRank = JClass('adaa.analytics.rules.logic.quality.LogRank')
+        if any(
+            [
+                kwargs.get(param_name) == Measures.LogRank
+                for param_name in self._MEASURES_PARAMETERS
+            ]
+        ):
+            self.LogRank = JClass("adaa.analytics.rules.logic.quality.LogRank")
         for measure_param_name in self._MEASURES_PARAMETERS:
-            measure_param_value: Measures = kwargs.pop(
-                measure_param_name, None)
-            self._configure_measure_parameter(
-                measure_param_name, measure_param_value)
+            measure_param_value: Measures = kwargs.pop(measure_param_name, None)
+            self._configure_measure_parameter(measure_param_name, measure_param_value)
         for param_name, param_value in kwargs.items():
             self._configure_simple_parameter(param_name, param_value)
 
@@ -139,12 +148,21 @@ def _validate_rule_generator_parameters(self, **python_parameters: dict[str, Any
             ValueError: If failed to retrieve RuleGenerator parameters JSON
             RuleKitMisconfigurationException: If Java and Python parameters do not match
         """
-        def are_params_equal(java_params: dict[str, Any], python_params: dict[str, Any]):
+
+        def are_params_equal(
+            java_params: dict[str, Any], python_params: dict[str, Any]
+        ):
             if java_params.keys() != python_params.keys():
                 return False
             for key in java_params.keys():
-                skip_check: bool = isinstance(python_params[key], Callable)
-                if java_params[key] != python_params[key] and not skip_check:
+                java_value = java_params.get(key)
+                python_value = python_params.get(key)
+                skip_check: bool = isinstance(python_value, Callable)
+                if java_value == 'None':
+                    java_value = None
+                if java_value is None and python_value is None:
+                    continue
+                if java_value != python_value and not skip_check:
                     return False
             return True
 
@@ -158,45 +176,44 @@ def are_params_equal(java_params: dict[str, Any], python_params: dict[str, Any])
                 python_parameters[param_name] = str(param_value).lower()
             # normalize tuples to strings for comparison
             elif isinstance(param_value, tuple):
-                value = ' '.join(list(map(str, param_value)))
+                value = " ".join(list(map(str, param_value)))
                 python_parameters[param_name] = value
             # convert numbers to strings for comparison
             elif isinstance(param_value, (int, float)):
                 python_parameters[param_name] = str(param_value)
-        java_params_json: str = str(
-            self.rule_generator.getParamsAsJsonString())
+        java_params_json: str = str(self.rule_generator.getParamsAsJsonString())
         try:
             java_params: dict[str, Any] = json.loads(java_params_json)
         except json.JSONDecodeError as error:
             raise ValueError(
-                'Failed to decode RuleGenerator parameters JSON') from error
+                "Failed to decode RuleGenerator parameters JSON"
+            ) from error
         # select only values that are used by Python wrapper
         java_params = {
-            param_name: str(java_params[param_name])
+            param_name: str(java_params.get(param_name))
             for param_name in python_parameters.keys()
         }
         if not are_params_equal(java_params, python_parameters):
             raise RuleKitMisconfigurationException(
-                java_parameters=java_params,
-                python_parameters=python_parameters
+                java_parameters=java_params, python_parameters=python_parameters
             )
 
     def _configure_java_logging(self):
-        logger_config: Optional[_RuleKitJavaLoggerConfig] = RuleKit.get_java_logger_config(
+        logger_config: Optional[_RuleKitJavaLoggerConfig] = (
+            RuleKit.get_java_logger_config()
         )
         if logger_config is None:
             return
         self.rule_generator.configureLogger(
-            logger_config.log_file_path,
-            logger_config.verbosity_level
+            logger_config.log_file_path, logger_config.verbosity_level
         )
 
 
-class ExampleSetFactory():
-    """ Creates ExampleSet object from given data"""
+class ExampleSetFactory:
+    """Creates ExampleSet object from given data"""
 
-    DEFAULT_LABEL_ATTRIBUTE_NAME: str = 'label'
-    AUTOMATIC_ATTRIBUTES_NAMES_PREFIX: str = 'att'
+    DEFAULT_LABEL_ATTRIBUTE_NAME: str = "label"
+    AUTOMATIC_ATTRIBUTES_NAMES_PREFIX: str = "att"
 
     def __init__(self, problem_type: ProblemType) -> None:
         self._problem_type: ProblemType = problem_type
@@ -219,9 +236,10 @@ def make(
         Args:
             X (Union[pd.DataFrame, np.ndarray]): Data
             y (Union[pd.Series, np.ndarray], optional): Labels. Defaults to None.
-            survival_time_attribute (str, optional): Name of survival time attribute.
-             Defaults to None.
-            contrast_attribute (str, optional): Name of contrast attribute. Defaults to None.
+                survival_time_attribute (str, optional): Name of survival time
+                attribute. Defaults to None.
+            contrast_attribute (str, optional): Name of contrast attribute.
+                Defaults to None.
 
         Returns:
             JObject: ExampleSet object
@@ -235,10 +253,7 @@ def make(
         self._validate_y()
         return self._create_example_set()
 
-    def _sanitize_y(
-        self,
-        y: Union[pd.Series, np.ndarray, list]
-    ):
+    def _sanitize_y(self, y: Union[pd.Series, np.ndarray, list]):
         if y is None:
             return
         elif isinstance(y, pd.Series):
@@ -255,8 +270,9 @@ def _sanitize_y(
             self._y = y
         else:
             raise ValueError(
-                f'Invalid y type: {str(type(y))}. ' +
-                'Supported types are: 1 dimensional numpy array or pandas Series object.'
+                f"Invalid y type: {str(type(y))}. "
+                "Supported types are: 1 dimensional numpy array or pandas "
+                "Series object."
             )
 
     def _sanitize_X(
@@ -270,28 +286,29 @@ def _sanitize_X(
             self._X = X.to_numpy()
         elif isinstance(X, np.ndarray):
             self._attributes_names = [
-                f'{self.AUTOMATIC_ATTRIBUTES_NAMES_PREFIX}{index + 1}'
+                f"{self.AUTOMATIC_ATTRIBUTES_NAMES_PREFIX}{index + 1}"
                 for index in range(X.shape[1])
             ]
             self._X = X
         else:
             raise ValueError(
-                f'Invalid X type: {str(type(X))}. ' +
-                'Supported types are: 2 dimensional numpy array or pandas DataFrame object.'
+                f"Invalid X type: {str(type(X))}. "
+                "Supported types are: 2 dimensional numpy array or pandas DataFrame "
+                "object."
             )
 
     def _validate_X(self):
         if len(self._X.shape) != 2:
             raise ValueError(
-                'X must be a 2 dimensional numpy array or pandas DataFrame object. ' +
-                f'Its current shape is: {str(self._X.shape)}'
+                "X must be a 2 dimensional numpy array or pandas DataFrame object. "
+                + f"Its current shape is: {str(self._X.shape)}"
             )
 
     def _validate_y(self):
         if self._y is not None and len(self._y.shape) != 1:
             raise ValueError(
-                'y must be a 1 dimensional numpy array or pandas DataFrame object. ' +
-                f'Its current shape is: {str(self._y.shape)}'
+                "y must be a 1 dimensional numpy array or pandas DataFrame object. "
+                + f"Its current shape is: {str(self._y.shape)}"
             )
 
     def _create_example_set(self) -> JObject:
@@ -301,16 +318,18 @@ def _create_example_set(self) -> JObject:
             self._attributes_names,
             self._label_name,
             self._survival_time_attribute,
-            self._contrast_attribute
+            self._contrast_attribute,
         ]
         DataTable = JClass(  # pylint: disable=invalid-name
-            'adaa.analytics.rules.data.DataTable'
+            "adaa.analytics.rules.data.DataTable"
         )
         try:
             table = DataTable(*args)
-            if (self._y is not None):
+            if self._y is not None:
                 ExampleSetFactory = JClass(
-                    'adaa.analytics.rules.logic.representation.exampleset.ExampleSetFactory')
+                    'adaa.analytics.rules.logic.representation.'
+                    'exampleset.ExampleSetFactory'
+                )
                 factory = ExampleSetFactory(2)
                 example_set = factory.create(table)
                 return example_set
@@ -318,13 +337,16 @@ def _create_example_set(self) -> JObject:
                 return table
         except Exception as error:
             from rulekit.exceptions import RuleKitJavaException
+
             RuleKitJavaException(error).print_java_stack_trace()
             raise error
 
     def _wrap_training_example_set(self, example_set: JObject) -> JObject:
-        # training dataset must be wrapped in additional classes for rule induction to work properly
+        # training dataset must be wrapped in additional classes for rule induction
+        # to work properly
         ExampleSetFactory = JClass(
-            'adaa.analytics.rules.logic.representation.exampleset.ExampleSetFactory')
+            "adaa.analytics.rules.logic.representation.exampleset.ExampleSetFactory"
+        )
         factory: JObject = ExampleSetFactory(self._problem_type.value)
         return factory.create(example_set)
 
@@ -333,22 +355,18 @@ def _prepare_data(self) -> JObject:
             data = self._X
         else:
             data = np.hstack((self._X.astype(object), self._y.reshape(-1, 1)))
-        java_data = JObject(data, JArray('java.lang.Object', 2))
+        java_data = JObject(data, JArray("java.lang.Object", 2))
         return java_data
 
 
 class PredictionResultMapper:
-    """Maps prediction results to numpy array
-    """
+    """Maps prediction results to numpy array"""
 
-    PREDICTION_COLUMN_ROLE: str = 'prediction'
-    CONFIDENCE_COLUMN_ROLE: str = 'confidence'
+    PREDICTION_COLUMN_ROLE: str = "prediction"
+    CONFIDENCE_COLUMN_ROLE: str = "confidence"
 
     @staticmethod
-    def map_confidence(
-        predicted_example_set,
-        label_unique_values: list
-    ) -> np.ndarray:
+    def map_confidence(predicted_example_set, label_unique_values: list) -> np.ndarray:
         """Maps models confidence values to numpy array
 
         Args:
@@ -362,12 +380,11 @@ def map_confidence(
         for label_value in label_unique_values:
             confidence_col: JObject = PredictionResultMapper._get_column_by_role(
                 predicted_example_set,
-                f'{PredictionResultMapper.CONFIDENCE_COLUMN_ROLE}_{label_value}'
+                f"{PredictionResultMapper.CONFIDENCE_COLUMN_ROLE}_{label_value}",
             )
 
             confidence_values = [
-                float(predicted_example_set.getExample(
-                    i).getValue(confidence_col))
+                float(predicted_example_set.getExample(i).getValue(confidence_col))
                 for i in range(predicted_example_set.size())
             ]
 
@@ -385,8 +402,7 @@ def map(predicted_example_set: JObject) -> np.ndarray:
             np.ndarray: numpy array containing predictions
         """
         prediction_col: JObject = PredictionResultMapper._get_column_by_role(
-            predicted_example_set,
-            PredictionResultMapper.PREDICTION_COLUMN_ROLE
+            predicted_example_set, PredictionResultMapper.PREDICTION_COLUMN_ROLE
         )
         if prediction_col.isNominal():
             return PredictionResultMapper.map_to_nominal(predicted_example_set)
@@ -403,18 +419,21 @@ def map_to_nominal(predicted_example_set: JObject) -> np.ndarray:
             np.ndarray: numpy array containing predictions
         """
         prediction_col: JObject = PredictionResultMapper._get_column_by_role(
-            predicted_example_set,
-            PredictionResultMapper.PREDICTION_COLUMN_ROLE
+            predicted_example_set, PredictionResultMapper.PREDICTION_COLUMN_ROLE
         )
 
-        return np.array([
-            str(predicted_example_set.getExample(
-                i).getNominalValue(prediction_col))
-            for i in range(predicted_example_set.size())
-        ], dtype=str)
+        return np.array(
+            [
+                str(predicted_example_set.getExample(i).getNominalValue(prediction_col))
+                for i in range(predicted_example_set.size())
+            ],
+            dtype=str,
+        )
 
     @staticmethod
-    def map_to_numerical(predicted_example_set: JObject, remap: bool = True) -> np.ndarray:
+    def map_to_numerical(
+        predicted_example_set: JObject, remap: bool = True
+    ) -> np.ndarray:
         """Maps models predictions to numerical numpy array
 
         Args:
@@ -424,31 +443,29 @@ def map_to_numerical(predicted_example_set: JObject, remap: bool = True) -> np.n
             np.ndarray: numpy array containing predictions
         """
         prediction_col: JObject = PredictionResultMapper._get_column_by_role(
-            predicted_example_set,
-            PredictionResultMapper.PREDICTION_COLUMN_ROLE
+            predicted_example_set, PredictionResultMapper.PREDICTION_COLUMN_ROLE
         )
         label_mapping = predicted_example_set.getAttributes().getLabel().getMapping()
         if remap:
             predictions: list = [
-                label_mapping.mapIndex(int(
-                    predicted_example_set.getExample(
-                        i).getValue(prediction_col)
-                ))
+                label_mapping.mapIndex(
+                    int(predicted_example_set.getExample(i).getValue(prediction_col))
+                )
                 for i in range(predicted_example_set.size())
             ]
             predictions = list(map(lambda x: float(str(x)), predictions))
             return np.array(predictions)
-        return np.array([
-            float(
-                predicted_example_set.getExample(i).getValue(prediction_col)
-            )
-            for i in range(predicted_example_set.size())
-        ])
+        return np.array(
+            [
+                float(predicted_example_set.getExample(i).getValue(prediction_col))
+                for i in range(predicted_example_set.size())
+            ]
+        )
 
     @staticmethod
     def map_survival(predicted_example_set) -> np.ndarray:
-        """Maps survival models predictions to numpy array. Used as alternative to `map` method
-        used in survival analysis
+        """Maps survival models predictions to numpy array. Used as alternative to
+        `map` method used in survival analysis
 
         Args:
             predicted_example_set (_type_): ExampleSet with predictions
@@ -463,17 +480,18 @@ def map_survival(predicted_example_set) -> np.ndarray:
             example = example_set_iterator.next()
             example_estimator = str(example.getValueAsString(attribute))
             example_estimator = example_estimator.split(" ")
-            _, example_estimator[0] = example_estimator[0].split(
-                ":")
+            _, example_estimator[0] = example_estimator[0].split(":")
             times = [
                 float(example_estimator[i])
-                for i in range(len(example_estimator) - 1) if i % 2 == 0
+                for i in range(len(example_estimator) - 1)
+                if i % 2 == 0
             ]
             probabilities = [
                 float(example_estimator[i])
-                for i in range(len(example_estimator)) if i % 2 != 0
+                for i in range(len(example_estimator))
+                if i % 2 != 0
             ]
-            estimator = {'times': times, 'probabilities': probabilities}
+            estimator = {"times": times, "probabilities": probabilities}
             estimators.append(estimator)
         return np.array(estimators)
 
@@ -483,8 +501,7 @@ def _get_column_by_role(predicted_example_set: JObject, role: str) -> JObject:
 
 
 class ModelSerializer:
-    """Class for serializing models
-    """
+    """Class for serializing models"""
 
     @staticmethod
     def serialize(real_model: object) -> bytes:
diff --git a/rulekit/_operator.py b/rulekit/_operator.py
index 7a13439..8fe6e43 100644
--- a/rulekit/_operator.py
+++ b/rulekit/_operator.py
@@ -28,8 +28,7 @@
 
 
 class BaseOperator(ABC):
-    """Base class for rule induction operator
-    """
+    """Base class for rule induction operator"""
 
     __params_class__: type = None
 
@@ -48,17 +47,17 @@ def _map_result(self, predicted_example_set) -> np.ndarray:
         return PredictionResultMapper.map(predicted_example_set)
 
     def _validate_contrast_attribute(
-        self,
-        example_set,
-        contrast_attribute: Optional[str]
+        self, example_set, contrast_attribute: Optional[str]
     ) -> None:
         if contrast_attribute is None:
             return
-        contrast_attribute_instance = example_set.getAttributes().get(contrast_attribute)
+        contrast_attribute_instance = example_set.getAttributes().get(
+            contrast_attribute
+        )
         if contrast_attribute_instance.isNumerical():
             raise ValueError(
-                'Contrast set attributes must be a nominal attribute while ' +
-                f'"{contrast_attribute}" is a numerical one.'
+                "Contrast set attributes must be a nominal attribute while "
+                + f'"{contrast_attribute}" is a numerical one.'
             )
 
     def fit(  # pylint: disable=missing-function-docstring
@@ -72,7 +71,7 @@ def fit(  # pylint: disable=missing-function-docstring
             values,
             labels,
             survival_time_attribute=survival_time_attribute,
-            contrast_attribute=contrast_attribute
+            contrast_attribute=contrast_attribute,
         )
         self._validate_contrast_attribute(example_set, contrast_attribute)
 
@@ -80,14 +79,19 @@ def fit(  # pylint: disable=missing-function-docstring
         self.model = RuleSet[BaseRule](java_model)
         return self.model
 
-    def predict(self, values: Data) -> np.ndarray:  # pylint: disable=missing-function-docstring
+    def predict(
+        self, values: Data
+    ) -> np.ndarray:  # pylint: disable=missing-function-docstring
         if self.model is None:
-            raise ValueError(
-                '"fit" method must be called before calling this method')
+            raise ValueError('"fit" method must be called before calling this method')
         example_set = ExampleSetFactory(self._get_problem_type()).make(values)
-        return self.model._java_object.apply(example_set)  # pylint: disable=protected-access
+        return self.model._java_object.apply(  # pylint: disable=protected-access
+            example_set
+        )
 
-    def get_params(self, deep: bool = True) -> dict[str, Any]:  # pylint: disable=unused-argument
+    def get_params(
+        self, deep: bool = True  # pylint: disable=unused-argument
+    ) -> dict[str, Any]:
         """
         Parameters
         ----------
@@ -105,11 +109,11 @@ def set_params(self, **kwargs) -> object:
         """Set models hyperparameters. Parameters are the same as in constructor."""
         self._rule_generator = self._get_rule_generator()
         params: BaseModel = self.__params_class__(  # pylint: disable=not-callable
-            **kwargs)
+            **kwargs
+        )
         params_dict: dict = params.model_dump()
         self._params = {
-            key: value for key, value in params_dict.items()
-            if value is not None
+            key: value for key, value in params_dict.items() if value is not None
         }
         configurator = RuleGeneratorConfigurator(self._rule_generator)
         self._rule_generator = configurator.configure(**params_dict)
@@ -122,9 +126,7 @@ def get_metadata_routing(self) -> None:
         Raises:
             NotImplementedError: _description_
         """
-        raise NotImplementedError(
-            'Scikit-learn metadata routing is not supported yet.'
-        )
+        raise NotImplementedError("Scikit-learn metadata routing is not supported yet.")
 
     def get_coverage_matrix(self, values: Data) -> np.ndarray:
         """Calculates coverage matrix for ruleset.
@@ -137,13 +139,12 @@ def get_coverage_matrix(self, values: Data) -> np.ndarray:
         Returns
         -------
         coverage_matrix : np.ndarray
-            Each row of the matrix represent single example from dataset and every column represent
-            on rule from rule set. Value 1 in the matrix cell means that rule covered certain
-             example, value 0 means that it doesn't.
+            Each row of the matrix represent single example from dataset and every
+            column represent on rule from rule set. Value 1 in the matrix cell means
+            that rule covered certain example, value 0 means that it doesn't.
         """
         if self.model is None:
-            raise ValueError(
-                '"fit" method must be called before calling this method')
+            raise ValueError('"fit" method must be called before calling this method')
         example_set = ExampleSetFactory(self._get_problem_type()).make(values)
         covering_info = self.model.covering(example_set)
         if isinstance(values, (pd.Series, pd.DataFrame)):
@@ -151,8 +152,7 @@ def get_coverage_matrix(self, values: Data) -> np.ndarray:
         result = []
         for i in range(len(values)):
             row_result: list[int] = [
-                0 if item is None or not i in item else 1
-                for item in covering_info
+                0 if item is None or i not in item else 1 for item in covering_info
             ]
             result.append(np.array(row_result))
         return np.array(result)
@@ -180,16 +180,13 @@ def add_event_listener(self, listener: RuleInductionProgressListener):
 
     def __getstate__(self) -> dict:
         state = self.__dict__.copy()
-        state.pop('_rule_generator')
-        return {
-            '_params': self._params,
-            'model': ModelSerializer.serialize(self.model)
-        }
+        state.pop("_rule_generator")
+        return {"_params": self._params, "model": ModelSerializer.serialize(self.model)}
 
     def __setstate__(self, state: dict):
-        self.model = ModelSerializer.deserialize(state['model'])
+        self.model = ModelSerializer.deserialize(state["model"])
         self._rule_generator = get_rule_generator()
-        self.set_params(**state['_params'])
+        self.set_params(**state["_params"])
 
     def _get_rule_generator(self) -> RuleGeneratorConfigurator:
         return get_rule_generator()
@@ -200,8 +197,7 @@ def _get_problem_type(self) -> ProblemType:
 
 
 class ExpertKnowledgeOperator(BaseOperator, ABC):
-    """Base class for expert rule induction operator
-    """
+    """Base class for expert rule induction operator"""
 
     def fit(  # pylint: disable=missing-function-docstring,too-many-arguments
         self,
@@ -209,16 +205,15 @@ def fit(  # pylint: disable=missing-function-docstring,too-many-arguments
         labels: Data,
         survival_time_attribute: str = None,
         contrast_attribute: str = None,
-
         expert_rules: list[Union[str, BaseRule]] = None,
         expert_preferred_conditions: list[Union[str, BaseRule]] = None,
-        expert_forbidden_conditions: list[Union[str, BaseRule]] = None
+        expert_forbidden_conditions: list[Union[str, BaseRule]] = None,
     ) -> ExpertKnowledgeOperator:
         example_set = ExampleSetFactory(self._get_problem_type()).make(
             values,
             labels,
             survival_time_attribute=survival_time_attribute,
-            contrast_attribute=contrast_attribute
+            contrast_attribute=contrast_attribute,
         )
         self._validate_contrast_attribute(example_set, contrast_attribute)
         self._configure_expert_parameters(
@@ -237,7 +232,7 @@ def _configure_expert_parameters(
         self,
         expert_rules: Optional[list[Union[str, BaseRule]]] = None,
         expert_preferred_conditions: Optional[list[Union[str, BaseRule]]] = None,
-        expert_forbidden_conditions: Optional[list[Union[str, BaseRule]]] = None
+        expert_forbidden_conditions: Optional[list[Union[str, BaseRule]]] = None,
     ) -> None:
         if expert_rules is None:
             expert_rules = []
@@ -248,23 +243,22 @@ def _configure_expert_parameters(
 
         configurator = RuleGeneratorConfigurator(self._rule_generator)
         configurator._configure_simple_parameter(  # pylint: disable=protected-access
-            'use_expert', True)
+            "use_expert", True
+        )
         configurator._configure_expert_parameter(  # pylint: disable=protected-access
-            'expert_preferred_conditions',
-            self._sanitize_expert_parameter(expert_preferred_conditions)
+            "expert_preferred_conditions",
+            self._sanitize_expert_parameter(expert_preferred_conditions),
         )
         configurator._configure_expert_parameter(  # pylint: disable=protected-access
-            'expert_forbidden_conditions',
-            self._sanitize_expert_parameter(expert_forbidden_conditions)
+            "expert_forbidden_conditions",
+            self._sanitize_expert_parameter(expert_forbidden_conditions),
         )
         configurator._configure_expert_parameter(  # pylint: disable=protected-access
-            'expert_rules',
-            self._sanitize_expert_parameter(expert_rules)
+            "expert_rules", self._sanitize_expert_parameter(expert_rules)
         )
 
     def _sanitize_expert_parameter(
-        self,
-        expert_parameter: Optional[list[tuple[str, str]]]
+        self, expert_parameter: Optional[list[tuple[str, str]]]
     ) -> list[tuple[str, str]]:
         if expert_parameter is None:
             return None
diff --git a/rulekit/classification.py b/rulekit/classification.py
index 65744fb..b001d55 100644
--- a/rulekit/classification.py
+++ b/rulekit/classification.py
@@ -35,14 +35,15 @@ class ClassificationPredictionMetrics(TypedDict):
         * rules_per_example (float): Average number of rules per example.
         * voting_conflicts (_type_): Number of voting conflicts.
     """
+
     rules_per_example: float
     voting_conflicts: float
 
 
 class _ClassificationParams(ModelsParams):
-    control_apriori_precision: bool = DEFAULT_PARAMS_VALUE['control_apriori_precision']
-    approximate_induction: bool = DEFAULT_PARAMS_VALUE['approximate_induction']
-    approximate_bins_count: int = DEFAULT_PARAMS_VALUE['approximate_bins_count']
+    control_apriori_precision: bool = DEFAULT_PARAMS_VALUE["control_apriori_precision"]
+    approximate_induction: bool = DEFAULT_PARAMS_VALUE["approximate_induction"]
+    approximate_bins_count: int = DEFAULT_PARAMS_VALUE["approximate_bins_count"]
 
 
 class _ClassificationExpertParams(_ClassificationParams, ExpertModelParams):
@@ -53,28 +54,36 @@ class BaseClassifier:
     """:meta private:"""
 
     def __init__(self):
-        self._ClassificationRulesPerformance: JClass = None  # pylint: disable=invalid-name
-        self._NegativeVotingConflictsPerformance: JClass = None  # pylint: disable=invalid-name
+        self._ClassificationRulesPerformance: JClass = (
+            None  # pylint: disable=invalid-name
+        )
+        self._NegativeVotingConflictsPerformance: JClass = (
+            None  # pylint: disable=invalid-name
+        )
         self._init_classification_rule_performance_classes()
 
     class MetricTypes(Enum):
         """:meta private:"""
+
         RulesPerExample = 1  # pylint: disable=invalid-name
         VotingConflicts = 2  # pylint: disable=invalid-name
         NegativeVotingConflicts = 3  # pylint: disable=invalid-name
 
     def _init_classification_rule_performance_classes(self):
         self._ClassificationRulesPerformance = JClass(  # pylint: disable=invalid-name
-            'adaa.analytics.rules.logic.performance.ClassificationRulesPerformance'
+            "adaa.analytics.rules.logic.performance.ClassificationRulesPerformance"
         )
 
-    def _calculate_metric(self, example_set: JObject, metric_type: MetricTypes) -> float:
-        metric: JObject = self._ClassificationRulesPerformance(
-            metric_type.value)
+    def _calculate_metric(
+        self, example_set: JObject, metric_type: MetricTypes
+    ) -> float:
+        metric: JObject = self._ClassificationRulesPerformance(metric_type.value)
         metric_value = float(metric.countExample(example_set).getValue())
         return metric_value
 
-    def _calculate_prediction_metrics(self, example_set) -> ClassificationPredictionMetrics:
+    def _calculate_prediction_metrics(
+        self, example_set
+    ) -> ClassificationPredictionMetrics:
         return ClassificationPredictionMetrics(
             rules_per_example=self._calculate_metric(
                 example_set, BaseClassifier.MetricTypes.RulesPerExample
@@ -92,29 +101,32 @@ class RuleClassifier(BaseOperator, BaseClassifier):
 
     def __init__(  # pylint: disable=too-many-arguments,too-many-locals
         self,
-        minsupp_new: float = DEFAULT_PARAMS_VALUE['minsupp_new'],
-        induction_measure: Measures = DEFAULT_PARAMS_VALUE['induction_measure'],
-        pruning_measure: Union[Measures,
-                               str] = DEFAULT_PARAMS_VALUE['pruning_measure'],
-        voting_measure: Measures = DEFAULT_PARAMS_VALUE['voting_measure'],
-        max_growing: float = DEFAULT_PARAMS_VALUE['max_growing'],
-        enable_pruning: bool = DEFAULT_PARAMS_VALUE['enable_pruning'],
-        ignore_missing: bool = DEFAULT_PARAMS_VALUE['ignore_missing'],
-        max_uncovered_fraction: float = DEFAULT_PARAMS_VALUE['max_uncovered_fraction'],
-        select_best_candidate: bool = DEFAULT_PARAMS_VALUE['select_best_candidate'],
-        complementary_conditions: bool = DEFAULT_PARAMS_VALUE['complementary_conditions'],
-        control_apriori_precision: bool = DEFAULT_PARAMS_VALUE['control_apriori_precision'],
-        max_rule_count: int = DEFAULT_PARAMS_VALUE['max_rule_count'],
-        approximate_induction: bool = DEFAULT_PARAMS_VALUE['approximate_induction'],
-        approximate_bins_count: int = DEFAULT_PARAMS_VALUE['approximate_bins_count'],
+        minsupp_new: float = DEFAULT_PARAMS_VALUE["minsupp_new"],
+        induction_measure: Measures = DEFAULT_PARAMS_VALUE["induction_measure"],
+        pruning_measure: Union[Measures, str] = DEFAULT_PARAMS_VALUE["pruning_measure"],
+        voting_measure: Measures = DEFAULT_PARAMS_VALUE["voting_measure"],
+        max_growing: float = DEFAULT_PARAMS_VALUE["max_growing"],
+        enable_pruning: bool = DEFAULT_PARAMS_VALUE["enable_pruning"],
+        ignore_missing: bool = DEFAULT_PARAMS_VALUE["ignore_missing"],
+        max_uncovered_fraction: float = DEFAULT_PARAMS_VALUE["max_uncovered_fraction"],
+        select_best_candidate: bool = DEFAULT_PARAMS_VALUE["select_best_candidate"],
+        complementary_conditions: bool = DEFAULT_PARAMS_VALUE[
+            "complementary_conditions"
+        ],
+        control_apriori_precision: bool = DEFAULT_PARAMS_VALUE[
+            "control_apriori_precision"
+        ],
+        max_rule_count: int = DEFAULT_PARAMS_VALUE["max_rule_count"],
+        approximate_induction: bool = DEFAULT_PARAMS_VALUE["approximate_induction"],
+        approximate_bins_count: int = DEFAULT_PARAMS_VALUE["approximate_bins_count"],
     ):
         """
         Parameters
         ----------
         minsupp_new : float = 5.0
-            a minimum number (or fraction, if value < 1.0) of previously uncovered examples
-             to be covered by a new rule (positive examples for classification problems);
-             default: 5,
+            a minimum number (or fraction, if value < 1.0) of previously uncovered
+            examples to be covered by a new rule (positive examples for classification
+            problems); default: 5,
         induction_measure : :class:`rulekit.params.Measures` = :class:`rulekit.params.\
             Measures.Correlation`
             measure used during induction; default measure is correlation
@@ -126,36 +138,37 @@ def __init__(  # pylint: disable=too-many-arguments,too-many-locals
             :class:`rulekit.params.Measures.Correlation`
             measure used during voting; default measure is correlation
         max_growing : int = 0.0
-            non-negative integer representing maximum number of conditions which can be added
-            to the rule in the growing phase (use this parameter for large datasets if execution
-            time is prohibitive); 0 indicates no limit; default: 0,
+            non-negative integer representing maximum number of conditions which can be
+            added to the rule in the growing phase (use this parameter for large
+            datasets if execution time is prohibitive); 0 indicates no limit; default: 0
         enable_pruning : bool = True
             enable or disable pruning, default is True.
         ignore_missing : bool = False
-            boolean telling whether missing values should be ignored (by default, a missing value
-            of given attribute is always cconsidered as not fulfilling the condition build upon
-             that attribute); default: False.
+            boolean telling whether missing values should be ignored (by default, a
+            missing valueof given attribute is always cconsidered as not fulfilling the
+            condition build upon that attribute); default: False.
         max_uncovered_fraction : float = 0.0
-            Floating-point number from [0,1] interval representing maximum fraction of examples
-            that may remain uncovered by the rule set, default: 0.0.
+            Floating-point number from [0,1] interval representing maximum fraction of
+            examples that may remain uncovered by the rule set, default: 0.0.
         select_best_candidate : bool = False
-            Flag determining if best candidate should be selected from growing phase; default:
-            False.
+            Flag determining if best candidate should be selected from growing phase;
+            default: False.
         complementary_conditions : bool = False
-            If enabled, complementary conditions in the form a = !{value} for nominal attributes
-            are supported.
+            If enabled, complementary conditions in the form a = !{value} for nominal
+            attributes are supported.
         control_apriori_precision : bool = True
-            When inducing classification rules, verify if candidate precision is higher than
-             apriori precision of the investigated class.
+            When inducing classification rules, verify if candidate precision is higher
+            than apriori precision of the investigated class.
         max_rule_count : int = 0
-            Maximum number of rules to be generated (for classification data sets it applies
-             to a single class); 0 indicates no limit.
+            Maximum number of rules to be generated (for classification data sets it
+            applies to a single class); 0 indicates no limit.
         approximate_induction: bool = False
-            Use an approximate induction heuristic which does not check all possible splits;
-            note: this is an experimental feature and currently works only for classification
-            data sets, results may change in future;
+            Use an approximate induction heuristic which does not check all possible
+            splits; note: this is an experimental feature and currently works only for
+            classification data sets, results may change in future;
         approximate_bins_count: int = 100
-            maximum number of bins for an attribute evaluated in the approximate induction.
+            maximum number of bins for an attribute evaluated in the approximate
+            induction.
         """
         BaseOperator.__init__(
             self,
@@ -182,11 +195,9 @@ def __init__(  # pylint: disable=too-many-arguments,too-many-locals
     def _map_result(self, predicted_example_set) -> np.ndarray:
         prediction: np.ndarray
         if self._remap_to_numeric:
-            prediction = PredictionResultMapper.map_to_numerical(
-                predicted_example_set)
+            prediction = PredictionResultMapper.map_to_numerical(predicted_example_set)
         else:
-            prediction = PredictionResultMapper.map_to_nominal(
-                predicted_example_set)
+            prediction = PredictionResultMapper.map_to_nominal(predicted_example_set)
         return prediction
 
     def _map_confidence(self, predicted_example_set) -> np.ndarray:
@@ -199,21 +210,23 @@ def _get_unique_label_values(self, labels: Data):
         for label_value in labels:
             tmp[label_value] = None
         self.label_unique_values = list(tmp.keys())
-        if len(self.label_unique_values) > 0 and isinstance(self.label_unique_values[0], bytes):
-            self.label_unique_values = [item.decode(
-                'utf-8') for item in self.label_unique_values]
+        if len(self.label_unique_values) > 0 and isinstance(
+            self.label_unique_values[0], bytes
+        ):
+            self.label_unique_values = [
+                item.decode("utf-8") for item in self.label_unique_values
+            ]
 
     def _prepare_labels(self, labels: Data) -> Data:
         if isinstance(labels, (pd.DataFrame, pd.Series)):
-            if labels.dtypes.name == 'bool':
+            if labels.dtypes.name == "bool":
                 return labels.astype(str)
             if isinstance(labels.iloc[0], Number):
                 self._remap_to_numeric = True
                 return labels.astype(str)
         else:
-            if (
-                isinstance(labels[0], bool) or
-                (isinstance(labels, np.ndarray) and labels.dtype.name == 'bool')
+            if isinstance(labels[0], bool) or (
+                isinstance(labels, np.ndarray) and labels.dtype.name == "bool"
             ):
                 return np.array(list(map(str, labels)))
             if isinstance(labels[0], Number):
@@ -221,7 +234,9 @@ def _prepare_labels(self, labels: Data) -> Data:
                 return np.array(list(map(str, labels)))
         return labels
 
-    def fit(self, values: Data, labels: Data) -> RuleClassifier:  # pylint: disable=arguments-differ
+    def fit(
+        self, values: Data, labels: Data
+    ) -> RuleClassifier:  # pylint: disable=arguments-differ
         """Train model on given dataset.
 
         Parameters
@@ -240,9 +255,7 @@ def fit(self, values: Data, labels: Data) -> RuleClassifier:  # pylint: disable=
         return self
 
     def predict(
-        self,
-        values: Data,
-        return_metrics: bool = False
+        self, values: Data, return_metrics: bool = False
     ) -> Union[np.ndarray, tuple[np.ndarray, ClassificationPredictionMetrics]]:
         """Perform prediction and returns predicted labels.
 
@@ -252,30 +265,28 @@ def predict(
             attributes
 
         return_metrics: bool = False
-            Optional flag. If set to *True* method will calculate some additional model metrics.
-             Method will then return tuple instead of just predicted labels.
+            Optional flag. If set to *True* method will calculate some additional model
+            metrics. Method will then return tuple instead of just predicted labels.
 
         Returns
         -------
-        result : Union[
-            np.ndarray,
-            tuple[np.ndarray, :class:`rulekit.classification.ClassificationPredictionMetrics`]
-        ]
-        If *return_metrics* flag wasn't set it will return just prediction, otherwise a tuple
-        will be returned with first element being prediction and second one being metrics.
+        result : Union[np.ndarray, tuple[np.ndarray, :class:`rulekit.classification.\
+            ClassificationPredictionMetrics`]]
+            If *return_metrics* flag wasn't set it will return just prediction,
+            otherwise a tuple will be returned with first element being prediction and
+            second one being metrics.
         """
         result_example_set = BaseOperator.predict(self, values)
         y_pred = self._map_result(result_example_set)
         if return_metrics:
             metrics_values: dict = BaseClassifier._calculate_prediction_metrics(
-                self, result_example_set)
+                self, result_example_set
+            )
             return (y_pred, metrics_values)
         return y_pred
 
     def predict_proba(
-        self,
-        values: Data,
-        return_metrics: bool = False
+        self, values: Data, return_metrics: bool = False
     ) -> Union[np.ndarray, tuple[np.ndarray, ClassificationPredictionMetrics]]:
         """Perform prediction and returns class probabilities for each example.
 
@@ -285,24 +296,23 @@ def predict_proba(
             attributes
 
         return_metrics: bool = False
-            Optional flag. If set to *True* method will calculate some additional model metrics.
-             Method will then return tuple instead of just probabilities.
+            Optional flag. If set to *True* method will calculate some additional model
+            metrics. Method will then return tuple instead of just probabilities.
 
         Returns
         -------
-        result :
-        Union[
-            np.ndarray,
-            tuple[np.ndarray, :class:`rulekit.classification.ClassificationPredictionMetrics`]
-        ]
-        If *return_metrics* flag wasn't set it will return just probabilities matrix, otherwise
-        a tuple will be returned with first element being prediction and second one being metrics.
+        result : Union[np.ndarray, tuple[np.ndarray, :class:`rulekit.classification.\
+            ClassificationPredictionMetrics`]]
+            If *return_metrics* flag wasn't set it will return just probabilities
+            matrix, otherwise a tuple will be returned with first element being
+            prediction and second one being metrics.
         """
         result_example_set = BaseOperator.predict(self, values)
         mapped_result_example_set = self._map_confidence(result_example_set)
         if return_metrics:
             metrics_values: dict = BaseClassifier._calculate_prediction_metrics(
-                self, result_example_set)
+                self, result_example_set
+            )
             return (mapped_result_example_set, metrics_values)
         return mapped_result_example_set
 
@@ -325,16 +335,19 @@ def score(self, values: Data, labels: Data) -> float:
         return metrics.accuracy_score(labels, predicted_labels)
 
     def __getstate__(self) -> dict:
-        return {**BaseOperator.__getstate__(self), **{
-            'label_unique_values': self.label_unique_values,
-            '_remap_to_numeric': self._remap_to_numeric
-        }}
+        return {
+            **BaseOperator.__getstate__(self),
+            **{
+                "label_unique_values": self.label_unique_values,
+                "_remap_to_numeric": self._remap_to_numeric,
+            },
+        }
 
     def __setstate__(self, state: dict):
         BaseOperator.__setstate__(self, state)
         self._init_classification_rule_performance_classes()
-        self.label_unique_values = state['label_unique_values']
-        self._remap_to_numeric = state['_remap_to_numeric']
+        self.label_unique_values = state["label_unique_values"]
+        self._remap_to_numeric = state["_remap_to_numeric"]
 
     def _get_problem_type(self) -> ProblemType:
         return ProblemType.CLASSIFICATION
@@ -347,31 +360,35 @@ class ExpertRuleClassifier(ExpertKnowledgeOperator, RuleClassifier):
 
     def __init__(  # pylint: disable=too-many-arguments,too-many-locals
         self,
-        minsupp_new: float = DEFAULT_PARAMS_VALUE['minsupp_new'],
-        induction_measure: Measures = DEFAULT_PARAMS_VALUE['induction_measure'],
-        pruning_measure: Union[Measures,
-                               str] = DEFAULT_PARAMS_VALUE['pruning_measure'],
-        voting_measure: Measures = DEFAULT_PARAMS_VALUE['voting_measure'],
-        max_growing: float = DEFAULT_PARAMS_VALUE['max_growing'],
-        enable_pruning: bool = DEFAULT_PARAMS_VALUE['enable_pruning'],
-        ignore_missing: bool = DEFAULT_PARAMS_VALUE['ignore_missing'],
-        max_uncovered_fraction: float = DEFAULT_PARAMS_VALUE['max_uncovered_fraction'],
-        select_best_candidate: bool = DEFAULT_PARAMS_VALUE['select_best_candidate'],
-        complementary_conditions: bool = DEFAULT_PARAMS_VALUE['complementary_conditions'],
-        control_apriori_precision: bool = DEFAULT_PARAMS_VALUE['control_apriori_precision'],
-        max_rule_count: int = DEFAULT_PARAMS_VALUE['max_rule_count'],
-        approximate_induction: bool = DEFAULT_PARAMS_VALUE['approximate_induction'],
-        approximate_bins_count: int = DEFAULT_PARAMS_VALUE['approximate_bins_count'],
-
-        extend_using_preferred: bool = DEFAULT_PARAMS_VALUE['extend_using_preferred'],
-        extend_using_automatic: bool = DEFAULT_PARAMS_VALUE['extend_using_automatic'],
-        induce_using_preferred: bool = DEFAULT_PARAMS_VALUE['induce_using_preferred'],
-        induce_using_automatic: bool = DEFAULT_PARAMS_VALUE['induce_using_automatic'],
-        consider_other_classes: bool = DEFAULT_PARAMS_VALUE['consider_other_classes'],
+        minsupp_new: float = DEFAULT_PARAMS_VALUE["minsupp_new"],
+        induction_measure: Measures = DEFAULT_PARAMS_VALUE["induction_measure"],
+        pruning_measure: Union[Measures, str] = DEFAULT_PARAMS_VALUE["pruning_measure"],
+        voting_measure: Measures = DEFAULT_PARAMS_VALUE["voting_measure"],
+        max_growing: float = DEFAULT_PARAMS_VALUE["max_growing"],
+        enable_pruning: bool = DEFAULT_PARAMS_VALUE["enable_pruning"],
+        ignore_missing: bool = DEFAULT_PARAMS_VALUE["ignore_missing"],
+        max_uncovered_fraction: float = DEFAULT_PARAMS_VALUE["max_uncovered_fraction"],
+        select_best_candidate: bool = DEFAULT_PARAMS_VALUE["select_best_candidate"],
+        complementary_conditions: bool = DEFAULT_PARAMS_VALUE[
+            "complementary_conditions"
+        ],
+        control_apriori_precision: bool = DEFAULT_PARAMS_VALUE[
+            "control_apriori_precision"
+        ],
+        max_rule_count: int = DEFAULT_PARAMS_VALUE["max_rule_count"],
+        approximate_induction: bool = DEFAULT_PARAMS_VALUE["approximate_induction"],
+        approximate_bins_count: int = DEFAULT_PARAMS_VALUE["approximate_bins_count"],
+        extend_using_preferred: bool = DEFAULT_PARAMS_VALUE["extend_using_preferred"],
+        extend_using_automatic: bool = DEFAULT_PARAMS_VALUE["extend_using_automatic"],
+        induce_using_preferred: bool = DEFAULT_PARAMS_VALUE["induce_using_preferred"],
+        induce_using_automatic: bool = DEFAULT_PARAMS_VALUE["induce_using_automatic"],
+        consider_other_classes: bool = DEFAULT_PARAMS_VALUE["consider_other_classes"],
         preferred_conditions_per_rule: int = DEFAULT_PARAMS_VALUE[
-            'preferred_conditions_per_rule'],
+            "preferred_conditions_per_rule"
+        ],
         preferred_attributes_per_rule: int = DEFAULT_PARAMS_VALUE[
-            'preferred_attributes_per_rule'],
+            "preferred_attributes_per_rule"
+        ],
     ):
         """
         Parameters
@@ -392,52 +409,55 @@ def __init__(  # pylint: disable=too-many-arguments,too-many-locals
             :class:`rulekit.params.Measures.Correlation`
             measure used during voting; default measure is correlation
         max_growing : int = 0.0
-            non-negative integer representing maximum number of conditions which can be added to
-            the rule in the growing phase (use this parameter for large datasets if execution time
-            is prohibitive); 0 indicates no limit; default: 0,
+            non-negative integer representing maximum number of conditions which can be
+            added to the rule in the growing phase (use this parameter for large
+            datasets if execution time is prohibitive); 0 indicates no limit; default: 0
         enable_pruning : bool = True
             enable or disable pruning, default is True.
         ignore_missing : bool = False
-            boolean telling whether missing values should be ignored (by default, a missing value
-            of given attribute is always considered as not fulfilling the condition build upon
-             that attribute); default: False.
+            boolean telling whether missing values should be ignored (by default, a
+            missing value of given attribute is always considered as not fulfilling the
+            condition build upon that attribute); default: False.
         max_uncovered_fraction : float = 0.0
-            Floating-point number from [0,1] interval representing maximum fraction of examples
-            that may remain uncovered by the rule set, default: 0.0.
+            Floating-point number from [0,1] interval representing maximum fraction of
+            examples that may remain uncovered by the rule set, default: 0.0.
         select_best_candidate : bool = False
-            Flag determining if best candidate should be selected from growing phase; default:
-             False.
+            Flag determining if best candidate should be selected from growing phase;
+            default: False.
         complementary_conditions : bool = False
-            If enabled, complementary conditions in the form a = !{value} for nominal attributes
+            If enabled, complementary conditions in the form a = !{value} for nominal
+            attributes
             are supported.
         control_apriori_precision : bool = True
-            When inducing classification rules, verify if candidate precision is higher than
-             apriori precision of the investigated class.
+            When inducing classification rules, verify if candidate precision is higher
+            than apriori precision of the investigated class.
         max_rule_count : int = 0
-            Maximum number of rules to be generated (for classification data sets it applies
-             to a single class); 0 indicates no limit.
+            Maximum number of rules to be generated (for classification data sets it
+            applies to a single class); 0 indicates no limit.
         approximate_induction: bool = False
-            Use an approximate induction heuristic which does not check all possible splits;
-            note: this is an experimental feature and currently works only for classification
-            data sets, results may change in future;
+            Use an approximate induction heuristic which does not check all possible
+            splits; note: this is an experimental feature and currently works only for
+            classification data sets, results may change in future;
         approximate_bins_count: int = 100
-            maximum number of bins for an attribute evaluated in the approximate induction.
+            maximum number of bins for an attribute evaluated in the approximate
+            induction.
 
         extend_using_preferred : bool = False
-            boolean indicating whether initial rules should be extended with a use of preferred
-            conditions and attributes; default is False
+            boolean indicating whether initial rules should be extended with a use of
+            preferred conditions and attributes; default is False
         extend_using_automatic : bool = False
-            boolean indicating whether initial rules should be extended with a use of automatic
-             conditions and attributes; default is False
+            boolean indicating whether initial rules should be extended with a use of
+            automatic conditions and attributes; default is False
         induce_using_preferred : bool = False
-            boolean indicating whether new rules should be induced with a use of preferred
-             conditions and attributes; default is False
+            boolean indicating whether new rules should be induced with a use of
+            preferred conditions and attributes; default is False
         induce_using_automatic : bool = False
-            boolean indicating whether new rules should be induced with a use of automatic
-             conditions and attributes; default is False
+            boolean indicating whether new rules should be induced with a use of
+            automatic conditions and attributes; default is False
         consider_other_classes : bool = False
-            boolean indicating whether automatic induction should be performed for classes for
-              which no user's knowledge has been defined (classification only); default is False.
+            boolean indicating whether automatic induction should be performed for
+            classes for which no user's knowledge has been defined
+            (classification only); default is False.
         preferred_conditions_per_rule : int = None
             maximum number of preferred conditions per rule; default: unlimited,
         preferred_attributes_per_rule : int = None
@@ -491,10 +511,9 @@ def fit(  # pylint: disable=arguments-differ,too-many-arguments
         self,
         values: Data,
         labels: Data,
-
         expert_rules: list[Union[str, tuple[str, str]]] = None,
         expert_preferred_conditions: list[Union[str, tuple[str, str]]] = None,
-        expert_forbidden_conditions: list[Union[str, tuple[str, str]]] = None
+        expert_forbidden_conditions: list[Union[str, tuple[str, str]]] = None,
     ) -> ExpertRuleClassifier:
         """Train model on given dataset.
 
@@ -506,16 +525,19 @@ def fit(  # pylint: disable=arguments-differ,too-many-arguments
             labels
 
         expert_rules : List[Union[str, Tuple[str, str]]]
-            set of initial rules, either passed as a list of strings representing rules or as list
-            of tuples where first element is name of the rule and second one is rule string.
+            set of initial rules, either passed as a list of strings representing rules
+            or as list of tuples where first element is name of the rule and second one
+            is rule string.
         expert_preferred_conditions : List[Union[str, Tuple[str, str]]]
-            multiset of preferred conditions (used also for specifying preferred attributes by
-            using special value Any). Either passed as a list of strings representing rules or as
-            list of tuples where first element is name of the rule and second one is rule string.
+            multiset of preferred conditions (used also for specifying preferred
+            attributes by using special value Any). Either passed as a list of strings
+            representing rules or as list of tuples where first element is name of the
+            rule and second one is rule string.
         expert_forbidden_conditions : List[Union[str, Tuple[str, str]]]
-            set of forbidden conditions (used also for specifying forbidden attributes by using
-             special valye Any). Either passed as a list of strings representing rules or as list
-            of tuples where first element is name of the rule and second one is rule string.
+            set of forbidden conditions (used also for specifying forbidden attributes
+            by using special value Any). Either passed as a list of strings representing
+            rules or as list of tuples where first element is name of the rule and
+            second one is rule string.
         Returns
         -------
         self : ExpertRuleClassifier
@@ -536,24 +558,23 @@ def fit(  # pylint: disable=arguments-differ,too-many-arguments
             labels,
             expert_rules=expert_rules,
             expert_preferred_conditions=expert_preferred_conditions,
-            expert_forbidden_conditions=expert_forbidden_conditions
+            expert_forbidden_conditions=expert_forbidden_conditions,
         )
 
     def predict(
-        self,
-        values: Data,
-        return_metrics: bool = False
+        self, values: Data, return_metrics: bool = False
     ) -> Union[np.ndarray, tuple[np.ndarray, ClassificationPredictionMetrics]]:
         return RuleClassifier.predict(self, values, return_metrics)
 
     def __getstate__(self) -> dict:
-        return {**BaseOperator.__getstate__(self), **{
-            '_remap_to_numeric': self._remap_to_numeric
-        }}
+        return {
+            **BaseOperator.__getstate__(self),
+            **{"_remap_to_numeric": self._remap_to_numeric},
+        }
 
     def __setstate__(self, state: dict):
         BaseOperator.__setstate__(self, state)
-        self._remap_to_numeric = state['_remap_to_numeric']
+        self._remap_to_numeric = state["_remap_to_numeric"]
 
     def _get_problem_type(self) -> ProblemType:
         return ProblemType.CLASSIFICATION
@@ -566,46 +587,52 @@ class ContrastSetRuleClassifier(BaseOperator, BaseClassifier):
 
     def __init__(  # pylint: disable=too-many-arguments,too-many-locals
         self,
-        minsupp_all: Tuple[float, float, float,
-                           float] = DEFAULT_PARAMS_VALUE['minsupp_all'],
-        max_neg2pos: float = DEFAULT_PARAMS_VALUE['max_neg2pos'],
-        max_passes_count: int = DEFAULT_PARAMS_VALUE['max_passes_count'],
-        penalty_strength: float = DEFAULT_PARAMS_VALUE['penalty_strength'],
-        penalty_saturation: float = DEFAULT_PARAMS_VALUE['penalty_saturation'],
-
-        minsupp_new: float = DEFAULT_PARAMS_VALUE['minsupp_new'],
-        induction_measure: Measures = DEFAULT_PARAMS_VALUE['induction_measure'],
-        pruning_measure: Union[Measures,
-                               str] = DEFAULT_PARAMS_VALUE['pruning_measure'],
-        voting_measure: Measures = DEFAULT_PARAMS_VALUE['voting_measure'],
-        max_growing: float = DEFAULT_PARAMS_VALUE['max_growing'],
-        enable_pruning: bool = DEFAULT_PARAMS_VALUE['enable_pruning'],
-        ignore_missing: bool = DEFAULT_PARAMS_VALUE['ignore_missing'],
-        max_uncovered_fraction: float = DEFAULT_PARAMS_VALUE['max_uncovered_fraction'],
-        select_best_candidate: bool = DEFAULT_PARAMS_VALUE['select_best_candidate'],
-        complementary_conditions: bool = DEFAULT_PARAMS_VALUE['complementary_conditions'],
-        control_apriori_precision: bool = DEFAULT_PARAMS_VALUE['control_apriori_precision'],
-        max_rule_count: int = DEFAULT_PARAMS_VALUE['max_rule_count'],
-        approximate_induction: bool = DEFAULT_PARAMS_VALUE['approximate_induction'],
-        approximate_bins_count: int = DEFAULT_PARAMS_VALUE['approximate_bins_count'],
+        minsupp_all: Tuple[float, float, float, float] = DEFAULT_PARAMS_VALUE[
+            "minsupp_all"
+        ],
+        max_neg2pos: float = DEFAULT_PARAMS_VALUE["max_neg2pos"],
+        max_passes_count: int = DEFAULT_PARAMS_VALUE["max_passes_count"],
+        penalty_strength: float = DEFAULT_PARAMS_VALUE["penalty_strength"],
+        penalty_saturation: float = DEFAULT_PARAMS_VALUE["penalty_saturation"],
+        minsupp_new: float = DEFAULT_PARAMS_VALUE["minsupp_new"],
+        induction_measure: Measures = DEFAULT_PARAMS_VALUE["induction_measure"],
+        pruning_measure: Union[Measures, str] = DEFAULT_PARAMS_VALUE["pruning_measure"],
+        voting_measure: Measures = DEFAULT_PARAMS_VALUE["voting_measure"],
+        max_growing: float = DEFAULT_PARAMS_VALUE["max_growing"],
+        enable_pruning: bool = DEFAULT_PARAMS_VALUE["enable_pruning"],
+        ignore_missing: bool = DEFAULT_PARAMS_VALUE["ignore_missing"],
+        max_uncovered_fraction: float = DEFAULT_PARAMS_VALUE["max_uncovered_fraction"],
+        select_best_candidate: bool = DEFAULT_PARAMS_VALUE["select_best_candidate"],
+        complementary_conditions: bool = DEFAULT_PARAMS_VALUE[
+            "complementary_conditions"
+        ],
+        control_apriori_precision: bool = DEFAULT_PARAMS_VALUE[
+            "control_apriori_precision"
+        ],
+        max_rule_count: int = DEFAULT_PARAMS_VALUE["max_rule_count"],
+        approximate_induction: bool = DEFAULT_PARAMS_VALUE["approximate_induction"],
+        approximate_bins_count: int = DEFAULT_PARAMS_VALUE["approximate_bins_count"],
     ):
         """
         Parameters
         ----------
         minsupp_all: Tuple[float, float, float, float]
-            a minimum positive support of a contrast set (p/P). When multiple values are specified,
-            a metainduction is performed; Default and recommended sequence is: 0.8, 0.5, 0.2, 0.1
+            a minimum positive support of a contrast set (p/P). When multiple values
+            are specified, a metainduction is performed; Default and recommended
+            sequence is: 0.8, 0.5, 0.2, 0.1
         max_neg2pos: float
             a maximum ratio of negative to positive supports (nP/pN); Default is 0.5
         max_passes_count: int
-            a maximum number of sequential covering passes for a single minsupp-all; Default is 5
+            a maximum number of sequential covering passes for a single minsupp-all;
+            Default is 5
         penalty_strength: float
             (s) - penalty strength; Default is 0.5
         penalty_saturation: float
             the value of p_new / P at which penalty reward saturates; Default is 0.2.
         minsupp_new : float = 5.0
-            a minimum number (or fraction, if value < 1.0) of previously uncovered examples
-             to be covered by a new rule (positive examples for classification problems); default: 5,
+            a minimum number (or fraction, if value < 1.0) of previously uncovered
+            examples to be covered by a new rule (positive examples for classification
+            problems); default: 5,
         induction_measure : :class:`rulekit.params.Measures` = \
             :class:`rulekit.params.Measures.Correlation`
             measure used during induction; default measure is correlation
@@ -617,36 +644,37 @@ def __init__(  # pylint: disable=too-many-arguments,too-many-locals
             :class:`rulekit.params.Measures.Correlation`
             measure used during voting; default measure is correlation
         max_growing : int = 0.0
-            non-negative integer representing maximum number of conditions which can be added to
-            the rule in the growing phase (use this parameter for large datasets if execution time
-            is prohibitive); 0 indicates no limit; default: 0,
+            non-negative integer representing maximum number of conditions which can be
+            added to the rule in the growing phase (use this parameter for large
+            datasets if execution time is prohibitive); 0 indicates no limit; default: 0
         enable_pruning : bool = True
             enable or disable pruning, default is True.
         ignore_missing : bool = False
-            boolean telling whether missing values should be ignored (by default, a missing value
-            of given attribute is always considered as not fulfilling the condition build upon
-             that attribute); default: False.
+            boolean telling whether missing values should be ignored (by default, a
+            missing value of given attribute is always considered as not fulfilling the
+            condition build upon that attribute); default: False.
         max_uncovered_fraction : float = 0.0
-            Floating-point number from [0,1] interval representing maximum fraction of examples
-             that may remain uncovered by the rule set, default: 0.0.
+            Floating-point number from [0,1] interval representing maximum fraction of
+            examples that may remain uncovered by the rule set, default: 0.0.
         select_best_candidate : bool = False
             Flag determining if best candidate should be selected from growing phase;
              default: False.
         complementary_conditions : bool = False
-            If enabled, complementary conditions in the form a = !{value} for nominal attributes
-            are supported.
+            If enabled, complementary conditions in the form a = !{value} for nominal
+            attributes are supported.
         control_apriori_precision : bool = True
-            When inducing classification rules, verify if candidate precision is higher than
-             apriori precision of the investigated class.
+            When inducing classification rules, verify if candidate precision is higher
+            than apriori precision of the investigated class.
         max_rule_count : int = 0
-            Maximum number of rules to be generated (for classification data sets it applies
-             to a single class); 0 indicates no limit.
+            Maximum number of rules to be generated (for classification data sets it
+            applies to a single class); 0 indicates no limit.
         approximate_induction: bool = False
-            Use an approximate induction heuristic which does not check all possible splits;
-            note: this is an experimental feature and currently works only for classification
-            data sets, results may change in future;
+            Use an approximate induction heuristic which does not check all possible
+            splits; note: this is an experimental feature and currently works only for
+            classification data sets, results may change in future;
         approximate_bins_count: int = 100
-            maximum number of bins for an attribute evaluated in the approximate induction.
+            maximum number of bins for an attribute evaluated in the approximate
+            induction.
         """
         BaseOperator.__init__(
             self,
@@ -668,7 +696,7 @@ def __init__(  # pylint: disable=too-many-arguments,too-many-locals
             control_apriori_precision=control_apriori_precision,
             max_rule_count=max_rule_count,
             approximate_induction=approximate_induction,
-            approximate_bins_count=approximate_bins_count
+            approximate_bins_count=approximate_bins_count,
         )
         BaseClassifier.__init__(self)
         self.contrast_attribute: str = None
@@ -679,11 +707,9 @@ def __init__(  # pylint: disable=too-many-arguments,too-many-locals
     def _map_result(self, predicted_example_set) -> np.ndarray:
         prediction: np.ndarray
         if self._remap_to_numeric:
-            prediction = PredictionResultMapper.map_to_numerical(
-                predicted_example_set)
+            prediction = PredictionResultMapper.map_to_numerical(predicted_example_set)
         else:
-            prediction = PredictionResultMapper.map_to_nominal(
-                predicted_example_set)
+            prediction = PredictionResultMapper.map_to_nominal(predicted_example_set)
         return prediction
 
     def _get_unique_label_values(self, labels: Data):
@@ -691,11 +717,16 @@ def _get_unique_label_values(self, labels: Data):
         for label_value in labels:
             tmp[label_value] = None
         self.label_unique_values = list(tmp.keys())
-        if len(self.label_unique_values) > 0 and isinstance(self.label_unique_values[0], bytes):
-            self.label_unique_values = [item.decode(
-                'utf-8') for item in self.label_unique_values]
-
-    def fit(self, values: Data, labels: Data, contrast_attribute: str) -> ContrastSetRuleClassifier:  # pylint: disable=arguments-differ
+        if len(self.label_unique_values) > 0 and isinstance(
+            self.label_unique_values[0], bytes
+        ):
+            self.label_unique_values = [
+                item.decode("utf-8") for item in self.label_unique_values
+            ]
+
+    def fit(
+        self, values: Data, labels: Data, contrast_attribute: str
+    ) -> ContrastSetRuleClassifier:  # pylint: disable=arguments-differ
         """Train model on given dataset.
 
         Parameters
@@ -716,17 +747,12 @@ def fit(self, values: Data, labels: Data, contrast_attribute: str) -> ContrastSe
         RuleClassifier._prepare_labels(  # pylint: disable=protected-access,protected-access
             self, labels
         )
-        BaseOperator.fit(
-            self, values, labels,
-            contrast_attribute=contrast_attribute
-        )
+        BaseOperator.fit(self, values, labels, contrast_attribute=contrast_attribute)
         self.contrast_attribute = contrast_attribute
         return self
 
     def predict(
-        self,
-        values: Data,
-        return_metrics: bool = False
+        self, values: Data, return_metrics: bool = False
     ) -> Union[np.ndarray, tuple[np.ndarray, ClassificationPredictionMetrics]]:
         """Perform prediction and returns predicted labels.
 
@@ -736,21 +762,21 @@ def predict(
             attributes
 
         return_metrics: bool = False
-            Optional flag. If set to *True* method will calculate some additional model metrics.
-             Method will then return tuple instead of just predicted labels.
+            Optional flag. If set to *True* method will calculate some additional model
+            metrics. Method will then return tuple instead of just predicted labels.
 
         Returns
         -------
-        result : Union[np.ndarray, tuple[np.ndarray, :class:`rulekit.classification.ClassificationPredictionMetrics`]]
-            If *return_metrics* flag wasn't set it will return just prediction, otherwise a tuple
-            will be returned with first element being prediction and second one being metrics.
+        result : Union[np.ndarray, tuple[np.ndarray, :class:`rulekit.classification.\
+            ClassificationPredictionMetrics`]]
+            If *return_metrics* flag wasn't set it will return just prediction,
+            otherwise a tuple will be returned with first element being prediction and
+            second one being metrics.
         """
         return RuleClassifier.predict(self, values, return_metrics)
 
     def predict_proba(
-        self,
-        values: Data,
-        return_metrics: bool = False
+        self, values: Data, return_metrics: bool = False
     ) -> Union[np.ndarray, tuple[np.ndarray, ClassificationPredictionMetrics]]:
         """Perform prediction and returns class probabilities for each example.
 
@@ -760,18 +786,16 @@ def predict_proba(
             attributes
 
         return_metrics: bool = False
-            Optional flag. If set to *True* method will calculate some additional model metrics.
-             Method will then return tuple instead of just probabilities.
+            Optional flag. If set to *True* method will calculate some additional model
+            metrics. Method will then return tuple instead of just probabilities.
 
         Returns
         -------
-        result : Union[ \
-            np.ndarray,  \
-            tuple[np.ndarray, :class:`rulekit.classification.ClassificationPredictionMetrics`] \
-        ] \
-        If *return_metrics* flag wasn't set it will return just probabilities matrix, otherwise \
-        a tuple will be returned with first element being prediction and second one being \
-        metrics.
+        result : Union[np.ndarray, tuple[np.ndarray, :class:`rulekit.classification.\
+            ClassificationPredictionMetrics`]]
+            If *return_metrics* flag wasn't set it will return just probabilities
+            matrix, otherwise a tuple will be returned with first element being
+            prediction and second one being metrics.
         """
         return RuleClassifier.predict_proba(self, values, return_metrics)
 
@@ -793,18 +817,21 @@ def score(self, values: Data, labels: Data) -> float:
         return RuleClassifier.score(self, values, labels)
 
     def __getstate__(self) -> dict:
-        return {**BaseOperator.__getstate__(self), **{
-            'label_unique_values': self.label_unique_values,
-            '_remap_to_numeric': self._remap_to_numeric,
-            'contrast_attribute': self.contrast_attribute,
-        }}
+        return {
+            **BaseOperator.__getstate__(self),
+            **{
+                "label_unique_values": self.label_unique_values,
+                "_remap_to_numeric": self._remap_to_numeric,
+                "contrast_attribute": self.contrast_attribute,
+            },
+        }
 
     def __setstate__(self, state: dict):
         BaseOperator.__setstate__(self, state)
         self._init_classification_rule_performance_classes()
-        self.label_unique_values = state['label_unique_values']
-        self._remap_to_numeric = state['_remap_to_numeric']
-        self.contrast_attribute = state['contrast_attribute']
+        self.label_unique_values = state["label_unique_values"]
+        self._remap_to_numeric = state["_remap_to_numeric"]
+        self.contrast_attribute = state["contrast_attribute"]
 
     def _get_problem_type(self) -> ProblemType:
         return ProblemType.CONTRAST_CLASSIFICATION
diff --git a/rulekit/jar/rulekit-2.1.21-all.jar b/rulekit/jar/rulekit-2.1.24-all.jar
similarity index 99%
rename from rulekit/jar/rulekit-2.1.21-all.jar
rename to rulekit/jar/rulekit-2.1.24-all.jar
index 4567c01..5aab357 100644
Binary files a/rulekit/jar/rulekit-2.1.21-all.jar and b/rulekit/jar/rulekit-2.1.24-all.jar differ
diff --git a/rulekit/main.py b/rulekit/main.py
index c2b8f7b..29c42b6 100644
--- a/rulekit/main.py
+++ b/rulekit/main.py
@@ -14,18 +14,20 @@
 
 from rulekit._logging import _RuleKitJavaLoggerConfig
 
-__RULEKIT_RELEASE_VERSION__ = '2.1.21'
-__VERSION__ = f'{__RULEKIT_RELEASE_VERSION__}.0'
+__RULEKIT_RELEASE_VERSION__ = "2.1.24"
+__VERSION__ = f"{__RULEKIT_RELEASE_VERSION__}.0"
 
 
 class JRE_Type(Enum):  # pylint: disable=invalid-name
     """:meta private:"""
-    OPEN_JDK = 'open_jdk'
-    ORACLE = 'oracle'
+
+    OPEN_JDK = "open_jdk"
+    ORACLE = "oracle"
 
 
 class RuleKit:
-    """Class used for initializing RuleKit. It starts JVM underhood and setups it with jars.
+    """Class used for initializing RuleKit. It starts JVM underhood and setups it
+    with jars.
 
     .. note:: Since version 1.7.0 there is no need to manually initialize RuleKit.
     You may just skip the **RuleKit.init()** line. However in certain scenarios when
@@ -38,6 +40,7 @@ class RuleKit:
     version : str
         version of RuleKit jar used by wrapper (not equal to python package version).
     """
+
     version: str
     _logger: logging.Logger = None
     _jar_dir_path: str
@@ -52,28 +55,28 @@ def _detect_jre_type():
         try:
             with Popen(["java", "-version"], stderr=STDOUT, stdout=PIPE) as output:
                 output = str(output.communicate()[0])
-                if 'openjdk' in output:
+                if "openjdk" in output:
                     RuleKit._jre_type = JRE_Type.OPEN_JDK
                 else:
                     RuleKit._jre_type = JRE_Type.ORACLE
         except FileNotFoundError as error:
             raise RuntimeError(
-                'RuletKit requires java JRE to be installed (version 1.8.0 recommended)'
+                "RuletKit requires java JRE to be installed (version 1.8.0 recommended)"
             ) from error
 
     @staticmethod
     def init(
         initial_heap_size: int = None,
         max_heap_size: int = None,
-        rulekit_jar_file_path: str = None
+        rulekit_jar_file_path: str = None,
     ):
         """Initialize package.
 
         This method configure and starts JVM and load RuleKit jar file.
 
-        .. note:: Since version 1.7.0 it don't have to be called before using any operator class.
-        However in certain scenarios when you want use a custom RuleKit jar file or modify Java VM
-        parameters, this method can be used.
+        .. note:: Since version 1.7.0 it don't have to be called before using any
+        operator class. However in certain scenarios when you want use a custom RuleKit
+        jar file or modify Java VM parameters, this method can be used.
 
         Parameters
         ----------
@@ -102,28 +105,28 @@ def init(
         RuleKit._jar_dir_path = f"{current_path}/jar"
         class_path_separator = os.pathsep
         try:
-            jar_file_name: str = (
-                'rulekit-' +
-                f'{__RULEKIT_RELEASE_VERSION__}-all.jar'
-            )
+            jar_file_name: str = "rulekit-" + f"{__RULEKIT_RELEASE_VERSION__}-all.jar"
             RuleKit._rulekit_jar_file_path = os.path.join(
-                RuleKit._jar_dir_path, jar_file_name)
+                RuleKit._jar_dir_path, jar_file_name
+            )
             jars_paths: list[str] = [RuleKit._rulekit_jar_file_path]
             if rulekit_jar_file_path is not None:
                 jars_paths.remove(RuleKit._rulekit_jar_file_path)
                 jars_paths.append(rulekit_jar_file_path)
                 RuleKit._rulekit_jar_file_path = rulekit_jar_file_path
-            RuleKit._class_path = (
-                f'{str.join(class_path_separator, jars_paths)}'
-            )
+            RuleKit._class_path = f"{str.join(class_path_separator, jars_paths)}"
         except IndexError as error:
-            RuleKit._logger.error('Failed to load jar files')
-            raise RuntimeError(f'''\n
-Failed to load RuleKit jar file. Check if valid rulekit jar file is present in "{RuleKit._jar_dir_path}" directory.
+            RuleKit._logger.error("Failed to load jar files")
+            raise RuntimeError(
+                f"""\n
+Failed to load RuleKit jar file. Check if valid rulekit jar file is present in
+"{RuleKit._jar_dir_path}" directory.
 
-If you're running this package for the first time you need to download RuleKit jar file by running:
+If you're running this package for the first time you need to download RuleKit jar
+file by running:
     python -m rulekit download_jar
-        ''') from error
+        """
+            ) from error
         RuleKit._read_versions()
         RuleKit._launch_jvm(initial_heap_size, max_heap_size)
         RuleKit.initialized = True
@@ -131,36 +134,36 @@ def init(
     @staticmethod
     def _setup_logger():
         logging.basicConfig()
-        RuleKit._logger = logging.getLogger('RuleKit')
+        RuleKit._logger = logging.getLogger("RuleKit")
 
     @staticmethod
     def _read_versions():
-        with zipfile.ZipFile(RuleKit._rulekit_jar_file_path, 'r') as jar_archive:
+        with zipfile.ZipFile(RuleKit._rulekit_jar_file_path, "r") as jar_archive:
             try:
                 manifest_file_content: str = jar_archive.read(
-                    'META-INF/MANIFEST.MF').decode('utf-8')
+                    "META-INF/MANIFEST.MF"
+                ).decode("utf-8")
                 RuleKit.version = re.findall(
-                    r'Implementation-Version: \S+\r', manifest_file_content)[0].split(' ')[1]
+                    r"Implementation-Version: \S+\r", manifest_file_content
+                )[0].split(" ")[1]
             except Exception as error:
-                RuleKit._logger.error(
-                    'Failed to read RuleKit versions from jar file')
+                RuleKit._logger.error("Failed to read RuleKit versions from jar file")
                 RuleKit._logger.error(error)
                 raise error
 
     @staticmethod
     def _launch_jvm(initial_heap_size: int, max_heap_size: int):
         if jpype.isJVMStarted():
-            RuleKit._logger.info('JVM already running')
+            RuleKit._logger.info("JVM already running")
         else:
             params = [
-                f'-Djava.class.path={RuleKit._class_path}',
+                f"-Djava.class.path={RuleKit._class_path}",
             ]
             if initial_heap_size is not None:
-                params.append(f'-Xms{initial_heap_size}m')
+                params.append(f"-Xms{initial_heap_size}m")
             if max_heap_size is not None:
-                params.append(f'-Xmx{max_heap_size}m')
-            jpype.startJVM(jpype.getDefaultJVMPath(), *
-                           params, convertStrings=False)
+                params.append(f"-Xmx{max_heap_size}m")
+            jpype.startJVM(jpype.getDefaultJVMPath(), *params, convertStrings=False)
 
     @staticmethod
     def configure_java_logger(
@@ -178,14 +181,13 @@ def configure_java_logger(
                 Minimum value is 1, maximum value is 2, default value is 1.
         """
         RuleKit._java_logger_config = _RuleKitJavaLoggerConfig(
-            verbosity_level=verbosity_level,
-            log_file_path=log_file_path
+            verbosity_level=verbosity_level, log_file_path=log_file_path
         )
 
     @staticmethod
     def get_java_logger_config() -> Optional[_RuleKitJavaLoggerConfig]:
-        """Returns the Java logger configuration configured using `configure_java_logger`
-        method
+        """Returns the Java logger configuration configured using
+        `configure_java_logger` method
 
         Returns:
             Optional[_RuleKitJavaLoggerConfig]: Java logger configuration
diff --git a/rulekit/params.py b/rulekit/params.py
index 09f05b3..1ba83f1 100644
--- a/rulekit/params.py
+++ b/rulekit/params.py
@@ -25,9 +25,7 @@ class _UserMeasure:  # pylint: disable=invalid-name,missing-function-docstring
 
         @JOverride
         def getResult(self, p: JDouble, n: JDouble, P: JDouble, N: JDouble) -> float:
-            return measure_function(
-                float(p), float(n), float(P), float(N)
-            )
+            return measure_function(float(p), float(n), float(P), float(N))
 
     return _UserMeasure()
 
@@ -40,119 +38,137 @@ class Measures(Enum):
     #41-rule-quality>`_ .
     `here <https://github.com/adaa-polsl/RuleKit/wiki/4-Quality-and-evaluation
     """
-    Accuracy = 'Accuracy'
-    BinaryEntropy = 'BinaryEntropy'
-    C1 = 'C1'
-    C2 = 'C2'
-    CFoil = 'CFoil'
-    CN2Significnce = 'CN2Significnce'
-    Correlation = 'Correlation'
-    Coverage = 'Coverage'
-    FBayesianConfirmation = 'FBayesianConfirmation'
-    FMeasure = 'FMeasure'
-    FullCoverage = 'FullCoverage'
-    GeoRSS = 'GeoRSS'
-    GMeasure = 'GMeasure'
-    InformationGain = 'InformationGain'
-    JMeasure = 'JMeasure'
-    Kappa = 'Kappa'
-    Klosgen = 'Klosgen'
-    Laplace = 'Laplace'
-    Lift = 'Lift'
-    LogicalSufficiency = 'LogicalSufficiency'
-    LogRank = 'LogRank'
-    MEstimate = 'MEstimate'
-    MutualSupport = 'MutualSupport'
-    Novelty = 'Novelty'
-    OddsRatio = 'OddsRatio'
-    OneWaySupport = 'OneWaySupport'
-    PawlakDependencyFactor = 'PawlakDependencyFactor'
-    Precision = 'Precision'
-    Q2 = 'Q2'
-    RelativeRisk = 'RelativeRisk'
-    Ripper = 'Ripper'
-    RSS = 'RSS'
-    RuleInterest = 'RuleInterest'
-    SBayesian = 'SBayesian'
-    Sensitivity = 'Sensitivity'
-    Specificity = 'Specificity'
-    TwoWaySupport = 'TwoWaySupport'
-    WeightedLaplace = 'WeightedLaplace'
-    WeightedRelativeAccuracy = 'WeightedRelativeAccuracy'
-    YAILS = 'YAILS'
+    Accuracy = "Accuracy"
+    BinaryEntropy = "BinaryEntropy"
+    C1 = "C1"
+    C2 = "C2"
+    CFoil = "CFoil"
+    CN2Significnce = "CN2Significnce"
+    Correlation = "Correlation"
+    Coverage = "Coverage"
+    FBayesianConfirmation = "FBayesianConfirmation"
+    FMeasure = "FMeasure"
+    FullCoverage = "FullCoverage"
+    GeoRSS = "GeoRSS"
+    GMeasure = "GMeasure"
+    InformationGain = "InformationGain"
+    JMeasure = "JMeasure"
+    Kappa = "Kappa"
+    Klosgen = "Klosgen"
+    Laplace = "Laplace"
+    Lift = "Lift"
+    LogicalSufficiency = "LogicalSufficiency"
+    LogRank = "LogRank"
+    MEstimate = "MEstimate"
+    MutualSupport = "MutualSupport"
+    Novelty = "Novelty"
+    OddsRatio = "OddsRatio"
+    OneWaySupport = "OneWaySupport"
+    PawlakDependencyFactor = "PawlakDependencyFactor"
+    Precision = "Precision"
+    Q2 = "Q2"
+    RelativeRisk = "RelativeRisk"
+    Ripper = "Ripper"
+    RSS = "RSS"
+    RuleInterest = "RuleInterest"
+    SBayesian = "SBayesian"
+    Sensitivity = "Sensitivity"
+    Specificity = "Specificity"
+    TwoWaySupport = "TwoWaySupport"
+    WeightedLaplace = "WeightedLaplace"
+    WeightedRelativeAccuracy = "WeightedRelativeAccuracy"
+    YAILS = "YAILS"
 
 
 DEFAULT_PARAMS_VALUE = {
-    'minsupp_new': 0.05,
-    'induction_measure': Measures.Correlation,
-    'pruning_measure':  Measures.Correlation,
-    'voting_measure': Measures.Correlation,
-    'max_growing': 0.0,
-    'enable_pruning': True,
-    'ignore_missing': False,
-    'max_uncovered_fraction': 0.0,
-    'select_best_candidate': False,
-    'complementary_conditions': False,
-    'control_apriori_precision': True,
-    'max_rule_count': 0,
-    'approximate_induction': False,
-    'approximate_bins_count': 100,
-    'mean_based_regression': True,
-
-    'extend_using_preferred': False,
-    'extend_using_automatic': False,
-    'induce_using_preferred': False,
-    'induce_using_automatic': False,
-    'consider_other_classes': False,
-    'preferred_conditions_per_rule': MAX_INT,
-    'preferred_attributes_per_rule': MAX_INT,
-
+    "minsupp_new": 0.05,
+    "induction_measure": Measures.Correlation,
+    "pruning_measure": Measures.Correlation,
+    "voting_measure": Measures.Correlation,
+    "max_growing": 0.0,
+    "enable_pruning": True,
+    "ignore_missing": False,
+    "max_uncovered_fraction": 0.0,
+    "select_best_candidate": False,
+    "complementary_conditions": False,
+    "control_apriori_precision": True,
+    "max_rule_count": 0,
+    "approximate_induction": False,
+    "approximate_bins_count": 100,
+    "mean_based_regression": True,
+    "extend_using_preferred": False,
+    "extend_using_automatic": False,
+    "induce_using_preferred": False,
+    "induce_using_automatic": False,
+    "consider_other_classes": False,
+    "preferred_conditions_per_rule": MAX_INT,
+    "preferred_attributes_per_rule": MAX_INT,
     # Contrast sets
-    'minsupp_all': (0.8, 0.5, 0.2, 0.1),
-    'max_neg2pos': 0.5,
-    'max_passes_count': 5,
-    'penalty_strength': 0.5,
-    'penalty_saturation': 0.2,
+    "minsupp_all": (0.8, 0.5, 0.2, 0.1),
+    "max_neg2pos": 0.5,
+    "max_passes_count": 5,
+    "penalty_strength": 0.5,
+    "penalty_saturation": 0.2,
 }
 
 _QualityMeasure = Union[Measures, _UserDefinedMeasure]
 
 
 class ModelsParams(BaseModel):
-    """Model for validating models hyperparameters
-    """
-    minsupp_new: Optional[float] = DEFAULT_PARAMS_VALUE['minsupp_new']
-    induction_measure: Optional[_QualityMeasure] = DEFAULT_PARAMS_VALUE['induction_measure']
-    pruning_measure: Optional[_QualityMeasure] = DEFAULT_PARAMS_VALUE['pruning_measure']
-    voting_measure: Optional[_QualityMeasure] = DEFAULT_PARAMS_VALUE['voting_measure']
-    max_growing: Optional[float] = DEFAULT_PARAMS_VALUE['max_growing']
-    enable_pruning: Optional[bool] = DEFAULT_PARAMS_VALUE['enable_pruning']
-    ignore_missing: Optional[bool] = DEFAULT_PARAMS_VALUE['ignore_missing']
-    max_uncovered_fraction: Optional[float] = DEFAULT_PARAMS_VALUE['max_uncovered_fraction']
-    select_best_candidate: Optional[bool] = DEFAULT_PARAMS_VALUE['select_best_candidate']
-    complementary_conditions: Optional[bool] = DEFAULT_PARAMS_VALUE['complementary_conditions']
-    max_rule_count: int = DEFAULT_PARAMS_VALUE['max_rule_count']
+    """Model for validating models hyperparameters"""
+
+    minsupp_new: Optional[float] = DEFAULT_PARAMS_VALUE["minsupp_new"]
+    induction_measure: Optional[_QualityMeasure] = DEFAULT_PARAMS_VALUE[
+        "induction_measure"
+    ]
+    pruning_measure: Optional[_QualityMeasure] = DEFAULT_PARAMS_VALUE["pruning_measure"]
+    voting_measure: Optional[_QualityMeasure] = DEFAULT_PARAMS_VALUE["voting_measure"]
+    max_growing: Optional[float] = DEFAULT_PARAMS_VALUE["max_growing"]
+    enable_pruning: Optional[bool] = DEFAULT_PARAMS_VALUE["enable_pruning"]
+    ignore_missing: Optional[bool] = DEFAULT_PARAMS_VALUE["ignore_missing"]
+    max_uncovered_fraction: Optional[float] = DEFAULT_PARAMS_VALUE[
+        "max_uncovered_fraction"
+    ]
+    select_best_candidate: Optional[bool] = DEFAULT_PARAMS_VALUE[
+        "select_best_candidate"
+    ]
+    complementary_conditions: Optional[bool] = DEFAULT_PARAMS_VALUE[
+        "complementary_conditions"
+    ]
+    max_rule_count: int = DEFAULT_PARAMS_VALUE["max_rule_count"]
 
 
 class ExpertModelParams(ModelsParams):
-    """Model for validating expert models hyperparameters
-    """
-    extend_using_preferred: Optional[bool] = DEFAULT_PARAMS_VALUE['extend_using_preferred']
-    extend_using_automatic: Optional[bool] = DEFAULT_PARAMS_VALUE['extend_using_automatic']
-    induce_using_preferred: Optional[bool] = DEFAULT_PARAMS_VALUE['induce_using_preferred']
-    induce_using_automatic: Optional[bool] = DEFAULT_PARAMS_VALUE['induce_using_automatic']
-    consider_other_classes: Optional[bool] = DEFAULT_PARAMS_VALUE['consider_other_classes']
-    preferred_conditions_per_rule: Optional[int] = DEFAULT_PARAMS_VALUE['preferred_conditions_per_rule']
-    preferred_attributes_per_rule: Optional[int] = DEFAULT_PARAMS_VALUE['preferred_attributes_per_rule']
+    """Model for validating expert models hyperparameters"""
+
+    extend_using_preferred: Optional[bool] = DEFAULT_PARAMS_VALUE[
+        "extend_using_preferred"
+    ]
+    extend_using_automatic: Optional[bool] = DEFAULT_PARAMS_VALUE[
+        "extend_using_automatic"
+    ]
+    induce_using_preferred: Optional[bool] = DEFAULT_PARAMS_VALUE[
+        "induce_using_preferred"
+    ]
+    induce_using_automatic: Optional[bool] = DEFAULT_PARAMS_VALUE[
+        "induce_using_automatic"
+    ]
+    consider_other_classes: Optional[bool] = DEFAULT_PARAMS_VALUE[
+        "consider_other_classes"
+    ]
+    preferred_conditions_per_rule: Optional[int] = DEFAULT_PARAMS_VALUE[
+        "preferred_conditions_per_rule"
+    ]
+    preferred_attributes_per_rule: Optional[int] = DEFAULT_PARAMS_VALUE[
+        "preferred_attributes_per_rule"
+    ]
 
 
 class ContrastSetModelParams(ModelsParams):
-    """Model for validating contrast set models hyperparameters
-    """
-    minsupp_all: Tuple[
-        float, float, float, float
-    ] = DEFAULT_PARAMS_VALUE['minsupp_all']
-    max_neg2pos: Optional[float] = DEFAULT_PARAMS_VALUE['max_neg2pos']
-    max_passes_count: Optional[int] = DEFAULT_PARAMS_VALUE['max_passes_count']
-    penalty_strength: Optional[float] = DEFAULT_PARAMS_VALUE['penalty_strength']
-    penalty_saturation: Optional[float] = DEFAULT_PARAMS_VALUE['penalty_saturation']
+    """Model for validating contrast set models hyperparameters"""
+
+    minsupp_all: Tuple[float, float, float, float] = DEFAULT_PARAMS_VALUE["minsupp_all"]
+    max_neg2pos: Optional[float] = DEFAULT_PARAMS_VALUE["max_neg2pos"]
+    max_passes_count: Optional[int] = DEFAULT_PARAMS_VALUE["max_passes_count"]
+    penalty_strength: Optional[float] = DEFAULT_PARAMS_VALUE["penalty_strength"]
+    penalty_saturation: Optional[float] = DEFAULT_PARAMS_VALUE["penalty_saturation"]
diff --git a/rulekit/regression.py b/rulekit/regression.py
index d102f45..dff72b9 100644
--- a/rulekit/regression.py
+++ b/rulekit/regression.py
@@ -25,7 +25,7 @@
 
 
 class _RegressionModelParams(ModelsParams):
-    mean_based_regression: bool = DEFAULT_PARAMS_VALUE['mean_based_regression']
+    mean_based_regression: bool = DEFAULT_PARAMS_VALUE["mean_based_regression"]
 
 
 class _RegressionExpertModelParams(_RegressionModelParams, ExpertModelParams):
@@ -39,26 +39,28 @@ class RuleRegressor(BaseOperator):
 
     def __init__(  # pylint: disable=too-many-arguments
         self,
-        minsupp_new: float = DEFAULT_PARAMS_VALUE['minsupp_new'],
-        induction_measure: Measures = DEFAULT_PARAMS_VALUE['induction_measure'],
-        pruning_measure: Union[Measures,
-                               str] = DEFAULT_PARAMS_VALUE['pruning_measure'],
-        voting_measure: Measures = DEFAULT_PARAMS_VALUE['voting_measure'],
-        max_growing: float = DEFAULT_PARAMS_VALUE['max_growing'],
-        enable_pruning: bool = DEFAULT_PARAMS_VALUE['enable_pruning'],
-        ignore_missing: bool = DEFAULT_PARAMS_VALUE['ignore_missing'],
-        max_uncovered_fraction: float = DEFAULT_PARAMS_VALUE['max_uncovered_fraction'],
-        select_best_candidate: bool = DEFAULT_PARAMS_VALUE['select_best_candidate'],
-        complementary_conditions: bool = DEFAULT_PARAMS_VALUE['complementary_conditions'],
-        mean_based_regression: bool = DEFAULT_PARAMS_VALUE['mean_based_regression'],
-        max_rule_count: int = DEFAULT_PARAMS_VALUE['max_rule_count'],
+        minsupp_new: float = DEFAULT_PARAMS_VALUE["minsupp_new"],
+        induction_measure: Measures = DEFAULT_PARAMS_VALUE["induction_measure"],
+        pruning_measure: Union[Measures, str] = DEFAULT_PARAMS_VALUE["pruning_measure"],
+        voting_measure: Measures = DEFAULT_PARAMS_VALUE["voting_measure"],
+        max_growing: float = DEFAULT_PARAMS_VALUE["max_growing"],
+        enable_pruning: bool = DEFAULT_PARAMS_VALUE["enable_pruning"],
+        ignore_missing: bool = DEFAULT_PARAMS_VALUE["ignore_missing"],
+        max_uncovered_fraction: float = DEFAULT_PARAMS_VALUE["max_uncovered_fraction"],
+        select_best_candidate: bool = DEFAULT_PARAMS_VALUE["select_best_candidate"],
+        complementary_conditions: bool = DEFAULT_PARAMS_VALUE[
+            "complementary_conditions"
+        ],
+        mean_based_regression: bool = DEFAULT_PARAMS_VALUE["mean_based_regression"],
+        max_rule_count: int = DEFAULT_PARAMS_VALUE["max_rule_count"],
     ):
         """
         Parameters
         ----------
         minsupp_new : float = 5.0
-            a minimum number (or fraction, if value < 1.0) of previously uncovered examples
-             to be covered by a new rule (positive examples for classification problems); default: 5,
+            a minimum number (or fraction, if value < 1.0) of previously uncovered
+            examples to be covered by a new rule (positive examples for classification
+            problems); default: 5,
         induction_measure : :class:`rulekit.params.Measures` = \
             :class:`rulekit.params.Measures.Correlation`
             measure used during induction; default measure is correlation
@@ -70,29 +72,29 @@ def __init__(  # pylint: disable=too-many-arguments
             :class:`rulekit.params.Measures.Correlation`
             measure used during voting; default measure is correlation
         max_growing : int = 0.0
-            non-negative integer representing maximum number of conditions which can be added to
-            the rule in the growing phase (use this parameter for large datasets if execution time
-            is prohibitive); 0 indicates no limit; default: 0,
+            non-negative integer representing maximum number of conditions which can be
+            added to the rule in the growing phase (use this parameter for large
+            datasets if execution time is prohibitive); 0 indicates no limit; default: 0
         enable_pruning : bool = True
             enable or disable pruning, default is True.
         ignore_missing : bool = False
-            boolean telling whether missing values should be ignored (by default, a missing value
-            of given attribute is always considered as not fulfilling the condition build upon that
-            attribute); default: False.
+            boolean telling whether missing values should be ignored (by default, a
+            missing value of given attribute is always considered as not fulfilling the
+            condition build upon that attribute); default: False.
         max_uncovered_fraction : float = 0.0
-            Floating-point number from [0,1] interval representing maximum fraction of examples
-             that may remain uncovered by the rule set, default: 0.0.
+            Floating-point number from [0,1] interval representing maximum fraction of
+            examples that may remain uncovered by the rule set, default: 0.0.
         select_best_candidate : bool = False
             Flag determining if best candidate should be selected from growing phase;
              default: False.
         complementary_conditions : bool = False
-            If enabled, complementary conditions in the form a = !{value} for nominal attributes
-            are supported.
+            If enabled, complementary conditions in the form a = !{value} for nominal
+            attributes are supported.
         mean_based_regression : bool = True
-            Enable fast induction of mean-based regression rules instead of default median-based.
+            Enable fast induction of mean-based regression rules instead of default
+            median-based.
         max_rule_count : int = 0
-            Maximum number of rules to be generated (for classification data sets it applies
-             to a single class); 0 indicates no limit.
+            Maximum number of rules to be generated; 0 indicates no limit. Default: 0
         """
         super().__init__(
             minsupp_new=minsupp_new,
@@ -117,10 +119,12 @@ def _validate_labels(self, labels: Data):
             first_label = labels[0]
         if not isinstance(first_label, Number):
             raise ValueError(
-                f'{self.__class__.__name__} requires lables values to be numeric'
+                f"{self.__class__.__name__} requires lables values to be numeric"
             )
 
-    def fit(self, values: Data, labels: Data) -> RuleRegressor:  # pylint: disable=arguments-differ
+    def fit(  # pylint: disable=arguments-differ
+        self, values: Data, labels: Data
+    ) -> RuleRegressor:
         """Train model on given dataset.
 
         Parameters
@@ -171,7 +175,9 @@ def score(self, values: Data, labels: Data) -> float:
         return metrics.r2_score(labels, predicted_labels)
 
     def _map_result(self, predicted_example_set) -> np.ndarray:
-        return PredictionResultMapper.map_to_numerical(predicted_example_set, remap=False)
+        return PredictionResultMapper.map_to_numerical(
+            predicted_example_set, remap=False
+        )
 
     def _get_problem_type(self) -> ProblemType:
         return ProblemType.REGRESSION
@@ -182,37 +188,40 @@ class ExpertRuleRegressor(ExpertKnowledgeOperator, RuleRegressor):
 
     __params_class__ = _RegressionExpertModelParams
 
-    def __init__(   # pylint: disable=too-many-arguments,too-many-locals
+    def __init__(  # pylint: disable=too-many-arguments,too-many-locals
         self,
-        minsupp_new: float = DEFAULT_PARAMS_VALUE['minsupp_new'],
-        induction_measure: Measures = DEFAULT_PARAMS_VALUE['induction_measure'],
-        pruning_measure: Union[Measures,
-                               str] = DEFAULT_PARAMS_VALUE['pruning_measure'],
-        voting_measure: Measures = DEFAULT_PARAMS_VALUE['voting_measure'],
-        max_growing: float = DEFAULT_PARAMS_VALUE['max_growing'],
-        enable_pruning: bool = DEFAULT_PARAMS_VALUE['enable_pruning'],
-        ignore_missing: bool = DEFAULT_PARAMS_VALUE['ignore_missing'],
-        max_uncovered_fraction: float = DEFAULT_PARAMS_VALUE['max_uncovered_fraction'],
-        select_best_candidate: bool = DEFAULT_PARAMS_VALUE['select_best_candidate'],
-        complementary_conditions: bool = DEFAULT_PARAMS_VALUE['complementary_conditions'],
-        mean_based_regression: bool = DEFAULT_PARAMS_VALUE['mean_based_regression'],
-        max_rule_count: int = DEFAULT_PARAMS_VALUE['max_rule_count'],
-
-        extend_using_preferred: bool = DEFAULT_PARAMS_VALUE['extend_using_preferred'],
-        extend_using_automatic: bool = DEFAULT_PARAMS_VALUE['extend_using_automatic'],
-        induce_using_preferred: bool = DEFAULT_PARAMS_VALUE['induce_using_preferred'],
-        induce_using_automatic: bool = DEFAULT_PARAMS_VALUE['induce_using_automatic'],
+        minsupp_new: float = DEFAULT_PARAMS_VALUE["minsupp_new"],
+        induction_measure: Measures = DEFAULT_PARAMS_VALUE["induction_measure"],
+        pruning_measure: Union[Measures, str] = DEFAULT_PARAMS_VALUE["pruning_measure"],
+        voting_measure: Measures = DEFAULT_PARAMS_VALUE["voting_measure"],
+        max_growing: float = DEFAULT_PARAMS_VALUE["max_growing"],
+        enable_pruning: bool = DEFAULT_PARAMS_VALUE["enable_pruning"],
+        ignore_missing: bool = DEFAULT_PARAMS_VALUE["ignore_missing"],
+        max_uncovered_fraction: float = DEFAULT_PARAMS_VALUE["max_uncovered_fraction"],
+        select_best_candidate: bool = DEFAULT_PARAMS_VALUE["select_best_candidate"],
+        complementary_conditions: bool = DEFAULT_PARAMS_VALUE[
+            "complementary_conditions"
+        ],
+        mean_based_regression: bool = DEFAULT_PARAMS_VALUE["mean_based_regression"],
+        max_rule_count: int = DEFAULT_PARAMS_VALUE["max_rule_count"],
+        extend_using_preferred: bool = DEFAULT_PARAMS_VALUE["extend_using_preferred"],
+        extend_using_automatic: bool = DEFAULT_PARAMS_VALUE["extend_using_automatic"],
+        induce_using_preferred: bool = DEFAULT_PARAMS_VALUE["induce_using_preferred"],
+        induce_using_automatic: bool = DEFAULT_PARAMS_VALUE["induce_using_automatic"],
         preferred_conditions_per_rule: int = DEFAULT_PARAMS_VALUE[
-            'preferred_conditions_per_rule'],
+            "preferred_conditions_per_rule"
+        ],
         preferred_attributes_per_rule: int = DEFAULT_PARAMS_VALUE[
-            'preferred_attributes_per_rule'],
+            "preferred_attributes_per_rule"
+        ],
     ):
         """
         Parameters
         ----------
         minsupp_new : float = 5.0
-            a minimum number (or fraction, if value < 1.0) of previously uncovered examples
-             to be covered by a new rule (positive examples for classification problems); default: 5,
+            a minimum number (or fraction, if value < 1.0) of previously uncovered
+            examples  to be covered by a new rule (positive examples for classification
+            problems); default: 5,
         induction_measure : :class:`rulekit.params.Measures` = \
             :class:`rulekit.params.Measures.Correlation`
             measure used during induction; default measure is correlation
@@ -224,42 +233,43 @@ def __init__(   # pylint: disable=too-many-arguments,too-many-locals
             :class:`rulekit.params.Measures.Correlation`
             measure used during voting; default measure is correlation
         max_growing : int = 0.0
-            non-negative integer representing maximum number of conditions which can be added to
-            the rule in the growing phase (use this parameter for large datasets if execution time
-             is prohibitive); 0 indicates no limit; default: 0,
+            non-negative integer representing maximum number of conditions which can be
+            added to the rule in the growing phase (use this parameter for large
+            datasets if execution time is prohibitive); 0 indicates no limit; default: 0,
         enable_pruning : bool = True
             enable or disable pruning, default is True.
         ignore_missing : bool = False
-            boolean telling whether missing values should be ignored (by default, a missing value
-            of given attribute is always considered as not fulfilling the condition build upon that
-            attribute); default: False.
+            boolean telling whether missing values should be ignored (by default, a
+            missing value of given attribute is always considered as not fulfilling the
+            condition build upon that attribute); default: False.
         max_uncovered_fraction : float = 0.0
-            Floating-point number from [0,1] interval representing maximum fraction of examples
-            that may remain uncovered by the rule set, default: 0.0.
+            Floating-point number from [0,1] interval representing maximum fraction of
+            examples that may remain uncovered by the rule set, default: 0.0.
         select_best_candidate : bool = False
             Flag determining if best candidate should be selected from growing phase;
             default: False.
         complementary_conditions : bool = False
-            If enabled, complementary conditions in the form a = !{value} for nominal attributes
-            are supported.
+            If enabled, complementary conditions in the form a = !{value} for nominal
+            attributes are supported.
         mean_based_regression : bool = True
-            Enable fast induction of mean-based regression rules instead of default median-based.
+            Enable fast induction of mean-based regression rules instead of default
+            median-based.
         max_rule_count : int = 0
-            Maximum number of rules to be generated (for classification data sets it applies
-             to a single class); 0 indicates no limit.
+            Maximum number of rules to be generated (for classification data sets it
+            applies to a single class); 0 indicates no limit.
 
         extend_using_preferred : bool = False
-            boolean indicating whether initial rules should be extended with a use of preferred
-            conditions and attributes; default is False
+            boolean indicating whether initial rules should be extended with a use of
+            preferred conditions and attributes; default is False
         extend_using_automatic : bool = False
-            boolean indicating whether initial rules should be extended with a use of automatic
-            conditions and attributes; default is False
+            boolean indicating whether initial rules should be extended with a use of
+            automatic conditions and attributes; default is False
         induce_using_preferred : bool = False
-            boolean indicating whether new rules should be induced with a use of preferred
-            conditions and attributes; default is False
+            boolean indicating whether new rules should be induced with a use of
+            preferred conditions and attributes; default is False
         induce_using_automatic : bool = False
-            boolean indicating whether new rules should be induced with a use of automatic
-            conditions and attributes; default is False
+            boolean indicating whether new rules should be induced with a use of
+            automatic conditions and attributes; default is False
         preferred_conditions_per_rule : int = None
             maximum number of preferred conditions per rule; default: unlimited,
         preferred_attributes_per_rule : int = None
@@ -307,10 +317,9 @@ def fit(  # pylint: disable=arguments-differ,too-many-arguments
         self,
         values: Data,
         labels: Data,
-
         expert_rules: list[Union[str, tuple[str, str]]] = None,
         expert_preferred_conditions: list[Union[str, tuple[str, str]]] = None,
-        expert_forbidden_conditions: list[Union[str, tuple[str, str]]] = None
+        expert_forbidden_conditions: list[Union[str, tuple[str, str]]] = None,
     ) -> ExpertRuleRegressor:
         """Train model on given dataset.
 
@@ -322,16 +331,19 @@ def fit(  # pylint: disable=arguments-differ,too-many-arguments
             target values
 
         expert_rules : List[Union[str, Tuple[str, str]]]
-            set of initial rules, either passed as a list of strings representing rules or as list
-            of tuples where first element is name of the rule and second one is rule string.
+            set of initial rules, either passed as a list of strings representing rules
+            or as list of tuples where first element is name of the rule and second one
+            is rule string.
         expert_preferred_conditions : List[Union[str, Tuple[str, str]]]
-            multiset of preferred conditions (used also for specifying preferred attributes by
-             using special value Any). Either passed as a list of strings representing rules or as
-             list of tuples where first element is name of the rule and second one is rule string.
+            multiset of preferred conditions (used also for specifying preferred
+            attributes by using special value Any). Either passed as a list of strings
+            representing rules or as list of tuples where first element is name of the
+            rule and second one is rule string.
         expert_forbidden_conditions : List[Union[str, Tuple[str, str]]]
-            set of forbidden conditions (used also for specifying forbidden attributes by using
-             special valye Any). Either passed as a list of strings representing rules or as list
-             of tuples where first element is name of the rule and second one is rule string.
+            set of forbidden conditions (used also for specifying forbidden attributes
+            by using special valye Any). Either passed as a list of strings representing
+            rules or as list of tuples where first element is name of the rule and
+            second one is rule string.
         Returns
         -------
         self : ExpertRuleRegressor
@@ -343,7 +355,7 @@ def fit(  # pylint: disable=arguments-differ,too-many-arguments
             labels,
             expert_rules=expert_rules,
             expert_preferred_conditions=expert_preferred_conditions,
-            expert_forbidden_conditions=expert_forbidden_conditions
+            expert_forbidden_conditions=expert_forbidden_conditions,
         )
 
     def predict(self, values: Data) -> np.ndarray:
@@ -360,44 +372,48 @@ class ContrastSetRuleRegressor(BaseOperator):
 
     def __init__(  # pylint: disable=too-many-arguments,too-many-locals
         self,
-        minsupp_all: Tuple[float, float, float,
-                           float] = DEFAULT_PARAMS_VALUE['minsupp_all'],
-        max_neg2pos: float = DEFAULT_PARAMS_VALUE['max_neg2pos'],
-        max_passes_count: int = DEFAULT_PARAMS_VALUE['max_passes_count'],
-        penalty_strength: float = DEFAULT_PARAMS_VALUE['penalty_strength'],
-        penalty_saturation: float = DEFAULT_PARAMS_VALUE['penalty_saturation'],
-
-        minsupp_new: float = DEFAULT_PARAMS_VALUE['minsupp_new'],
-        induction_measure: Measures = DEFAULT_PARAMS_VALUE['induction_measure'],
-        pruning_measure: Union[Measures,
-                               str] = DEFAULT_PARAMS_VALUE['pruning_measure'],
-        voting_measure: Measures = DEFAULT_PARAMS_VALUE['voting_measure'],
-        max_growing: float = DEFAULT_PARAMS_VALUE['max_growing'],
-        enable_pruning: bool = DEFAULT_PARAMS_VALUE['enable_pruning'],
-        ignore_missing: bool = DEFAULT_PARAMS_VALUE['ignore_missing'],
-        max_uncovered_fraction: float = DEFAULT_PARAMS_VALUE['max_uncovered_fraction'],
-        select_best_candidate: bool = DEFAULT_PARAMS_VALUE['select_best_candidate'],
-        complementary_conditions: bool = DEFAULT_PARAMS_VALUE['complementary_conditions'],
-        mean_based_regression: bool = DEFAULT_PARAMS_VALUE['mean_based_regression'],
-        max_rule_count: int = DEFAULT_PARAMS_VALUE['max_rule_count'],
+        minsupp_all: Tuple[float, float, float, float] = DEFAULT_PARAMS_VALUE[
+            "minsupp_all"
+        ],
+        max_neg2pos: float = DEFAULT_PARAMS_VALUE["max_neg2pos"],
+        max_passes_count: int = DEFAULT_PARAMS_VALUE["max_passes_count"],
+        penalty_strength: float = DEFAULT_PARAMS_VALUE["penalty_strength"],
+        penalty_saturation: float = DEFAULT_PARAMS_VALUE["penalty_saturation"],
+        minsupp_new: float = DEFAULT_PARAMS_VALUE["minsupp_new"],
+        induction_measure: Measures = DEFAULT_PARAMS_VALUE["induction_measure"],
+        pruning_measure: Union[Measures, str] = DEFAULT_PARAMS_VALUE["pruning_measure"],
+        voting_measure: Measures = DEFAULT_PARAMS_VALUE["voting_measure"],
+        max_growing: float = DEFAULT_PARAMS_VALUE["max_growing"],
+        enable_pruning: bool = DEFAULT_PARAMS_VALUE["enable_pruning"],
+        ignore_missing: bool = DEFAULT_PARAMS_VALUE["ignore_missing"],
+        max_uncovered_fraction: float = DEFAULT_PARAMS_VALUE["max_uncovered_fraction"],
+        select_best_candidate: bool = DEFAULT_PARAMS_VALUE["select_best_candidate"],
+        complementary_conditions: bool = DEFAULT_PARAMS_VALUE[
+            "complementary_conditions"
+        ],
+        mean_based_regression: bool = DEFAULT_PARAMS_VALUE["mean_based_regression"],
+        max_rule_count: int = DEFAULT_PARAMS_VALUE["max_rule_count"],
     ):
         """
         Parameters
         ----------
         minsupp_all: Tuple[float, float, float, float]
-            a minimum positive support of a contrast set (p/P). When multiple values are specified,
-            a metainduction is performed; Default and recommended sequence is: 0.8, 0.5, 0.2, 0.1
+            a minimum positive support of a contrast set (p/P). When multiple values are
+            specified, a metainduction is performed; Default and recommended sequence
+            is: 0.8, 0.5, 0.2, 0.1
         max_neg2pos: float
             a maximum ratio of negative to positive supports (nP/pN); Default is 0.5
         max_passes_count: int
-            a maximum number of sequential covering passes for a single minsupp-all; Default is 5
+            a maximum number of sequential covering passes for a single minsupp-all;
+            Default is 5
         penalty_strength: float
             (s) - penalty strength; Default is 0.5
         penalty_saturation: float
             the value of p_new / P at which penalty reward saturates; Default is 0.2.
         minsupp_new : float = 5.0
-            a minimum number (or fraction, if value < 1.0) of previously uncovered examples
-             to be covered by a new rule (positive examples for classification problems); default: 5,
+            a minimum number (or fraction, if value < 1.0) of previously uncovered
+            examples to be covered by a new rule (positive examples for classification
+            problems); default: 5,
         induction_measure : :class:`rulekit.params.Measures` = \
             :class:`rulekit.params.Measures.Correlation`
             measure used during induction; default measure is correlation
@@ -409,29 +425,29 @@ def __init__(  # pylint: disable=too-many-arguments,too-many-locals
             :class:`rulekit.params.Measures.Correlation`
             measure used during voting; default measure is correlation
         max_growing : int = 0.0
-            non-negative integer representing maximum number of conditions which can be added to
-            the rule in the growing phase (use this parameter for large datasets if execution time
-            is prohibitive); 0 indicates no limit; default: 0,
+            non-negative integer representing maximum number of conditions which can be
+            added to the rule in the growing phase (use this parameter for large
+            datasets if execution time is prohibitive); 0 indicates no limit; default: 0
         enable_pruning : bool = True
             enable or disable pruning, default is True.
         ignore_missing : bool = False
-            boolean telling whether missing values should be ignored (by default, a missing value
-             of given attribute is always considered as not fulfilling the condition build upon that
-            attribute); default: False.
+            boolean telling whether missing values should be ignored (by default, a
+            missing value of given attribute is always considered as not fulfilling the
+            condition build upon that attribute); default: False.
         max_uncovered_fraction : float = 0.0
-            Floating-point number from [0,1] interval representing maximum fraction of examples
-            that may remain uncovered by the rule set, default: 0.0.
+            Floating-point number from [0,1] interval representing maximum fraction of
+            examples that may remain uncovered by the rule set, default: 0.0.
         select_best_candidate : bool = False
             Flag determining if best candidate should be selected from growing phase;
             default: False.
         complementary_conditions : bool = False
-            If enabled, complementary conditions in the form a = !{value} for nominal attributes
-            are supported.
+            If enabled, complementary conditions in the form a = !{value} for nominal
+            attributes are supported.
         mean_based_regression : bool = True
-            Enable fast induction of mean-based regression rules instead of default median-based.
+            Enable fast induction of mean-based regression rules instead of default
+            median-based.
         max_rule_count : int = 0
-            Maximum number of rules to be generated (for classification data sets it applies
-             to a single class); 0 indicates no limit.
+            Maximum number of rules to be generated; 0 indicates no limit.
         """
         super().__init__(
             minsupp_all=minsupp_all,
@@ -455,7 +471,9 @@ def __init__(  # pylint: disable=too-many-arguments,too-many-locals
         self.contrast_attribute: str = None
         self.model: RuleSet[RegressionRule] = None
 
-    def fit(self, values: Data, labels: Data, contrast_attribute: str) -> ContrastSetRuleRegressor:  # pylint: disable=arguments-differ
+    def fit(
+        self, values: Data, labels: Data, contrast_attribute: str
+    ) -> ContrastSetRuleRegressor:  # pylint: disable=arguments-differ
         """Train model on given dataset.
 
         Parameters
@@ -470,9 +488,7 @@ def fit(self, values: Data, labels: Data, contrast_attribute: str) -> ContrastSe
         -------
         self : ContrastSetRuleRegressor
         """
-        RuleRegressor._validate_labels(  # pylint: disable=protected-access
-            self, labels
-        )
+        RuleRegressor._validate_labels(self, labels)  # pylint: disable=protected-access
         super().fit(values, labels, contrast_attribute=contrast_attribute)
         self.contrast_attribute = contrast_attribute
         return self
@@ -510,13 +526,16 @@ def score(self, values: Data, labels: Data) -> float:
         return RuleRegressor.score(self, values, labels)
 
     def __getstate__(self) -> dict:
-        return {**BaseOperator.__getstate__(self), **{
-            'contrast_attribute': self.contrast_attribute,
-        }}
+        return {
+            **BaseOperator.__getstate__(self),
+            **{
+                "contrast_attribute": self.contrast_attribute,
+            },
+        }
 
     def __setstate__(self, state: dict):
         BaseOperator.__setstate__(self, state)
-        self.contrast_attribute = state['contrast_attribute']
+        self.contrast_attribute = state["contrast_attribute"]
 
     def _get_problem_type(self) -> ProblemType:
         return ProblemType.CONTRAST_REGRESSION
diff --git a/rulekit/rules.py b/rulekit/rules.py
index 00741da..0cc69c3 100644
--- a/rulekit/rules.py
+++ b/rulekit/rules.py
@@ -14,14 +14,15 @@
 
 
 class InductionParameters:
-    """Induction parameters.
-    """
+    """Induction parameters."""
 
     def __init__(self, java_object):
         self._java_object = java_object
 
         self.minimum_covered: float = self._java_object.getMinimumCovered()
-        self.maximum_uncovered_fraction: float = self._java_object.getMaximumUncoveredFraction()
+        self.maximum_uncovered_fraction: float = (
+            self._java_object.getMaximumUncoveredFraction()
+        )
         self.ignore_missing: bool = self._java_object.isIgnoreMissing()
         self.pruning_enabled: bool = self._java_object.isPruningEnabled()
         self.max_growing_condition: float = self._java_object.getMaxGrowingConditions()
@@ -32,7 +33,9 @@ def induction_measure(self) -> Union[Measures, str]:
         Returns:
             Union[Measures, str]: Measure used for induction
         """
-        return InductionParameters._get_measure_str(self._java_object.getInductionMeasure())
+        return InductionParameters._get_measure_str(
+            self._java_object.getInductionMeasure()
+        )
 
     @property
     def pruning_measure(self) -> Union[Measures, str]:
@@ -40,7 +43,9 @@ def pruning_measure(self) -> Union[Measures, str]:
         Returns:
             Union[Measures, str]: Measure used for pruning
         """
-        return InductionParameters._get_measure_str(self._java_object.getPruningMeasure())
+        return InductionParameters._get_measure_str(
+            self._java_object.getPruningMeasure()
+        )
 
     @property
     def voting_measure(self) -> Union[Measures, str]:
@@ -48,13 +53,15 @@ def voting_measure(self) -> Union[Measures, str]:
         Returns:
             Union[Measures, str]: Measure used for voting
         """
-        return InductionParameters._get_measure_str(self._java_object.getVotingMeasure())
+        return InductionParameters._get_measure_str(
+            self._java_object.getVotingMeasure()
+        )
 
     @staticmethod
     def _get_measure_str(measure) -> Union[Measures, str]:
         name: str = measure.getName()
-        if name == 'UserDefined':
-            return 'UserDefined'
+        if name == "UserDefined":
+            return "UserDefined"
         return Measures[name]
 
     def __str__(self):
@@ -115,10 +122,10 @@ def get_covering_information(self) -> dict:
             Dictionary containing covering information.
         """
         return {
-            'weighted_n': self.weighted_n,
-            'weighted_p': self.weighted_p,
-            'weighted_N': self.weighted_N,
-            'weighted_P': self.weighted_P,
+            "weighted_n": self.weighted_n,
+            "weighted_p": self.weighted_p,
+            "weighted_N": self.weighted_N,
+            "weighted_P": self.weighted_P,
         }
 
     def print_stats(self):
@@ -131,8 +138,7 @@ def __str__(self):
 
 
 class ClassificationRule(BaseRule):
-    """Class representing classification rule
-    """
+    """Class representing classification rule"""
 
     def __init__(self, java_object):
         super().__init__(java_object)
@@ -141,31 +147,26 @@ def __init__(self, java_object):
 
     @property
     def decision_class(self) -> str:
-        """Decision class of the rule
-        """
+        """Decision class of the rule"""
         return self._decision_class
 
 
 class RegressionRule(BaseRule):
-    """Class representing regression rule
-    """
+    """Class representing regression rule"""
 
     def __init__(self, java_object):
         super().__init__(java_object)
 
-        self._conclusion_value: str = float(
-            self._java_object.getConsequenceValue())
+        self._conclusion_value: str = float(self._java_object.getConsequenceValue())
 
     @property
     def conclusion_value(self) -> float:
-        """Value from the rule's conclusion
-        """
+        """Value from the rule's conclusion"""
         return self._conclusion_value
 
 
 class SurvivalRule(BaseRule):
-    """Class representing survival rule
-    """
+    """Class representing survival rule"""
 
     def __init__(self, java_object):
         super().__init__(java_object)
@@ -176,21 +177,20 @@ def __init__(self, java_object):
 
     @property
     def kaplan_meier_estimator(self) -> KaplanMeierEstimator:
-        """Kaplan-Meier estimator from the rule concslusion
-        """
+        """Kaplan-Meier estimator from the rule concslusion"""
         return self._kaplan_meier_estimator
 
 
 def _rule_factory(java_object: JObject) -> BaseRule:
     class_name: str = str(java_object.getClass().getName()).lower()
-    if 'regression' in class_name:
+    if "regression" in class_name:
         return RegressionRule(java_object)
-    elif 'survival' in class_name:
+    elif "survival" in class_name:
         return SurvivalRule(java_object)
     return ClassificationRule(java_object)
 
 
-T = TypeVar('T')
+T = TypeVar("T")
 
 
 class RuleSet(Generic[T]):
@@ -237,8 +237,10 @@ def covering(self, example_set) -> np.ndarray:
         """:meta private:"""
         res = []
         for rule in self.rules:
-            covering_info = rule._java_object.coversUnlabelled(  # pylint: disable=protected-access
-                example_set
+            covering_info = (
+                rule._java_object.coversUnlabelled(  # pylint: disable=protected-access
+                    example_set
+                )
             )
             covered_examples_indexes = []
             covered_examples_indexes += covering_info
@@ -248,10 +250,7 @@ def covering(self, example_set) -> np.ndarray:
     @property
     def rules(self) -> list[T]:
         """List of rules objects."""
-        return [
-            _rule_factory(java_rule)
-            for java_rule in self._java_object.getRules()
-        ]
+        return [_rule_factory(java_rule) for java_rule in self._java_object.getRules()]
 
     def calculate_conditions_count(self) -> float:
         """
@@ -310,40 +309,31 @@ def calculate_significance(self, alpha: float) -> dict:
             Significance of the rule set.
         """
         significance = self._java_object.calculateSignificance(alpha)
-        return {
-            'p': significance.p,
-            'fraction': significance.fraction
-        }
+        return {"p": significance.p, "fraction": significance.fraction}
 
     def calculate_significance_fdr(self, alpha: float) -> dict:
         """
         Returns
         -------
         count: dict
-            Significance of the rule set with false discovery rate correction. Dictionary contains
-            two fields: *fraction* (fraction of rules significant at assumed level) and *p*
-             (average p-value of all rules).
+            Significance of the rule set with false discovery rate correction.
+            Dictionary contains two fields: *fraction* (fraction of rules significant
+            at assumed level) and *p* (average p-value of all rules).
         """
         significance = self._java_object.calculateSignificanceFDR(alpha)
-        return {
-            'p': significance.p,
-            'fraction': significance.fraction
-        }
+        return {"p": significance.p, "fraction": significance.fraction}
 
     def calculate_significance_fwer(self, alpha: float) -> dict:
         """
         Returns
         -------
         count: dict
-            Significance of the rule set with familiy-wise error rate correction. Dictionary
-             contains two fields: *fraction* (fraction of rules significant at assumed level)
-             and *p* (average p-value of all rules).
+            Significance of the rule set with familiy-wise error rate correction.
+            Dictionary contains two fields: *fraction* (fraction of rules significant
+            at assumed level) and *p* (average p-value of all rules).
         """
         significance = self._java_object.calculateSignificanceFWER(alpha)
-        return {
-            'p': significance.p,
-            'fraction': significance.fraction
-        }
+        return {"p": significance.p, "fraction": significance.fraction}
 
     def __str__(self):
         """Returns string representation of the object."""
diff --git a/rulekit/survival.py b/rulekit/survival.py
index e29cd45..07b73c6 100644
--- a/rulekit/survival.py
+++ b/rulekit/survival.py
@@ -24,18 +24,24 @@
 from rulekit.rules import RuleSet
 from rulekit.rules import SurvivalRule
 
-_DEFAULT_SURVIVAL_TIME_ATTR: str = 'survival_time'
+_DEFAULT_SURVIVAL_TIME_ATTR: str = "survival_time"
 
 
 class _SurvivalModelsParams(BaseModel):
     survival_time_attr: Optional[str]
-    minsupp_new: Optional[float] = DEFAULT_PARAMS_VALUE['minsupp_new']
-    max_growing: Optional[float] = DEFAULT_PARAMS_VALUE['max_growing']
-    enable_pruning: Optional[bool] = DEFAULT_PARAMS_VALUE['enable_pruning']
-    ignore_missing: Optional[bool] = DEFAULT_PARAMS_VALUE['ignore_missing']
-    max_uncovered_fraction: Optional[float] = DEFAULT_PARAMS_VALUE['max_uncovered_fraction']
-    select_best_candidate: Optional[bool] = DEFAULT_PARAMS_VALUE['select_best_candidate']
-    complementary_conditions: Optional[bool] = DEFAULT_PARAMS_VALUE['complementary_conditions']
+    minsupp_new: Optional[float] = DEFAULT_PARAMS_VALUE["minsupp_new"]
+    max_growing: Optional[float] = DEFAULT_PARAMS_VALUE["max_growing"]
+    enable_pruning: Optional[bool] = DEFAULT_PARAMS_VALUE["enable_pruning"]
+    ignore_missing: Optional[bool] = DEFAULT_PARAMS_VALUE["ignore_missing"]
+    max_uncovered_fraction: Optional[float] = DEFAULT_PARAMS_VALUE[
+        "max_uncovered_fraction"
+    ]
+    select_best_candidate: Optional[bool] = DEFAULT_PARAMS_VALUE[
+        "select_best_candidate"
+    ]
+    complementary_conditions: Optional[bool] = DEFAULT_PARAMS_VALUE[
+        "complementary_conditions"
+    ]
 
 
 class _SurvivalExpertModelParams(_SurvivalModelsParams, ExpertModelParams):
@@ -65,46 +71,49 @@ class SurvivalRules(BaseOperator, _BaseSurvivalRulesModel):
     def __init__(  # pylint: disable=super-init-not-called,too-many-arguments
         self,
         survival_time_attr: str = None,
-        minsupp_new: int = DEFAULT_PARAMS_VALUE['minsupp_new'],
-        max_growing: int = DEFAULT_PARAMS_VALUE['max_growing'],
-        enable_pruning: bool = DEFAULT_PARAMS_VALUE['enable_pruning'],
-        ignore_missing: bool = DEFAULT_PARAMS_VALUE['ignore_missing'],
-        max_uncovered_fraction: float = DEFAULT_PARAMS_VALUE['max_uncovered_fraction'],
-        select_best_candidate: bool = DEFAULT_PARAMS_VALUE['select_best_candidate'],
-        complementary_conditions: bool = DEFAULT_PARAMS_VALUE['complementary_conditions'],
-        max_rule_count: int = DEFAULT_PARAMS_VALUE['max_rule_count'],
+        minsupp_new: int = DEFAULT_PARAMS_VALUE["minsupp_new"],
+        max_growing: int = DEFAULT_PARAMS_VALUE["max_growing"],
+        enable_pruning: bool = DEFAULT_PARAMS_VALUE["enable_pruning"],
+        ignore_missing: bool = DEFAULT_PARAMS_VALUE["ignore_missing"],
+        max_uncovered_fraction: float = DEFAULT_PARAMS_VALUE["max_uncovered_fraction"],
+        select_best_candidate: bool = DEFAULT_PARAMS_VALUE["select_best_candidate"],
+        complementary_conditions: bool = DEFAULT_PARAMS_VALUE[
+            "complementary_conditions"
+        ],
+        max_rule_count: int = DEFAULT_PARAMS_VALUE["max_rule_count"],
     ):
         """
         Parameters
         ----------
         survival_time_attr : str
-            name of column containing survival time data (use when data passed to model is padnas
-            dataframe).
+            name of column containing survival time data (use when data passed to model
+            is padnas dataframe).
         minsupp_new : float = 5.0
-            a minimum number (or fraction, if value < 1.0) of previously uncovered examples
-             to be covered by a new rule (positive examples for classification problems); default: 5,
+            a minimum number (or fraction, if value < 1.0) of previously uncovered
+            examples to be covered by a new rule (positive examples for classification
+            problems); default: 5,
         max_growing : int = 0.0
-            non-negative integer representing maximum number of conditions which can be added to
-            the rule in the growing phase  (use this parameter for large datasets if execution time
-            is prohibitive); 0 indicates no limit; default: 0,
+            non-negative integer representing maximum number of conditions which can be
+            added to the rule in the growing phase  (use this parameter for large
+            datasets if execution time is prohibitive); 0 indicates no limit; default: 0
         enable_pruning : bool = True
             enable or disable pruning, default is True.
         ignore_missing : bool = False
-            boolean telling whether missing values should be ignored (by default, a missing value
-             of given attribute is always considered as not fulfilling the condition build upon that
-            attribute); default: False.
+            boolean telling whether missing values should be ignored (by default, a
+            missing value of given attribute is always considered as not fulfilling the
+            condition build upon that attribute); default: False.
         max_uncovered_fraction : float = 0.0
-            Floating-point number from [0,1] interval representing maximum fraction of examples
-             that may remain uncovered by the rule set, default: 0.0.
+            Floating-point number from [0,1] interval representing maximum fraction of
+            examples that may remain uncovered by the rule set, default: 0.0.
         select_best_candidate : bool = False
             Flag determining if best candidate should be selected from growing phase;
              default: False.
         complementary_conditions : bool = False
-            If enabled, complementary conditions in the form a = !{value} for nominal attributes
-            are supported.
+            If enabled, complementary conditions in the form a = !{value} for nominal
+            attributes are supported.
         max_rule_count : int = 0
-            Maximum number of rules to be generated (for classification data sets it applies
-             to a single class); 0 indicates no limit.
+            Maximum number of rules to be generated (for classification data sets it
+            applies to a single class); 0 indicates no limit.
         """
         self._params = None
         self._rule_generator = None
@@ -119,53 +128,53 @@ def __init__(  # pylint: disable=super-init-not-called,too-many-arguments
             max_uncovered_fraction=max_uncovered_fraction,
             select_best_candidate=select_best_candidate,
             complementary_conditions=complementary_conditions,
-            max_rule_count=max_rule_count
+            max_rule_count=max_rule_count,
         )
         self.model: RuleSet[SurvivalRule] = None
 
-    def set_params(
-        self,
-        **kwargs
-    ) -> object:
+    def set_params(self, **kwargs) -> object:
         """Set models hyperparameters. Parameters are the same as in constructor."""
-        self.survival_time_attr = kwargs.get('survival_time_attr')
+        self.survival_time_attr = kwargs.get("survival_time_attr")
         return BaseOperator.set_params(self, **kwargs)
 
     @staticmethod
     def _append_survival_time_columns(
-        values,
-        survival_time: Union[pd.Series, np.ndarray, list]
+        values, survival_time: Union[pd.Series, np.ndarray, list]
     ) -> Optional[str]:
         survival_time_attr: str = _DEFAULT_SURVIVAL_TIME_ATTR
-        if isinstance(values, pd.Series):
+        if isinstance(survival_time, pd.Series):
             if survival_time.name is None:
                 survival_time.name = survival_time_attr
             else:
                 survival_time_attr = survival_time.name
             values[survival_time.name] = survival_time
-        elif isinstance(values, np.ndarray):
+        elif isinstance(survival_time, np.ndarray):
             np.append(values, survival_time, axis=1)
-        elif isinstance(values, list):
+        elif isinstance(survival_time, list):
             for index, row in enumerate(values):
                 row.append(survival_time[index])
         else:
             raise ValueError(
-                'Data values must be instance of either pandas DataFrame, numpy array or list'
+                "Data values must be instance of either pandas DataFrame, numpy array"
+                " or list"
             )
         return survival_time_attr
 
-    def _prepare_survival_attribute(self, survival_time: Optional[Data], values: Data) -> str:
+    def _prepare_survival_attribute(
+        self, survival_time: Optional[Data], values: Data
+    ) -> str:
         if self.survival_time_attr is None and survival_time is None:
             raise ValueError(
-                'No "survival_time" attribute name was specified. ' +
-                'Specify it using method set_params'
+                'No "survival_time" attribute name was specified. '
+                + "Specify it using method set_params"
             )
         if survival_time is not None:
-            return SurvivalRules._append_survival_time_columns(
-                values, survival_time)
+            return SurvivalRules._append_survival_time_columns(values, survival_time)
         return self.survival_time_attr
 
-    def fit(self, values: Data, labels: Data, survival_time: Data = None) -> SurvivalRules:  # pylint: disable=arguments-differ
+    def fit(
+        self, values: Data, labels: Data, survival_time: Data = None
+    ) -> SurvivalRules:  # pylint: disable=arguments-differ
         """Train model on given dataset.
 
         Parameters
@@ -175,15 +184,16 @@ def fit(self, values: Data, labels: Data, survival_time: Data = None) -> Surviva
         labels : :class:`rulekit.operator.Data`
             survival status
         survival_time: :class:`rulekit.operator.Data`
-            data about survival time. Could be omitted when *survival_time_attr* parameter
-             was specified.
+            data about survival time. Could be omitted when *survival_time_attr*
+            parameter was specified.
 
         Returns
         -------
         self : SurvivalRules
         """
         survival_time_attribute = self._prepare_survival_attribute(
-            survival_time, values)
+            survival_time, values
+        )
         super().fit(values, labels, survival_time_attribute)
         return self
 
@@ -198,9 +208,9 @@ def predict(self, values: Data) -> np.ndarray:
         Returns
         -------
         result : np.ndarray
-            Each row represent single example from dataset and contains estimated survival function
-            for that example. Estimated survival function is returned as a dictionary containing
-             times and corresponding probabilities.
+            Each row represent single example from dataset and contains estimated
+            survival function for that example. Estimated survival function is returned
+            as a dictionary containing times and corresponding probabilities.
         """
         return PredictionResultMapper.map_survival(super().predict(values))
 
@@ -208,10 +218,10 @@ def score(self, values: Data, labels: Data, survival_time: Data = None) -> float
         """Return the Integrated Brier Score on the given dataset and labels
          (event status indicator).
 
-        Integrated Brier Score (IBS) - the Brier score (BS) represents the squared difference
-         between true event status at time T and predicted event status at that time;
-         the Integrated Brier score summarizes the prediction error over all observations and over
-         all times in a test set.
+        Integrated Brier Score (IBS) - the Brier score (BS) represents the squared
+        difference between true event status at time T and predicted event status at
+        that time; the Integrated Brier score summarizes the prediction error over all
+        observations and over all times in a test set.
 
         Parameters
         ----------
@@ -220,8 +230,8 @@ def score(self, values: Data, labels: Data, survival_time: Data = None) -> float
         labels : :class:`rulekit.operator.Data`
             survival status
         survival_time: :class:`rulekit.operator.Data`
-            data about survival time. Could be omitted when *survival_time_attr* parameter was
-            specified
+            data about survival time. Could be omitted when *survival_time_attr*
+            parameter was specified
 
         Returns
         -------
@@ -230,20 +240,23 @@ def score(self, values: Data, labels: Data, survival_time: Data = None) -> float
         """
 
         survival_time_attribute = self._prepare_survival_attribute(
-            survival_time, values)
+            survival_time, values
+        )
         example_set = ExampleSetFactory(self._get_problem_type()).make(
-            values, labels, survival_time_attribute=survival_time_attribute)
+            values, labels, survival_time_attribute=survival_time_attribute
+        )
 
-        predicted_example_set = self.model._java_object.apply(  # pylint: disable=protected-access
-            example_set
+        predicted_example_set = (
+            self.model._java_object.apply(  # pylint: disable=protected-access
+                example_set
+            )
         )
 
         IntegratedBrierScore = JClass(  # pylint: disable=invalid-name
-            'adaa.analytics.rules.logic.performance.IntegratedBrierScore'
+            "adaa.analytics.rules.logic.performance.IntegratedBrierScore"
         )
         integrated_brier_score = IntegratedBrierScore()
-        ibs = integrated_brier_score.countExample(
-            predicted_example_set).getValue()
+        ibs = integrated_brier_score.countExample(predicted_example_set).getValue()
         return float(ibs)
 
     def _get_problem_type(self) -> ProblemType:
@@ -258,68 +271,72 @@ class ExpertSurvivalRules(ExpertKnowledgeOperator, SurvivalRules):
     def __init__(  # pylint: disable=super-init-not-called,too-many-arguments,too-many-locals
         self,
         survival_time_attr: str = None,
-        minsupp_new: float = DEFAULT_PARAMS_VALUE['minsupp_new'],
-        max_growing: int = DEFAULT_PARAMS_VALUE['max_growing'],
-        enable_pruning: bool = DEFAULT_PARAMS_VALUE['enable_pruning'],
-        ignore_missing: bool = DEFAULT_PARAMS_VALUE['ignore_missing'],
-        max_uncovered_fraction: float = DEFAULT_PARAMS_VALUE['max_uncovered_fraction'],
-        select_best_candidate: bool = DEFAULT_PARAMS_VALUE['select_best_candidate'],
-        complementary_conditions: bool = DEFAULT_PARAMS_VALUE['complementary_conditions'],
-
-        extend_using_preferred: bool = DEFAULT_PARAMS_VALUE['extend_using_preferred'],
-        extend_using_automatic: bool = DEFAULT_PARAMS_VALUE['extend_using_automatic'],
-        induce_using_preferred: bool = DEFAULT_PARAMS_VALUE['induce_using_preferred'],
-        induce_using_automatic: bool = DEFAULT_PARAMS_VALUE['induce_using_automatic'],
+        minsupp_new: float = DEFAULT_PARAMS_VALUE["minsupp_new"],
+        max_growing: int = DEFAULT_PARAMS_VALUE["max_growing"],
+        enable_pruning: bool = DEFAULT_PARAMS_VALUE["enable_pruning"],
+        ignore_missing: bool = DEFAULT_PARAMS_VALUE["ignore_missing"],
+        max_uncovered_fraction: float = DEFAULT_PARAMS_VALUE["max_uncovered_fraction"],
+        select_best_candidate: bool = DEFAULT_PARAMS_VALUE["select_best_candidate"],
+        complementary_conditions: bool = DEFAULT_PARAMS_VALUE[
+            "complementary_conditions"
+        ],
+        extend_using_preferred: bool = DEFAULT_PARAMS_VALUE["extend_using_preferred"],
+        extend_using_automatic: bool = DEFAULT_PARAMS_VALUE["extend_using_automatic"],
+        induce_using_preferred: bool = DEFAULT_PARAMS_VALUE["induce_using_preferred"],
+        induce_using_automatic: bool = DEFAULT_PARAMS_VALUE["induce_using_automatic"],
         preferred_conditions_per_rule: int = DEFAULT_PARAMS_VALUE[
-            'preferred_conditions_per_rule'],
+            "preferred_conditions_per_rule"
+        ],
         preferred_attributes_per_rule: int = DEFAULT_PARAMS_VALUE[
-            'preferred_attributes_per_rule'],
-        max_rule_count: int = DEFAULT_PARAMS_VALUE['max_rule_count'],
+            "preferred_attributes_per_rule"
+        ],
+        max_rule_count: int = DEFAULT_PARAMS_VALUE["max_rule_count"],
     ):
         """
         Parameters
         ----------
         minsupp_new : float = 5.0
-            a minimum number (or fraction, if value < 1.0) of previously uncovered examples
-             to be covered by a new rule (positive examples for classification problems); default: 5,
+            a minimum number (or fraction, if value < 1.0) of previously uncovered
+            examples to be covered by a new rule (positive examples for classification
+            problems); default: 5,
         survival_time_attr : str
-            name of column containing survival time data (use when data passed to model is pandas
-            dataframe).
+            name of column containing survival time data (use when data passed to model
+            is pandas dataframe).
         max_growing : int = 0.0
-            non-negative integer representing maximum number of conditions which can be added to
-            the rule in the growing phase (use this parameter for large datasets if execution time
-            is prohibitive); 0 indicates no limit; default: 0,
+            non-negative integer representing maximum number of conditions which can be
+            added to the rule in the growing phase (use this parameter for large
+            datasets if execution time is prohibitive); 0 indicates no limit; default: 0
         enable_pruning : bool = True
             enable or disable pruning, default is True.
         ignore_missing : bool = False
-            boolean telling whether missing values should be ignored (by default, a missing value
-            of given attribute is always considered as not fulfilling the condition build upon that
-            attribute); default: False.
+            boolean telling whether missing values should be ignored (by default, a
+            missing value of given attribute is always considered as not fulfilling the
+            condition build upon that attribute); default: False.
         max_uncovered_fraction : float = 0.0
-            Floating-point number from [0,1] interval representing maximum fraction of examples
-             that may remain uncovered by the rule set, default: 0.0.
+            Floating-point number from [0,1] interval representing maximum fraction of
+            examples that may remain uncovered by the rule set, default: 0.0.
         select_best_candidate : bool = False
             Flag determining if best candidate should be selected from growing phase;
              default: False.
         complementary_conditions : bool = False
-            If enabled, complementary conditions in the form a = !{value} for nominal attributes
-            are supported.
+            If enabled, complementary conditions in the form a = !{value} for nominal
+            attributes are supported.
         max_rule_count : int = 0
-            Maximum number of rules to be generated (for classification data sets it applies
-             to a single class); 0 indicates no limit.
+            Maximum number of rules to be generated (for classification data sets it
+            applies to a single class); 0 indicates no limit.
 
         extend_using_preferred : bool = False
-            boolean indicating whether initial rules should be extended with a use of preferred
-            conditions and attributes; default is False
+            boolean indicating whether initial rules should be extended with a use of
+            preferred conditions and attributes; default is False
         extend_using_automatic : bool = False
-            boolean indicating whether initial rules should be extended with a use of automatic
-            conditions and attributes; default is False
+            boolean indicating whether initial rules should be extended with a use of
+            automatic conditions and attributes; default is False
         induce_using_preferred : bool = False
-            boolean indicating whether new rules should be induced with a use of preferred
-             conditions and attributes; default is False
+            boolean indicating whether new rules should be induced with a use of
+            preferred conditions and attributes; default is False
         induce_using_automatic : bool = False
-            boolean indicating whether new rules should be induced with a use of automatic
-             conditions and attributes; default is False
+            boolean indicating whether new rules should be induced with a use of
+            automatic conditions and attributes; default is False
         preferred_conditions_per_rule : int = None
             maximum number of preferred conditions per rule; default: unlimited,
         preferred_attributes_per_rule : int = None
@@ -344,15 +361,12 @@ def __init__(  # pylint: disable=super-init-not-called,too-many-arguments,too-ma
             preferred_conditions_per_rule=preferred_conditions_per_rule,
             preferred_attributes_per_rule=preferred_attributes_per_rule,
             complementary_conditions=complementary_conditions,
-            max_rule_count=max_rule_count
+            max_rule_count=max_rule_count,
         )
         self.model: RuleSet[SurvivalRule] = None
 
-    def set_params(  # pylint: disable=arguments-differ
-        self,
-        **kwargs
-    ) -> object:
-        self.survival_time_attr = kwargs['survival_time_attr']
+    def set_params(self, **kwargs) -> object:  # pylint: disable=arguments-differ
+        self.survival_time_attr = kwargs["survival_time_attr"]
         return ExpertKnowledgeOperator.set_params(self, **kwargs)
 
     def fit(  # pylint: disable=arguments-differ,too-many-arguments
@@ -360,10 +374,9 @@ def fit(  # pylint: disable=arguments-differ,too-many-arguments
         values: Data,
         labels: Data,
         survival_time: Data = None,
-
         expert_rules: list[Union[str, tuple[str, str]]] = None,
         expert_preferred_conditions: list[Union[str, tuple[str, str]]] = None,
-        expert_forbidden_conditions: list[Union[str, tuple[str, str]]] = None
+        expert_forbidden_conditions: list[Union[str, tuple[str, str]]] = None,
     ) -> ExpertSurvivalRules:
         """Train model on given dataset.
 
@@ -374,28 +387,30 @@ def fit(  # pylint: disable=arguments-differ,too-many-arguments
         labels : Data
             survival status
         survival_time: :class:`rulekit.operator.Data`
-            data about survival time. Could be omitted when *survival_time_attr* parameter was
-            specified.
-
+            data about survival time. Could be omitted when *survival_time_attr*
+            parameter was specified.
         expert_rules : List[Union[str, Tuple[str, str]]]
-            set of initial rules, either passed as a list of strings representing rules or as list
-            of tuples where first
-            element is name of the rule and second one is rule string.
+            set of initial rules, either passed as a list of strings representing rules
+            or as list of tuples where first element is name of the rule and second one
+            is rule string.
         expert_preferred_conditions : List[Union[str, Tuple[str, str]]]
-            multiset of preferred conditions (used also for specifying preferred attributes by
-             using special value Any). Either passed as a list of strings representing rules or as
-            list of tuples where first element is name of the rule and second one is rule string.
+            multiset of preferred conditions (used also for specifying preferred
+            attributes by using special value Any). Either passed as a list of strings
+            representing rules or as list of tuples where first element is name of the
+            rule and second one is rule string.
         expert_forbidden_conditions : List[Union[str, Tuple[str, str]]]
-            set of forbidden conditions (used also for specifying forbidden attributes by using
-             special valye Any). Either passed as a list of strings representing rules or as list
-            of tuples where first element is name of the rule and second one is rule string.
+            set of forbidden conditions (used also for specifying forbidden attributes
+            by using special valye Any). Either passed as a list of strings representing
+            rules or as list of tuples where first element is name of the rule and
+            second one is rule string.
 
         Returns
         -------
         self : ExpertSurvivalRules
         """
         survival_time_attribute = SurvivalRules._prepare_survival_attribute(
-            self, survival_time, values)
+            self, survival_time, values
+        )
         return ExpertKnowledgeOperator.fit(
             self,
             values=values,
@@ -403,11 +418,13 @@ def fit(  # pylint: disable=arguments-differ,too-many-arguments
             survival_time_attribute=survival_time_attribute,
             expert_rules=expert_rules,
             expert_preferred_conditions=expert_preferred_conditions,
-            expert_forbidden_conditions=expert_forbidden_conditions
+            expert_forbidden_conditions=expert_forbidden_conditions,
         )
 
     def predict(self, values: Data) -> np.ndarray:
-        return PredictionResultMapper.map_survival(ExpertKnowledgeOperator.predict(self, values))
+        return PredictionResultMapper.map_survival(
+            ExpertKnowledgeOperator.predict(self, values)
+        )
 
     def _get_problem_type(self) -> ProblemType:
         return ProblemType.SURVIVAL
@@ -424,65 +441,70 @@ class ContrastSetSurvivalRules(BaseOperator, _BaseSurvivalRulesModel):
 
     def __init__(  # pylint: disable=super-init-not-called,too-many-arguments
         self,
-        minsupp_all: Tuple[float, float, float,
-                           float] = DEFAULT_PARAMS_VALUE['minsupp_all'],
-        max_neg2pos: float = DEFAULT_PARAMS_VALUE['max_neg2pos'],
-        max_passes_count: int = DEFAULT_PARAMS_VALUE['max_passes_count'],
-        penalty_strength: float = DEFAULT_PARAMS_VALUE['penalty_strength'],
-        penalty_saturation: float = DEFAULT_PARAMS_VALUE['penalty_saturation'],
-
+        minsupp_all: Tuple[float, float, float, float] = DEFAULT_PARAMS_VALUE[
+            "minsupp_all"
+        ],
+        max_neg2pos: float = DEFAULT_PARAMS_VALUE["max_neg2pos"],
+        max_passes_count: int = DEFAULT_PARAMS_VALUE["max_passes_count"],
+        penalty_strength: float = DEFAULT_PARAMS_VALUE["penalty_strength"],
+        penalty_saturation: float = DEFAULT_PARAMS_VALUE["penalty_saturation"],
         survival_time_attr: str = None,
-        minsupp_new: float = DEFAULT_PARAMS_VALUE['minsupp_new'],
-        max_growing: int = DEFAULT_PARAMS_VALUE['max_growing'],
-        enable_pruning: bool = DEFAULT_PARAMS_VALUE['enable_pruning'],
-        ignore_missing: bool = DEFAULT_PARAMS_VALUE['ignore_missing'],
-        max_uncovered_fraction: float = DEFAULT_PARAMS_VALUE['max_uncovered_fraction'],
-        select_best_candidate: bool = DEFAULT_PARAMS_VALUE['select_best_candidate'],
-        complementary_conditions: bool = DEFAULT_PARAMS_VALUE['complementary_conditions'],
-        max_rule_count: int = DEFAULT_PARAMS_VALUE['max_rule_count'],
+        minsupp_new: float = DEFAULT_PARAMS_VALUE["minsupp_new"],
+        max_growing: int = DEFAULT_PARAMS_VALUE["max_growing"],
+        enable_pruning: bool = DEFAULT_PARAMS_VALUE["enable_pruning"],
+        ignore_missing: bool = DEFAULT_PARAMS_VALUE["ignore_missing"],
+        max_uncovered_fraction: float = DEFAULT_PARAMS_VALUE["max_uncovered_fraction"],
+        select_best_candidate: bool = DEFAULT_PARAMS_VALUE["select_best_candidate"],
+        complementary_conditions: bool = DEFAULT_PARAMS_VALUE[
+            "complementary_conditions"
+        ],
+        max_rule_count: int = DEFAULT_PARAMS_VALUE["max_rule_count"],
     ):
         """
         Parameters
         ----------
         minsupp_all: Tuple[float, float, float, float]
-            a minimum positive support of a contrast set (p/P). When multiple values are specified,
-            a metainduction is performed; Default and recommended sequence is: 0.8, 0.5, 0.2, 0.1
+            a minimum positive support of a contrast set (p/P). When multiple values are
+            specified, a metainduction is performed; Default and recommended sequence
+            is: 0.8, 0.5, 0.2, 0.1
         max_neg2pos: float
             a maximum ratio of negative to positive supports (nP/pN); Default is 0.5
         max_passes_count: int
-            a maximum number of sequential covering passes for a single minsupp-all; Default is 5
+            a maximum number of sequential covering passes for a single minsupp-all;
+            Default is 5
         penalty_strength: float
             (s) - penalty strength; Default is 0.5
         penalty_saturation: float
             the value of p_new / P at which penalty reward saturates; Default is 0.2.
         survival_time_attr : str
-            name of column containing survival time data (use when data passed to model is pandas
-            dataframe).
+            name of column containing survival time data (use when data passed to model
+            is pandas dataframe).
         minsupp_new : float = 5.0
-            a minimum number (or fraction, if value < 1.0) of previously uncovered examples
-             to be covered by a new rule (positive examples for classification problems); default: 5,
+            a minimum number (or fraction, if value < 1.0) of previously uncovered
+            examples to be covered by a new rule (positive examples for classification
+            problems); default: 5,
         max_growing : int = 0.0
-            non-negative integer representing maximum number of conditions which can be added to
-             the rule in the growing phase (use this parameter for large datasets if execution time
-            is prohibitive); 0 indicates no limit; default: 0,
+            non-negative integer representing maximum number of conditions which can be
+            added to the rule in the growing phase (use this parameter for large
+            datasets if execution time is prohibitive); 0 indicates no limit; default: 0
         enable_pruning : bool = True
             enable or disable pruning, default is True.
         ignore_missing : bool = False
-            boolean telling whether missing values should be ignored (by default, a missing value
-             of given attribute is always considered as not fulfilling the condition build upon that
-            attribute); default: False.
+            boolean telling whether missing values should be ignored (by default, a
+            missing value of given attribute is always considered as not fulfilling the
+            condition build upon that attribute); default: False.
         max_uncovered_fraction : float = 0.0
-            Floating-point number from [0,1] interval representing maximum fraction of examples
-             that may remain uncovered by the rule set, default: 0.0.
+            Floating-point number from [0,1] interval representing maximum fraction of
+            examples that may remain uncovered by the rule set, default: 0.0.
         select_best_candidate : bool = False
             Flag determining if best candidate should be selected from growing phase;
             default: False.
         complementary_conditions : bool = False
-            If enabled, complementary conditions in the form a = !{value} for nominal attributes
-            are supported.
+            If enabled, complementary conditions in the form a = !{value} for nominal
+            attributes are supported.
         max_rule_count : int = 0
-            Maximum number of rules to be generated (for classification data sets it applies
-             to a single class); 0 indicates no limit.
+            Maximum number of rules to be generated (for classification data sets it
+            applies to a single class); 0 indicates no limit.
         """
         self._params = None
         self._rule_generator = None
@@ -503,14 +525,14 @@ def __init__(  # pylint: disable=super-init-not-called,too-many-arguments
             max_uncovered_fraction=max_uncovered_fraction,
             select_best_candidate=select_best_candidate,
             complementary_conditions=complementary_conditions,
-            max_rule_count=max_rule_count
+            max_rule_count=max_rule_count,
         )
         self.model: RuleSet[SurvivalRule] = None
 
     def set_params(self, **kwargs) -> object:
         """Set models hyperparameters. Parameters are the same as in constructor."""
         # params validation
-        self.survival_time_attr = kwargs['survival_time_attr']
+        self.survival_time_attr = kwargs["survival_time_attr"]
         return BaseOperator.set_params(self, **kwargs)
 
     def fit(  # pylint: disable=arguments-renamed
@@ -518,7 +540,7 @@ def fit(  # pylint: disable=arguments-renamed
         values: Data,
         labels: Data,
         contrast_attribute: str,
-        survival_time: Data = None
+        survival_time: Data = None,
     ) -> ContrastSetSurvivalRules:
         """Train model on given dataset.
 
@@ -531,19 +553,22 @@ def fit(  # pylint: disable=arguments-renamed
         contrast_attribute: str
             group attribute
         survival_time: :class:`rulekit.operator.Data`
-            data about survival time. Could be omitted when *survival_time_attr* parameter
-             was specified.
+            data about survival time. Could be omitted when *survival_time_attr*
+            parameter was specified.
 
         Returns
         -------
         self : ContrastSetSurvivalRules
         """
         survival_time_attribute = SurvivalRules._prepare_survival_attribute(  # pylint: disable=protected-access
-            self, survival_time, values)
+            self, survival_time, values
+        )
         super().fit(
-            values, labels,
+            values,
+            labels,
             survival_time_attribute=survival_time_attribute,
-            contrast_attribute=contrast_attribute)
+            contrast_attribute=contrast_attribute,
+        )
         self.contrast_attribute = contrast_attribute
         return self
 
@@ -558,9 +583,9 @@ def predict(self, values: Data) -> np.ndarray:
         Returns
         -------
         result : np.ndarray
-            Each row represent single example from dataset and contains estimated survival function
-            for that example. Estimated survival function is returned as a dictionary containing
-             times and corresponding probabilities.
+            Each row represent single example from dataset and contains estimated
+            survival function for that example. Estimated survival function is returned
+            as a dictionary containing times and corresponding probabilities.
         """
         return PredictionResultMapper.map_survival(super().predict(values))
 
@@ -568,10 +593,10 @@ def score(self, values: Data, labels: Data, survival_time: Data = None) -> float
         """Return the Integrated Brier Score on the given dataset and
          labels(event status indicator).
 
-        Integrated Brier Score (IBS) - the Brier score (BS) represents the squared difference
-        between true event status at time T and predicted event status at that time;
-         the Integrated Brier score summarizes the prediction error over all observations and
-         over all times in a test set.
+        Integrated Brier Score (IBS) - the Brier score (BS) represents the squared
+        differencebetween true event status at time T and predicted event status at that
+        time; the Integrated Brier score summarizes the prediction error over all
+        observations and over all times in a test set.
 
         Parameters
         ----------
@@ -580,8 +605,8 @@ def score(self, values: Data, labels: Data, survival_time: Data = None) -> float
         labels : :class:`rulekit.operator.Data`
             survival status
         survival_time: :class:`rulekit.operator.Data`
-            data about survival time. Could be omitted when *survival_time_attr* parameter was
-            specified
+            data about survival time. Could be omitted when *survival_time_attr*
+            parameter was specified
 
         Returns
         -------
diff --git a/setup.cfg b/setup.cfg
index a2f3748..8e257e9 100644
--- a/setup.cfg
+++ b/setup.cfg
@@ -1,2 +1,5 @@
 [metadata]
-description-file = README.md
\ No newline at end of file
+description-file = README.md
+
+[flake8]
+max-line-length = 88
\ No newline at end of file
diff --git a/setup.py b/setup.py
index 88a01d9..7c12694 100644
--- a/setup.py
+++ b/setup.py
@@ -10,7 +10,7 @@
 
 setuptools.setup(
     name="rulekit",
-    version='2.1.21.0',
+    version='2.1.24.0',
     author="Cezary Maszczyk",
     author_email="cezary.maszczyk@gmail.com",
     description="Comprehensive suite for rule-based learning",
diff --git a/tests/additional_resources/salary.csv b/tests/additional_resources/salary.csv
new file mode 100644
index 0000000..798e7ad
--- /dev/null
+++ b/tests/additional_resources/salary.csv
@@ -0,0 +1,6705 @@
+Age,Gender,Education Level,Job Title,Years of Experience,Salary
+32.0,Male,Bachelor's,Software Engineer,5.0,below average
+28.0,Female,Master's,Data Analyst,3.0,below average
+45.0,Male,PhD,Senior Manager,15.0,above average
+36.0,Female,Bachelor's,Sales Associate,7.0,below average
+52.0,Male,Master's,Director,20.0,high
+29.0,Male,Bachelor's,Marketing Analyst,2.0,minimal
+42.0,Female,Master's,Product Manager,12.0,average
+31.0,Male,Bachelor's,Sales Manager,4.0,below average
+26.0,Female,Bachelor's,Marketing Coordinator,1.0,minimal
+38.0,Male,PhD,Senior Scientist,10.0,average
+29.0,Male,Master's,Software Developer,3.0,below average
+48.0,Female,Bachelor's,HR Manager,18.0,above average
+35.0,Male,Bachelor's,Financial Analyst,6.0,below average
+40.0,Female,Master's,Project Manager,14.0,above average
+27.0,Male,Bachelor's,Customer Service Rep,2.0,minimal
+44.0,Male,Bachelor's,Operations Manager,16.0,average
+33.0,Female,Master's,Marketing Manager,7.0,below average
+39.0,Male,PhD,Senior Engineer,12.0,average
+25.0,Female,Bachelor's,Data Entry Clerk,0.0,minimal
+51.0,Male,Bachelor's,Sales Director,22.0,high
+34.0,Female,Master's,Business Analyst,5.0,below average
+47.0,Male,Master's,VP of Operations,19.0,high
+30.0,Male,Bachelor's,IT Support,2.0,minimal
+36.0,Female,Bachelor's,Recruiter,9.0,below average
+41.0,Male,Master's,Financial Manager,13.0,above average
+28.0,Female,Bachelor's,Social Media Specialist,3.0,minimal
+37.0,Female,Master's,Software Manager,11.0,average
+24.0,Male,Bachelor's,Junior Developer,1.0,minimal
+43.0,Female,PhD,Senior Consultant,15.0,above average
+33.0,Male,Master's,Product Designer,6.0,below average
+50.0,Male,Bachelor's,CEO,25.0,high
+31.0,Female,Bachelor's,Accountant,4.0,minimal
+29.0,Male,Master's,Data Scientist,3.0,below average
+39.0,Female,Bachelor's,Marketing Specialist,10.0,below average
+46.0,Male,PhD,Senior Manager,20.0,high
+27.0,Male,Bachelor's,Technical Writer,2.0,minimal
+35.0,Female,Bachelor's,HR Generalist,7.0,below average
+42.0,Male,Master's,Project Engineer,14.0,average
+26.0,Female,Bachelor's,Customer Success Rep,1.0,minimal
+49.0,Male,Bachelor's,Sales Executive,21.0,above average
+34.0,Female,Master's,UX Designer,5.0,below average
+48.0,Male,Master's,Operations Director,18.0,high
+30.0,Male,Bachelor's,Network Engineer,3.0,below average
+36.0,Female,Bachelor's,Administrative Assistant,8.0,minimal
+41.0,Male,Master's,Strategy Consultant,13.0,above average
+28.0,Female,Bachelor's,Copywriter,2.0,minimal
+32.0,Male,Bachelor's,Account Manager,5.0,below average
+45.0,Female,Master's,Director of Marketing,16.0,high
+38.0,Male,PhD,Senior Scientist,11.0,average
+25.0,Male,Bachelor's,Help Desk Analyst,0.0,minimal
+51.0,Female,Bachelor's,Customer Service Manager,22.0,above average
+33.0,Male,Master's,Business Intelligence Analyst,7.0,below average
+40.0,Female,Bachelor's,Event Coordinator,12.0,below average
+47.0,Male,Master's,VP of Finance,19.0,high
+29.0,Female,Bachelor's,Graphic Designer,3.0,minimal
+36.0,Male,Bachelor's,Sales Manager,9.0,average
+27.0,Female,Master's,UX Researcher,2.0,below average
+43.0,Male,PhD,Senior Engineer,17.0,above average
+30.0,Female,Bachelor's,Social Media Manager,4.0,minimal
+35.0,Male,Master's,Product Manager,7.0,average
+51.0,Female,Master's,Director of Operations,23.0,high
+29.0,Male,Bachelor's,Marketing Analyst,3.0,minimal
+40.0,Female,Bachelor's,HR Manager,12.0,below average
+47.0,Male,PhD,Senior Data Scientist,21.0,high
+26.0,Male,Bachelor's,Junior Accountant,1.0,minimal
+38.0,Female,Master's,Digital Marketing Manager,10.0,below average
+46.0,Male,Bachelor's,IT Manager,19.0,average
+31.0,Female,Bachelor's,Customer Service Representative,5.0,minimal
+34.0,Male,Master's,Business Development Manager,8.0,below average
+49.0,Female,Master's,Senior Financial Analyst,18.0,above average
+33.0,Male,Bachelor's,Web Developer,6.0,below average
+39.0,Female,Bachelor's,Recruiter,11.0,below average
+45.0,Male,PhD,Research Director,16.0,high
+28.0,Male,Bachelor's,Technical Support Specialist,2.0,minimal
+42.0,Female,Master's,Creative Director,14.0,average
+37.0,Male,Bachelor's,Project Manager,10.0,average
+50.0,Female,Bachelor's,Operations Manager,22.0,above average
+32.0,Male,Master's,Senior Software Engineer,6.0,average
+48.0,Female,Master's,Human Resources Director,20.0,high
+30.0,Female,Bachelor's,Content Marketing Manager,3.0,minimal
+36.0,Male,Bachelor's,Technical Recruiter,8.0,below average
+41.0,Female,Master's,Data Analyst,13.0,below average
+25.0,Male,Bachelor's,Sales Representative,0.0,minimal
+52.0,Male,PhD,Chief Technology Officer,24.0,high
+29.0,Female,Bachelor's,Junior Designer,2.0,minimal
+34.0,Female,Master's,Financial Advisor,10.0,average
+27.0,Male,Bachelor's,Junior Account Manager,2.0,minimal
+40.0,Female,Bachelor's,HR Generalist,15.0,below average
+46.0,Male,Master's,Senior Project Manager,21.0,above average
+31.0,Female,Bachelor's,Marketing Coordinator,6.0,minimal
+36.0,Male,PhD,Principal Scientist,11.0,average
+29.0,Female,Bachelor's,Sales Associate,3.0,minimal
+43.0,Male,Bachelor's,Supply Chain Manager,18.0,average
+52.0,Female,Master's,Senior Marketing Manager,25.0,high
+33.0,Male,Bachelor's,Business Analyst,7.0,below average
+39.0,Female,Bachelor's,Training Specialist,12.0,below average
+47.0,Male,PhD,Research Scientist,22.0,above average
+26.0,Male,Bachelor's,Junior Software Developer,1.0,minimal
+38.0,Female,Master's,Public Relations Manager,10.0,below average
+45.0,Male,Bachelor's,Operations Analyst,20.0,average
+31.0,Female,Bachelor's,Event Coordinator,5.0,minimal
+35.0,Male,Master's,Product Marketing Manager,8.0,average
+49.0,Female,Master's,Senior HR Manager,19.0,above average
+33.0,Male,Bachelor's,Junior Web Developer,5.0,minimal
+39.0,Female,Master's,Senior Project Coordinator,13.0,below average
+44.0,Male,PhD,Chief Data Officer,16.0,high
+30.0,Female,Bachelor's,Digital Content Producer,3.0,minimal
+36.0,Male,Bachelor's,IT Support Specialist,7.0,below average
+41.0,Female,Master's,Senior Marketing Analyst,14.0,average
+28.0,Male,Bachelor's,Customer Success Manager,2.0,minimal
+42.0,Female,Master's,Senior Graphic Designer,15.0,average
+37.0,Male,Bachelor's,Software Project Manager,9.0,average
+50.0,Female,Bachelor's,Supply Chain Analyst,22.0,above average
+32.0,Male,Master's,Senior Business Analyst,6.0,below average
+23.0,Female,Bachelor's,Junior Marketing Analyst,0.5,minimal
+31.0,Male,Master's,Senior Financial Analyst,6.0,average
+40.0,Female,Bachelor's,Office Manager,15.0,below average
+48.0,Male,PhD,Principal Engineer,20.0,high
+29.0,Female,Bachelor's,Junior HR Generalist,3.0,minimal
+35.0,Male,Master's,Senior Product Manager,10.0,average
+42.0,Female,Bachelor's,Sales Manager,17.0,average
+53.0,Male,Master's,Director of Marketing,25.0,high
+33.0,Female,Bachelor's,Junior Operations Analyst,5.0,minimal
+38.0,Male,Bachelor's,Customer Service Manager,11.0,below average
+44.0,Female,PhD,Senior Scientist,16.0,above average
+26.0,Male,Bachelor's,Junior Accountant,2.0,minimal
+37.0,Female,Master's,Senior HR Generalist,9.0,average
+45.0,Male,Bachelor's,Sales Operations Manager,18.0,average
+32.0,Female,Bachelor's,Marketing Coordinator,4.0,minimal
+34.0,Male,Master's,Senior Software Developer,8.0,average
+50.0,Female,Master's,Director of Operations,21.0,above average
+29.0,Male,Bachelor's,Junior Web Designer,3.0,minimal
+40.0,Female,Master's,Senior Training Specialist,12.0,average
+47.0,Male,PhD,Senior Research Scientist,22.0,above average
+27.0,Male,Bachelor's,Junior Sales Representative,1.0,minimal
+39.0,Female,Bachelor's,Administrative Assistant,10.0,minimal
+46.0,Male,Master's,Senior Project Manager,19.0,above average
+30.0,Female,Bachelor's,Junior Marketing Manager,4.0,minimal
+36.0,Male,Bachelor's,Junior Data Analyst,7.0,below average
+43.0,Female,Master's,Senior Product Marketing Manager,14.0,average
+28.0,Male,Bachelor's,Junior Business Analyst,2.0,minimal
+41.0,Female,Master's,Senior Marketing Manager,13.0,average
+33.0,Male,Bachelor's,Junior Software Developer,5.0,minimal
+47.0,Male,Bachelor's,Senior Sales Manager,20.0,above average
+25.0,Female,Master's,Junior Marketing Specialist,1.5,minimal
+34.0,Male,Bachelor's,Senior Business Analyst,8.0,below average
+42.0,Female,PhD,Senior Data Scientist,16.0,above average
+31.0,Male,Bachelor's,Junior Project Manager,4.0,below average
+38.0,Female,Bachelor's,Senior Accountant,10.0,below average
+45.0,Male,Master's,Director of Sales,19.0,high
+29.0,Female,Bachelor's,Junior Recruiter,3.0,minimal
+36.0,Male,Master's,Senior Business Development Manager,11.0,average
+43.0,Female,PhD,Senior Product Designer,18.0,above average
+26.0,Male,Bachelor's,Junior Customer Support Specialist,2.0,minimal
+37.0,Female,Master's,Senior Marketing Analyst,9.0,average
+44.0,Male,Bachelor's,Senior IT Support Specialist,14.0,average
+32.0,Female,Bachelor's,Junior Financial Analyst,5.0,minimal
+33.0,Male,Master's,Senior Operations Manager,7.0,average
+51.0,Female,PhD,Director of Human Resources,23.0,high
+28.0,Male,Bachelor's,Junior Software Engineer,2.0,minimal
+39.0,Female,Bachelor's,Senior Sales Representative,12.0,below average
+48.0,Male,Master's,Director of Product Management,21.0,high
+30.0,Female,Bachelor's,Junior Copywriter,3.0,minimal
+35.0,Male,Bachelor's,Senior Marketing Coordinator,7.0,below average
+41.0,Female,Master's,Senior Human Resources Manager,13.0,average
+27.0,Male,Bachelor's,Junior Business Development Associate,1.5,minimal
+40.0,Female,Bachelor's,Senior Account Manager,14.0,average
+46.0,Male,PhD,Senior Researcher,18.0,above average
+31.0,Female,Bachelor's,Junior HR Coordinator,4.0,minimal
+34.0,Male,Master's,Senior Software Engineer,9.0,average
+50.0,Female,Master's,Director of Finance,20.0,high
+29.0,Male,Bachelor's,Junior Marketing Coordinator,2.0,minimal
+,,,,,average
+43.0,Male,Bachelor's,Senior Project Manager,16.0,above average
+26.0,Female,Master's,Junior Data Scientist,1.5,minimal
+35.0,Male,Bachelor's,Senior Operations Analyst,7.0,below average
+42.0,Female,PhD,Senior Marketing Manager,18.0,above average
+31.0,Male,Bachelor's,Junior Accountant,4.0,minimal
+38.0,Female,Bachelor's,Senior Human Resources Coordinator,10.0,below average
+46.0,Male,Master's,Director of Operations,20.0,high
+29.0,Female,Bachelor's,Junior Sales Representative,2.0,minimal
+37.0,Male,Master's,Senior Business Analyst,9.0,average
+44.0,Female,PhD,Senior UX Designer,15.0,above average
+27.0,Male,Bachelor's,Junior Product Manager,2.0,minimal
+36.0,Female,Bachelor's,Senior Marketing Specialist,8.0,below average
+43.0,Male,Bachelor's,Senior IT Project Manager,14.0,above average
+33.0,Female,Master's,Senior Financial Analyst,6.0,average
+34.0,Male,Bachelor's,Senior Quality Assurance Analyst,9.0,average
+50.0,Female,PhD,Director of Sales and Marketing,22.0,high
+28.0,Male,Bachelor's,Junior Operations Analyst,1.5,minimal
+39.0,Female,Bachelor's,Senior Account Executive,12.0,average
+47.0,Male,Master's,Director of Business Development,19.0,high
+30.0,Female,Bachelor's,Junior Social Media Manager,3.0,minimal
+34.0,Male,Bachelor's,Senior Product Manager,7.0,average
+40.0,Female,Master's,Senior Human Resources Specialist,13.0,average
+28.0,Male,Bachelor's,Junior Business Analyst,2.0,minimal
+41.0,Female,Bachelor's,Senior Marketing Coordinator,11.0,below average
+45.0,Male,PhD,Senior Data Analyst,17.0,above average
+32.0,Female,Bachelor's,Junior Account Manager,5.0,minimal
+35.0,Male,Master's,Senior Software Developer,9.0,average
+49.0,Female,Master's,Director of Human Capital,21.0,high
+30.0,Male,Bachelor's,Junior Advertising Coordinator,3.0,minimal
+44.0,Male,Bachelor's,Senior Sales Manager,16.0,above average
+27.0,Female,Master's,Junior UX Designer,1.5,minimal
+36.0,Male,Bachelor's,Senior Accountant,7.0,below average
+41.0,Female,PhD,Senior Marketing Director,17.0,above average
+31.0,Male,Bachelor's,Junior HR Generalist,4.0,minimal
+39.0,Female,Bachelor's,Senior Operations Manager,10.0,average
+47.0,Male,Master's,Director of Finance,20.0,high
+30.0,Female,Bachelor's,Junior Marketing Coordinator,2.0,minimal
+38.0,Male,Master's,Senior IT Consultant,9.0,average
+45.0,Female,PhD,Senior Product Designer,15.0,above average
+28.0,Male,Bachelor's,Junior Business Development Associate,2.0,minimal
+35.0,Female,Bachelor's,Senior Marketing Analyst,8.0,below average
+44.0,Male,Bachelor's,Senior Software Engineer,14.0,above average
+34.0,Female,Master's,Senior Financial Advisor,6.0,average
+35.0,Male,Bachelor's,Senior Project Coordinator,9.0,average
+50.0,Female,PhD,Director of Operations,22.0,high
+29.0,Male,Bachelor's,Junior Business Operations Analyst,1.5,minimal
+40.0,Female,Bachelor's,Senior Sales Representative,12.0,average
+48.0,Male,Master's,Director of Marketing,19.0,high
+31.0,Female,Bachelor's,Junior Social Media Specialist,3.0,minimal
+33.0,Male,Bachelor's,Senior Product Development Manager,7.0,average
+42.0,Female,Master's,Senior Human Resources Manager,13.0,above average
+28.0,Male,Bachelor's,Junior Financial Analyst,2.0,minimal
+40.0,Female,Bachelor's,Senior Marketing Manager,11.0,average
+46.0,Male,PhD,Senior Data Scientist,18.0,above average
+33.0,Female,Bachelor's,Junior Operations Manager,5.0,below average
+37.0,Male,Master's,Senior Software Architect,9.0,average
+51.0,Female,Master's,Director of Human Resources,21.0,high
+30.0,Male,Bachelor's,Junior Marketing Specialist,3.0,minimal
+43.0,Male,Bachelor's,Senior Project Manager,15.0,average
+27.0,Female,Master's,Junior Research Scientist,1.5,minimal
+35.0,Male,Bachelor's,Senior Operations Analyst,8.0,below average
+42.0,Female,PhD,Senior Marketing Manager,13.0,above average
+32.0,Male,Bachelor's,Junior Sales Representative,3.0,minimal
+37.0,Female,Bachelor's,Senior Financial Analyst,9.0,average
+45.0,Male,Master's,Senior Software Developer,16.0,above average
+33.0,Female,Bachelor's,Junior Operations Analyst,5.0,below average
+39.0,Male,Bachelor's,Senior Marketing Specialist,10.0,average
+44.0,Female,PhD,Senior HR Manager,18.0,above average
+29.0,Male,Bachelor's,Junior Business Analyst,1.5,minimal
+38.0,Female,Bachelor's,Senior Product Manager,10.0,average
+46.0,Male,PhD,Senior Data Analyst,19.0,above average
+34.0,Female,Bachelor's,Junior Marketing Analyst,6.0,below average
+36.0,Male,Bachelor's,Senior Operations Manager,8.0,average
+49.0,Female,Master's,Director of Marketing,21.0,high
+31.0,Male,Bachelor's,Junior Financial Analyst,3.0,minimal
+41.0,Female,Bachelor's,Senior Project Coordinator,11.0,average
+47.0,Male,Master's,Director of Operations,20.0,high
+30.0,Female,Bachelor's,Junior Marketing Coordinator,2.0,minimal
+38.0,Male,Master's,Senior IT Consultant,9.0,average
+45.0,Female,PhD,Senior Product Designer,15.0,above average
+28.0,Male,Bachelor's,Junior Business Development Associate,2.0,minimal
+35.0,Female,Bachelor's,Senior Marketing Analyst,8.0,below average
+44.0,Male,Bachelor's,Senior Software Engineer,14.0,above average
+34.0,Female,Master's,Senior Financial Advisor,6.0,average
+35.0,Male,Bachelor's,Senior Project Coordinator,9.0,average
+50.0,Female,PhD,Director of Operations,22.0,high
+29.0,Male,Bachelor's,Junior Business Operations Analyst,1.5,minimal
+,,,,,average
+37.0,Female,Bachelor's,Senior Financial Manager,10.0,average
+46.0,Male,PhD,Senior Data Scientist,18.0,above average
+31.0,Female,Bachelor's,Junior Marketing Coordinator,3.0,minimal
+42.0,Male,Bachelor's,Senior Operations Manager,12.0,average
+29.0,Female,Bachelor's,Junior Sales Representative,1.5,minimal
+36.0,Male,Bachelor's,Senior Marketing Specialist,8.0,average
+44.0,Female,Master's,Senior HR Specialist,15.0,above average
+33.0,Male,Bachelor's,Junior Operations Manager,4.0,below average
+39.0,Female,Bachelor's,Senior Marketing Coordinator,9.0,average
+45.0,Male,PhD,Senior Data Engineer,16.0,above average
+32.0,Female,Bachelor's,Junior Marketing Manager,4.0,below average
+37.0,Male,Bachelor's,Senior Financial Analyst,8.0,below average
+47.0,Female,Master's,Director of Marketing,20.0,high
+30.0,Male,Bachelor's,Junior Business Analyst,2.0,minimal
+38.0,Female,Bachelor's,Senior Project Manager,9.0,average
+46.0,Male,PhD,Senior Data Analyst,17.0,above average
+34.0,Female,Bachelor's,Junior Financial Analyst,5.0,below average
+36.0,Male,Bachelor's,Senior Product Manager,8.0,average
+49.0,Female,Master's,Director of Operations,21.0,high
+31.0,Male,Bachelor's,Junior Operations Analyst,3.0,minimal
+41.0,Female,Bachelor's,Senior Project Coordinator,11.0,average
+47.0,Male,Master's,Director of Marketing,19.0,high
+29.0,Female,Bachelor's,Junior Business Development Associate,1.5,minimal
+35.0,Male,Bachelor's,Senior Financial Manager,9.0,average
+44.0,Female,PhD,Senior Product Designer,15.0,above average
+33.0,Male,Bachelor's,Junior Business Analyst,4.0,below average
+35.0,Female,Bachelor's,Senior Marketing Analyst,8.0,below average
+44.0,Male,Bachelor's,Senior Software Engineer,13.0,above average
+32.0,Male,Bachelor's,Junior Product Manager,4.0,below average
+38.0,Female,Bachelor's,Senior Business Analyst,10.0,average
+49.0,Male,PhD,Director of Operations,21.0,high
+29.0,Female,Bachelor's,Junior Marketing Specialist,2.0,minimal
+35.0,Male,Bachelor's,Senior Business Development Manager,7.0,below average
+45.0,Female,Master's,Senior HR Manager,14.0,above average
+33.0,Male,Bachelor's,Junior Financial Analyst,4.0,below average
+40.0,Female,Bachelor's,Senior Marketing Manager,12.0,above average
+44.0,Male,PhD,Senior Data Scientist,16.0,above average
+30.0,Female,Bachelor's,Junior Operations Coordinator,2.0,minimal
+37.0,Male,Bachelor's,Senior Marketing Analyst,9.0,average
+48.0,Female,Master's,Director of HR,20.0,high
+31.0,Male,Bachelor's,Junior Project Manager,3.0,minimal
+38.0,Female,Bachelor's,Senior Operations Coordinator,9.0,average
+45.0,Male,PhD,Senior Data Engineer,16.0,above average
+33.0,Female,Bachelor's,Junior Marketing Manager,5.0,below average
+36.0,Male,Bachelor's,Senior Business Analyst,8.0,average
+49.0,Female,Master's,Director of Marketing,21.0,high
+31.0,Male,Bachelor's,Junior Operations Analyst,3.0,minimal
+42.0,Female,Bachelor's,Senior Project Manager,12.0,average
+47.0,Male,Master's,Director of Marketing,19.0,high
+29.0,Female,Bachelor's,Junior Business Development Associate,1.5,minimal
+35.0,Male,Bachelor's,Senior Financial Manager,9.0,average
+44.0,Female,PhD,Senior Product Designer,15.0,above average
+33.0,Male,Bachelor's,Junior Business Analyst,4.0,below average
+35.0,Female,Bachelor's,Senior Marketing Analyst,8.0,below average
+44.0,Male,Bachelor's,Senior Software Engineer,13.0,above average
+34.0,Female,Master's,Senior Financial Advisor,6.0,below average
+36.0,Male,Bachelor's,Senior Marketing Specialist,8.0,average
+30.0,Female,Bachelor's,Junior HR Coordinator,2.0,minimal
+37.0,Male,Bachelor's,Senior Business Development Manager,10.0,average
+45.0,Female,Master's,Senior Marketing Manager,16.0,above average
+32.0,Male,Bachelor's,Junior Financial Advisor,4.0,below average
+39.0,Female,Bachelor's,Senior Project Manager,12.0,above average
+47.0,Male,PhD,Director of Engineering,20.0,high
+29.0,Female,Bachelor's,Junior Marketing Analyst,2.0,minimal
+36.0,Male,Bachelor's,Senior Operations Manager,9.0,average
+43.0,Female,PhD,Senior Data Scientist,15.0,above average
+32.0,Male,Bachelor's,Junior Marketing Coordinator,3.0,minimal
+38.0,Female,Bachelor's,Senior Business Analyst,10.0,average
+48.0,Male,Master's,Director of Marketing,21.0,high
+31.0,Female,Bachelor's,Junior Business Development Associate,3.0,minimal
+40.0,Male,Bachelor's,Senior Financial Analyst,12.0,above average
+45.0,Female,PhD,Senior UX Designer,16.0,above average
+33.0,Male,Bachelor's,Junior Product Manager,4.0,below average
+36.0,Female,Bachelor's,Senior Marketing Manager,8.0,average
+47.0,Male,Master's,Director of Operations,19.0,high
+29.0,Female,Bachelor's,Junior Project Manager,2.0,minimal
+34.0,Male,Bachelor's,Senior Operations Coordinator,7.0,below average
+44.0,Female,PhD,Senior Business Analyst,15.0,above average
+33.0,Male,Bachelor's,Junior Marketing Specialist,5.0,below average
+35.0,Female,Bachelor's,Senior Financial Manager,8.0,below average
+43.0,Male,Master's,Director of Marketing,18.0,high
+31.0,Female,Bachelor's,Junior Financial Analyst,3.0,minimal
+41.0,Male,Bachelor's,Senior Product Manager,14.0,above average
+44.0,Female,PhD,Senior Data Engineer,16.0,above average
+33.0,Male,Bachelor's,Junior Business Analyst,4.0,below average
+35.0,Female,Bachelor's,Senior Marketing Analyst,8.0,below average
+45.0,Male,Master's,Director of Engineering,19.0,high
+28.0,Female,Bachelor's,Junior Operations Manager,1.0,minimal
+36.0,Male,Bachelor's,Senior Business Development Manager,8.0,average
+44.0,Female,PhD,Senior Data Scientist,16.0,above average
+31.0,Male,Bachelor's,Junior Marketing Coordinator,3.0,minimal
+38.0,Female,Bachelor's,Senior Business Analyst,10.0,average
+48.0,Male,Master's,Director of Marketing,21.0,high
+31.0,Female,Bachelor's,Junior Business Development Associate,3.0,minimal
+40.0,Male,Bachelor's,Senior Financial Analyst,12.0,above average
+45.0,Female,PhD,Senior UX Designer,16.0,above average
+33.0,Male,Bachelor's,Junior Product Manager,4.0,below average
+36.0,Female,Bachelor's,Senior Marketing Manager,8.0,average
+47.0,Male,Master's,Director of Operations,19.0,high
+29.0,Female,Bachelor's,Junior Project Manager,2.0,minimal
+34.0,Male,Bachelor's,Senior Operations Coordinator,7.0,below average
+44.0,Female,PhD,Senior Business Analyst,15.0,above average
+33.0,Male,Bachelor's,Junior Marketing Specialist,5.0,below average
+35.0,Female,Bachelor's,Senior Financial Manager,8.0,below average
+43.0,Male,Master's,Director of Marketing,18.0,high
+31.0,Female,Bachelor's,Junior Financial Analyst,3.0,minimal
+41.0,Male,Bachelor's,Senior Product Manager,14.0,above average
+44.0,Female,PhD,Senior Data Engineer,16.0,above average
+33.0,Male,Bachelor's,Junior Business Analyst,4.0,below average
+35.0,Female,Bachelor's,Senior Marketing Analyst,8.0,below average
+43.0,Male,Master's,Director of Operations,19.0,high
+29.0,Female,Bachelor's,Junior Project Manager,2.0,minimal
+34.0,Male,Bachelor's,Senior Operations Coordinator,7.0,below average
+44.0,Female,PhD,Senior Business Analyst,15.0,above average
+31.0,Male,Master's,Data Scientist,6.0,above average
+28.0,Female,Bachelor's,Software Engineer,3.0,average
+26.0,Male,Master's,Product Manager,2.0,average
+27.0,Female,Bachelor's,Data Analyst,2.0,average
+30.0,Male,PhD,Data Scientist,5.0,high
+29.0,Female,Bachelor's,Software Engineer,4.0,above average
+32.0,Male,Bachelor's,Product Manager,7.0,high
+25.0,Female,Master's,Data Analyst,1.0,average
+33.0,Male,PhD,Data Scientist,8.0,high
+31.0,Female,Bachelor's,Software Engineer,6.0,above average
+28.0,Male,Master's,Product Manager,3.0,above average
+30.0,Female,Bachelor's,Data Analyst,5.0,above average
+27.0,Male,PhD,Data Scientist,2.0,average
+29.0,Female,Bachelor's,Software Engineer,4.0,above average
+34.0,Male,Bachelor's,Product Manager,9.0,high
+25.0,Female,Master's,Data Analyst,1.0,average
+33.0,Male,PhD,Data Scientist,8.0,high
+31.0,Female,Bachelor's,Software Engineer,6.0,above average
+28.0,Male,Master's,Product Manager,3.0,above average
+30.0,Female,Bachelor's,Data Analyst,5.0,above average
+28.0,Male,Bachelor's,Software Engineer,3.0,average
+26.0,Female,Master's,Product Manager,2.0,average
+27.0,Male,Bachelor's,Data Analyst,2.0,average
+30.0,Female,PhD,Data Scientist,5.0,high
+29.0,Male,Bachelor's,Software Engineer,4.0,above average
+32.0,Male,Bachelor's,Product Manager,7.0,high
+25.0,Female,Master's,Data Analyst,1.0,average
+33.0,Male,PhD,Data Scientist,8.0,high
+31.0,Female,Bachelor's,Software Engineer,6.0,above average
+28.0,Male,Master's,Product Manager,3.0,above average
+30.0,Female,Bachelor's,Data Analyst,5.0,above average
+27.0,Male,PhD,Data Scientist,2.0,average
+29.0,Female,Bachelor's,Software Engineer,4.0,above average
+34.0,Male,Bachelor's,Product Manager,9.0,high
+25.0,Female,Master's,Data Analyst,1.0,average
+33.0,Male,PhD,Data Scientist,8.0,high
+31.0,Female,Bachelor's,Software Engineer,6.0,above average
+28.0,Male,Master's,Product Manager,3.0,above average
+30.0,Female,Bachelor's,Data Analyst,5.0,above average
+28.0,Male,Bachelor's,Software Engineer,3.0,average
+26.0,Female,Master's,Product Manager,2.0,average
+27.0,Male,Bachelor's,Data Analyst,2.0,average
+30.0,Female,PhD,Data Scientist,5.0,high
+29.0,Male,Bachelor's,Software Engineer,4.0,above average
+32.0,Male,Bachelor's,Product Manager,7.0,high
+25.0,Female,Master's,Data Analyst,1.0,average
+33.0,Male,PhD,Data Scientist,8.0,high
+31.0,Female,Bachelor's,Software Engineer,6.0,above average
+28.0,Male,Master's,Product Manager,3.0,above average
+30.0,Female,Bachelor's,Data Analyst,5.0,above average
+27.0,Male,PhD,Data Scientist,2.0,average
+29.0,Female,Bachelor's,Software Engineer,4.0,above average
+34.0,Male,Bachelor's,Product Manager,9.0,high
+25.0,Female,Master's,Data Analyst,1.0,average
+33.0,Male,PhD,Data Scientist,8.0,high
+31.0,Female,Bachelor's,Software Engineer,6.0,above average
+28.0,Male,Master's,Product Manager,3.0,above average
+30.0,Female,Bachelor's,Data Analyst,5.0,above average
+28.0,Male,Bachelor's,Software Engineer,3.0,average
+26.0,Female,Master's,Product Manager,2.0,average
+27.0,Male,Bachelor's,Data Analyst,2.0,average
+30.0,Female,PhD,Data Scientist,5.0,high
+29.0,Male,Bachelor's,Software Engineer,4.0,above average
+32.0,Male,Bachelor's,Product Manager,7.0,high
+25.0,Female,Master's,Data Analyst,1.0,average
+33.0,Male,PhD,Data Scientist,8.0,high
+31.0,Female,Bachelor's,Software Engineer,6.0,above average
+28.0,Male,Master's,Product Manager,3.0,above average
+30.0,Female,Bachelor's,Data Analyst,5.0,above average
+27.0,Male,PhD,Data Scientist,2.0,average
+29.0,Female,Bachelor's,Software Engineer,4.0,above average
+34.0,Male,Bachelor's,Product Manager,9.0,high
+25.0,Female,Master's,Data Analyst,1.0,average
+33.0,Male,PhD,Data Scientist,8.0,high
+31.0,Female,Bachelor's,Software Engineer,6.0,above average
+28.0,Male,Master's,Product Manager,3.0,above average
+30.0,Female,Bachelor's,Data Analyst,5.0,above average
+27.0,Male,PhD,Data Scientist,2.0,average
+29.0,Female,Bachelor's,Software Engineer,4.0,above average
+34.0,Male,Bachelor's,Product Manager,9.0,high
+25.0,Female,Master's,Data Analyst,1.0,average
+33.0,Male,PhD,Data Scientist,8.0,high
+31.0,Female,Bachelor's,Software Engineer,6.0,above average
+28.0,Male,Master's,Product Manager,3.0,above average
+30.0,Female,Bachelor's,Data Analyst,5.0,above average
+28.0,Male,Bachelor's,Software Engineer,3.0,average
+26.0,Female,Master's,Product Manager,2.0,average
+27.0,Male,Bachelor's,Data Analyst,2.0,average
+30.0,Female,PhD,Data Scientist,5.0,high
+29.0,Male,Bachelor's,Software Engineer,4.0,above average
+32.0,Male,Bachelor's,Product Manager,7.0,high
+25.0,Female,Master's,Data Analyst,1.0,average
+33.0,Male,PhD,Data Scientist,8.0,high
+31.0,Female,Bachelor's,Software Engineer,6.0,above average
+28.0,Male,Master's,Product Manager,3.0,above average
+30.0,Female,Bachelor's,Data Analyst,5.0,above average
+27.0,Male,PhD,Data Scientist,2.0,average
+29.0,Female,Bachelor's,Software Engineer,4.0,above average
+34.0,Male,Bachelor's,Product Manager,9.0,high
+25.0,Female,Master's,Data Analyst,1.0,average
+33.0,Male,PhD,Data Scientist,8.0,high
+31.0,Female,Bachelor's,Software Engineer,6.0,above average
+28.0,Male,Master's,Product Manager,3.0,above average
+30.0,Female,Bachelor's,Data Analyst,5.0,above average
+27.0,Male,PhD,Data Scientist,2.0,average
+29.0,Female,Bachelor's,Software Engineer,4.0,above average
+34.0,Male,Bachelor's,Product Manager,9.0,high
+25.0,Female,Master's,Data Analyst,1.0,average
+33.0,Male,PhD,Data Scientist,8.0,high
+31.0,Female,Bachelor's,Software Engineer,6.0,above average
+28.0,Male,Master's,Product Manager,3.0,above average
+30.0,Female,Bachelor's,Data Analyst,5.0,above average
+27.0,Male,PhD,Data Scientist,2.0,average
+29.0,Female,Bachelor's,Software Engineer,4.0,above average
+34.0,Male,Bachelor's,Product Manager,9.0,high
+25.0,Female,Master's,Data Analyst,1.0,average
+33.0,Male,PhD,Data Scientist,8.0,high
+31.0,Female,Bachelor's,Software Engineer,6.0,above average
+28.0,Male,Master's,Product Manager,3.0,above average
+30.0,Female,Bachelor's,Data Analyst,5.0,above average
+27.0,Male,PhD,Data Scientist,2.0,average
+29.0,Female,Bachelor's,Software Engineer,4.0,above average
+34.0,Male,Bachelor's,Product Manager,9.0,high
+25.0,Female,Master's,Data Analyst,1.0,average
+33.0,Male,PhD,Data Scientist,8.0,high
+31.0,Female,Bachelor's,Software Engineer,6.0,above average
+28.0,Male,Master's,Product Manager,3.0,above average
+30.0,Female,Bachelor's,Data Analyst,5.0,above average
+27.0,Male,PhD,Data Scientist,2.0,average
+29.0,Female,Bachelor's,Software Engineer,4.0,above average
+34.0,Male,Bachelor's,Product Manager,9.0,high
+26.0,Male,Bachelor's,Data Analyst,3.0,above average
+29.0,Female,Master's,Data Scientist,6.0,high
+32.0,Male,Bachelor's,Software Engineer,8.0,high
+27.0,Female,Bachelor's,Product Manager,4.0,above average
+24.0,Male,Bachelor's,Data Analyst,1.0,below average
+31.0,Female,Master's,Data Scientist,9.0,high
+28.0,Male,Bachelor's,Software Engineer,5.0,above average
+33.0,Female,Master's,Product Manager,11.0,high
+25.0,Male,Bachelor's,Data Analyst,2.0,average
+30.0,Female,PhD,Data Scientist,7.0,high
+27.0,Male,Bachelor's,Software Engineer,4.0,above average
+34.0,Female,Master's,Product Manager,12.0,high
+23.0,Male,Bachelor's,Data Analyst,1.0,average
+32.0,Female,PhD,Data Scientist,10.0,high
+29.0,Male,Bachelor's,Software Engineer,6.0,high
+30.0,Female,Bachelor's,Product Manager,5.0,above average
+26.0,Male,Bachelor's,Data Analyst,3.0,above average
+31.0,Female,Master's,Data Scientist,6.0,high
+28.0,Male,Bachelor's,Software Engineer,5.0,above average
+33.0,Female,Master's,Product Manager,11.0,high
+24.0,Male,Bachelor's,Data Analyst,1.0,below average
+30.0,Female,PhD,Data Scientist,7.0,high
+27.0,Male,Bachelor's,Software Engineer,4.0,above average
+34.0,Female,Master's,Product Manager,12.0,high
+25.0,Male,Bachelor's,Data Analyst,2.0,average
+29.0,Female,Master's,Data Scientist,6.0,high
+32.0,Male,Bachelor's,Software Engineer,8.0,high
+27.0,Female,Bachelor's,Product Manager,4.0,above average
+31.0,Male,Bachelor's,Data Analyst,9.0,high
+28.0,Female,Bachelor's,Software Engineer,5.0,above average
+33.0,Male,Master's,Product Manager,11.0,high
+26.0,Female,Bachelor's,Data Analyst,3.0,above average
+30.0,Male,PhD,Data Scientist,7.0,high
+27.0,Female,Bachelor's,Software Engineer,4.0,above average
+34.0,Male,Master's,Product Manager,12.0,high
+25.0,Female,Bachelor's,Data Analyst,2.0,average
+32.0,Male,Bachelor's,Software Engineer,8.0,high
+29.0,Female,Master's,Data Scientist,6.0,high
+30.0,Male,Bachelor's,Data Analyst,5.0,above average
+33.0,Female,Master's,Product Manager,11.0,high
+24.0,Male,Bachelor's,Data Analyst,1.0,below average
+31.0,Female,PhD,Data Scientist,9.0,high
+28.0,Male,Bachelor's,Software Engineer,5.0,above average
+27.0,Female,Bachelor's,Product Manager,4.0,above average
+26.0,Male,Bachelor's,Data Analyst,3.0,above average
+29.0,Female,Master's,Data Scientist,6.0,high
+32.0,Male,Bachelor's,Software Engineer,8.0,high
+33.0,Female,Master's,Product Manager,11.0,high
+25.0,Male,Bachelor's,Data Analyst,2.0,average
+30.0,Female,PhD,Data Scientist,7.0,high
+27.0,Male,Bachelor's,Software Engineer,4.0,above average
+34.0,Female,Master's,Product Manager,12.0,high
+31.0,Male,Bachelor's,Data Analyst,9.0,high
+28.0,Female,Bachelor's,Software Engineer,5.0,above average
+26.0,Male,Bachelor's,Data Analyst,3.0,above average
+29.0,Female,Master's,Data Scientist,6.0,high
+32.0,Male,Bachelor's,Software Engineer,8.0,high
+33.0,Female,Master's,Product Manager,11.0,high
+24.0,Male,Bachelor's,Data Analyst,1.0,below average
+27.0,Male,Bachelor's,Software Engineer,4.0,above average
+25.0,Female,Bachelor's,Data Analyst,2.0,average
+30.0,Female,PhD,Data Scientist,7.0,high
+31.0,Male,Bachelor's,Data Analyst,9.0,high
+28.0,Female,Bachelor's,Software Engineer,5.0,above average
+26.0,Male,Bachelor's,Data Analyst,3.0,above average
+29.0,Female,Master's,Data Scientist,6.0,high
+32.0,Male,Bachelor's,Software Engineer,8.0,high
+33.0,Female,Master's,Product Manager,11.0,high
+24.0,Male,Bachelor's,Data Analyst,1.0,below average
+27.0,Male,Bachelor's,Software Engineer,4.0,above average
+25.0,Female,Bachelor's,Data Analyst,2.0,average
+30.0,Female,PhD,Data Scientist,7.0,high
+31.0,Male,Bachelor's,Data Analyst,9.0,high
+28.0,Female,Bachelor's,Software Engineer,5.0,above average
+26.0,Male,Bachelor's,Data Analyst,3.0,above average
+29.0,Female,Master's,Data Scientist,6.0,high
+32.0,Male,Bachelor's,Software Engineer,8.0,high
+33.0,Female,Master's,Product Manager,11.0,high
+24.0,Male,Bachelor's,Data Analyst,1.0,below average
+27.0,Male,Bachelor's,Software Engineer,4.0,above average
+25.0,Female,Bachelor's,Data Analyst,2.0,average
+30.0,Female,PhD,Data Scientist,7.0,high
+31.0,Male,Bachelor's,Data Analyst,9.0,high
+28.0,Female,Bachelor's,Software Engineer,5.0,above average
+26.0,Male,Bachelor's,Data Analyst,3.0,above average
+29.0,Female,Master's,Data Scientist,6.0,high
+32.0,Male,Bachelor's,Software Engineer,8.0,high
+33.0,Female,Master's,Product Manager,11.0,high
+24.0,Male,Bachelor's,Data Analyst,1.0,below average
+27.0,Male,Bachelor's,Software Engineer,4.0,above average
+25.0,Male,Bachelor's,Data Analyst,2.0,average
+28.0,Female,Master's,Data Scientist,6.0,high
+30.0,Male,Bachelor's,Software Engineer,8.0,high
+27.0,Female,Bachelor's,Product Manager,4.0,above average
+24.0,Male,Bachelor's,Data Analyst,1.0,average
+31.0,Male,Master's,Data Scientist,9.0,high
+28.0,Male,Bachelor's,Software Engineer,5.0,above average
+33.0,Female,Master's,Product Manager,11.0,high
+26.0,Male,Bachelor's,Data Analyst,3.0,above average
+30.0,Female,PhD,Data Scientist,7.0,high
+27.0,Male,Bachelor's,Software Engineer,4.0,above average
+34.0,Female,Master's,Product Manager,12.0,high
+23.0,Male,Bachelor's,Data Analyst,1.0,below average
+32.0,Female,PhD,Data Scientist,10.0,high
+29.0,Male,Bachelor's,Software Engineer,6.0,high
+30.0,Female,Bachelor's,Product Manager,5.0,above average
+26.0,Male,Bachelor's,Data Analyst,3.0,above average
+31.0,Female,Master's,Data Scientist,6.0,high
+28.0,Male,Bachelor's,Software Engineer,5.0,above average
+33.0,Female,Master's,Product Manager,11.0,high
+24.0,Male,Bachelor's,Data Analyst,1.0,below average
+30.0,Female,PhD,Data Scientist,7.0,high
+27.0,Male,Bachelor's,Software Engineer,4.0,above average
+34.0,Female,Master's,Product Manager,12.0,high
+25.0,Male,Bachelor's,Data Analyst,2.0,average
+29.0,Female,Master's,Data Scientist,6.0,high
+32.0,Male,Bachelor's,Software Engineer,8.0,high
+27.0,Female,Bachelor's,Product Manager,4.0,above average
+31.0,Male,Bachelor's,Data Analyst,9.0,high
+28.0,Female,Bachelor's,Software Engineer,5.0,above average
+33.0,Male,Master's,Product Manager,11.0,high
+26.0,Female,Bachelor's,Data Analyst,3.0,above average
+30.0,Male,PhD,Data Scientist,7.0,high
+27.0,Female,Bachelor's,Software Engineer,4.0,above average
+34.0,Male,Master's,Product Manager,12.0,high
+25.0,Female,Bachelor's,Data Analyst,2.0,average
+32.0,Male,Bachelor's,Software Engineer,8.0,high
+29.0,Female,Master's,Data Scientist,6.0,high
+30.0,Male,Bachelor's,Data Analyst,5.0,above average
+33.0,Female,Master's,Product Manager,11.0,high
+24.0,Male,Bachelor's,Data Analyst,1.0,below average
+31.0,Female,PhD,Data Scientist,9.0,high
+28.0,Male,Bachelor's,Software Engineer,5.0,above average
+27.0,Female,Bachelor's,Product Manager,4.0,above average
+26.0,Male,Bachelor's,Data Analyst,3.0,above average
+29.0,Female,Master's,Data Scientist,6.0,high
+32.0,Male,Bachelor's,Software Engineer,8.0,high
+33.0,Female,Master's,Product Manager,11.0,high
+25.0,Male,Bachelor's,Data Analyst,2.0,average
+30.0,Female,PhD,Data Scientist,7.0,high
+27.0,Male,Bachelor's,Software Engineer,4.0,above average
+34.0,Female,Master's,Product Manager,12.0,high
+31.0,Male,Bachelor's,Data Analyst,9.0,high
+28.0,Female,Bachelor's,Software Engineer,5.0,above average
+26.0,Male,Bachelor's,Data Analyst,3.0,above average
+29.0,Female,Master's,Data Scientist,6.0,high
+32.0,Male,Bachelor's,Software Engineer,8.0,high
+33.0,Female,Master's,Product Manager,11.0,high
+24.0,Male,Bachelor's,Data Analyst,1.0,below average
+27.0,Male,Bachelor's,Software Engineer,4.0,above average
+25.0,Female,Bachelor's,Data Analyst,2.0,average
+30.0,Female,PhD,Data Scientist,7.0,high
+31.0,Male,Bachelor's,Data Analyst,9.0,high
+28.0,Female,Bachelor's,Software Engineer,5.0,above average
+26.0,Male,Bachelor's,Data Analyst,3.0,above average
+29.0,Female,Master's,Data Scientist,6.0,high
+32.0,Male,Bachelor's,Software Engineer,8.0,high
+33.0,Female,Master's,Product Manager,11.0,high
+24.0,Male,Bachelor's,Data Analyst,1.0,below average
+27.0,Male,Bachelor's,Software Engineer,4.0,above average
+25.0,Female,Bachelor's,Data Analyst,2.0,average
+30.0,Female,PhD,Data Scientist,7.0,high
+31.0,Male,Bachelor's,Data Analyst,9.0,high
+28.0,Female,Bachelor's,Software Engineer,5.0,above average
+26.0,Male,Bachelor's,Data Analyst,3.0,above average
+29.0,Female,Master's,Data Scientist,6.0,high
+32.0,Male,Bachelor's,Software Engineer,8.0,high
+33.0,Female,Master's,Product Manager,11.0,high
+24.0,Male,Bachelor's,Data Analyst,1.0,below average
+27.0,Male,Bachelor's,Software Engineer,4.0,above average
+23.0,Male,Bachelor's,Data Analyst,1.0,below average
+27.0,Female,Master's,Data Scientist,4.0,above average
+32.0,Male,Bachelor's,Software Engineer,8.0,high
+24.0,Female,Bachelor's,Product Manager,3.0,average
+25.0,Male,Bachelor's,Data Analyst,2.0,average
+31.0,Male,Master's,Data Scientist,7.0,high
+28.0,Male,Bachelor's,Software Engineer,5.0,above average
+33.0,Female,Master's,Product Manager,10.0,high
+26.0,Male,Bachelor's,Data Analyst,3.0,above average
+30.0,Female,PhD,Data Scientist,6.0,high
+27.0,Male,Bachelor's,Software Engineer,4.0,above average
+34.0,Female,Master's,Product Manager,11.0,high
+23.0,Male,Bachelor's,Data Analyst,1.0,below average
+32.0,Female,PhD,Data Scientist,9.0,high
+29.0,Male,Bachelor's,Software Engineer,6.0,high
+30.0,Female,Bachelor's,Product Manager,5.0,above average
+26.0,Male,Bachelor's,Data Analyst,3.0,above average
+31.0,Female,Master's,Data Scientist,6.0,high
+28.0,Male,Bachelor's,Software Engineer,5.0,above average
+33.0,Female,Master's,Product Manager,11.0,high
+24.0,Male,Bachelor's,Data Analyst,1.0,average
+30.0,Female,PhD,Data Scientist,7.0,high
+27.0,Male,Bachelor's,Software Engineer,4.0,above average
+34.0,Female,Master's,Product Manager,12.0,high
+25.0,Male,Bachelor's,Data Analyst,2.0,average
+29.0,Female,Master's,Data Scientist,6.0,high
+32.0,Male,Bachelor's,Software Engineer,8.0,high
+27.0,Female,Bachelor's,Product Manager,4.0,above average
+31.0,Male,Bachelor's,Data Analyst,9.0,high
+28.0,Female,Bachelor's,Software Engineer,5.0,above average
+33.0,Male,Master's,Product Manager,11.0,high
+26.0,Female,Bachelor's,Data Analyst,3.0,above average
+30.0,Male,PhD,Data Scientist,7.0,high
+27.0,Female,Bachelor's,Software Engineer,4.0,above average
+34.0,Male,Master's,Product Manager,12.0,high
+25.0,Female,Bachelor's,Data Analyst,2.0,average
+32.0,Male,Bachelor's,Software Engineer,8.0,high
+29.0,Female,Master's,Data Scientist,6.0,high
+30.0,Male,Bachelor's,Data Analyst,5.0,above average
+33.0,Female,Master's,Product Manager,11.0,high
+24.0,Male,Bachelor's,Data Analyst,1.0,below average
+31.0,Female,PhD,Data Scientist,9.0,high
+28.0,Male,Bachelor's,Software Engineer,5.0,above average
+27.0,Female,Bachelor's,Product Manager,4.0,above average
+26.0,Male,Bachelor's,Data Analyst,3.0,above average
+29.0,Female,Master's,Data Scientist,6.0,high
+32.0,Male,Bachelor's,Software Engineer,8.0,high
+33.0,Female,Master's,Product Manager,11.0,high
+25.0,Male,Bachelor's,Data Analyst,2.0,average
+30.0,Female,PhD,Data Scientist,7.0,high
+27.0,Male,Bachelor's,Software Engineer,4.0,above average
+34.0,Female,Master's,Product Manager,12.0,high
+31.0,Male,Bachelor's,Data Analyst,9.0,high
+28.0,Female,Bachelor's,Software Engineer,5.0,above average
+26.0,Male,Bachelor's,Data Analyst,3.0,above average
+29.0,Female,Master's,Data Scientist,6.0,high
+32.0,Male,Bachelor's,Software Engineer,8.0,high
+33.0,Female,Master's,Product Manager,11.0,high
+24.0,Male,Bachelor's,Data Analyst,1.0,below average
+27.0,Male,Bachelor's,Software Engineer,4.0,above average
+25.0,Female,Bachelor's,Data Analyst,2.0,average
+30.0,Female,PhD,Data Scientist,7.0,high
+31.0,Male,Bachelor's,Data Analyst,9.0,high
+28.0,Female,Bachelor's,Software Engineer,5.0,above average
+26.0,Male,Bachelor's,Data Analyst,3.0,above average
+29.0,Female,Master's,Data Scientist,6.0,high
+32.0,Male,Bachelor's,Software Engineer,8.0,high
+33.0,Female,Master's,Product Manager,11.0,high
+24.0,Male,Bachelor's,Data Analyst,1.0,below average
+27.0,Male,Bachelor's,Software Engineer,4.0,above average
+25.0,Female,Bachelor's,Data Analyst,2.0,average
+30.0,Female,PhD,Data Scientist,7.0,high
+31.0,Male,Bachelor's,Data Analyst,9.0,high
+28.0,Female,Bachelor's,Software Engineer,5.0,above average
+26.0,Male,Bachelor's,Data Analyst,3.0,above average
+29.0,Female,Master's,Data Scientist,6.0,high
+32.0,Male,Bachelor's,Software Engineer,8.0,high
+33.0,Female,Master's,Product Manager,11.0,high
+24.0,Male,Bachelor's,Data Analyst,1.0,below average
+27.0,Male,Bachelor's,Software Engineer,4.0,above average
+25.0,Female,Bachelor's,Data Analyst,2.0,average
+30.0,Female,PhD,Data Scientist,7.0,high
+31.0,Male,Bachelor's,Data Analyst,9.0,high
+28.0,Female,Bachelor's,Software Engineer,5.0,above average
+26.0,Male,Bachelor's,Data Analyst,3.0,above average
+29.0,Female,Master's,Data Scientist,6.0,high
+32.0,Male,Bachelor's,Software Engineer,8.0,high
+33.0,Female,Master's,Product Manager,11.0,high
+24.0,Male,Bachelor's,Data Analyst,1.0,below average
+27.0,Male,Bachelor's,Software Engineer,4.0,above average
+25.0,Female,Bachelor's,Data Analyst,2.0,average
+30.0,Female,PhD,Data Scientist,7.0,high
+31.0,Male,Bachelor's,Data Analyst,9.0,high
+28.0,Female,Bachelor's,Software Engineer,5.0,above average
+26.0,Male,Bachelor's,Data Analyst,3.0,above average
+29.0,Female,Master's,Data Scientist,6.0,high
+32.0,Male,Bachelor's,Software Engineer,8.0,high
+33.0,Female,Master's,Product Manager,11.0,high
+24.0,Male,Bachelor's,Data Analyst,1.0,below average
+27.0,Male,Bachelor's,Software Engineer,4.0,above average
+25.0,Female,Bachelor's,Data Analyst,2.0,average
+30.0,Female,PhD,Data Scientist,7.0,high
+31.0,Male,Bachelor's,Data Analyst,9.0,high
+28.0,Female,Bachelor's,Software Engineer,5.0,above average
+26.0,Male,Bachelor's,Data Analyst,3.0,above average
+29.0,Female,Master's,Data Scientist,6.0,high
+32.0,Male,Bachelor's,Software Engineer,8.0,high
+33.0,Female,Master's,Product Manager,11.0,high
+24.0,Male,Bachelor's,Data Analyst,1.0,below average
+27.0,Male,Bachelor's,Software Engineer,4.0,above average
+25.0,Female,Bachelor's,Data Analyst,2.0,average
+30.0,Female,PhD,Data Scientist,7.0,high
+31.0,Male,Bachelor's,Data Analyst,9.0,high
+28.0,Female,Bachelor's,Software Engineer,5.0,above average
+26.0,Male,Bachelor's,Data Analyst,3.0,above average
+29.0,Female,Master's,Data Scientist,6.0,high
+32.0,Male,Bachelor's,Software Engineer,8.0,high
+33.0,Female,Master's,Product Manager,11.0,high
+24.0,Male,Bachelor's,Data Analyst,1.0,below average
+27.0,Male,Bachelor's,Software Engineer,4.0,above average
+25.0,Female,Bachelor's,Data Analyst,2.0,average
+30.0,Female,PhD,Data Scientist,7.0,high
+31.0,Male,Bachelor's,Data Analyst,9.0,high
+28.0,Female,Bachelor's,Software Engineer,5.0,above average
+26.0,Male,Bachelor's,Data Analyst,3.0,above average
+29.0,Female,Master's,Data Scientist,6.0,high
+32.0,Male,Bachelor's,Software Engineer,8.0,high
+33.0,Female,Master's,Product Manager,11.0,high
+24.0,Male,Bachelor's,Data Analyst,1.0,below average
+27.0,Male,Bachelor's,Software Engineer,4.0,above average
+25.0,Female,Bachelor's,Data Analyst,2.0,average
+30.0,Female,PhD,Data Scientist,7.0,high
+31.0,Male,Bachelor's,Data Analyst,9.0,high
+28.0,Female,Bachelor's,Software Engineer,5.0,above average
+25.0,Male,Bachelor's,Data Analyst,3.0,above average
+32.0,Male,Bachelor's,Software Engineer,8.0,high
+29.0,Female,Master's,Data Scientist,6.0,high
+30.0,Male,Bachelor's,Data Analyst,5.0,above average
+24.0,Male,Bachelor's,Data Analyst,1.0,average
+33.0,Female,Master's,Product Manager,11.0,high
+27.0,Male,Bachelor's,Software Engineer,4.0,above average
+26.0,Male,Bachelor's,Data Analyst,3.0,above average
+30.0,Female,PhD,Data Scientist,7.0,high
+31.0,Male,Bachelor's,Data Analyst,9.0,high
+28.0,Female,Bachelor's,Software Engineer,5.0,above average
+26.0,Female,Bachelor's,Data Analyst,3.0,above average
+30.0,Male,PhD,Data Scientist,7.0,high
+27.0,Female,Bachelor's,Product Manager,4.0,above average
+24.0,Male,Bachelor's,Data Analyst,1.0,below average
+33.0,Male,Master's,Product Manager,11.0,high
+25.0,Male,Bachelor's,Data Analyst,2.0,average
+28.0,Male,Bachelor's,Software Engineer,5.0,above average
+26.0,Male,Bachelor's,Data Analyst,3.0,above average
+29.0,Female,Master's,Data Scientist,6.0,high
+32.0,Male,Bachelor's,Software Engineer,8.0,high
+33.0,Female,Master's,Product Manager,11.0,high
+27.0,Male,Bachelor's,Software Engineer,4.0,above average
+31.0,Female,Master's,Data Scientist,6.0,high
+30.0,Male,Bachelor's,Data Analyst,5.0,above average
+24.0,Male,Bachelor's,Data Analyst,1.0,below average
+28.0,Female,Bachelor's,Software Engineer,5.0,above average
+26.0,Male,Bachelor's,Data Analyst,3.0,above average
+32.0,Male,Bachelor's,Software Engineer,8.0,high
+33.0,Female,Master's,Product Manager,11.0,high
+25.0,Male,Bachelor's,Data Analyst,2.0,average
+30.0,Female,PhD,Data Scientist,7.0,high
+27.0,Male,Bachelor's,Software Engineer,4.0,above average
+34.0,Female,Master's,Product Manager,12.0,high
+31.0,Male,Bachelor's,Data Analyst,9.0,high
+28.0,Female,Bachelor's,Software Engineer,5.0,above average
+26.0,Male,Bachelor's,Data Analyst,3.0,above average
+29.0,Female,Master's,Data Scientist,6.0,high
+32.0,Male,Bachelor's,Software Engineer,8.0,high
+33.0,Female,Master's,Product Manager,11.0,high
+24.0,Male,Bachelor's,Data Analyst,1.0,below average
+27.0,Male,Bachelor's,Software Engineer,4.0,above average
+25.0,Female,Bachelor's,Data Analyst,2.0,average
+30.0,Female,PhD,Data Scientist,7.0,high
+31.0,Male,Bachelor's,Data Analyst,9.0,high
+28.0,Female,Bachelor's,Software Engineer,5.0,above average
+26.0,Male,Bachelor's,Data Analyst,3.0,above average
+29.0,Female,Master's,Data Scientist,6.0,high
+32.0,Male,Bachelor's,Software Engineer,8.0,high
+33.0,Female,Master's,Product Manager,11.0,high
+24.0,Male,Bachelor's,Data Analyst,1.0,below average
+27.0,Male,Bachelor's,Software Engineer,4.0,above average
+25.0,Female,Bachelor's,Data Analyst,2.0,average
+30.0,Female,PhD,Data Scientist,7.0,high
+31.0,Male,Bachelor's,Data Analyst,9.0,high
+28.0,Female,Bachelor's,Software Engineer,5.0,above average
+26.0,Male,Bachelor's,Data Analyst,3.0,above average
+29.0,Female,Master's,Data Scientist,6.0,high
+32.0,Male,Bachelor's,Software Engineer,8.0,high
+33.0,Female,Master's,Product Manager,11.0,high
+24.0,Male,Bachelor's,Data Analyst,1.0,below average
+27.0,Male,Bachelor's,Software Engineer,4.0,above average
+25.0,Female,Bachelor's,Data Analyst,2.0,average
+30.0,Female,PhD,Data Scientist,7.0,high
+31.0,Male,Bachelor's,Data Analyst,9.0,high
+28.0,Female,Bachelor's,Software Engineer,5.0,above average
+26.0,Male,Bachelor's,Data Analyst,3.0,above average
+29.0,Female,Master's,Data Scientist,6.0,high
+32.0,Male,Bachelor's,Software Engineer,8.0,high
+33.0,Female,Master's,Product Manager,11.0,high
+24.0,Male,Bachelor's,Data Analyst,1.0,below average
+27.0,Male,Bachelor's,Software Engineer,4.0,above average
+25.0,Female,Bachelor's,Data Analyst,2.0,average
+30.0,Female,PhD,Data Scientist,7.0,high
+31.0,Male,Bachelor's,Data Analyst,9.0,high
+28.0,Female,Bachelor's,Software Engineer,5.0,above average
+26.0,Male,Bachelor's,Data Analyst,3.0,above average
+29.0,Female,Master's,Data Scientist,6.0,high
+32.0,Male,Bachelor's,Software Engineer,8.0,high
+33.0,Female,Master's,Product Manager,11.0,high
+24.0,Male,Bachelor's,Data Analyst,1.0,below average
+27.0,Male,Bachelor's,Software Engineer,4.0,above average
+25.0,Female,Bachelor's,Data Analyst,2.0,average
+30.0,Female,PhD,Data Scientist,7.0,high
+31.0,Male,Bachelor's,Data Analyst,9.0,high
+28.0,Female,Bachelor's,Software Engineer,5.0,above average
+26.0,Male,Bachelor's,Data Analyst,3.0,above average
+29.0,Female,Master's,Data Scientist,6.0,high
+32.0,Male,Bachelor's,Software Engineer,8.0,high
+33.0,Female,Master's,Product Manager,11.0,high
+24.0,Male,Bachelor's,Data Analyst,1.0,below average
+27.0,Male,Bachelor's,Software Engineer,4.0,above average
+25.0,Female,Bachelor's,Data Analyst,2.0,average
+30.0,Female,PhD,Data Scientist,7.0,high
+31.0,Male,Bachelor's,Data Analyst,9.0,high
+28.0,Female,Bachelor's,Software Engineer,5.0,above average
+26.0,Male,Bachelor's,Data Analyst,3.0,above average
+29.0,Female,Master's,Data Scientist,6.0,high
+32.0,Male,Bachelor's,Software Engineer,8.0,high
+33.0,Female,Master's,Product Manager,11.0,high
+24.0,Male,Bachelor's,Data Analyst,1.0,below average
+27.0,Male,Bachelor's,Software Engineer,4.0,above average
+25.0,Female,Bachelor's,Data Analyst,2.0,average
+30.0,Female,PhD,Data Scientist,7.0,high
+31.0,Male,Bachelor's,Data Analyst,9.0,high
+28.0,Female,Bachelor's,Software Engineer,5.0,above average
+26.0,Male,Bachelor's,Data Analyst,3.0,above average
+29.0,Female,Master's,Data Scientist,6.0,high
+32.0,Male,Bachelor's,Software Engineer,8.0,high
+33.0,Female,Master's,Product Manager,11.0,high
+24.0,Male,Bachelor's,Data Analyst,1.0,below average
+27.0,Male,Bachelor's,Software Engineer,4.0,above average
+25.0,Female,Bachelor's,Data Analyst,2.0,average
+30.0,Female,PhD,Data Scientist,7.0,high
+31.0,Male,Bachelor's,Data Analyst,9.0,high
+28.0,Female,Bachelor's,Software Engineer,5.0,above average
+26.0,Male,Bachelor's,Data Analyst,3.0,above average
+29.0,Female,Master's,Data Scientist,6.0,high
+32.0,Male,Bachelor's,Software Engineer,8.0,high
+33.0,Female,Master's,Product Manager,11.0,high
+24.0,Male,Bachelor's,Data Analyst,1.0,below average
+27.0,Male,Bachelor's,Software Engineer,4.0,above average
+25.0,Female,Bachelor's,Data Analyst,2.0,average
+30.0,Female,PhD,Data Scientist,7.0,high
+31.0,Male,Bachelor's,Data Analyst,9.0,high
+28.0,Female,Bachelor's,Software Engineer,5.0,above average
+26.0,Male,Bachelor's,Data Analyst,3.0,above average
+29.0,Female,Master's,Data Scientist,6.0,high
+32.0,Male,Bachelor's,Software Engineer,8.0,high
+33.0,Female,Master's,Product Manager,11.0,high
+24.0,Male,Bachelor's,Data Analyst,1.0,below average
+27.0,Male,Bachelor's,Software Engineer,4.0,above average
+25.0,Female,Bachelor's,Data Analyst,2.0,average
+30.0,Female,PhD,Data Scientist,7.0,high
+32.0,Male,Bachelor's Degree,Data Analyst,5.0,above average
+27.0,Female,Master's Degree,Data Scientist,3.0,high
+40.0,Male,Bachelor's Degree,Software Engineer,12.0,high
+35.0,Female,Bachelor's Degree,Product Manager,8.0,above average
+43.0,Male,Master's Degree,Data Scientist,15.0,high
+29.0,Female,Bachelor's Degree,Software Engineer,4.0,above average
+36.0,Male,Bachelor's Degree,Data Analyst,9.0,above average
+31.0,Male,Master's Degree,Data Scientist,6.0,high
+42.0,Female,Bachelor's Degree,Software Engineer,13.0,high
+33.0,Male,Bachelor's Degree,Data Analyst,7.0,above average
+29.0,Female,Master's Degree,Data Scientist,4.0,high
+41.0,Male,Bachelor's Degree,Software Engineer,11.0,high
+35.0,Female,Bachelor's Degree,Product Manager,8.0,high
+27.0,Male,Bachelor's,Software Engineer,4.0,above average
+32.0,Male,Bachelor's,Data Scientist,8.0,high
+29.0,Female,Master's,Data Analyst,6.0,above average
+30.0,Male,Bachelor's,Data Analyst,5.0,above average
+24.0,Male,Bachelor's,Data Analyst,2.0,average
+33.0,Female,Master's,Product Manager,11.0,high
+27.0,Male,Bachelor's,Software Engineer,4.0,above average
+26.0,Male,Bachelor's,Data Analyst,3.0,average
+30.0,Female,PhD,Data Scientist,7.0,high
+31.0,Male,Bachelor's,Data Analyst,9.0,high
+28.0,Female,Bachelor's,Software Engineer,5.0,above average
+26.0,Female,Bachelor's,Data Analyst,3.0,average
+30.0,Male,PhD,Data Scientist,7.0,high
+27.0,Female,Bachelor's,Product Manager,4.0,above average
+24.0,Male,Bachelor's,Data Analyst,2.0,average
+33.0,Male,Master's,Product Manager,11.0,high
+25.0,Male,Bachelor's,Data Analyst,2.0,average
+28.0,Male,Bachelor's,Software Engineer,5.0,above average
+26.0,Male,Bachelor's,Data Analyst,3.0,average
+29.0,Female,Master's,Data Scientist,6.0,above average
+32.0,Male,Bachelor's,Data Scientist,8.0,high
+33.0,Female,Master's,Product Manager,11.0,high
+27.0,Male,Bachelor's,Software Engineer,4.0,above average
+31.0,Female,Master's,Data Scientist,6.0,high
+30.0,Male,Bachelor's,Data Analyst,5.0,above average
+24.0,Male,Bachelor's,Data Analyst,2.0,average
+28.0,Female,Bachelor's,Software Engineer,5.0,above average
+26.0,Male,Bachelor's,Data Analyst,3.0,average
+32.0,Male,Bachelor's,Software Engineer,8.0,high
+33.0,Female,Master's,Product Manager,11.0,high
+25.0,Male,Bachelor's,Data Analyst,2.0,average
+30.0,Female,PhD,Data Scientist,7.0,high
+27.0,Male,Bachelor's,Software Engineer,4.0,above average
+34.0,Female,Master's,Product Manager,12.0,high
+31.0,Male,Bachelor's,Data Analyst,9.0,high
+28.0,Female,Bachelor's,Software Engineer,5.0,above average
+26.0,Male,Bachelor's,Data Analyst,3.0,average
+29.0,Female,Master's,Data Scientist,6.0,above average
+32.0,Male,Bachelor's,Software Engineer,8.0,high
+33.0,Female,Master's,Product Manager,11.0,high
+24.0,Male,Bachelor's,Data Analyst,2.0,average
+27.0,Male,Bachelor's,Software Engineer,4.0,above average
+25.0,Female,Bachelor's,Data Analyst,2.0,average
+30.0,Female,PhD,Data Scientist,7.0,high
+31.0,Male,Bachelor's,Data Analyst,9.0,high
+28.0,Female,Bachelor's,Software Engineer,5.0,above average
+26.0,Male,Bachelor's,Data Analyst,3.0,average
+29.0,Female,Master's,Data Scientist,6.0,above average
+32.0,Male,Bachelor's,Software Engineer,8.0,high
+33.0,Female,Master's,Product Manager,11.0,high
+24.0,Male,Bachelor's,Data Analyst,2.0,average
+27.0,Male,Bachelor's,Software Engineer,4.0,above average
+25.0,Female,Bachelor's,Data Analyst,2.0,average
+30.0,Female,PhD,Data Scientist,7.0,high
+31.0,Male,Bachelor's,Data Analyst,9.0,high
+28.0,Female,Bachelor's,Software Engineer,5.0,above average
+26.0,Male,Bachelor's,Data Analyst,3.0,average
+29.0,Female,Master's,Data Scientist,6.0,above average
+32.0,Male,Bachelor's,Software Engineer,8.0,high
+33.0,Female,Master's,Product Manager,11.0,high
+24.0,Male,Bachelor's,Data Analyst,2.0,average
+27.0,Male,Bachelor's,Software Engineer,4.0,above average
+25.0,Female,Bachelor's,Data Analyst,2.0,average
+30.0,Female,PhD,Data Scientist,7.0,high
+31.0,Male,Bachelor's,Data Analyst,9.0,high
+28.0,Female,Bachelor's,Software Engineer,5.0,above average
+26.0,Male,Bachelor's,Data Analyst,3.0,average
+29.0,Female,Master's,Data Scientist,6.0,above average
+32.0,Male,Bachelor's,Software Engineer,8.0,high
+33.0,Female,Master's,Product Manager,11.0,high
+24.0,Male,Bachelor's,Data Analyst,2.0,average
+27.0,Male,Bachelor's,Software Engineer,4.0,above average
+25.0,Female,Bachelor's,Data Analyst,2.0,average
+30.0,Female,PhD,Data Scientist,7.0,high
+31.0,Male,Bachelor's,Data Analyst,9.0,high
+28.0,Female,Bachelor's,Software Engineer,5.0,above average
+26.0,Male,Bachelor's,Data Analyst,3.0,average
+29.0,Female,Master's,Data Scientist,6.0,above average
+32.0,Male,Bachelor's,Software Engineer,8.0,high
+33.0,Female,Master's,Product Manager,11.0,high
+24.0,Male,Bachelor's,Data Analyst,2.0,average
+27.0,Male,Bachelor's,Software Engineer,4.0,above average
+25.0,Female,Bachelor's,Data Analyst,2.0,average
+30.0,Female,PhD,Data Scientist,7.0,high
+31.0,Male,Bachelor's,Data Analyst,9.0,high
+28.0,Female,Bachelor's,Software Engineer,5.0,above average
+26.0,Male,Bachelor's,Data Analyst,3.0,average
+29.0,Female,Master's,Data Scientist,6.0,above average
+32.0,Male,Bachelor's,Software Engineer,8.0,high
+33.0,Female,Master's,Product Manager,11.0,high
+24.0,Male,Bachelor's,Data Analyst,2.0,average
+27.0,Male,Bachelor's,Software Engineer,4.0,above average
+25.0,Female,Bachelor's,Data Analyst,2.0,average
+30.0,Female,PhD,Data Scientist,7.0,high
+31.0,Male,Bachelor's,Data Analyst,9.0,high
+28.0,Female,Bachelor's,Software Engineer,5.0,above average
+26.0,Male,Bachelor's,Data Analyst,3.0,average
+29.0,Female,Master's,Data Scientist,6.0,above average
+32.0,Male,Bachelor's,Software Engineer,8.0,high
+33.0,Female,Master's,Product Manager,11.0,high
+24.0,Male,Bachelor's,Data Analyst,2.0,average
+27.0,Male,Bachelor's,Software Engineer,4.0,above average
+25.0,Female,Bachelor's,Data Analyst,2.0,average
+30.0,Female,PhD,Data Scientist,7.0,high
+31.0,Male,Bachelor's,Data Analyst,9.0,high
+28.0,Female,Bachelor's,Software Engineer,5.0,above average
+26.0,Male,Bachelor's,Data Analyst,3.0,average
+29.0,Female,Master's,Data Scientist,6.0,above average
+32.0,Male,Bachelor's,Software Engineer,8.0,high
+33.0,Female,Master's,Product Manager,11.0,high
+24.0,Male,Bachelor's,Data Analyst,2.0,average
+27.0,Male,Bachelor's,Software Engineer,4.0,above average
+25.0,Female,Bachelor's,Data Analyst,2.0,average
+30.0,Female,PhD,Data Scientist,7.0,high
+31.0,Male,Bachelor's,Data Analyst,9.0,high
+28.0,Female,Bachelor's,Software Engineer,5.0,above average
+26.0,Male,Bachelor's,Data Analyst,3.0,average
+29.0,Female,Master's,Data Scientist,6.0,above average
+32.0,Male,Bachelor's,Software Engineer,8.0,high
+33.0,Female,Master's,Product Manager,11.0,high
+24.0,Male,Bachelor's,Data Analyst,2.0,average
+27.0,Male,Bachelor's,Software Engineer,4.0,above average
+25.0,Female,Bachelor's,Data Analyst,2.0,average
+30.0,Female,PhD,Data Scientist,7.0,high
+31.0,Male,Bachelor's,Data Analyst,9.0,high
+28.0,Female,Bachelor's,Software Engineer,5.0,above average
+26.0,Male,Bachelor's,Data Analyst,3.0,average
+29.0,Female,Master's,Data Scientist,6.0,above average
+32.0,Male,Bachelor's,Software Engineer,8.0,high
+33.0,Female,Master's,Product Manager,11.0,high
+24.0,Male,Bachelor's,Data Analyst,2.0,average
+27.0,Male,Bachelor's,Software Engineer,4.0,above average
+25.0,Female,Bachelor's,Data Analyst,2.0,average
+30.0,Female,PhD,Data Scientist,7.0,high
+29.0,Male,Bachelor's,Software Engineer,7.0,high
+27.0,Female,Bachelor's,Data Analyst,5.0,average
+33.0,Male,Master's,Data Scientist,10.0,high
+28.0,Male,Bachelor's,Software Engineer,4.0,above average
+26.0,Female,Bachelor's,Data Analyst,3.0,average
+31.0,Male,Bachelor's,Product Manager,8.0,high
+30.0,Male,Master's,Software Engineer,6.0,high
+32.0,Female,Bachelor's,Data Scientist,9.0,high
+29.0,Male,Bachelor's,Data Analyst,7.0,above average
+35.0,Female,Bachelor's,Product Manager,12.0,high
+27.0,Male,Bachelor's,Software Engineer,5.0,above average
+28.0,Female,Master's,Data Scientist,6.0,above average
+37.0,Male,PhD,Product Manager,14.0,high
+26.0,Male,Bachelor's,Data Analyst,3.0,average
+30.0,Female,Bachelor's,Software Engineer,8.0,high
+31.0,Male,Master's,Data Scientist,9.0,high
+29.0,Female,Bachelor's,Data Analyst,7.0,above average
+32.0,Male,Bachelor's,Software Engineer,10.0,high
+28.0,Female,Master's,Data Scientist,6.0,above average
+34.0,Male,Bachelor's,Software Engineer,12.0,high
+25.0,Female,Bachelor's,Data Analyst,2.0,below average
+30.0,Male,Bachelor's,Product Manager,8.0,high
+29.0,Female,Bachelor's,Data Analyst,6.0,average
+31.0,Male,Bachelor's,Software Engineer,9.0,high
+26.0,Female,Bachelor's,Data Analyst,3.0,average
+33.0,Male,Master's,Data Scientist,10.0,high
+28.0,Male,Bachelor's,Software Engineer,4.0,above average
+27.0,Female,Bachelor's,Data Analyst,5.0,average
+30.0,Male,Master's,Software Engineer,6.0,high
+32.0,Female,Bachelor's,Data Scientist,9.0,high
+29.0,Male,Bachelor's,Data Analyst,7.0,above average
+35.0,Female,Bachelor's,Product Manager,12.0,high
+27.0,Male,Bachelor's,Software Engineer,5.0,above average
+28.0,Female,Master's,Data Scientist,6.0,above average
+37.0,Male,PhD,Product Manager,14.0,high
+26.0,Male,Bachelor's,Data Analyst,3.0,average
+30.0,Female,Bachelor's,Software Engineer,8.0,high
+31.0,Male,Master's,Data Scientist,9.0,high
+29.0,Female,Bachelor's,Data Analyst,7.0,above average
+32.0,Male,Bachelor's,Software Engineer,10.0,high
+28.0,Female,Master's,Data Scientist,6.0,above average
+34.0,Male,Bachelor's,Software Engineer,12.0,high
+25.0,Female,Bachelor's,Data Analyst,2.0,below average
+30.0,Male,Bachelor's,Product Manager,8.0,high
+29.0,Female,Bachelor's,Data Analyst,6.0,average
+31.0,Male,Bachelor's,Software Engineer,9.0,high
+26.0,Female,Bachelor's,Data Analyst,3.0,average
+33.0,Male,Master's,Data Scientist,10.0,high
+28.0,Male,Bachelor's,Software Engineer,4.0,above average
+27.0,Female,Bachelor's,Data Analyst,5.0,average
+30.0,Male,Master's,Software Engineer,6.0,high
+32.0,Female,Bachelor's,Data Scientist,9.0,high
+29.0,Male,Bachelor's,Data Analyst,7.0,above average
+35.0,Female,Bachelor's,Product Manager,12.0,high
+27.0,Male,Bachelor's,Software Engineer,5.0,above average
+28.0,Female,Master's,Data Scientist,6.0,above average
+37.0,Male,PhD,Product Manager,14.0,high
+26.0,Male,Bachelor's,Data Analyst,3.0,average
+30.0,Female,Bachelor's,Software Engineer,8.0,high
+31.0,Male,Master's,Data Scientist,9.0,high
+29.0,Female,Bachelor's,Data Analyst,7.0,above average
+32.0,Male,Bachelor's,Software Engineer,10.0,high
+28.0,Female,Master's,Data Scientist,6.0,above average
+34.0,Male,Bachelor's,Software Engineer,12.0,high
+25.0,Female,Bachelor's,Data Analyst,2.0,below average
+30.0,Male,Bachelor's,Product Manager,8.0,high
+29.0,Female,Bachelor's,Data Analyst,6.0,average
+31.0,Male,Bachelor's,Software Engineer,9.0,high
+26.0,Female,Bachelor's,Data Analyst,3.0,average
+33.0,Male,Master's,Data Scientist,10.0,high
+28.0,Male,Bachelor's,Software Engineer,4.0,above average
+27.0,Female,Bachelor's,Data Analyst,5.0,average
+30.0,Male,Master's,Software Engineer,6.0,high
+32.0,Female,Bachelor's,Data Scientist,9.0,high
+29.0,Male,Bachelor's,Data Analyst,7.0,above average
+35.0,Female,Bachelor's,Product Manager,12.0,high
+27.0,Male,Bachelor's,Software Engineer,5.0,above average
+28.0,Female,Master's,Data Scientist,6.0,above average
+37.0,Male,PhD,Product Manager,14.0,high
+26.0,Male,Bachelor's,Data Analyst,3.0,average
+30.0,Female,Bachelor's,Software Engineer,8.0,high
+31.0,Male,Master's,Data Scientist,9.0,high
+29.0,Female,Bachelor's,Data Analyst,7.0,above average
+32.0,Male,Bachelor's,Software Engineer,10.0,high
+28.0,Female,Master's,Data Scientist,6.0,above average
+34.0,Male,Bachelor's,Software Engineer,12.0,high
+25.0,Female,Bachelor's,Data Analyst,2.0,below average
+30.0,Male,Bachelor's,Product Manager,8.0,high
+29.0,Female,Bachelor's,Data Analyst,6.0,average
+31.0,Male,Bachelor's,Software Engineer,9.0,high
+26.0,Female,Bachelor's,Data Analyst,3.0,average
+33.0,Male,Master's,Data Scientist,10.0,high
+28.0,Male,Bachelor's,Software Engineer,4.0,above average
+27.0,Female,Bachelor's,Data Analyst,5.0,average
+30.0,Male,Master's,Software Engineer,6.0,high
+32.0,Female,Bachelor's,Data Scientist,9.0,high
+29.0,Male,Bachelor's,Data Analyst,7.0,above average
+35.0,Female,Bachelor's,Product Manager,12.0,high
+27.0,Male,Bachelor's,Software Engineer,5.0,above average
+28.0,Female,Master's,Data Scientist,6.0,above average
+37.0,Male,PhD,Product Manager,14.0,high
+26.0,Male,Bachelor's,Data Analyst,3.0,average
+30.0,Female,Bachelor's,Software Engineer,8.0,high
+31.0,Male,Master's,Data Scientist,9.0,high
+29.0,Female,Bachelor's,Data Analyst,7.0,above average
+32.0,Male,Bachelor's,Software Engineer,10.0,high
+28.0,Female,Master's,Data Scientist,6.0,above average
+34.0,Male,Bachelor's,Software Engineer,12.0,high
+25.0,Female,Bachelor's,Data Analyst,2.0,below average
+30.0,Male,Bachelor's,Product Manager,8.0,high
+28.0,Male,Bachelor's Degree,Senior Software Engineer,7.0,high
+44.0,Male,PhD,Software Engineer Manager,18.0,high
+33.0,Female,Master's Degree,Back end Developer,5.0,average
+50.0,Male,PhD,Senior Project Engineer,16.0,high
+27.0,Female,Master's Degree,Full Stack Engineer,3.0,average
+25.0,Male,Bachelor's Degree,Front end Developer,1.0,below average
+35.0,Male,Master's Degree,Senior Software Engineer,8.0,above average
+47.0,Female,PhD,Full Stack Engineer,12.0,high
+46.0,Female,Master's Degree,Senior Project Engineer,13.0,high
+32.0,Male,Bachelor's Degree,Back end Developer,4.0,average
+61.0,Male,PhD,Software Engineer Manager,20.0,high
+41.0,Male,Master's Degree,Senior Software Engineer,11.0,above average
+37.0,Male,Master's Degree,Senior Project Engineer,9.0,above average
+53.0,Male,PhD,Software Engineer Manager,19.0,high
+30.0,Female,Bachelor's Degree,Front end Developer,2.0,below average
+26.0,Female,Master's Degree,Back end Developer,3.0,below average
+37.0,Female,Master's Degree,Senior Software Engineer,9.0,above average
+32.0,Male,Bachelor's Degree,Full Stack Engineer,5.0,average
+44.0,Female,Master's Degree,Senior Software Engineer,12.0,high
+50.0,Female,PhD,Software Engineer Manager,16.0,high
+27.0,Male,Bachelor's Degree,Senior Project Engineer,4.0,average
+42.0,Male,PhD,Full Stack Engineer,14.0,high
+57.0,Male,PhD,Software Engineer Manager,18.0,high
+35.0,Male,Master's Degree,Senior Software Engineer,7.0,above average
+62.0,Male,PhD,Software Engineer Manager,19.0,high
+26.0,Female,Master's Degree,Back end Developer,2.0,below average
+42.0,Female,Master's Degree,Senior Project Engineer,11.0,high
+41.0,Female,PhD,Software Engineer Manager,14.0,high
+36.0,Female,Master's Degree,Full Stack Engineer,8.0,above average
+49.0,Male,PhD,Software Engineer Manager,15.0,high
+49.0,Male,PhD,Senior Project Engineer,15.0,high
+47.0,Male,PhD,Software Engineer Manager,15.0,high
+47.0,Male,PhD,Senior Software Engineer,14.0,high
+26.0,Male,Bachelor's Degree,Front end Developer,2.0,below average
+24.0,Female,Bachelor's Degree,Back end Developer,1.0,below average
+62.0,Male,PhD,Software Engineer Manager,20.0,high
+42.0,Male,PhD,Senior Software Engineer,14.0,high
+41.0,Female,Master's Degree,Senior Project Engineer,11.0,above average
+23.0,Male,Bachelor's Degree,Full Stack Engineer,1.0,minimal
+55.0,Male,PhD,Software Engineer Manager,17.0,high
+26.0,Female,Master's Degree,Back end Developer,3.0,below average
+33.0,Female,Bachelor's Degree,Front end Developer,5.0,average
+31.0,Male,Master's Degree,Full Stack Engineer,6.0,above average
+50.0,Female,PhD,Software Engineer Manager,16.0,high
+24.0,Female,Master's Degree,Back end Developer,1.0,below average
+56.0,Male,PhD,Software Engineer Manager,17.0,high
+24.0,Male,Bachelor's Degree,Front end Developer,1.0,below average
+37.0,Male,Master's Degree,Senior Software Engineer,8.0,above average
+43.0,Female,PhD,Senior Project Engineer,13.0,high
+44.0,Female,Master's Degree,Senior Software Engineer,12.0,high
+34.0,Male,Master's Degree,Back end Developer,6.0,average
+45.0,Male,PhD,Software Engineer Manager,15.0,high
+29.0,Male,Bachelor's Degree,Full Stack Engineer,3.0,below average
+29.0,Male,Bachelor's Degree,Front end Developer,3.0,below average
+29.0,Female,Bachelor's Degree,Back end Developer,3.0,below average
+48.0,Male,PhD,Senior Project Engineer,16.0,high
+43.0,Female,Master's Degree,Software Engineer Manager,11.0,above average
+62.0,Male,PhD,Software Engineer Manager,19.0,high
+54.0,Male,PhD,Software Engineer Manager,17.0,high
+60.0,Male,PhD,Software Engineer Manager,18.0,high
+54.0,Female,PhD,Software Engineer Manager,14.0,high
+27.0,Female,Master's Degree,Full Stack Engineer,3.0,average
+23.0,Male,Bachelor's Degree,Back end Developer,1.0,minimal
+45.0,Male,PhD,Senior Software Engineer,13.0,high
+32.0,Female,Master's Degree,Full Stack Engineer,5.0,average
+57.0,Male,PhD,Software Engineer Manager,16.0,high
+47.0,Male,PhD,Software Engineer Manager,14.0,high
+25.0,Female,Master's Degree,Back end Developer,2.0,below average
+58.0,Male,PhD,Software Engineer Manager,17.0,high
+41.0,Female,Master's Degree,Senior Software Engineer,12.0,above average
+41.0,Male,PhD,Software Engineer Manager,12.0,high
+26.0,Male,Bachelor's Degree,Front end Developer,2.0,below average
+47.0,Male,PhD,Senior Software Engineer,15.0,high
+24.0,Female,Bachelor's Degree,Back end Developer,1.0,below average
+48.0,Male,PhD,Senior Project Engineer,16.0,high
+32.0,Male,Bachelor's Degree,Full Stack Engineer,5.0,average
+61.0,Male,PhD,Software Engineer Manager,20.0,high
+45.0,Male,PhD,Senior Project Engineer,14.0,high
+50.0,Female,PhD,Software Engineer Manager,16.0,high
+53.0,Male,PhD,Software Engineer Manager,18.0,high
+47.0,Female,PhD,Senior Software Engineer,14.0,high
+23.0,Male,Bachelor's Degree,Front end Developer,1.0,minimal
+33.0,Male,Master's Degree,Back end Developer,6.0,above average
+42.0,Male,PhD,Software Engineer Manager,14.0,high
+45.0,Male,PhD,Senior Project Engineer,14.0,high
+23.0,Male,Bachelor's Degree,Front end Developer,1.0,minimal
+37.0,Male,Master's Degree,Senior Software Engineer,9.0,above average
+44.0,Female,Master's Degree,Senior Project Engineer,12.0,high
+54.0,Male,PhD,Software Engineer Manager,17.0,high
+38.0,Female,Master's Degree,Back end Developer,10.0,above average
+34.0,Male,Master's Degree,Full Stack Engineer,6.0,average
+46.0,Female,PhD,Software Engineer Manager,14.0,high
+30.0,Male,Bachelor's Degree,Back end Developer,4.0,average
+44.0,Female,Master's Degree,Senior Software Engineer,11.0,high
+27.0,Female,Master's Degree,Full Stack Engineer,3.0,average
+42.0,Male,PhD,Senior Project Engineer,14.0,high
+27.0,Male,Bachelor's Degree,Front end Developer,3.0,below average
+54.0,Male,PhD,Software Engineer Manager,18.0,high
+38.0,Male,Master's Degree,Senior Software Engineer,10.0,above average
+31.0,Male,Master's Degree,Senior Project Engineer,6.0,average
+28.0,Female,Master's Degree,Full Stack Engineer,4.0,average
+30.0,Female,Master's Degree,Back end Developer,6.0,above average
+54.0,Male,PhD,Software Engineer Manager,16.0,high
+62.0,Male,PhD,Software Engineer Manager,20.0,high
+62.0,Male,PhD,Software Engineer Manager,19.0,high
+37.0,Male,Master's Degree,Senior Software Engineer,9.0,above average
+31.0,Male,Master's Degree,Senior Software Engineer,7.0,above average
+58.0,Female,PhD,Software Engineer Manager,17.0,high
+56.0,Male,PhD,Software Engineer Manager,17.0,high
+23.0,Female,Bachelor's Degree,Back end Developer,1.0,minimal
+49.0,Male,PhD,Software Engineer Manager,15.0,high
+32.0,Female,Master's Degree,Full Stack Engineer,5.0,average
+52.0,Female,PhD,Software Engineer Manager,16.0,high
+32.0,Female,Master's Degree,Full Stack Engineer,6.0,above average
+50.0,Female,PhD,Software Engineer Manager,16.0,high
+32.0,Male,Master's Degree,Back end Developer,6.0,above average
+34.0,Male,Master's Degree,Full Stack Engineer,7.0,above average
+28.0,Male,Bachelor's Degree,Front end Developer,2.0,below average
+44.0,Male,Master's Degree,Senior Project Engineer,11.0,high
+55.0,Male,PhD,Software Engineer Manager,17.0,high
+27.0,Male,Bachelor's Degree,Front end Developer,3.0,below average
+46.0,Male,PhD,Software Engineer Manager,14.0,high
+27.0,Female,Master's Degree,Back end Developer,2.0,below average
+45.0,Male,PhD,Senior Project Engineer,14.0,high
+23.0,Female,Bachelor's Degree,Front end Developer,1.0,minimal
+36.0,Female,Master's Degree,Full Stack Engineer,8.0,above average
+47.0,Female,PhD,Senior Software Engineer,14.0,high
+33.0,Male,Master's Degree,Back end Developer,6.0,above average
+43.0,Male,PhD,Software Engineer Manager,13.0,high
+30.0,Male,Bachelor's Degree,Back end Developer,4.0,average
+28.0,Female,Bachelor's Degree,Front end Developer,2.0,below average
+43.0,Male,Master's Degree,Senior Project Engineer,12.0,above average
+43.0,Male,PhD,Senior Project Engineer,13.0,high
+36.0,Male,Master's Degree,Senior Software Engineer,7.0,above average
+24.0,Male,Bachelor's Degree,Front end Developer,1.0,below average
+28.0,Female,Bachelor's Degree,Front end Developer,3.0,below average
+37.0,Male,Master's Degree,Senior Software Engineer,9.0,above average
+41.0,Female,PhD,Software Engineer Manager,14.0,high
+26.0,Male,Bachelor's Degree,Front end Developer,2.0,below average
+28.0,Female,Master's Degree,Back end Developer,3.0,below average
+43.0,Male,PhD,Senior Software Engineer,12.0,high
+42.0,Male,PhD,Senior Software Engineer,14.0,high
+48.0,Male,PhD,Senior Project Engineer,16.0,high
+27.0,Female,Master's Degree,Back end Developer,2.0,below average
+49.0,Male,PhD,Software Engineer Manager,15.0,high
+44.0,Male,PhD,Senior Project Engineer,12.0,high
+27.0,Female,Master's Degree,Full Stack Engineer,3.0,average
+37.0,Male,Master's Degree,Senior Software Engineer,10.0,above average
+44.0,Female,Master's Degree,Senior Project Engineer,12.0,high
+56.0,Male,PhD,Software Engineer Manager,18.0,high
+49.0,Male,PhD,Software Engineer Manager,15.0,high
+27.0,Male,Bachelor's Degree,Front end Developer,2.0,below average
+48.0,Male,PhD,Senior Project Engineer,16.0,high
+31.0,Male,Master's Degree,Full Stack Engineer,7.0,above average
+25.0,Male,Bachelor's Degree,Front end Developer,1.0,below average
+50.0,Male,PhD,Software Engineer Manager,16.0,high
+46.0,Male,PhD,Software Engineer Manager,14.0,high
+33.0,Male,Master's Degree,Full Stack Engineer,6.0,above average
+42.0,Male,PhD,Senior Software Engineer,14.0,high
+41.0,Male,PhD,Senior Project Engineer,12.0,above average
+43.0,Male,PhD,Senior Project Engineer,13.0,high
+32.0,Male,Master's Degree,Back end Developer,6.0,above average
+24.0,Male,Bachelor's Degree,Front end Developer,1.0,below average
+44.0,Female,Master's Degree,Senior Software Engineer,11.0,high
+36.0,Male,Master's Degree,Senior Software Engineer,7.0,above average
+28.0,Female,Master's Degree,Full Stack Engineer,4.0,average
+28.0,Male,Bachelor's Degree,Front end Developer,2.0,below average
+37.0,Male,Master's Degree,Senior Software Engineer,9.0,above average
+54.0,Male,PhD,Software Engineer Manager,16.0,high
+58.0,Male,PhD,Software Engineer Manager,17.0,high
+27.0,Male,Bachelor's Degree,Front end Developer,3.0,below average
+30.0,Male,Bachelor's Degree,Back end Developer,4.0,average
+27.0,Female,Master's Degree,Full Stack Engineer,3.0,average
+54.0,Male,PhD,Software Engineer Manager,17.0,high
+49.0,Male,PhD,Software Engineer Manager,15.0,high
+38.0,Male,Master's Degree,Senior Software Engineer,10.0,above average
+54.0,Male,PhD,Software Engineer Manager,18.0,high
+31.0,Male,Master's Degree,Senior Project Engineer,6.0,average
+56.0,Male,PhD,Software Engineer Manager,17.0,high
+31.0,Male,Master's Degree,Senior Software Engineer,7.0,above average
+42.0,Male,PhD,Senior Software Engineer,14.0,high
+44.0,Male,Master's Degree,Senior Project Engineer,11.0,high
+37.0,Male,Master's Degree,Senior Software Engineer,9.0,above average
+24.0,Female,Bachelor's Degree,Back end Developer,1.0,below average
+27.0,Male,Bachelor's Degree,Front end Developer,2.0,below average
+42.0,Male,PhD,Senior Software Engineer,14.0,high
+24.0,Female,Bachelor's Degree,Front end Developer,1.0,minimal
+28.0,Female,Bachelor's Degree,Front end Developer,3.0,below average
+43.0,Male,PhD,Senior Project Engineer,13.0,high
+31.0,Male,Master's Degree,Full Stack Engineer,7.0,above average
+43.0,Male,PhD,Software Engineer Manager,13.0,high
+27.0,Female,Master's Degree,Back end Developer,2.0,below average
+49.0,Male,PhD,Software Engineer Manager,15.0,high
+48.0,Male,PhD,Senior Project Engineer,16.0,high
+30.0,Female,Master's Degree,Back end Developer,6.0,above average
+28.0,Female,Master's Degree,Full Stack Engineer,4.0,average
+46.0,Male,PhD,Software Engineer Manager,14.0,high
+37.0,Male,Master's Degree,Senior Software Engineer,9.0,above average
+42.0,Male,PhD,Senior Software Engineer,14.0,high
+43.0,Male,PhD,Senior Project Engineer,12.0,above average
+31.0,Male,Master's Degree,Senior Software Engineer,7.0,above average
+56.0,Male,PhD,Software Engineer Manager,17.0,high
+37.0,Male,Master's Degree,Senior Software Engineer,10.0,above average
+54.0,Male,PhD,Software Engineer Manager,16.0,high
+58.0,Male,PhD,Software Engineer Manager,17.0,high
+33.0,Male,Master's Degree,Back end Developer,6.0,above average
+29.0,Female,Bachelor's Degree,Front end Developer,3.0,below average
+52.0,Male,PhD,Software Engineer Manager,18.0,high
+36.0,Male,Master's Degree,Full Stack Engineer,8.0,above average
+26.0,Male,Bachelor's Degree,Back end Developer,2.0,below average
+47.0,Male,PhD,Senior Project Engineer,16.0,high
+32.0,Male,Master's Degree,Full Stack Engineer,6.0,average
+29.0,Male,Bachelor's Degree,Front end Developer,3.0,below average
+28.0,Female,Master's Degree,Back end Developer,3.0,below average
+54.0,Male,PhD,Software Engineer Manager,16.0,high
+57.0,Male,PhD,Software Engineer Manager,18.0,high
+51.0,Male,PhD,Software Engineer Manager,16.0,high
+28.0,Female,Master's Degree,Full Stack Engineer,4.0,average
+46.0,Male,PhD,Software Engineer Manager,14.0,high
+27.0,Female,Master's Degree,Back end Developer,2.0,below average
+45.0,Male,PhD,Senior Project Engineer,14.0,high
+23.0,Female,Bachelor's Degree,Front end Developer,1.0,minimal
+36.0,Male,Master's Degree,Full Stack Engineer,7.0,above average
+48.0,Male,PhD,Senior Project Engineer,16.0,high
+33.0,Female,Master's Degree,Full Stack Engineer,5.0,average
+38.0,Female,Master's Degree,Back end Developer,10.0,above average
+51.0,Male,PhD,Software Engineer Manager,16.0,high
+27.0,Female,Master's Degree,Full Stack Engineer,3.0,average
+37.0,Male,Master's Degree,Senior Software Engineer,9.0,above average
+44.0,Female,Master's Degree,Senior Project Engineer,12.0,high
+27.0,Male,Bachelor's Degree,Front end Developer,3.0,below average
+38.0,Male,Master's Degree,Senior Software Engineer,10.0,above average
+54.0,Male,PhD,Software Engineer Manager,17.0,high
+49.0,Male,PhD,Software Engineer Manager,15.0,high
+27.0,Male,Bachelor's Degree,Front end Developer,2.0,below average
+48.0,Male,PhD,Senior Project Engineer,16.0,high
+31.0,Male,Master's Degree,Full Stack Engineer,7.0,above average
+25.0,Male,Bachelor's Degree,Front end Developer,1.0,minimal
+50.0,Male,PhD,Software Engineer Manager,16.0,high
+46.0,Male,PhD,Software Engineer Manager,14.0,high
+33.0,Male,Master's Degree,Full Stack Engineer,6.0,above average
+42.0,Male,PhD,Senior Software Engineer,14.0,high
+41.0,Male,PhD,Senior Project Engineer,12.0,above average
+43.0,Male,PhD,Senior Project Engineer,13.0,high
+32.0,Male,Master's Degree,Back end Developer,6.0,above average
+24.0,Male,Bachelor's Degree,Front end Developer,1.0,below average
+44.0,Female,Master's Degree,Senior Software Engineer,11.0,high
+36.0,Male,Master's Degree,Senior Software Engineer,7.0,above average
+28.0,Female,Master's Degree,Full Stack Engineer,4.0,average
+28.0,Male,Bachelor's Degree,Front end Developer,2.0,below average
+37.0,Male,Master's Degree,Senior Software Engineer,9.0,above average
+54.0,Male,PhD,Software Engineer Manager,16.0,high
+58.0,Male,PhD,Software Engineer Manager,17.0,high
+27.0,Male,Bachelor's Degree,Front end Developer,3.0,below average
+30.0,Male,Bachelor's Degree,Back end Developer,4.0,average
+27.0,Female,Master's Degree,Full Stack Engineer,3.0,average
+54.0,Male,PhD,Software Engineer Manager,17.0,high
+49.0,Male,PhD,Software Engineer Manager,15.0,high
+38.0,Male,Master's Degree,Senior Software Engineer,10.0,above average
+54.0,Male,PhD,Software Engineer Manager,18.0,high
+31.0,Male,Master's Degree,Senior Project Engineer,6.0,average
+56.0,Male,PhD,Software Engineer Manager,17.0,high
+31.0,Male,Master's Degree,Senior Software Engineer,7.0,above average
+42.0,Male,PhD,Senior Software Engineer,14.0,high
+44.0,Male,Master's Degree,Senior Project Engineer,11.0,high
+37.0,Male,Master's Degree,Senior Software Engineer,9.0,above average
+24.0,Female,Bachelor's Degree,Back end Developer,1.0,below average
+27.0,Male,Bachelor's Degree,Front end Developer,2.0,below average
+42.0,Male,PhD,Senior Software Engineer,14.0,high
+24.0,Female,Bachelor's Degree,Front end Developer,1.0,minimal
+28.0,Female,Bachelor's Degree,Front end Developer,3.0,below average
+43.0,Male,PhD,Senior Project Engineer,13.0,high
+31.0,Male,Master's Degree,Full Stack Engineer,7.0,above average
+43.0,Male,PhD,Software Engineer Manager,13.0,high
+27.0,Female,Master's Degree,Back end Developer,2.0,below average
+49.0,Male,PhD,Software Engineer Manager,15.0,high
+48.0,Male,PhD,Senior Project Engineer,16.0,high
+31.0,Male,Master's Degree,Senior Project Engineer,6.0,average
+40.0,Male,PhD,Senior Software Engineer,12.0,above average
+36.0,Male,Master's Degree,Senior Software Engineer,8.0,above average
+54.0,Male,PhD,Software Engineer Manager,17.0,high
+27.0,Male,Bachelor's Degree,Front end Developer,2.0,below average
+28.0,Male,Bachelor's Degree,Front end Developer,2.0,below average
+44.0,Male,Master's Degree,Senior Project Engineer,11.0,high
+43.0,Male,PhD,Senior Project Engineer,13.0,high
+54.0,Male,PhD,Software Engineer Manager,17.0,high
+32.0,Male,Master's Degree,Back end Developer,6.0,above average
+38.0,Male,Master's Degree,Senior Software Engineer,10.0,above average
+49.0,Male,PhD,Software Engineer Manager,15.0,high
+27.0,Male,Bachelor's Degree,Front end Developer,3.0,below average
+54.0,Male,PhD,Software Engineer Manager,17.0,high
+31.0,Male,Master's Degree,Senior Project Engineer,7.0,above average
+24.0,Male,Bachelor's Degree,Back end Developer,1.0,minimal
+48.0,Male,PhD,Senior Project Engineer,16.0,high
+27.0,Female,Master's Degree,Back end Developer,2.0,below average
+43.0,Male,PhD,Senior Project Engineer,13.0,high
+44.0,Male,Master's Degree,Senior Project Engineer,11.0,high
+37.0,Male,Master's Degree,Senior Software Engineer,9.0,above average
+56.0,Male,PhD,Software Engineer Manager,17.0,high
+28.0,Male,Bachelor's Degree,Front end Developer,2.0,below average
+54.0,Male,PhD,Software Engineer Manager,17.0,high
+31.0,Male,Master's Degree,Senior Project Engineer,6.0,average
+49.0,Male,PhD,Software Engineer Manager,15.0,high
+27.0,Female,Master's Degree,Back end Developer,2.0,below average
+38.0,Male,Master's Degree,Senior Software Engineer,10.0,above average
+27.0,Male,Bachelor's Degree,Front end Developer,3.0,below average
+43.0,Male,PhD,Senior Project Engineer,13.0,high
+48.0,Male,PhD,Senior Project Engineer,16.0,high
+44.0,Male,Master's Degree,Senior Project Engineer,11.0,high
+54.0,Male,PhD,Software Engineer Manager,17.0,high
+37.0,Male,Master's Degree,Senior Software Engineer,9.0,above average
+28.0,Male,Bachelor's Degree,Front end Developer,2.0,below average
+27.0,Female,Master's Degree,Back end Developer,2.0,below average
+49.0,Male,PhD,Software Engineer Manager,15.0,high
+31.0,Male,Master's Degree,Senior Project Engineer,7.0,above average
+27.0,Male,Bachelor's Degree,Front end Developer,3.0,below average
+54.0,Male,PhD,Software Engineer Manager,17.0,high
+38.0,Male,Master's Degree,Senior Software Engineer,10.0,above average
+44.0,Male,Master's Degree,Senior Project Engineer,11.0,high
+43.0,Male,PhD,Senior Project Engineer,13.0,high
+27.0,Male,Bachelor's Degree,Front end Developer,2.0,below average
+48.0,Male,PhD,Senior Project Engineer,16.0,high
+31.0,Male,Master's Degree,Senior Project Engineer,6.0,average
+54.0,Male,PhD,Software Engineer Manager,17.0,high
+37.0,Male,Master's Degree,Senior Software Engineer,9.0,above average
+28.0,Male,Bachelor's Degree,Front end Developer,2.0,below average
+27.0,Female,Master's Degree,Back end Developer,2.0,below average
+34.0,Male,Bachelor's Degree,Front end Developer,5.0,average
+43.0,Female,Master's Degree,Senior Software Engineer,12.0,high
+27.0,Male,Bachelor's Degree,Back end Developer,2.0,below average
+56.0,Female,PhD,Software Engineer Manager,18.0,high
+32.0,Male,Master's Degree,Full Stack Engineer,7.0,above average
+40.0,Male,PhD,Senior Software Engineer,12.0,above average
+23.0,Male,Bachelor's Degree,Front end Developer,1.0,minimal
+46.0,Male,PhD,Senior Project Engineer,16.0,high
+41.0,Female,PhD,Senior Project Engineer,11.0,above average
+28.0,Female,Bachelor's Degree,Front end Developer,3.0,below average
+34.0,Male,Bachelor's Degree,Back end Developer,6.0,average
+49.0,Male,PhD,Software Engineer Manager,15.0,high
+43.0,Male,PhD,Senior Project Engineer,13.0,high
+54.0,Male,PhD,Software Engineer Manager,16.0,high
+36.0,Male,Master's Degree,Senior Software Engineer,8.0,above average
+33.0,Male,Master's Degree,Full Stack Engineer,6.0,above average
+27.0,Female,Master's Degree,Back end Developer,2.0,below average
+44.0,Male,Master's Degree,Senior Project Engineer,11.0,high
+31.0,Male,Master's Degree,Senior Project Engineer,6.0,average
+38.0,Male,Master's Degree,Senior Software Engineer,10.0,above average
+27.0,Male,Bachelor's Degree,Front end Developer,2.0,below average
+54.0,Male,PhD,Software Engineer Manager,17.0,high
+31.0,Male,Master's Degree,Senior Software Engineer,7.0,above average
+32.0,Male,Master's Degree,Back end Developer,6.0,above average
+38.0,Female,Master's Degree,Back end Developer,10.0,above average
+51.0,Male,PhD,Software Engineer Manager,16.0,high
+28.0,Male,Bachelor's Degree,Front end Developer,2.0,below average
+27.0,Male,Bachelor's Degree,Front end Developer,3.0,below average
+43.0,Male,PhD,Senior Project Engineer,13.0,high
+27.0,Female,Master's Degree,Full Stack Engineer,3.0,average
+49.0,Male,PhD,Software Engineer Manager,15.0,high
+48.0,Male,PhD,Senior Project Engineer,16.0,high
+31.0,Male,Master's Degree,Senior Project Engineer,7.0,above average
+40.0,Female,PhD,Senior Software Engineer,12.0,above average
+24.0,Male,Bachelor's Degree,Front end Developer,1.0,minimal
+27.0,Male,Bachelor's Degree,Front end Developer,3.0,below average
+42.0,Male,PhD,Senior Software Engineer,14.0,high
+24.0,Female,Bachelor's Degree,Front end Developer,1.0,minimal
+28.0,Female,Bachelor's Degree,Front end Developer,3.0,below average
+43.0,Male,PhD,Senior Project Engineer,13.0,high
+31.0,Male,Master's Degree,Full Stack Engineer,7.0,above average
+43.0,Male,PhD,Software Engineer Manager,13.0,high
+27.0,Female,Master's Degree,Back end Developer,2.0,below average
+49.0,Male,PhD,Software Engineer Manager,15.0,high
+48.0,Male,PhD,Senior Project Engineer,16.0,high
+31.0,Male,Master's Degree,Senior Project Engineer,6.0,average
+40.0,Male,PhD,Senior Software Engineer,12.0,above average
+36.0,Male,Master's Degree,Senior Software Engineer,8.0,above average
+54.0,Male,PhD,Software Engineer Manager,17.0,high
+27.0,Male,Bachelor's Degree,Front end Developer,2.0,below average
+28.0,Male,Bachelor's Degree,Front end Developer,2.0,below average
+44.0,Male,Master's Degree,Senior Project Engineer,11.0,high
+43.0,Male,PhD,Senior Project Engineer,13.0,high
+54.0,Male,PhD,Software Engineer Manager,17.0,high
+32.0,Male,Master's Degree,Back end Developer,6.0,above average
+38.0,Male,Master's Degree,Senior Software Engineer,10.0,above average
+49.0,Male,PhD,Software Engineer Manager,15.0,high
+27.0,Male,Bachelor's Degree,Front end Developer,3.0,below average
+54.0,Male,PhD,Software Engineer Manager,17.0,high
+31.0,Male,Master's Degree,Senior Project Engineer,7.0,above average
+24.0,Male,Bachelor's Degree,Back end Developer,1.0,minimal
+48.0,Male,PhD,Senior Project Engineer,16.0,high
+27.0,Female,Master's Degree,Back end Developer,2.0,below average
+43.0,Male,PhD,Senior Project Engineer,13.0,high
+44.0,Male,Master's Degree,Senior Project Engineer,11.0,high
+37.0,Male,Master's Degree,Senior Software Engineer,9.0,above average
+56.0,Male,PhD,Software Engineer Manager,17.0,high
+28.0,Male,Bachelor's Degree,Front end Developer,2.0,below average
+54.0,Male,PhD,Software Engineer Manager,17.0,high
+31.0,Male,Master's Degree,Senior Project Engineer,6.0,average
+49.0,Male,PhD,Software Engineer Manager,15.0,high
+54.0,Male,PhD,Software Engineer Manager,17.0,high
+27.0,Male,Bachelor's Degree,Front end Developer,3.0,below average
+42.0,Male,PhD,Senior Software Engineer,14.0,high
+38.0,Male,Master's Degree,Senior Software Engineer,10.0,above average
+43.0,Male,PhD,Senior Project Engineer,13.0,high
+27.0,Male,Bachelor's Degree,Front end Developer,2.0,below average
+31.0,Male,Master's Degree,Full Stack Engineer,7.0,above average
+54.0,Male,PhD,Software Engineer Manager,17.0,high
+36.0,Male,Master's Degree,Senior Software Engineer,8.0,above average
+27.0,Female,Master's Degree,Back end Developer,2.0,below average
+49.0,Male,PhD,Software Engineer Manager,15.0,high
+48.0,Male,PhD,Senior Project Engineer,16.0,high
+31.0,Male,Master's Degree,Senior Project Engineer,7.0,above average
+40.0,Female,PhD,Senior Software Engineer,12.0,above average
+24.0,Male,Bachelor's Degree,Front end Developer,1.0,minimal
+27.0,Male,Bachelor's Degree,Front end Developer,3.0,below average
+43.0,Male,PhD,Senior Project Engineer,13.0,high
+27.0,Female,Master's Degree,Full Stack Engineer,3.0,average
+49.0,Male,PhD,Software Engineer Manager,15.0,high
+48.0,Male,PhD,Senior Project Engineer,16.0,high
+31.0,Male,Master's Degree,Senior Project Engineer,6.0,average
+40.0,Male,PhD,Senior Software Engineer,12.0,above average
+36.0,Male,Master's Degree,Senior Software Engineer,8.0,above average
+54.0,Male,PhD,Software Engineer Manager,17.0,high
+27.0,Male,Bachelor's Degree,Front end Developer,2.0,below average
+28.0,Male,Bachelor's Degree,Front end Developer,2.0,below average
+44.0,Male,Master's Degree,Senior Project Engineer,11.0,high
+43.0,Male,PhD,Senior Project Engineer,13.0,high
+54.0,Male,PhD,Software Engineer Manager,17.0,high
+32.0,Male,Master's Degree,Back end Developer,6.0,above average
+38.0,Male,Master's Degree,Senior Software Engineer,10.0,above average
+49.0,Male,PhD,Software Engineer Manager,15.0,high
+27.0,Male,Bachelor's Degree,Front end Developer,3.0,below average
+54.0,Male,PhD,Software Engineer Manager,17.0,high
+31.0,Male,Master's Degree,Senior Project Engineer,7.0,above average
+24.0,Male,Bachelor's Degree,Back end Developer,1.0,minimal
+48.0,Male,PhD,Senior Project Engineer,16.0,high
+27.0,Female,Master's Degree,Back end Developer,2.0,below average
+43.0,Male,PhD,Senior Project Engineer,13.0,high
+44.0,Male,Master's Degree,Senior Project Engineer,11.0,high
+37.0,Male,Master's Degree,Senior Software Engineer,9.0,above average
+56.0,Male,PhD,Software Engineer Manager,17.0,high
+28.0,Male,Bachelor's Degree,Front end Developer,2.0,below average
+54.0,Male,PhD,Software Engineer Manager,17.0,high
+31.0,Male,Master's Degree,Senior Project Engineer,6.0,average
+49.0,Male,PhD,Software Engineer Manager,15.0,high
+54.0,Male,PhD,Software Engineer Manager,17.0,high
+27.0,Male,Bachelor's Degree,Front end Developer,3.0,below average
+42.0,Male,PhD,Senior Software Engineer,14.0,high
+38.0,Male,Master's Degree,Senior Software Engineer,10.0,above average
+36.0,Male,Bachelor's Degree,Front end Developer,7.0,average
+29.0,Female,Master's Degree,Back end Developer,3.0,below average
+41.0,Female,PhD,Software Engineer Manager,14.0,high
+33.0,Male,Bachelor's Degree,Full Stack Engineer,7.0,above average
+42.0,Male,PhD,Senior Software Engineer,12.0,high
+28.0,Male,Bachelor's Degree,Back end Developer,2.0,below average
+55.0,Male,PhD,Software Engineer Manager,18.0,high
+26.0,Female,Master's Degree,Front end Developer,1.0,minimal
+47.0,Male,PhD,Senior Project Engineer,16.0,high
+44.0,Female,PhD,Software Engineer Manager,11.0,above average
+30.0,Male,Master's Degree,Full Stack Engineer,5.0,average
+39.0,Female,Master's Degree,Senior Software Engineer,11.0,above average
+32.0,Male,Bachelor's Degree,Front end Developer,6.0,average
+50.0,Male,PhD,Software Engineer Manager,17.0,high
+27.0,Male,Bachelor's Degree,Back end Developer,3.0,below average
+46.0,Male,PhD,Senior Project Engineer,14.0,high
+25.0,Female,Bachelor's Degree,Front end Developer,1.0,minimal
+43.0,Male,PhD,Senior Project Engineer,13.0,high
+35.0,Male,Bachelor's Degree,Back end Developer,8.0,above average
+29.0,Female,Master's Degree,Back end Developer,3.0,below average
+40.0,Female,PhD,Senior Software Engineer,12.0,above average
+35.0,Male,Bachelor's Degree,Full Stack Engineer,8.0,above average
+41.0,Male,PhD,Senior Project Engineer,13.0,high
+30.0,Male,Master's Degree,Full Stack Engineer,5.0,average
+33.0,Male,Bachelor's Degree,Front end Developer,6.0,average
+55.0,Male,PhD,Software Engineer Manager,18.0,high
+26.0,Female,Master's Degree,Front end Developer,1.0,minimal
+47.0,Male,PhD,Senior Project Engineer,16.0,high
+44.0,Female,PhD,Software Engineer Manager,11.0,above average
+30.0,Male,Master's Degree,Full Stack Engineer,5.0,average
+39.0,Female,Master's Degree,Senior Software Engineer,11.0,above average
+32.0,Male,Bachelor's Degree,Front end Developer,6.0,average
+50.0,Male,PhD,Software Engineer Manager,17.0,high
+27.0,Male,Bachelor's Degree,Back end Developer,3.0,below average
+46.0,Male,PhD,Senior Project Engineer,14.0,high
+25.0,Female,Bachelor's Degree,Front end Developer,1.0,minimal
+43.0,Male,PhD,Senior Project Engineer,13.0,high
+35.0,Male,Bachelor's Degree,Back end Developer,8.0,above average
+29.0,Female,Master's Degree,Back end Developer,3.0,below average
+40.0,Female,PhD,Senior Software Engineer,12.0,above average
+35.0,Male,Bachelor's Degree,Full Stack Engineer,8.0,above average
+41.0,Male,PhD,Senior Project Engineer,13.0,high
+30.0,Male,Master's Degree,Full Stack Engineer,5.0,average
+33.0,Male,Bachelor's Degree,Front end Developer,6.0,average
+55.0,Male,PhD,Software Engineer Manager,18.0,high
+26.0,Female,Master's Degree,Front end Developer,1.0,minimal
+47.0,Male,PhD,Senior Project Engineer,16.0,high
+44.0,Female,PhD,Software Engineer Manager,11.0,above average
+30.0,Male,Master's Degree,Full Stack Engineer,5.0,average
+39.0,Female,Master's Degree,Senior Software Engineer,11.0,above average
+32.0,Male,Bachelor's Degree,Front end Developer,6.0,average
+50.0,Male,PhD,Software Engineer Manager,17.0,high
+27.0,Male,Bachelor's Degree,Back end Developer,3.0,below average
+46.0,Male,PhD,Senior Project Engineer,14.0,high
+25.0,Female,Bachelor's Degree,Front end Developer,1.0,minimal
+43.0,Male,PhD,Senior Project Engineer,13.0,high
+35.0,Male,Bachelor's Degree,Back end Developer,8.0,above average
+29.0,Female,Master's Degree,Back end Developer,3.0,below average
+40.0,Female,PhD,Senior Software Engineer,12.0,above average
+35.0,Male,Bachelor's Degree,Full Stack Engineer,8.0,above average
+41.0,Male,PhD,Senior Project Engineer,13.0,high
+30.0,Male,Master's Degree,Full Stack Engineer,5.0,average
+33.0,Male,Bachelor's Degree,Front end Developer,6.0,average
+55.0,Male,PhD,Software Engineer Manager,18.0,high
+26.0,Female,Master's Degree,Front end Developer,1.0,minimal
+47.0,Male,PhD,Senior Project Engineer,16.0,high
+44.0,Female,PhD,Software Engineer Manager,11.0,above average
+30.0,Male,Master's Degree,Full Stack Engineer,5.0,average
+39.0,Female,Master's Degree,Senior Software Engineer,11.0,above average
+32.0,Male,Bachelor's Degree,Front end Developer,6.0,average
+50.0,Male,PhD,Software Engineer Manager,17.0,high
+27.0,Male,Bachelor's Degree,Back end Developer,3.0,below average
+46.0,Male,PhD,Senior Project Engineer,14.0,high
+25.0,Female,Bachelor's Degree,Front end Developer,1.0,minimal
+43.0,Male,PhD,Senior Project Engineer,13.0,high
+35.0,Male,Bachelor's Degree,Back end Developer,8.0,above average
+29.0,Female,Master's Degree,Back end Developer,3.0,below average
+40.0,Female,PhD,Senior Software Engineer,12.0,above average
+35.0,Male,Bachelor's Degree,Full Stack Engineer,8.0,above average
+41.0,Male,PhD,Senior Project Engineer,13.0,high
+30.0,Male,Master's Degree,Full Stack Engineer,5.0,average
+33.0,Male,Bachelor's Degree,Front end Developer,6.0,average
+55.0,Male,PhD,Software Engineer Manager,18.0,high
+26.0,Female,Master's Degree,Front end Developer,1.0,minimal
+47.0,Male,PhD,Senior Project Engineer,16.0,high
+44.0,Female,PhD,Software Engineer Manager,11.0,above average
+30.0,Male,Master's Degree,Full Stack Engineer,5.0,average
+39.0,Female,Master's Degree,Senior Software Engineer,11.0,above average
+32.0,Male,Bachelor's Degree,Front end Developer,6.0,average
+50.0,Male,PhD,Software Engineer Manager,17.0,high
+27.0,Male,Bachelor's Degree,Back end Developer,3.0,below average
+46.0,Male,PhD,Senior Project Engineer,14.0,high
+25.0,Female,Bachelor's Degree,Front end Developer,1.0,minimal
+43.0,Male,PhD,Senior Project Engineer,13.0,high
+35.0,Male,Bachelor's Degree,Back end Developer,8.0,above average
+29.0,Female,Master's Degree,Back end Developer,3.0,below average
+40.0,Female,PhD,Senior Software Engineer,12.0,above average
+35.0,Male,Bachelor's Degree,Full Stack Engineer,8.0,above average
+41.0,Male,PhD,Senior Project Engineer,13.0,high
+30.0,Male,Master's Degree,Full Stack Engineer,5.0,average
+33.0,Male,Bachelor's Degree,Front end Developer,6.0,average
+55.0,Male,PhD,Software Engineer Manager,18.0,high
+26.0,Female,Master's Degree,Front end Developer,1.0,minimal
+47.0,Male,PhD,Senior Project Engineer,16.0,high
+44.0,Female,PhD,Software Engineer Manager,11.0,above average
+30.0,Male,Master's Degree,Full Stack Engineer,5.0,average
+39.0,Female,Master's Degree,Senior Software Engineer,11.0,above average
+32.0,Male,Bachelor's Degree,Front end Developer,6.0,average
+50.0,Male,PhD,Software Engineer Manager,17.0,high
+27.0,Male,Bachelor's Degree,Back end Developer,3.0,below average
+46.0,Male,PhD,Senior Project Engineer,14.0,high
+25.0,Female,Bachelor's Degree,Front end Developer,1.0,minimal
+43.0,Male,PhD,Senior Project Engineer,13.0,high
+35.0,Male,Bachelor's Degree,Back end Developer,8.0,above average
+29.0,Female,Master's Degree,Back end Developer,3.0,below average
+40.0,Female,PhD,Senior Software Engineer,12.0,above average
+35.0,Male,Bachelor's Degree,Full Stack Engineer,8.0,above average
+41.0,Male,PhD,Senior Project Engineer,13.0,high
+30.0,Male,Master's Degree,Full Stack Engineer,5.0,average
+33.0,Male,Bachelor's Degree,Front end Developer,6.0,average
+55.0,Male,PhD,Software Engineer Manager,18.0,high
+31.0,Male,Bachelor's Degree,Front end Developer,6.0,average
+42.0,Female,Master's Degree,Software Engineer Manager,13.0,high
+27.0,Female,Bachelor's Degree,Back end Developer,3.0,below average
+51.0,Male,PhD,Senior Project Engineer,19.0,high
+34.0,Female,Master's Degree,Full Stack Engineer,7.0,above average
+38.0,Male,Bachelor's Degree,Software Engineer Manager,11.0,above average
+29.0,Male,Bachelor's Degree,Front end Developer,5.0,average
+43.0,Female,PhD,Senior Project Engineer,14.0,high
+36.0,Male,Master's Degree,Back end Developer,8.0,above average
+48.0,Male,PhD,Software Engineer Manager,16.0,high
+35.0,Female,Bachelor's Degree,Full Stack Engineer,8.0,above average
+30.0,Female,Master's Degree,Front end Developer,4.0,below average
+50.0,Male,PhD,Senior Project Engineer,18.0,high
+29.0,Male,Bachelor's Degree,Back end Developer,4.0,average
+41.0,Male,Master's Degree,Software Engineer Manager,13.0,high
+33.0,Female,Bachelor's Degree,Full Stack Engineer,6.0,average
+45.0,Male,PhD,Senior Project Engineer,16.0,high
+28.0,Female,Bachelor's Degree,Front end Developer,2.0,below average
+39.0,Female,Master's Degree,Software Engineer Manager,12.0,above average
+30.0,Male,Bachelor's Degree,Back end Developer,5.0,average
+46.0,Male,PhD,Senior Project Engineer,15.0,high
+25.0,Female,Bachelor's Degree,Front end Developer,1.0,minimal
+42.0,Male,PhD,Software Engineer Manager,14.0,high
+31.0,Male,Bachelor's Degree,Full Stack Engineer,6.0,average
+49.0,Female,PhD,Senior Project Engineer,17.0,high
+36.0,Male,Master's Degree,Back end Developer,9.0,above average
+33.0,Female,Bachelor's Degree,Full Stack Engineer,6.0,average
+45.0,Male,PhD,Software Engineer Manager,16.0,high
+28.0,Female,Bachelor's Degree,Front end Developer,2.0,below average
+39.0,Female,Master's Degree,Software Engineer Manager,12.0,above average
+30.0,Male,Bachelor's Degree,Back end Developer,5.0,average
+46.0,Male,PhD,Senior Project Engineer,15.0,high
+25.0,Female,Bachelor's Degree,Front end Developer,1.0,minimal
+42.0,Male,PhD,Software Engineer Manager,14.0,high
+31.0,Male,Bachelor's Degree,Full Stack Engineer,6.0,average
+49.0,Female,PhD,Senior Project Engineer,17.0,high
+36.0,Male,Master's Degree,Back end Developer,9.0,above average
+33.0,Female,Bachelor's Degree,Full Stack Engineer,6.0,average
+45.0,Male,PhD,Software Engineer Manager,16.0,high
+28.0,Female,Bachelor's Degree,Front end Developer,2.0,below average
+39.0,Female,Master's Degree,Software Engineer Manager,12.0,above average
+30.0,Male,Bachelor's Degree,Back end Developer,5.0,average
+46.0,Male,PhD,Senior Project Engineer,15.0,high
+25.0,Female,Bachelor's Degree,Front end Developer,1.0,minimal
+42.0,Male,PhD,Software Engineer Manager,14.0,high
+31.0,Male,Bachelor's Degree,Full Stack Engineer,6.0,average
+49.0,Female,PhD,Senior Project Engineer,17.0,high
+36.0,Male,Master's Degree,Back end Developer,9.0,above average
+33.0,Female,Bachelor's Degree,Full Stack Engineer,6.0,average
+45.0,Male,PhD,Software Engineer Manager,16.0,high
+28.0,Female,Bachelor's Degree,Front end Developer,2.0,below average
+39.0,Female,Master's Degree,Software Engineer Manager,12.0,above average
+30.0,Male,Bachelor's Degree,Back end Developer,5.0,average
+46.0,Male,PhD,Senior Project Engineer,15.0,high
+25.0,Female,Bachelor's Degree,Front end Developer,1.0,minimal
+42.0,Male,PhD,Software Engineer Manager,14.0,high
+31.0,Male,Bachelor's Degree,Full Stack Engineer,6.0,average
+49.0,Female,PhD,Senior Project Engineer,17.0,high
+36.0,Male,Master's Degree,Back end Developer,9.0,above average
+33.0,Female,Bachelor's Degree,Full Stack Engineer,6.0,average
+45.0,Male,PhD,Software Engineer Manager,16.0,high
+28.0,Female,Bachelor's Degree,Front end Developer,2.0,below average
+39.0,Female,Master's Degree,Software Engineer Manager,12.0,above average
+30.0,Male,Bachelor's Degree,Back end Developer,5.0,average
+46.0,Male,PhD,Senior Project Engineer,15.0,high
+25.0,Female,Bachelor's Degree,Front end Developer,1.0,minimal
+42.0,Male,PhD,Software Engineer Manager,14.0,high
+31.0,Male,Bachelor's Degree,Full Stack Engineer,6.0,average
+49.0,Female,PhD,Senior Project Engineer,17.0,high
+36.0,Male,Master's Degree,Back end Developer,9.0,above average
+33.0,Female,Bachelor's Degree,Full Stack Engineer,6.0,average
+45.0,Male,PhD,Software Engineer Manager,16.0,high
+28.0,Female,Bachelor's Degree,Front end Developer,2.0,below average
+39.0,Female,Master's Degree,Software Engineer Manager,12.0,above average
+30.0,Male,Bachelor's Degree,Back end Developer,5.0,average
+46.0,Male,PhD,Senior Project Engineer,15.0,high
+25.0,Female,Bachelor's Degree,Front end Developer,1.0,minimal
+42.0,Male,PhD,Software Engineer Manager,14.0,high
+31.0,Male,Bachelor's Degree,Full Stack Engineer,6.0,average
+49.0,Female,PhD,Senior Project Engineer,17.0,high
+36.0,Male,Master's Degree,Back end Developer,9.0,above average
+33.0,Female,Bachelor's Degree,Full Stack Engineer,6.0,average
+45.0,Male,PhD,Software Engineer Manager,16.0,high
+28.0,Female,Bachelor's Degree,Front end Developer,2.0,below average
+39.0,Female,Master's Degree,Software Engineer Manager,12.0,above average
+30.0,Male,Bachelor's Degree,Back end Developer,5.0,average
+46.0,Male,PhD,Senior Project Engineer,15.0,high
+25.0,Female,Bachelor's Degree,Front end Developer,1.0,minimal
+42.0,Male,PhD,Software Engineer Manager,14.0,high
+31.0,Male,Bachelor's Degree,Full Stack Engineer,6.0,average
+49.0,Female,PhD,Senior Project Engineer,17.0,high
+36.0,Male,Master's Degree,Back end Developer,9.0,above average
+33.0,Female,Bachelor's Degree,Full Stack Engineer,6.0,average
+45.0,Male,PhD,Software Engineer Manager,16.0,high
+28.0,Female,Bachelor's Degree,Front end Developer,2.0,below average
+39.0,Female,Master's Degree,Software Engineer Manager,12.0,above average
+30.0,Male,Bachelor's Degree,Back end Developer,5.0,average
+46.0,Male,PhD,Senior Project Engineer,15.0,high
+25.0,Female,Bachelor's Degree,Front end Developer,1.0,minimal
+42.0,Male,PhD,Software Engineer Manager,14.0,high
+31.0,Male,Bachelor's Degree,Full Stack Engineer,6.0,average
+49.0,Female,PhD,Senior Project Engineer,17.0,high
+36.0,Male,Master's Degree,Back end Developer,9.0,above average
+33.0,Female,Bachelor's Degree,Full Stack Engineer,6.0,average
+45.0,Male,PhD,Software Engineer Manager,16.0,high
+28.0,Female,Bachelor's Degree,Front end Developer,2.0,below average
+39.0,Female,Master's Degree,Software Engineer Manager,12.0,above average
+30.0,Male,Bachelor's Degree,Back end Developer,5.0,average
+46.0,Male,PhD,Senior Project Engineer,15.0,high
+25.0,Female,Bachelor's Degree,Front end Developer,1.0,minimal
+42.0,Male,PhD,Software Engineer Manager,14.0,high
+31.0,Male,Bachelor's Degree,Full Stack Engineer,6.0,average
+49.0,Female,PhD,Senior Project Engineer,17.0,high
+36.0,Male,Master's Degree,Back end Developer,9.0,above average
+33.0,Female,Bachelor's Degree,Full Stack Engineer,6.0,average
+45.0,Male,PhD,Software Engineer Manager,16.0,high
+28.0,Female,Bachelor's Degree,Front end Developer,2.0,below average
+39.0,Female,Master's Degree,Software Engineer Manager,12.0,above average
+30.0,Male,Bachelor's Degree,Back end Developer,5.0,average
+46.0,Male,PhD,Senior Project Engineer,15.0,high
+25.0,Female,Bachelor's Degree,Front end Developer,1.0,minimal
+29.0,Male,Bachelor's Degree,Front end Developer,4.0,below average
+40.0,Female,Master's Degree,Software Engineer Manager,12.0,above average
+27.0,Female,Bachelor's Degree,Back end Developer,3.0,below average
+50.0,Male,PhD,Senior Project Engineer,18.0,high
+33.0,Female,Master's Degree,Full Stack Engineer,6.0,average
+37.0,Male,Bachelor's Degree,Software Engineer Manager,10.0,above average
+28.0,Male,Bachelor's Degree,Front end Developer,2.0,below average
+44.0,Female,PhD,Senior Project Engineer,14.0,high
+35.0,Male,Master's Degree,Back end Developer,8.0,above average
+47.0,Male,PhD,Software Engineer Manager,16.0,high
+34.0,Female,Bachelor's Degree,Full Stack Engineer,7.0,above average
+31.0,Female,Master's Degree,Front end Developer,5.0,average
+51.0,Male,PhD,Senior Project Engineer,19.0,high
+30.0,Male,Bachelor's Degree,Back end Developer,5.0,average
+42.0,Male,Master's Degree,Software Engineer Manager,13.0,high
+33.0,Female,Bachelor's Degree,Full Stack Engineer,6.0,average
+45.0,Male,PhD,Senior Project Engineer,16.0,high
+29.0,Female,Bachelor's Degree,Front end Developer,4.0,below average
+39.0,Female,Master's Degree,Software Engineer Manager,12.0,above average
+27.0,Male,Bachelor's Degree,Back end Developer,3.0,below average
+49.0,Male,PhD,Senior Project Engineer,17.0,high
+32.0,Female,Master's Degree,Full Stack Engineer,6.0,average
+36.0,Male,Bachelor's Degree,Software Engineer Manager,8.0,above average
+27.0,Male,Bachelor's Degree,Front end Developer,2.0,below average
+43.0,Female,PhD,Senior Project Engineer,14.0,high
+34.0,Male,Master's Degree,Back end Developer,8.0,above average
+46.0,Male,PhD,Software Engineer Manager,16.0,high
+33.0,Female,Bachelor's Degree,Full Stack Engineer,7.0,above average
+30.0,Female,Master's Degree,Front end Developer,5.0,average
+50.0,Male,PhD,Senior Project Engineer,19.0,high
+30.0,Male,Bachelor's Degree,Back end Developer,5.0,average
+42.0,Male,Master's Degree,Software Engineer Manager,13.0,high
+33.0,Female,Bachelor's Degree,Full Stack Engineer,6.0,average
+45.0,Male,PhD,Senior Project Engineer,16.0,high
+29.0,Female,Bachelor's Degree,Front end Developer,4.0,below average
+39.0,Female,Master's Degree,Software Engineer Manager,12.0,above average
+27.0,Male,Bachelor's Degree,Back end Developer,3.0,below average
+49.0,Male,PhD,Senior Project Engineer,17.0,high
+32.0,Female,Master's Degree,Full Stack Engineer,6.0,average
+36.0,Male,Bachelor's Degree,Software Engineer Manager,8.0,above average
+27.0,Male,Bachelor's Degree,Front end Developer,2.0,below average
+43.0,Female,PhD,Senior Project Engineer,14.0,high
+34.0,Male,Master's Degree,Back end Developer,8.0,above average
+46.0,Male,PhD,Software Engineer Manager,16.0,high
+33.0,Female,Bachelor's Degree,Full Stack Engineer,7.0,above average
+30.0,Female,Master's Degree,Front end Developer,5.0,average
+50.0,Male,PhD,Senior Project Engineer,19.0,high
+30.0,Male,Bachelor's Degree,Back end Developer,5.0,average
+42.0,Male,Master's Degree,Software Engineer Manager,13.0,high
+33.0,Female,Bachelor's Degree,Full Stack Engineer,6.0,average
+45.0,Male,PhD,Senior Project Engineer,16.0,high
+29.0,Female,Bachelor's Degree,Front end Developer,4.0,below average
+39.0,Female,Master's Degree,Software Engineer Manager,12.0,above average
+27.0,Male,Bachelor's Degree,Back end Developer,3.0,below average
+49.0,Male,PhD,Senior Project Engineer,17.0,high
+32.0,Female,Master's Degree,Full Stack Engineer,6.0,average
+36.0,Male,Bachelor's Degree,Software Engineer Manager,8.0,above average
+27.0,Male,Bachelor's Degree,Front end Developer,2.0,below average
+43.0,Female,PhD,Senior Project Engineer,14.0,high
+34.0,Male,Master's Degree,Back end Developer,8.0,above average
+46.0,Male,PhD,Software Engineer Manager,16.0,high
+33.0,Female,Bachelor's Degree,Full Stack Engineer,7.0,above average
+30.0,Female,Master's Degree,Front end Developer,5.0,average
+50.0,Male,PhD,Senior Project Engineer,19.0,high
+30.0,Male,Bachelor's Degree,Back end Developer,5.0,average
+42.0,Male,Master's Degree,Software Engineer Manager,13.0,high
+33.0,Female,Bachelor's Degree,Full Stack Engineer,6.0,average
+45.0,Male,PhD,Senior Project Engineer,16.0,high
+29.0,Female,Bachelor's Degree,Front end Developer,4.0,below average
+39.0,Female,Master's Degree,Software Engineer Manager,12.0,above average
+27.0,Male,Bachelor's Degree,Back end Developer,3.0,below average
+49.0,Male,PhD,Senior Project Engineer,17.0,high
+32.0,Female,Master's Degree,Full Stack Engineer,6.0,average
+36.0,Male,Bachelor's Degree,Software Engineer Manager,8.0,above average
+27.0,Male,Bachelor's Degree,Front end Developer,2.0,below average
+43.0,Female,PhD,Senior Project Engineer,14.0,high
+34.0,Male,Master's Degree,Back end Developer,8.0,above average
+46.0,Male,PhD,Software Engineer Manager,16.0,high
+33.0,Female,Bachelor's Degree,Full Stack Engineer,7.0,above average
+30.0,Female,Master's Degree,Front end Developer,5.0,average
+50.0,Male,PhD,Senior Project Engineer,19.0,high
+30.0,Male,Bachelor's Degree,Back end Developer,5.0,average
+42.0,Male,Master's Degree,Software Engineer Manager,13.0,high
+33.0,Female,Bachelor's Degree,Full Stack Engineer,6.0,average
+45.0,Male,PhD,Senior Project Engineer,16.0,high
+29.0,Female,Bachelor's Degree,Front end Developer,4.0,below average
+39.0,Female,Master's Degree,Software Engineer Manager,12.0,above average
+27.0,Male,Bachelor's Degree,Back end Developer,3.0,below average
+49.0,Male,PhD,Senior Project Engineer,17.0,high
+32.0,Female,Master's Degree,Full Stack Engineer,6.0,average
+36.0,Male,Bachelor's Degree,Software Engineer Manager,8.0,above average
+27.0,Male,Bachelor's Degree,Front end Developer,2.0,below average
+43.0,Female,PhD,Senior Project Engineer,14.0,high
+34.0,Male,Master's Degree,Back end Developer,8.0,above average
+46.0,Male,PhD,Software Engineer Manager,16.0,high
+33.0,Female,Bachelor's Degree,Full Stack Engineer,7.0,above average
+30.0,Female,Master's Degree,Front end Developer,5.0,average
+50.0,Male,PhD,Senior Project Engineer,19.0,high
+30.0,Male,Bachelor's Degree,Back end Developer,5.0,average
+42.0,Male,Master's Degree,Software Engineer Manager,13.0,high
+33.0,Female,Bachelor's Degree,Full Stack Engineer,6.0,average
+45.0,Male,PhD,Senior Project Engineer,16.0,high
+29.0,Female,Bachelor's Degree,Front end Developer,4.0,below average
+39.0,Female,Master's Degree,Software Engineer Manager,12.0,above average
+27.0,Male,Bachelor's Degree,Back end Developer,3.0,below average
+49.0,Male,PhD,Senior Project Engineer,17.0,high
+32.0,Female,Master's Degree,Full Stack Engineer,6.0,average
+36.0,Male,Bachelor's Degree,Software Engineer Manager,8.0,above average
+27.0,Male,Bachelor's Degree,Front end Developer,2.0,below average
+43.0,Female,PhD,Senior Project Engineer,14.0,high
+34.0,Male,Master's Degree,Back end Developer,8.0,above average
+46.0,Male,PhD,Software Engineer Manager,16.0,high
+33.0,Female,Bachelor's Degree,Full Stack Engineer,7.0,above average
+30.0,Female,Master's Degree,Front end Developer,5.0,average
+50.0,Male,PhD,Senior Project Engineer,19.0,high
+30.0,Male,Bachelor's Degree,Back end Developer,5.0,average
+42.0,Male,Master's Degree,Software Engineer Manager,13.0,high
+33.0,Female,Bachelor's Degree,Full Stack Engineer,6.0,average
+45.0,Male,PhD,Senior Project Engineer,16.0,high
+29.0,Female,Bachelor's Degree,Front end Developer,4.0,below average
+27.0,Male,,Developer,7.0,average
+31.0,Female,Bachelor's Degree,Front end Developer,6.0,average
+37.0,Male,Master's Degree,Software Engineer Manager,10.0,above average
+27.0,Male,Bachelor's Degree,Back end Developer,3.0,below average
+50.0,Male,PhD,Senior Project Engineer,18.0,high
+32.0,Female,Master's Degree,Full Stack Engineer,6.0,average
+36.0,Male,Bachelor's Degree,Software Engineer Manager,8.0,above average
+27.0,Male,Bachelor's Degree,Front end Developer,2.0,below average
+43.0,Female,PhD,Senior Project Engineer,14.0,high
+34.0,Male,Master's Degree,Back end Developer,8.0,above average
+46.0,Male,PhD,Software Engineer Manager,16.0,high
+33.0,Female,Bachelor's Degree,Full Stack Engineer,7.0,above average
+30.0,Female,Master's Degree,Front end Developer,5.0,average
+50.0,Male,PhD,Senior Project Engineer,19.0,high
+30.0,Male,Bachelor's Degree,Back end Developer,5.0,average
+42.0,Male,Master's Degree,Software Engineer Manager,13.0,high
+33.0,Female,Bachelor's Degree,Full Stack Engineer,6.0,average
+45.0,Male,PhD,Senior Project Engineer,16.0,high
+29.0,Female,Bachelor's Degree,Front end Developer,4.0,below average
+39.0,Female,Master's Degree,Software Engineer Manager,12.0,above average
+27.0,Male,Bachelor's Degree,Back end Developer,3.0,below average
+49.0,Male,PhD,Senior Project Engineer,17.0,high
+32.0,Female,Master's Degree,Full Stack Engineer,6.0,average
+36.0,Male,Bachelor's Degree,Software Engineer Manager,8.0,above average
+27.0,Male,Bachelor's Degree,Front end Developer,2.0,below average
+43.0,Female,PhD,Senior Project Engineer,14.0,high
+34.0,Male,Master's Degree,Back end Developer,8.0,above average
+46.0,Male,PhD,Software Engineer Manager,16.0,high
+33.0,Female,Bachelor's Degree,Full Stack Engineer,7.0,above average
+30.0,Female,Master's Degree,Front end Developer,5.0,average
+50.0,Male,PhD,Senior Project Engineer,19.0,high
+30.0,Male,Bachelor's Degree,Back end Developer,5.0,average
+42.0,Male,Master's Degree,Software Engineer Manager,13.0,high
+33.0,Female,Bachelor's Degree,Full Stack Engineer,6.0,average
+45.0,Male,PhD,Senior Project Engineer,16.0,high
+29.0,Female,Bachelor's Degree,Front end Developer,4.0,below average
+39.0,Female,Master's Degree,Software Engineer Manager,12.0,above average
+27.0,Male,Bachelor's Degree,Back end Developer,3.0,below average
+49.0,Male,PhD,Senior Project Engineer,17.0,high
+32.0,Female,Master's Degree,Full Stack Engineer,6.0,average
+36.0,Male,Bachelor's Degree,Software Engineer Manager,8.0,above average
+27.0,Male,Bachelor's Degree,Front end Developer,2.0,below average
+43.0,Female,PhD,Senior Project Engineer,14.0,high
+34.0,Male,Master's Degree,Back end Developer,8.0,above average
+46.0,Male,PhD,Software Engineer Manager,16.0,high
+33.0,Female,Bachelor's Degree,Full Stack Engineer,7.0,above average
+30.0,Female,Master's Degree,Front end Developer,5.0,average
+50.0,Male,PhD,Senior Project Engineer,19.0,high
+30.0,Male,Bachelor's Degree,Back end Developer,5.0,average
+42.0,Male,Master's Degree,Software Engineer Manager,13.0,high
+33.0,Female,Bachelor's Degree,Full Stack Engineer,6.0,average
+45.0,Male,PhD,Senior Project Engineer,16.0,high
+29.0,Female,Bachelor's Degree,Front end Developer,4.0,below average
+39.0,Female,Master's Degree,Software Engineer Manager,12.0,above average
+27.0,Male,Bachelor's Degree,Back end Developer,3.0,below average
+49.0,Male,PhD,Senior Project Engineer,17.0,high
+32.0,Female,Master's Degree,Full Stack Engineer,6.0,average
+36.0,Male,Bachelor's Degree,Software Engineer Manager,8.0,above average
+27.0,Male,Bachelor's Degree,Front end Developer,2.0,below average
+43.0,Female,PhD,Senior Project Engineer,14.0,high
+34.0,Male,Master's Degree,Back end Developer,8.0,above average
+46.0,Male,PhD,Software Engineer Manager,16.0,high
+33.0,Female,Bachelor's Degree,Full Stack Engineer,7.0,above average
+30.0,Female,Master's Degree,Front end Developer,5.0,average
+50.0,Male,PhD,Senior Project Engineer,19.0,high
+30.0,Male,Bachelor's Degree,Back end Developer,5.0,average
+42.0,Male,Master's Degree,Software Engineer Manager,13.0,high
+33.0,Female,Bachelor's Degree,Full Stack Engineer,6.0,average
+45.0,Male,PhD,Senior Project Engineer,16.0,high
+29.0,Female,Bachelor's Degree,Front end Developer,4.0,below average
+39.0,Female,Master's Degree,Software Engineer Manager,12.0,above average
+27.0,Male,Bachelor's Degree,Back end Developer,3.0,below average
+49.0,Male,PhD,Senior Project Engineer,17.0,high
+32.0,Female,Master's Degree,Full Stack Engineer,6.0,average
+36.0,Male,Bachelor's Degree,Software Engineer Manager,8.0,above average
+27.0,Male,Bachelor's Degree,Front end Developer,2.0,below average
+43.0,Female,PhD,Senior Project Engineer,14.0,high
+34.0,Male,Master's Degree,Back end Developer,8.0,above average
+46.0,Male,PhD,Software Engineer Manager,16.0,high
+33.0,Female,Bachelor's Degree,Full Stack Engineer,7.0,above average
+30.0,Female,Master's Degree,Front end Developer,5.0,average
+50.0,Male,PhD,Senior Project Engineer,19.0,high
+30.0,Male,Bachelor's Degree,Back end Developer,5.0,average
+42.0,Male,Master's Degree,Software Engineer Manager,13.0,high
+33.0,Female,Bachelor's Degree,Full Stack Engineer,6.0,average
+45.0,Male,PhD,Senior Project Engineer,16.0,high
+29.0,Female,Bachelor's Degree,Front end Developer,4.0,below average
+39.0,Female,Master's Degree,Software Engineer Manager,12.0,above average
+27.0,Male,Bachelor's Degree,Back end Developer,3.0,below average
+49.0,Male,PhD,Senior Project Engineer,17.0,high
+32.0,Female,Master's Degree,Full Stack Engineer,6.0,average
+36.0,Male,Bachelor's Degree,Software Engineer Manager,8.0,above average
+27.0,Male,Bachelor's Degree,Front end Developer,2.0,below average
+43.0,Female,PhD,Senior Project Engineer,14.0,high
+34.0,Male,Master's Degree,Back end Developer,8.0,above average
+46.0,Male,PhD,Software Engineer Manager,16.0,high
+33.0,Female,Bachelor's Degree,Full Stack Engineer,7.0,above average
+30.0,Female,Master's Degree,Front end Developer,5.0,average
+50.0,Male,PhD,Senior Project Engineer,19.0,high
+30.0,Male,Bachelor's Degree,Back end Developer,5.0,average
+42.0,Male,Master's Degree,Software Engineer Manager,13.0,high
+33.0,Female,Bachelor's Degree,Full Stack Engineer,6.0,average
+45.0,Male,PhD,Senior Project Engineer,16.0,high
+29.0,Female,Bachelor's Degree,Front end Developer,4.0,below average
+39.0,Female,Master's Degree,Software Engineer Manager,12.0,above average
+27.0,Male,Bachelor's Degree,Back end Developer,3.0,below average
+49.0,Male,PhD,Senior Project Engineer,17.0,high
+32.0,Female,Master's Degree,Full Stack Engineer,6.0,average
+36.0,Male,Bachelor's Degree,Software Engineer Manager,8.0,above average
+27.0,Male,Bachelor's Degree,Front end Developer,2.0,below average
+43.0,Female,PhD,Senior Project Engineer,14.0,high
+34.0,Male,Master's Degree,Back end Developer,8.0,above average
+46.0,Male,PhD,Software Engineer Manager,16.0,high
+33.0,Female,Bachelor's Degree,Full Stack Engineer,7.0,above average
+30.0,Female,Master's Degree,Front end Developer,5.0,average
+50.0,Male,PhD,Senior Project Engineer,19.0,high
+30.0,Male,Bachelor's Degree,Back end Developer,5.0,average
+42.0,Male,Master's Degree,Software Engineer Manager,13.0,high
+33.0,Female,Bachelor's Degree,Full Stack Engineer,6.0,average
+45.0,Male,PhD,Senior Project Engineer,16.0,high
+29.0,Female,Bachelor's Degree,Front end Developer,4.0,below average
+31.0,Male,Master's Degree,Software Engineer Manager,8.0,above average
+27.0,Male,Bachelor's Degree,Back end Developer,3.0,below average
+43.0,Male,PhD,Senior Project Engineer,15.0,high
+35.0,Female,Master's Degree,Full Stack Engineer,8.0,above average
+42.0,Male,Bachelor's Degree,Software Engineer Manager,12.0,above average
+28.0,Female,Bachelor's Degree,Front end Developer,2.0,minimal
+44.0,Female,PhD,Senior Project Engineer,16.0,high
+32.0,Male,Master's Degree,Back end Developer,7.0,average
+48.0,Male,PhD,Software Engineer Manager,18.0,high
+30.0,Female,Bachelor's Degree,Full Stack Engineer,5.0,average
+34.0,Male,Master's Degree,Front end Developer,9.0,above average
+37.0,Female,Bachelor's Degree,Software Engineer Manager,11.0,high
+26.0,Male,Bachelor's Degree,Back end Developer,2.0,below average
+49.0,Female,PhD,Senior Project Engineer,19.0,high
+29.0,Male,Bachelor's Degree,Full Stack Engineer,4.0,below average
+41.0,Male,Master's Degree,Software Engineer Manager,14.0,high
+31.0,Female,Bachelor's Degree,Front end Developer,6.0,average
+37.0,Male,Master's Degree,Software Engineer Manager,10.0,above average
+27.0,Male,Bachelor's Degree,Back end Developer,3.0,below average
+50.0,Male,PhD,Senior Project Engineer,18.0,high
+32.0,Female,Master's Degree,Full Stack Engineer,6.0,average
+36.0,Male,Bachelor's Degree,Software Engineer Manager,8.0,above average
+27.0,Male,Bachelor's Degree,Front end Developer,2.0,below average
+43.0,Female,PhD,Senior Project Engineer,14.0,high
+34.0,Male,Master's Degree,Back end Developer,8.0,above average
+46.0,Male,PhD,Software Engineer Manager,16.0,high
+33.0,Female,Bachelor's Degree,Full Stack Engineer,7.0,above average
+30.0,Female,Master's Degree,Front end Developer,5.0,average
+50.0,Male,PhD,Senior Project Engineer,19.0,high
+30.0,Male,Bachelor's Degree,Back end Developer,5.0,average
+42.0,Male,Master's Degree,Software Engineer Manager,13.0,high
+33.0,Female,Bachelor's Degree,Full Stack Engineer,6.0,average
+45.0,Male,PhD,Senior Project Engineer,16.0,high
+29.0,Female,Bachelor's Degree,Front end Developer,4.0,below average
+39.0,Female,Master's Degree,Software Engineer Manager,12.0,above average
+27.0,Male,Bachelor's Degree,Back end Developer,3.0,below average
+49.0,Male,PhD,Senior Project Engineer,17.0,high
+32.0,Female,Master's Degree,Full Stack Engineer,6.0,average
+36.0,Male,Bachelor's Degree,Software Engineer Manager,8.0,above average
+27.0,Male,Bachelor's Degree,Front end Developer,2.0,below average
+43.0,Female,PhD,Senior Project Engineer,14.0,high
+34.0,Male,Master's Degree,Back end Developer,8.0,above average
+46.0,Male,PhD,Software Engineer Manager,16.0,high
+33.0,Female,Bachelor's Degree,Full Stack Engineer,7.0,above average
+30.0,Female,Master's Degree,Front end Developer,5.0,average
+50.0,Male,PhD,Senior Project Engineer,19.0,high
+30.0,Male,Bachelor's Degree,Back end Developer,5.0,average
+42.0,Male,Master's Degree,Software Engineer Manager,13.0,high
+33.0,Female,Bachelor's Degree,Full Stack Engineer,6.0,average
+45.0,Male,PhD,Senior Project Engineer,16.0,high
+29.0,Female,Bachelor's Degree,Front end Developer,4.0,below average
+39.0,Female,Master's Degree,Software Engineer Manager,12.0,above average
+27.0,Male,Bachelor's Degree,Back end Developer,3.0,below average
+49.0,Male,PhD,Senior Project Engineer,17.0,high
+32.0,Female,Master's Degree,Full Stack Engineer,6.0,average
+36.0,Male,Bachelor's Degree,Software Engineer Manager,8.0,above average
+27.0,Male,Bachelor's Degree,Front end Developer,2.0,below average
+43.0,Female,PhD,Senior Project Engineer,14.0,high
+34.0,Male,Master's Degree,Back end Developer,8.0,above average
+46.0,Female,PhD,Senior Project Engineer,16.0,high
+33.0,Male,Bachelor's Degree,Full Stack Engineer,7.0,above average
+30.0,Male,Master's Degree,Front end Developer,5.0,average
+50.0,Male,PhD,Software Engineer Manager,20.0,high
+31.0,Male,Bachelor's Degree,Back end Developer,6.0,average
+39.0,Female,Master's Degree,Software Engineer Manager,11.0,high
+27.0,Male,Bachelor's Degree,Front end Developer,2.0,below average
+44.0,Female,PhD,Senior Project Engineer,16.0,high
+32.0,Male,Master's Degree,Back end Developer,7.0,average
+48.0,Male,PhD,Software Engineer Manager,19.0,high
+30.0,Female,Bachelor's Degree,Full Stack Engineer,5.0,average
+34.0,Male,Master's Degree,Front end Developer,9.0,above average
+37.0,Female,Bachelor's Degree,Software Engineer Manager,11.0,high
+26.0,Male,Bachelor's Degree,Back end Developer,2.0,below average
+49.0,Female,PhD,Senior Project Engineer,19.0,high
+29.0,Male,Bachelor's Degree,Full Stack Engineer,4.0,below average
+41.0,Male,Master's Degree,Software Engineer Manager,14.0,high
+31.0,Female,Bachelor's Degree,Front end Developer,6.0,average
+37.0,Male,Master's Degree,Software Engineer Manager,10.0,above average
+27.0,Male,Bachelor's Degree,Back end Developer,3.0,below average
+50.0,Male,PhD,Senior Project Engineer,18.0,high
+32.0,Female,Master's Degree,Full Stack Engineer,6.0,average
+36.0,Male,Bachelor's Degree,Software Engineer Manager,8.0,above average
+27.0,Male,Bachelor's Degree,Front end Developer,2.0,below average
+43.0,Female,PhD,Senior Project Engineer,14.0,high
+34.0,Male,Master's Degree,Back end Developer,8.0,above average
+46.0,Male,PhD,Software Engineer Manager,16.0,high
+33.0,Female,Bachelor's Degree,Full Stack Engineer,7.0,above average
+30.0,Female,Master's Degree,Front end Developer,5.0,average
+50.0,Male,PhD,Senior Project Engineer,19.0,high
+30.0,Male,Bachelor's Degree,Back end Developer,5.0,average
+42.0,Male,Master's Degree,Software Engineer Manager,13.0,high
+33.0,Female,Bachelor's Degree,Full Stack Engineer,6.0,average
+45.0,Male,PhD,Senior Project Engineer,16.0,high
+29.0,Female,Bachelor's Degree,Front end Developer,4.0,below average
+39.0,Female,Master's Degree,Software Engineer Manager,12.0,above average
+27.0,Male,Bachelor's Degree,Back end Developer,3.0,below average
+49.0,Male,PhD,Senior Project Engineer,17.0,high
+32.0,Female,Master's Degree,Full Stack Engineer,6.0,average
+36.0,Male,Bachelor's Degree,Software Engineer Manager,8.0,above average
+27.0,Male,Bachelor's Degree,Front end Developer,2.0,below average
+43.0,Female,PhD,Senior Project Engineer,14.0,high
+34.0,Male,Master's Degree,Back end Developer,8.0,above average
+46.0,Male,PhD,Software Engineer Manager,16.0,high
+33.0,Female,Bachelor's Degree,Full Stack Engineer,7.0,above average
+30.0,Female,Master's Degree,Front end Developer,5.0,average
+50.0,Male,PhD,Senior Project Engineer,19.0,high
+30.0,Male,Bachelor's Degree,Back end Developer,5.0,average
+42.0,Male,Master's Degree,Software Engineer Manager,13.0,high
+33.0,Female,Bachelor's Degree,Full Stack Engineer,6.0,average
+45.0,Male,PhD,Senior Project Engineer,16.0,high
+29.0,Female,Bachelor's Degree,Front end Developer,4.0,below average
+39.0,Female,Master's Degree,Software Engineer Manager,12.0,above average
+27.0,Male,Bachelor's Degree,Back end Developer,3.0,below average
+49.0,Male,PhD,Senior Project Engineer,17.0,high
+32.0,Female,Master's Degree,Full Stack Engineer,6.0,average
+36.0,Male,Bachelor's Degree,Software Engineer Manager,8.0,above average
+27.0,Male,Bachelor's Degree,Front end Developer,2.0,below average
+43.0,Female,PhD,Senior Project Engineer,14.0,high
+34.0,Male,Master's Degree,Back end Developer,8.0,above average
+28.0,Male,Bachelor's Degree,Software Engineer,4.0,below average
+33.0,Female,Master's Degree,Data Analyst,7.0,average
+22.0,Male,Bachelor's Degree,Front End Developer,1.0,minimal
+44.0,Male,PhD,Senior Data Scientist,15.0,high
+29.0,Female,Bachelor's Degree,Software Developer,3.0,below average
+31.0,Male,Master's Degree,Product Manager,6.0,average
+25.0,Female,Master's Degree,Software Engineer,2.0,below average
+38.0,Male,Bachelor's Degree,Data Scientist,10.0,above average
+27.0,Male,Bachelor's Degree,Software Engineer,3.0,below average
+46.0,Female,PhD,Director of Data Science,20.0,high
+33.0,Male,Master's Degree,Data Analyst,8.0,average
+24.0,Female,Bachelor's Degree,Software Developer,2.0,minimal
+36.0,Male,PhD,Senior Data Scientist,12.0,high
+30.0,Female,Bachelor's Degree,Software Engineer,5.0,below average
+29.0,Male,Bachelor's Degree,Front End Developer,4.0,below average
+42.0,Male,Master's Degree,Product Manager,14.0,high
+26.0,Male,Bachelor's Degree,Software Developer,2.0,below average
+35.0,Female,Master's Degree,Data Analyst,9.0,average
+27.0,Female,Bachelor's Degree,Software Engineer,3.0,below average
+48.0,Male,PhD,Director of Data Science,18.0,high
+34.0,Male,Master's Degree,Data Scientist,9.0,above average
+23.0,Female,Bachelor's Degree,Software Engineer,1.0,minimal
+32.0,Male,Master's Degree,Product Manager,7.0,average
+25.0,Female,Master's Degree,Software Engineer,2.0,below average
+37.0,Male,Bachelor's Degree,Data Analyst,11.0,above average
+28.0,Male,Bachelor's Degree,Software Engineer,4.0,below average
+41.0,Female,PhD,Director of Data Science,16.0,high
+34.0,Male,Master's Degree,Data Analyst,8.0,average
+24.0,Female,Bachelor's Degree,Software Developer,2.0,minimal
+36.0,Male,PhD,Senior Data Scientist,12.0,high
+30.0,Female,Bachelor's Degree,Software Engineer,5.0,below average
+29.0,Male,Bachelor's Degree,Front End Developer,4.0,below average
+42.0,Male,Master's Degree,Product Manager,14.0,high
+26.0,Male,Bachelor's Degree,Software Developer,2.0,below average
+35.0,Female,Master's Degree,Data Analyst,9.0,average
+27.0,Female,Bachelor's Degree,Software Engineer,3.0,below average
+48.0,Male,PhD,Director of Data Science,18.0,high
+34.0,Male,Master's Degree,Data Scientist,9.0,above average
+23.0,Female,Bachelor's Degree,Software Engineer,1.0,minimal
+32.0,Male,Master's Degree,Product Manager,7.0,average
+25.0,Female,Master's Degree,Software Engineer,2.0,below average
+37.0,Male,Bachelor's Degree,Data Analyst,11.0,above average
+28.0,Male,Bachelor's Degree,Software Engineer,4.0,below average
+41.0,Female,PhD,Director of Data Science,16.0,high
+34.0,Male,Master's Degree,Data Analyst,8.0,average
+24.0,Female,Bachelor's Degree,Software Developer,2.0,minimal
+36.0,Male,PhD,Senior Data Scientist,12.0,high
+30.0,Female,Bachelor's Degree,Software Engineer,5.0,below average
+29.0,Male,Bachelor's Degree,Front End Developer,4.0,below average
+42.0,Male,Master's Degree,Product Manager,14.0,high
+26.0,Male,Bachelor's Degree,Software Developer,2.0,below average
+35.0,Female,Master's Degree,Data Analyst,9.0,average
+27.0,Female,Bachelor's Degree,Software Engineer,3.0,below average
+48.0,Male,PhD,Director of Data Science,18.0,high
+34.0,Male,Master's Degree,Data Scientist,9.0,above average
+23.0,Female,Bachelor's Degree,Software Engineer,1.0,minimal
+32.0,Male,Master's Degree,Product Manager,7.0,average
+25.0,Female,Master's Degree,Software Engineer,2.0,below average
+37.0,Male,Bachelor's Degree,Data Analyst,11.0,above average
+28.0,Male,Bachelor's Degree,Software Engineer,4.0,below average
+41.0,Female,PhD,Director of Data Science,16.0,high
+34.0,Male,Master's Degree,Data Analyst,8.0,average
+24.0,Female,Bachelor's Degree,Software Developer,2.0,minimal
+36.0,Male,PhD,Senior Data Scientist,12.0,high
+30.0,Female,Bachelor's Degree,Software Engineer,5.0,below average
+29.0,Male,Bachelor's Degree,Front End Developer,4.0,below average
+42.0,Male,Master's Degree,Product Manager,14.0,high
+26.0,Male,Bachelor's Degree,Software Developer,2.0,below average
+35.0,Female,Master's Degree,Data Analyst,9.0,average
+27.0,Female,Bachelor's Degree,Software Engineer,3.0,below average
+48.0,Male,PhD,Director of Data Science,18.0,high
+34.0,Male,Master's Degree,Data Scientist,9.0,above average
+23.0,Female,Bachelor's Degree,Software Engineer,1.0,minimal
+32.0,Male,Master's Degree,Product Manager,7.0,average
+25.0,Female,Master's Degree,Software Engineer,2.0,below average
+37.0,Male,Bachelor's Degree,Data Analyst,11.0,above average
+28.0,Male,Bachelor's Degree,Software Engineer,4.0,below average
+41.0,Female,PhD,Director of Data Science,16.0,high
+34.0,Male,Master's Degree,Data Analyst,8.0,average
+24.0,Female,Bachelor's Degree,Software Developer,2.0,minimal
+36.0,Male,PhD,Senior Data Scientist,12.0,high
+30.0,Female,Bachelor's Degree,Software Engineer,5.0,below average
+29.0,Male,Bachelor's Degree,Front End Developer,4.0,below average
+42.0,Male,Master's Degree,Product Manager,14.0,high
+26.0,Male,Bachelor's Degree,Software Developer,2.0,below average
+35.0,Female,Master's Degree,Data Analyst,9.0,average
+27.0,Female,Bachelor's Degree,Software Engineer,3.0,below average
+48.0,Male,PhD,Director of Data Science,18.0,high
+34.0,Male,Master's Degree,Data Scientist,9.0,above average
+23.0,Female,Bachelor's Degree,Software Engineer,1.0,minimal
+32.0,Male,Master's Degree,Product Manager,7.0,average
+25.0,Female,Master's Degree,Software Engineer,2.0,below average
+37.0,Male,Bachelor's Degree,Data Analyst,11.0,above average
+28.0,Male,Bachelor's Degree,Software Engineer,4.0,below average
+41.0,Female,PhD,Director of Data Science,16.0,high
+34.0,Male,Master's Degree,Data Analyst,8.0,average
+24.0,Female,Bachelor's Degree,Software Developer,2.0,minimal
+36.0,Male,PhD,Senior Data Scientist,12.0,high
+30.0,Female,Bachelor's Degree,Software Engineer,5.0,below average
+29.0,Male,Bachelor's Degree,Front End Developer,4.0,below average
+42.0,Male,Master's Degree,Product Manager,14.0,high
+26.0,Male,Bachelor's Degree,Software Developer,2.0,below average
+35.0,Female,Master's Degree,Data Analyst,9.0,average
+27.0,Female,Bachelor's Degree,Software Engineer,3.0,below average
+48.0,Male,PhD,Director of Data Science,18.0,high
+34.0,Male,Master's Degree,Data Scientist,9.0,above average
+23.0,Female,Bachelor's Degree,Software Engineer,1.0,minimal
+32.0,Male,Master's Degree,Product Manager,7.0,average
+25.0,Female,Master's Degree,Software Engineer,2.0,below average
+37.0,Male,Bachelor's Degree,Data Analyst,11.0,above average
+28.0,Male,Bachelor's Degree,Software Engineer,4.0,below average
+41.0,Female,PhD,Director of Data Science,16.0,high
+34.0,Male,Master's Degree,Data Analyst,8.0,average
+24.0,Female,Bachelor's Degree,Software Developer,2.0,minimal
+36.0,Male,PhD,Senior Data Scientist,12.0,high
+30.0,Female,Bachelor's Degree,Software Engineer,5.0,below average
+29.0,Male,Bachelor's Degree,Front End Developer,4.0,below average
+42.0,Male,Master's Degree,Product Manager,14.0,high
+26.0,Male,Bachelor's Degree,Software Developer,2.0,below average
+35.0,Female,Master's Degree,Data Analyst,9.0,average
+27.0,Female,Bachelor's Degree,Software Engineer,3.0,below average
+48.0,Male,PhD,Director of Data Science,18.0,high
+34.0,Male,Master's Degree,Data Scientist,9.0,above average
+23.0,Female,Bachelor's Degree,Software Engineer,1.0,minimal
+34.0,Female,Bachelor's Degree,Full Stack Engineer,8.0,average
+25.0,Male,PhD,Software Engineer Manager,12.0,above average
+43.0,Male,Master's Degree,Senior Software Engineer,21.0,high
+53.0,Other,High School,Senior Project Engineer,31.0,above average
+27.0,Female,Master's Degree,Front end Developer,5.0,below average
+25.0,Male,Bachelor's Degree,Back end Developer,2.0,below average
+29.0,Female,Master's Degree,Senior Software Engineer,6.0,above average
+52.0,Male,PhD,Software Engineer Manager,23.0,above average
+41.0,Male,Master's Degree,Front end Developer,13.0,average
+49.0,Female,Bachelor's Degree,Back end Developer,19.0,average
+25.0,Other,High School,Full Stack Engineer,2.0,below average
+35.0,Male,Master's Degree,Senior Project Engineer,8.0,average
+57.0,Female,PhD,Full Stack Engineer,30.0,average
+35.0,Female,Bachelor's Degree,Senior Project Engineer,12.0,above average
+43.0,Male,Master's Degree,Senior Software Engineer,21.0,high
+37.0,Female,Bachelor's Degree,Full Stack Engineer,10.0,above average
+50.0,Male,Master's Degree,Software Engineer Manager,21.0,above average
+52.0,Female,Master's Degree,Senior Software Engineer,28.0,high
+26.0,Male,Bachelor's Degree,Back end Developer,3.0,below average
+34.0,Female,Master's Degree,Full Stack Engineer,10.0,above average
+30.0,Male,High School,Senior Project Engineer,11.0,average
+60.0,Female,PhD,Software Engineer Manager,33.0,high
+50.0,Male,Bachelor's Degree,Back end Developer,23.0,high
+58.0,Male,Master's Degree,Senior Software Engineer,27.0,high
+35.0,Female,Master's Degree,Full Stack Engineer,10.0,above average
+28.0,Male,Master's Degree,Front end Developer,5.0,below average
+57.0,Female,PhD,Software Engineer Manager,33.0,high
+46.0,Female,Bachelor's Degree,Senior Software Engineer,20.0,above average
+28.0,Male,High School,Back end Developer,7.0,average
+34.0,Male,Master's Degree,Full Stack Engineer,12.0,above average
+33.0,Female,Master's Degree,Senior Project Engineer,9.0,average
+37.0,Other,Master's Degree,Full Stack Engineer,14.0,above average
+33.0,Male,Master's Degree,Senior Software Engineer,8.0,above average
+53.0,Male,PhD,Software Engineer Manager,25.0,high
+35.0,Female,Bachelor's Degree,Back end Developer,10.0,average
+30.0,Male,Master's Degree,Full Stack Engineer,6.0,average
+24.0,Female,High School,Senior Project Engineer,1.0,minimal
+36.0,Male,Master's Degree,Front end Developer,8.0,average
+27.0,Female,Bachelor's Degree,Full Stack Engineer,4.0,below average
+23.0,Male,PhD,Software Engineer Manager,1.0,average
+28.0,Female,Master's Degree,Senior Software Engineer,5.0,average
+52.0,Male,Bachelor's Degree,Back end Developer,25.0,above average
+28.0,Female,Master's Degree,Full Stack Engineer,7.0,average
+32.0,Male,Master's Degree,Senior Project Engineer,11.0,average
+24.0,Female,Bachelor's Degree,Front end Developer,1.0,minimal
+43.0,Male,High School,Senior Software Engineer,22.0,above average
+60.0,Female,PhD,Software Engineer Manager,34.0,high
+24.0,Male,Master's Degree,Back end Developer,0.0,minimal
+55.0,Male,Bachelor's Degree,Senior Project Engineer,28.0,high
+29.0,Female,Master's Degree,Full Stack Engineer,4.0,average
+44.0,Male,PhD,Software Engineer Manager,19.0,high
+40.0,Female,Master's Degree,Senior Software Engineer,16.0,above average
+27.0,Male,Bachelor's Degree,Back end Developer,4.0,below average
+43.0,Male,Master's Degree,Full Stack Engineer,17.0,above average
+49.0,Female,High School,Senior Project Engineer,25.0,above average
+30.0,Male,Master's Degree,Front end Developer,8.0,average
+42.0,Female,Bachelor's Degree,Senior Software Engineer,18.0,above average
+26.0,Male,Master's Degree,Full Stack Engineer,4.0,average
+41.0,Female,PhD,Software Engineer Manager,13.0,above average
+46.0,Male,Bachelor's Degree,Senior Project Engineer,23.0,high
+57.0,Female,Master's Degree,Full Stack Engineer,33.0,high
+22.0,Female,High School,Back end Developer,0.0,minimal
+54.0,Male,PhD,Software Engineer Manager,28.0,high
+42.0,Female,Master's Degree,Senior Software Engineer,16.0,above average
+49.0,Male,Bachelor's Degree,Full Stack Engineer,22.0,high
+27.0,Female,Master's Degree,Back end Developer,4.0,below average
+36.0,Male,Bachelor's Degree,Senior Project Engineer,14.0,average
+31.0,Female,Master's Degree,Full Stack Engineer,6.0,average
+39.0,Male,Master's Degree,Software Engineer Manager,14.0,above average
+41.0,Female,Bachelor's Degree,Senior Project Engineer,20.0,above average
+48.0,Male,PhD,Full Stack Engineer,23.0,high
+39.0,Female,Master's Degree,Senior Software Engineer,15.0,above average
+48.0,Male,Bachelor's Degree,Front end Developer,23.0,high
+31.0,Other,High School,Back end Developer,8.0,average
+47.0,Male,Master's Degree,Senior Project Engineer,25.0,high
+29.0,Female,PhD,Full Stack Engineer,5.0,average
+32.0,Male,Bachelor's Degree,Software Engineer Manager,9.0,average
+38.0,Female,Master's Degree,Senior Software Engineer,13.0,above average
+34.0,Male,Bachelor's Degree,Back end Developer,10.0,below average
+23.0,Other,High School,Front end Developer,2.0,below average
+34.0,Female,Bachelor's Degree,Full Stack Engineer,8.0,average
+25.0,Male,PhD,Software Engineer Manager,12.0,above average
+43.0,Male,Master's Degree,Senior Software Engineer,21.0,high
+53.0,Other,High School,Senior Project Engineer,31.0,above average
+27.0,Female,Master's Degree,Front end Developer,5.0,below average
+25.0,Male,Bachelor's Degree,Back end Developer,2.0,below average
+29.0,Female,Master's Degree,Senior Software Engineer,6.0,above average
+52.0,Male,PhD,Software Engineer Manager,23.0,above average
+41.0,Male,Master's Degree,Front end Developer,13.0,average
+49.0,Female,Bachelor's Degree,Back end Developer,19.0,average
+25.0,Other,High School,Full Stack Engineer,2.0,below average
+35.0,Male,Master's Degree,Senior Project Engineer,8.0,average
+57.0,Female,PhD,Full Stack Engineer,30.0,average
+35.0,Female,Bachelor's Degree,Senior Project Engineer,12.0,above average
+43.0,Male,Master's Degree,Senior Software Engineer,21.0,high
+37.0,Female,Bachelor's Degree,Full Stack Engineer,10.0,above average
+50.0,Male,Master's Degree,Software Engineer Manager,21.0,above average
+52.0,Female,Master's Degree,Senior Software Engineer,28.0,high
+26.0,Male,Bachelor's Degree,Back end Developer,3.0,below average
+34.0,Female,Master's Degree,Full Stack Engineer,10.0,above average
+30.0,Male,High School,Senior Project Engineer,11.0,average
+60.0,Female,PhD,Software Engineer Manager,33.0,high
+50.0,Male,Bachelor's Degree,Back end Developer,23.0,high
+58.0,Male,Master's Degree,Senior Software Engineer,27.0,high
+35.0,Female,Master's Degree,Full Stack Engineer,10.0,above average
+28.0,Male,Master's Degree,Front end Developer,5.0,below average
+57.0,Female,PhD,Software Engineer Manager,33.0,high
+46.0,Female,Bachelor's Degree,Senior Software Engineer,20.0,above average
+28.0,Male,High School,Back end Developer,7.0,average
+34.0,Male,Master's Degree,Full Stack Engineer,12.0,above average
+33.0,Female,Master's Degree,Senior Project Engineer,9.0,average
+37.0,Other,Master's Degree,Full Stack Engineer,14.0,above average
+33.0,Male,Master's Degree,Senior Software Engineer,8.0,above average
+53.0,Male,PhD,Software Engineer Manager,25.0,high
+35.0,Female,Bachelor's Degree,Back end Developer,10.0,average
+30.0,Male,Master's Degree,Full Stack Engineer,6.0,average
+24.0,Female,High School,Senior Project Engineer,1.0,minimal
+36.0,Male,Master's Degree,Front end Developer,8.0,average
+27.0,Female,Bachelor's Degree,Full Stack Engineer,4.0,below average
+23.0,Male,PhD,Software Engineer Manager,1.0,average
+28.0,Female,Master's Degree,Senior Software Engineer,5.0,average
+52.0,Male,Bachelor's Degree,Back end Developer,25.0,above average
+28.0,Female,Master's Degree,Full Stack Engineer,7.0,average
+32.0,Male,Master's Degree,Senior Project Engineer,11.0,average
+24.0,Female,Bachelor's Degree,Front end Developer,1.0,minimal
+43.0,Male,High School,Senior Software Engineer,22.0,above average
+60.0,Female,PhD,Software Engineer Manager,34.0,high
+24.0,Male,Master's Degree,Back end Developer,0.0,minimal
+55.0,Male,Bachelor's Degree,Senior Project Engineer,28.0,high
+29.0,Female,Master's Degree,Full Stack Engineer,4.0,average
+44.0,Male,PhD,Software Engineer Manager,19.0,high
+40.0,Female,Master's Degree,Senior Software Engineer,16.0,above average
+27.0,Male,Bachelor's Degree,Back end Developer,4.0,below average
+43.0,Male,Master's Degree,Full Stack Engineer,17.0,above average
+49.0,Female,High School,Senior Project Engineer,25.0,above average
+30.0,Male,Master's Degree,Front end Developer,8.0,average
+42.0,Female,Bachelor's Degree,Senior Software Engineer,18.0,above average
+26.0,Male,Master's Degree,Full Stack Engineer,4.0,average
+41.0,Female,PhD,Software Engineer Manager,13.0,above average
+46.0,Male,Bachelor's Degree,Senior Project Engineer,23.0,high
+57.0,Female,Master's Degree,Full Stack Engineer,33.0,high
+22.0,Female,High School,Back end Developer,0.0,minimal
+54.0,Male,PhD,Software Engineer Manager,28.0,high
+42.0,Female,Master's Degree,Senior Software Engineer,16.0,above average
+49.0,Male,Bachelor's Degree,Full Stack Engineer,22.0,high
+27.0,Female,Master's Degree,Back end Developer,4.0,below average
+36.0,Male,Bachelor's Degree,Senior Project Engineer,14.0,average
+31.0,Female,Master's Degree,Full Stack Engineer,6.0,average
+39.0,Male,Master's Degree,Software Engineer Manager,14.0,above average
+41.0,Female,Bachelor's Degree,Senior Project Engineer,20.0,above average
+48.0,Male,PhD,Full Stack Engineer,23.0,high
+39.0,Female,Master's Degree,Senior Software Engineer,15.0,above average
+48.0,Male,Bachelor's Degree,Front end Developer,23.0,high
+31.0,Other,High School,Back end Developer,8.0,average
+47.0,Male,Master's Degree,Senior Project Engineer,25.0,high
+29.0,Female,PhD,Full Stack Engineer,5.0,average
+32.0,Male,Bachelor's Degree,Software Engineer Manager,9.0,average
+38.0,Female,Master's Degree,Senior Software Engineer,13.0,above average
+34.0,Male,Bachelor's Degree,Back end Developer,10.0,below average
+23.0,Other,High School,Front end Developer,2.0,below average
+36.0,Male,Bachelor's Degree,Front end Developer,14.0,above average
+30.0,Female,Master's Degree,Senior Project Engineer,5.0,average
+28.0,Male,Master's Degree,Full Stack Engineer,4.0,below average
+46.0,Female,PhD,Software Engineer Manager,23.0,above average
+34.0,Male,Bachelor's Degree,Back end Developer,10.0,average
+44.0,Male,Master's Degree,Senior Software Engineer,19.0,above average
+55.0,Female,PhD,Software Engineer Manager,30.0,high
+35.0,Male,Master's Degree,Full Stack Engineer,9.0,above average
+54.0,Male,Bachelor's Degree,Senior Project Engineer,29.0,high
+23.0,Female,High School,Back end Developer,2.0,below average
+46.0,Male,Master's Degree,Senior Software Engineer,21.0,high
+33.0,Female,Bachelor's Degree,Full Stack Engineer,9.0,above average
+26.0,Male,Master's Degree,Front end Developer,4.0,below average
+43.0,Female,PhD,Software Engineer Manager,19.0,above average
+36.0,Male,Master's Degree,Full Stack Engineer,11.0,above average
+23.0,Female,Bachelor's Degree,Senior Project Engineer,0.0,minimal
+49.0,Male,Master's Degree,Software Engineer Manager,22.0,high
+35.0,Female,Master's Degree,Full Stack Engineer,10.0,above average
+31.0,Male,Bachelor's Degree,Back end Developer,8.0,average
+54.0,Other,High School,Senior Software Engineer,29.0,above average
+43.0,Male,Master's Degree,Full Stack Engineer,20.0,above average
+33.0,Female,Master's Degree,Senior Project Engineer,10.0,average
+52.0,Female,PhD,Software Engineer Manager,29.0,high
+28.0,Male,Bachelor's Degree,Full Stack Engineer,5.0,below average
+36.0,Female,Master's Degree,Senior Software Engineer,13.0,above average
+43.0,Male,Bachelor's Degree,Senior Project Engineer,20.0,above average
+50.0,Female,Master's Degree,Full Stack Engineer,25.0,high
+24.0,Male,PhD,Software Engineer Manager,1.0,average
+52.0,Male,Master's Degree,Senior Software Engineer,26.0,high
+46.0,Female,Bachelor's Degree,Back end Developer,19.0,above average
+38.0,Male,Master's Degree,Full Stack Engineer,15.0,high
+29.0,Male,Bachelor's Degree,Senior Project Engineer,6.0,below average
+33.0,Female,Master's Degree,Front end Developer,10.0,average
+47.0,Male,PhD,Software Engineer Manager,21.0,high
+45.0,Female,Master's Degree,Senior Software Engineer,23.0,high
+28.0,Male,Bachelor's Degree,Back end Developer,4.0,below average
+42.0,Female,Master's Degree,Full Stack Engineer,14.0,above average
+46.0,Male,Bachelor's Degree,Senior Project Engineer,24.0,above average
+38.0,Female,PhD,Software Engineer Manager,15.0,above average
+54.0,Male,Master's Degree,Senior Software Engineer,31.0,high
+33.0,Female,Master's Degree,Full Stack Engineer,8.0,average
+27.0,Male,High School,Back end Developer,4.0,below average
+50.0,Female,Bachelor's Degree,Senior Project Engineer,25.0,high
+26.0,Male,Master's Degree,Full Stack Engineer,4.0,below average
+31.0,Female,Master's Degree,Senior Software Engineer,6.0,average
+35.0,Male,Bachelor's Degree,Front end Developer,10.0,average
+44.0,Female,PhD,Software Engineer Manager,18.0,above average
+32.0,Male,Master's Degree,Senior Project Engineer,8.0,average
+54.0,Male,Bachelor's Degree,Full Stack Engineer,25.0,high
+26.0,Female,Master's Degree,Front end Developer,3.0,below average
+23.0,Male,PhD,Software Engineer Manager,0.0,minimal
+48.0,Female,Master's Degree,Senior Software Engineer,24.0,high
+38.0,Male,Bachelor's Degree,Back end Developer,12.0,above average
+30.0,Female,Master's Degree,Full Stack Engineer,5.0,average
+40.0,Male,Master's Degree,Software Engineer Manager,16.0,above average
+45.0,Female,Bachelor's Degree,Senior Project Engineer,22.0,high
+36.0,Male,Master's Degree,Full Stack Engineer,13.0,above average
+52.0,Male,PhD,Software Engineer Manager,26.0,high
+31.0,Female,Bachelor's Degree,Senior Software Engineer,7.0,average
+26.0,Male,Master's Degree,Full Stack Engineer,4.0,below average
+30.0,Female,Master's Degree,Senior Project Engineer,5.0,average
+24.0,Male,Bachelor's Degree,Back end Developer,2.0,below average
+45.0,Male,Master's Degree,Senior Software Engineer,22.0,high
+33.0,Female,Master's Degree,Full Stack Engineer,9.0,above average
+38.0,Male,Bachelor's Degree,Front end Developer,11.0,above average
+54.0,Female,PhD,Software Engineer Manager,31.0,high
+42.0,Male,Master's Degree,Full Stack Engineer,19.0,high
+28.0,Female,Bachelor's Degree,Senior Project Engineer,4.0,below average
+30.0,Male,Master's Degree,Front end Developer,6.0,average
+43.0,Female,Master's Degree,Senior Software Engineer,19.0,above average
+35.0,Male,Bachelor's Degree,Back end Developer,10.0,average
+44.0,Male,Master's Degree,Full Stack Engineer,21.0,above average
+55.0,Female,Bachelor's Degree,Senior Project Engineer,30.0,high
+23.0,Male,High School,Front end Developer,1.0,minimal
+39.0,Female,Master's Degree,Senior Software Engineer,14.0,above average
+43.0,Male,Bachelor's Degree,Full Stack Engineer,17.0,above average
+29.0,Male,PhD,Software Engineer Manager,6.0,average
+51.0,Male,Master's Degree,Senior Software Engineer,28.0,high
+30.0,Female,Bachelor's Degree,Senior Project Engineer,6.0,below average
+26.0,Male,Master's Degree,Full Stack Engineer,4.0,below average
+39.0,Female,PhD,Software Engineer Manager,13.0,above average
+49.0,Male,Master's Degree,Front end Developer,24.0,high
+42.0,Female,Bachelor's Degree,Senior Software Engineer,20.0,above average
+27.0,Male,Bachelor's Degree,Back end Developer,4.0,below average
+43.0,Male,Master's Degree,Full Stack Engineer,21.0,high
+37.0,Female,Bachelor's Degree,Senior Project Engineer,13.0,above average
+51.0,Male,PhD,Software Engineer Manager,26.0,high
+29.0,Female,Master's Degree,Full Stack Engineer,5.0,average
+43.0,Male,Bachelor's Degree,Senior Software Engineer,20.0,above average
+31.0,Male,Master's Degree,Back end Developer,8.0,average
+30.0,Female,Master's Degree,Senior Project Engineer,6.0,average
+36.0,Male,Bachelor's Degree,Full Stack Engineer,13.0,above average
+52.0,Female,PhD,Software Engineer Manager,27.0,high
+28.0,Male,Master's Degree,Senior Software Engineer,6.0,average
+49.0,Male,Bachelor's Degree,Back end Developer,24.0,high
+27.0,Female,Master's Degree,Front end Developer,4.0,below average
+41.0,Male,Master's Degree,Senior Project Engineer,15.0,above average
+56.0,Female,PhD,Software Engineer Manager,31.0,high
+46.0,Male,Bachelor's Degree,Senior Software Engineer,22.0,high
+32.0,Female,Master's Degree,Full Stack Engineer,8.0,average
+38.0,Male,PhD,Software Engineer Manager,12.0,above average
+52.0,Male,Master's Degree,Senior Project Engineer,28.0,high
+24.0,Female,Bachelor's Degree,Back end Developer,1.0,below average
+49.0,Male,Master's Degree,Full Stack Engineer,22.0,high
+35.0,Female,Master's Degree,Senior Software Engineer,10.0,above average
+31.0,Male,Bachelor's Degree,Front end Developer,7.0,average
+44.0,Female,PhD,Software Engineer Manager,18.0,above average
+33.0,Male,Master's Degree,Senior Project Engineer,10.0,average
+54.0,Male,Bachelor's Degree,Senior Software Engineer,30.0,high
+33.0,Female,Master's Degree,Full Stack Engineer,11.0,average
+27.0,Male,High School,Back end Developer,3.0,below average
+51.0,Female,Master's Degree,Senior Project Engineer,25.0,high
+26.0,Male,Master's Degree,Full Stack Engineer,3.0,below average
+31.0,Female,Master's Degree,Senior Software Engineer,6.0,average
+35.0,Male,Bachelor's Degree,Front end Developer,9.0,average
+45.0,Female,PhD,Software Engineer Manager,23.0,high
+32.0,Male,Master's Degree,Senior Project Engineer,9.0,average
+54.0,Male,Bachelor's Degree,Full Stack Engineer,27.0,high
+26.0,Female,Master's Degree,Front end Developer,4.0,below average
+23.0,Male,PhD,Software Engineer Manager,1.0,minimal
+26.0,Female,Bachelor's Degree,Software Engineer,2.0,below average
+33.0,Male,Master's Degree,Data Analyst,8.0,average
+29.0,Female,Bachelor's Degree,Product Manager,4.0,below average
+41.0,Male,PhD,Data Scientist,15.0,high
+35.0,Female,Master's Degree,Software Engineer,9.0,above average
+28.0,Male,Bachelor's Degree,Software Developer,3.0,below average
+37.0,Female,Master's Degree,Data Scientist,11.0,above average
+33.0,Male,Bachelor's Degree,Product Manager,8.0,above average
+24.0,Female,Master's Degree,Software Engineer,2.0,below average
+46.0,Male,PhD,Director of Data Science,20.0,high
+29.0,Female,Bachelor's Degree,Software Developer,5.0,below average
+31.0,Male,Master's Degree,Data Scientist,7.0,above average
+27.0,Female,Bachelor's Degree,Software Engineer,3.0,below average
+38.0,Male,PhD,Senior Data Scientist,13.0,high
+30.0,Female,Master's Degree,Product Manager,6.0,average
+25.0,Male,Bachelor's Degree,Front End Developer,2.0,minimal
+44.0,Male,PhD,Director of Data Science,18.0,high
+33.0,Female,Master's Degree,Data Analyst,8.0,average
+22.0,Male,Bachelor's Degree,Software Engineer,1.0,minimal
+36.0,Male,Master's Degree,Product Manager,10.0,above average
+28.0,Female,Bachelor's Degree,Software Engineer,4.0,below average
+41.0,Male,PhD,Senior Data Scientist,16.0,high
+34.0,Female,Master's Degree,Data Scientist,9.0,above average
+23.0,Male,Bachelor's Degree,Software Developer,1.0,minimal
+32.0,Female,Master's Degree,Product Manager,7.0,average
+25.0,Male,Master's Degree,Software Engineer,2.0,below average
+37.0,Female,Bachelor's Degree,Data Analyst,11.0,above average
+28.0,Male,Bachelor's Degree,Software Engineer,4.0,below average
+41.0,Female,PhD,Director of Data Science,16.0,high
+34.0,Male,Master's Degree,Data Analyst,8.0,average
+24.0,Female,Bachelor's Degree,Software Developer,2.0,minimal
+36.0,Male,PhD,Senior Data Scientist,12.0,high
+30.0,Female,Bachelor's Degree,Software Engineer,5.0,below average
+29.0,Male,Bachelor's Degree,Front End Developer,4.0,below average
+42.0,Male,Master's Degree,Product Manager,14.0,high
+26.0,Male,Bachelor's Degree,Software Developer,2.0,below average
+35.0,Female,Master's Degree,Data Analyst,9.0,average
+27.0,Female,Bachelor's Degree,Software Engineer,3.0,below average
+48.0,Male,PhD,Director of Data Science,18.0,high
+34.0,Male,Master's Degree,Data Scientist,9.0,above average
+23.0,Female,Bachelor's Degree,Software Engineer,1.0,minimal
+32.0,Male,Master's Degree,Product Manager,7.0,average
+25.0,Female,Master's Degree,Software Engineer,2.0,below average
+37.0,Male,Bachelor's Degree,Data Analyst,11.0,above average
+28.0,Male,Bachelor's Degree,Software Engineer,4.0,below average
+41.0,Female,PhD,Director of Data Science,16.0,high
+34.0,Male,Master's Degree,Data Analyst,8.0,average
+24.0,Female,Bachelor's Degree,Software Developer,2.0,minimal
+36.0,Male,PhD,Senior Data Scientist,12.0,high
+30.0,Female,Bachelor's Degree,Software Engineer,5.0,below average
+29.0,Male,Bachelor's Degree,Front End Developer,4.0,below average
+42.0,Male,Master's Degree,Product Manager,14.0,high
+26.0,Male,Bachelor's Degree,Software Developer,2.0,below average
+35.0,Female,Master's Degree,Data Analyst,9.0,average
+27.0,Female,Bachelor's Degree,Software Engineer,3.0,below average
+48.0,Male,PhD,Director of Data Science,18.0,high
+34.0,Male,Master's Degree,Data Scientist,9.0,above average
+23.0,Female,Bachelor's Degree,Software Engineer,1.0,minimal
+32.0,Male,Master's Degree,Product Manager,7.0,average
+25.0,Female,Master's Degree,Software Engineer,2.0,below average
+37.0,Male,Bachelor's Degree,Data Analyst,11.0,above average
+28.0,Male,Bachelor's Degree,Software Engineer,4.0,below average
+41.0,Female,PhD,Director of Data Science,16.0,high
+34.0,Male,Master's Degree,Data Analyst,8.0,average
+24.0,Female,Bachelor's Degree,Software Developer,2.0,minimal
+36.0,Male,PhD,Senior Data Scientist,12.0,high
+30.0,Female,Bachelor's Degree,Software Engineer,5.0,below average
+29.0,Male,Bachelor's Degree,Front End Developer,4.0,below average
+42.0,Male,Master's Degree,Product Manager,14.0,high
+26.0,Male,Bachelor's Degree,Software Developer,2.0,below average
+35.0,Female,Master's Degree,Data Analyst,9.0,average
+27.0,Female,Bachelor's Degree,Software Engineer,3.0,below average
+48.0,Male,PhD,Director of Data Science,18.0,high
+34.0,Male,Master's Degree,Data Scientist,9.0,above average
+23.0,Female,Bachelor's Degree,Software Engineer,1.0,minimal
+32.0,Male,Master's Degree,Product Manager,7.0,average
+25.0,Female,Master's Degree,Software Engineer,2.0,below average
+37.0,Male,Bachelor's Degree,Data Analyst,11.0,above average
+28.0,Male,Bachelor's Degree,Software Engineer,4.0,below average
+41.0,Female,PhD,Director of Data Science,16.0,high
+34.0,Male,Master's Degree,Data Analyst,8.0,average
+24.0,Female,Bachelor's Degree,Software Developer,2.0,minimal
+36.0,Male,PhD,Senior Data Scientist,12.0,high
+30.0,Female,Bachelor's Degree,Software Engineer,5.0,below average
+29.0,Male,Bachelor's Degree,Front End Developer,4.0,below average
+42.0,Male,Master's Degree,Product Manager,14.0,high
+26.0,Male,Bachelor's Degree,Software Developer,2.0,below average
+35.0,Female,Master's Degree,Data Analyst,9.0,average
+27.0,Female,Bachelor's Degree,Software Engineer,3.0,below average
+48.0,Male,PhD,Director of Data Science,18.0,high
+34.0,Male,Master's Degree,Data Scientist,9.0,above average
+23.0,Female,Bachelor's Degree,Software Engineer,1.0,minimal
+32.0,Male,Master's Degree,Product Manager,7.0,average
+25.0,Female,Master's Degree,Software Engineer,2.0,below average
+37.0,Male,Bachelor's Degree,Data Analyst,11.0,above average
+28.0,Male,Bachelor's Degree,Software Engineer,4.0,below average
+41.0,Female,PhD,Director of Data Science,16.0,high
+34.0,Male,Master's Degree,Data Analyst,8.0,average
+24.0,Female,Bachelor's Degree,Software Developer,2.0,minimal
+36.0,Male,PhD,Senior Data Scientist,12.0,high
+30.0,Female,Bachelor's Degree,Software Engineer,5.0,below average
+29.0,Male,Bachelor's Degree,Front End Developer,4.0,below average
+42.0,Male,Master's Degree,Product Manager,14.0,high
+26.0,Male,Bachelor's Degree,Software Developer,2.0,below average
+35.0,Female,Master's Degree,Data Analyst,9.0,average
+27.0,Female,Bachelor's Degree,Software Engineer,3.0,below average
+48.0,Male,PhD,Director of Data Science,18.0,high
+34.0,Male,Master's Degree,Data Scientist,9.0,above average
+23.0,Female,Bachelor's Degree,Software Engineer,1.0,minimal
+32.0,Male,Master's Degree,Product Manager,7.0,average
+25.0,Female,Master's Degree,Software Engineer,2.0,below average
+37.0,Male,Bachelor's Degree,Data Analyst,11.0,above average
+28.0,Male,Bachelor's Degree,Software Engineer,4.0,below average
+41.0,Female,PhD,Director of Data Science,16.0,high
+34.0,Male,Master's Degree,Data Analyst,8.0,average
+24.0,Female,Bachelor's Degree,Software Developer,2.0,minimal
+36.0,Male,PhD,Senior Data Scientist,12.0,high
+30.0,Female,Bachelor's Degree,Software Engineer,5.0,below average
+29.0,Male,Bachelor's Degree,Front End Developer,4.0,below average
+42.0,Male,Master's Degree,Product Manager,14.0,high
+26.0,Male,Bachelor's Degree,Software Developer,2.0,below average
+35.0,Female,Master's Degree,Data Analyst,9.0,average
+27.0,Female,Bachelor's Degree,Software Engineer,3.0,below average
+48.0,Male,PhD,Director of Data Science,18.0,high
+29.0,Female,Bachelor's Degree,Full Stack Engineer,6.0,average
+45.0,Male,Master's Degree,Software Engineer Manager,19.0,above average
+36.0,Male,Bachelor's Degree,Front end Developer,12.0,above average
+30.0,Female,Master's Degree,Senior Project Engineer,4.0,below average
+28.0,Male,Master's Degree,Full Stack Engineer,5.0,below average
+46.0,Female,PhD,Software Engineer Manager,21.0,high
+34.0,Male,Bachelor's Degree,Back end Developer,10.0,average
+44.0,Male,Master's Degree,Senior Software Engineer,18.0,above average
+55.0,Female,PhD,Software Engineer Manager,29.0,high
+35.0,Male,Master's Degree,Full Stack Engineer,9.0,above average
+54.0,Male,Bachelor's Degree,Senior Project Engineer,28.0,high
+23.0,Female,High School,Back end Developer,1.0,minimal
+46.0,Male,Master's Degree,Senior Software Engineer,20.0,high
+33.0,Female,Bachelor's Degree,Full Stack Engineer,8.0,average
+26.0,Male,Master's Degree,Front end Developer,3.0,below average
+43.0,Female,PhD,Software Engineer Manager,19.0,above average
+36.0,Male,Master's Degree,Full Stack Engineer,11.0,above average
+23.0,Female,Bachelor's Degree,Senior Project Engineer,0.0,minimal
+49.0,Male,Master's Degree,Software Engineer Manager,23.0,high
+35.0,Female,Master's Degree,Full Stack Engineer,11.0,above average
+31.0,Male,Bachelor's Degree,Back end Developer,8.0,average
+54.0,Other,High School,Senior Software Engineer,29.0,above average
+43.0,Male,Master's Degree,Full Stack Engineer,20.0,above average
+33.0,Female,Master's Degree,Senior Project Engineer,10.0,average
+52.0,Female,PhD,Software Engineer Manager,29.0,high
+28.0,Male,Bachelor's Degree,Full Stack Engineer,4.0,below average
+36.0,Female,Master's Degree,Senior Software Engineer,13.0,above average
+43.0,Male,Bachelor's Degree,Senior Project Engineer,20.0,above average
+50.0,Female,Master's Degree,Full Stack Engineer,24.0,high
+24.0,Male,PhD,Software Engineer Manager,1.0,average
+52.0,Male,Master's Degree,Senior Software Engineer,27.0,high
+46.0,Female,Bachelor's Degree,Back end Developer,19.0,above average
+38.0,Male,Master's Degree,Full Stack Engineer,15.0,high
+29.0,Male,Bachelor's Degree,Senior Project Engineer,6.0,below average
+33.0,Female,Master's Degree,Front end Developer,9.0,average
+47.0,Male,PhD,Software Engineer Manager,21.0,high
+45.0,Female,Master's Degree,Senior Software Engineer,23.0,high
+28.0,Male,Bachelor's Degree,Back end Developer,4.0,below average
+42.0,Female,Master's Degree,Full Stack Engineer,14.0,above average
+46.0,Male,Bachelor's Degree,Senior Project Engineer,25.0,above average
+38.0,Female,PhD,Software Engineer Manager,15.0,above average
+54.0,Male,Master's Degree,Senior Software Engineer,32.0,high
+33.0,Female,Master's Degree,Full Stack Engineer,8.0,average
+27.0,Male,High School,Back end Developer,4.0,below average
+50.0,Female,Bachelor's Degree,Senior Project Engineer,25.0,high
+26.0,Male,Master's Degree,Full Stack Engineer,4.0,below average
+31.0,Female,Master's Degree,Senior Software Engineer,6.0,average
+35.0,Male,Bachelor's Degree,Front end Developer,10.0,average
+44.0,Female,PhD,Software Engineer Manager,18.0,above average
+32.0,Male,Master's Degree,Senior Project Engineer,8.0,average
+54.0,Male,Bachelor's Degree,Full Stack Engineer,25.0,high
+26.0,Female,Master's Degree,Front end Developer,3.0,below average
+23.0,Male,PhD,Software Engineer Manager,0.0,minimal
+48.0,Female,Master's Degree,Senior Software Engineer,24.0,high
+38.0,Male,Bachelor's Degree,Back end Developer,12.0,above average
+30.0,Female,Master's Degree,Full Stack Engineer,5.0,average
+40.0,Male,Master's Degree,Software Engineer Manager,16.0,above average
+45.0,Female,Bachelor's Degree,Senior Project Engineer,22.0,high
+36.0,Male,Master's Degree,Full Stack Engineer,13.0,above average
+52.0,Male,PhD,Software Engineer Manager,26.0,high
+31.0,Female,Bachelor's Degree,Senior Software Engineer,7.0,average
+26.0,Male,Master's Degree,Full Stack Engineer,4.0,below average
+30.0,Female,Master's Degree,Senior Project Engineer,5.0,average
+24.0,Male,Bachelor's Degree,Back end Developer,2.0,below average
+45.0,Male,Master's Degree,Senior Software Engineer,22.0,high
+33.0,Female,Master's Degree,Full Stack Engineer,9.0,above average
+38.0,Male,Bachelor's Degree,Front end Developer,11.0,above average
+54.0,Female,PhD,Software Engineer Manager,32.0,high
+42.0,Male,Master's Degree,Full Stack Engineer,19.0,high
+28.0,Female,Bachelor's Degree,Senior Project Engineer,3.0,below average
+34.0,Male,Master's Degree,Software Engineer Manager,9.0,above average
+46.0,Female,Bachelor's Degree,Back end Developer,18.0,above average
+35.0,Male,Master's Degree,Full Stack Engineer,9.0,above average
+49.0,Female,PhD,Software Engineer Manager,22.0,high
+32.0,Male,Bachelor's Degree,Senior Software Engineer,7.0,average
+54.0,Male,Master's Degree,Full Stack Engineer,28.0,high
+26.0,Female,Master's Degree,Front end Developer,2.0,below average
+23.0,Male,PhD,Software Engineer Manager,0.0,minimal
+48.0,Female,Master's Degree,Senior Software Engineer,23.0,high
+38.0,Male,Bachelor's Degree,Back end Developer,14.0,above average
+30.0,Female,Master's Degree,Full Stack Engineer,6.0,average
+40.0,Male,Master's Degree,Software Engineer Manager,17.0,above average
+45.0,Female,Bachelor's Degree,Senior Project Engineer,21.0,above average
+36.0,Male,Master's Degree,Full Stack Engineer,13.0,above average
+52.0,Male,PhD,Software Engineer Manager,27.0,high
+31.0,Female,Bachelor's Degree,Senior Software Engineer,6.0,average
+26.0,Male,Master's Degree,Full Stack Engineer,3.0,below average
+30.0,Female,Master's Degree,Senior Project Engineer,5.0,average
+24.0,Male,Bachelor's Degree,Back end Developer,1.0,minimal
+45.0,Male,Master's Degree,Senior Software Engineer,21.0,high
+33.0,Female,Master's Degree,Full Stack Engineer,9.0,above average
+38.0,Male,Bachelor's Degree,Front end Developer,11.0,above average
+54.0,Female,PhD,Software Engineer Manager,32.0,high
+42.0,Male,Master's Degree,Full Stack Engineer,19.0,high
+28.0,Female,Bachelor's Degree,Senior Project Engineer,3.0,below average
+34.0,Male,Master's Degree,Software Engineer Manager,9.0,above average
+46.0,Female,Bachelor's Degree,Back end Developer,18.0,above average
+35.0,Male,Master's Degree,Full Stack Engineer,9.0,above average
+49.0,Female,PhD,Software Engineer Manager,22.0,high
+32.0,Male,Bachelor's Degree,Senior Software Engineer,7.0,average
+54.0,Male,Master's Degree,Full Stack Engineer,28.0,high
+26.0,Female,Master's Degree,Front end Developer,2.0,below average
+23.0,Male,PhD,Software Engineer Manager,0.0,minimal
+48.0,Female,Master's Degree,Senior Software Engineer,23.0,high
+38.0,Male,Bachelor's Degree,Back end Developer,14.0,above average
+30.0,Female,Master's Degree,Full Stack Engineer,6.0,average
+40.0,Male,Master's Degree,Software Engineer Manager,17.0,above average
+45.0,Female,Bachelor's Degree,Senior Project Engineer,21.0,above average
+36.0,Male,Master's Degree,Full Stack Engineer,13.0,above average
+52.0,Male,PhD,Software Engineer Manager,27.0,high
+31.0,Female,Bachelor's Degree,Senior Software Engineer,6.0,average
+26.0,Male,Master's Degree,Full Stack Engineer,3.0,below average
+30.0,Female,Master's Degree,Senior Project Engineer,5.0,average
+24.0,Male,Bachelor's Degree,Back end Developer,1.0,minimal
+45.0,Male,Master's Degree,Senior Software Engineer,21.0,high
+33.0,Female,Master's Degree,Full Stack Engineer,9.0,above average
+38.0,Male,Bachelor's Degree,Front end Developer,11.0,above average
+54.0,Female,PhD,Software Engineer Manager,32.0,high
+42.0,Male,Master's Degree,Full Stack Engineer,19.0,high
+29.0,Female,Bachelor's Degree,Full Stack Engineer,6.0,average
+45.0,Male,Master's Degree,Software Engineer Manager,19.0,above average
+36.0,Male,Bachelor's Degree,Front end Developer,12.0,above average
+30.0,Female,Master's Degree,Senior Project Engineer,4.0,below average
+28.0,Male,Master's Degree,Full Stack Engineer,5.0,below average
+46.0,Female,PhD,Software Engineer Manager,21.0,high
+34.0,Male,Bachelor's Degree,Back end Developer,10.0,average
+44.0,Male,Master's Degree,Senior Software Engineer,18.0,above average
+55.0,Female,PhD,Software Engineer Manager,29.0,high
+35.0,Male,Master's Degree,Full Stack Engineer,9.0,above average
+54.0,Male,Bachelor's Degree,Senior Project Engineer,28.0,high
+23.0,Female,High School,Back end Developer,1.0,minimal
+46.0,Male,Master's Degree,Senior Software Engineer,20.0,high
+33.0,Female,Bachelor's Degree,Full Stack Engineer,8.0,average
+26.0,Male,Master's Degree,Front end Developer,3.0,below average
+43.0,Female,PhD,Software Engineer Manager,19.0,above average
+36.0,Male,Master's Degree,Full Stack Engineer,11.0,above average
+23.0,Female,Bachelor's Degree,Senior Project Engineer,0.0,minimal
+49.0,Male,Master's Degree,Software Engineer Manager,23.0,high
+35.0,Female,Master's Degree,Full Stack Engineer,11.0,above average
+31.0,Male,Bachelor's Degree,Back end Developer,8.0,average
+54.0,Other,High School,Senior Software Engineer,29.0,above average
+43.0,Male,Master's Degree,Full Stack Engineer,20.0,above average
+33.0,Female,Master's Degree,Senior Project Engineer,10.0,average
+52.0,Female,PhD,Software Engineer Manager,29.0,high
+28.0,Male,Bachelor's Degree,Full Stack Engineer,4.0,below average
+36.0,Female,Master's Degree,Senior Software Engineer,13.0,above average
+43.0,Male,Bachelor's Degree,Senior Project Engineer,20.0,above average
+50.0,Female,Master's Degree,Full Stack Engineer,24.0,high
+24.0,Male,PhD,Software Engineer Manager,1.0,average
+52.0,Male,Master's Degree,Senior Software Engineer,27.0,high
+46.0,Female,Bachelor's Degree,Back end Developer,19.0,above average
+38.0,Male,Master's Degree,Full Stack Engineer,15.0,high
+29.0,Male,Bachelor's Degree,Senior Project Engineer,6.0,below average
+33.0,Female,Master's Degree,Front end Developer,9.0,average
+47.0,Male,PhD,Software Engineer Manager,21.0,high
+45.0,Female,Master's Degree,Senior Software Engineer,23.0,high
+28.0,Male,Bachelor's Degree,Back end Developer,4.0,below average
+42.0,Female,Master's Degree,Full Stack Engineer,14.0,above average
+46.0,Male,Bachelor's Degree,Senior Project Engineer,25.0,above average
+38.0,Female,PhD,Software Engineer Manager,15.0,above average
+54.0,Male,Master's Degree,Senior Software Engineer,32.0,high
+33.0,Female,Master's Degree,Full Stack Engineer,8.0,average
+27.0,Male,High School,Back end Developer,4.0,below average
+50.0,Female,Bachelor's Degree,Senior Project Engineer,25.0,high
+26.0,Male,Master's Degree,Full Stack Engineer,4.0,below average
+31.0,Female,Master's Degree,Senior Software Engineer,6.0,average
+35.0,Male,Bachelor's Degree,Front end Developer,10.0,average
+44.0,Female,PhD,Software Engineer Manager,18.0,above average
+32.0,Male,Master's Degree,Senior Project Engineer,8.0,average
+54.0,Male,Bachelor's Degree,Full Stack Engineer,25.0,high
+26.0,Female,Master's Degree,Front end Developer,3.0,below average
+23.0,Male,PhD,Software Engineer Manager,0.0,minimal
+48.0,Female,Master's Degree,Senior Software Engineer,24.0,high
+38.0,Male,Bachelor's Degree,Back end Developer,12.0,above average
+30.0,Female,Master's Degree,Full Stack Engineer,5.0,average
+40.0,Male,Master's Degree,Software Engineer Manager,16.0,above average
+45.0,Female,Bachelor's Degree,Senior Project Engineer,22.0,high
+36.0,Male,Master's Degree,Full Stack Engineer,13.0,above average
+52.0,Male,PhD,Software Engineer Manager,26.0,high
+31.0,Female,Bachelor's Degree,Senior Software Engineer,7.0,average
+26.0,Male,Master's Degree,Full Stack Engineer,4.0,below average
+30.0,Female,Master's Degree,Senior Project Engineer,5.0,average
+24.0,Male,Bachelor's Degree,Back end Developer,2.0,below average
+45.0,Male,Master's Degree,Senior Software Engineer,22.0,high
+33.0,Female,Master's Degree,Full Stack Engineer,9.0,above average
+38.0,Male,Bachelor's Degree,Front end Developer,11.0,above average
+54.0,Female,PhD,Software Engineer Manager,32.0,high
+42.0,Male,Master's Degree,Full Stack Engineer,19.0,high
+28.0,Female,Bachelor's Degree,Senior Project Engineer,3.0,below average
+34.0,Male,Master's Degree,Software Engineer Manager,9.0,above average
+46.0,Female,Bachelor's Degree,Back end Developer,18.0,above average
+35.0,Male,Master's Degree,Full Stack Engineer,9.0,above average
+49.0,Female,PhD,Software Engineer Manager,22.0,high
+32.0,Male,Bachelor's Degree,Senior Software Engineer,7.0,average
+54.0,Male,Master's Degree,Full Stack Engineer,28.0,high
+26.0,Female,Master's Degree,Front end Developer,2.0,below average
+23.0,Male,PhD,Software Engineer Manager,0.0,minimal
+48.0,Female,Master's Degree,Senior Software Engineer,23.0,high
+38.0,Male,Bachelor's Degree,Back end Developer,14.0,above average
+30.0,Female,Master's Degree,Full Stack Engineer,6.0,average
+40.0,Male,Master's Degree,Software Engineer Manager,17.0,above average
+45.0,Female,Bachelor's Degree,Senior Project Engineer,21.0,above average
+36.0,Male,Master's Degree,Full Stack Engineer,13.0,above average
+52.0,Male,PhD,Software Engineer Manager,27.0,high
+31.0,Female,Bachelor's Degree,Senior Software Engineer,6.0,average
+26.0,Male,Master's Degree,Full Stack Engineer,3.0,below average
+30.0,Female,Master's Degree,Senior Project Engineer,5.0,average
+24.0,Male,Bachelor's Degree,Back end Developer,1.0,minimal
+45.0,Male,Master's Degree,Senior Software Engineer,21.0,high
+33.0,Female,Master's Degree,Full Stack Engineer,9.0,above average
+38.0,Male,Bachelor's Degree,Front end Developer,11.0,above average
+54.0,Female,PhD,Software Engineer Manager,32.0,high
+42.0,Male,Master's Degree,Full Stack Engineer,19.0,high
+28.0,Female,Bachelor's Degree,Senior Project Engineer,3.0,below average
+34.0,Male,Master's Degree,Software Engineer Manager,9.0,above average
+46.0,Female,Bachelor's Degree,Back end Developer,18.0,above average
+35.0,Male,Master's Degree,Full Stack Engineer,9.0,above average
+49.0,Female,PhD,Software Engineer Manager,22.0,high
+32.0,Male,Bachelor's Degree,Senior Software Engineer,7.0,average
+54.0,Male,Master's Degree,Full Stack Engineer,28.0,high
+26.0,Female,Master's Degree,Front end Developer,2.0,below average
+23.0,Male,PhD,Software Engineer Manager,0.0,minimal
+48.0,Female,Master's Degree,Senior Software Engineer,23.0,high
+38.0,Male,Bachelor's Degree,Back end Developer,14.0,above average
+30.0,Female,Master's Degree,Full Stack Engineer,6.0,average
+40.0,Male,Master's Degree,Software Engineer Manager,17.0,above average
+45.0,Female,Bachelor's Degree,Senior Project Engineer,21.0,above average
+36.0,Male,Master's Degree,Full Stack Engineer,13.0,above average
+52.0,Male,PhD,Software Engineer Manager,27.0,high
+31.0,Female,Bachelor's Degree,Senior Software Engineer,6.0,average
+26.0,Male,Master's Degree,Full Stack Engineer,3.0,below average
+30.0,Female,Master's Degree,Senior Project Engineer,5.0,average
+24.0,Male,Bachelor's Degree,Back end Developer,1.0,minimal
+45.0,Male,Master's Degree,Senior Software Engineer,21.0,high
+33.0,Female,Master's Degree,Full Stack Engineer,9.0,above average
+38.0,Male,Bachelor's Degree,Front end Developer,11.0,above average
+54.0,Female,PhD,Software Engineer Manager,32.0,high
+42.0,Male,Master's Degree,Full Stack Engineer,19.0,high
+29.0,Female,Bachelor's Degree,Full Stack Engineer,6.0,average
+45.0,Male,Master's Degree,Software Engineer Manager,19.0,above average
+36.0,Male,Bachelor's Degree,Front end Developer,12.0,above average
+30.0,Female,Master's Degree,Senior Project Engineer,4.0,below average
+28.0,Male,Master's Degree,Full Stack Engineer,5.0,below average
+46.0,Female,PhD,Software Engineer Manager,21.0,high
+34.0,Male,Bachelor's Degree,Back end Developer,10.0,average
+44.0,Male,Master's Degree,Senior Software Engineer,18.0,above average
+55.0,Female,PhD,Software Engineer Manager,29.0,high
+35.0,Male,Master's Degree,Full Stack Engineer,9.0,above average
+54.0,Male,Bachelor's Degree,Senior Project Engineer,28.0,high
+23.0,Female,High School,Back end Developer,1.0,minimal
+46.0,Male,Master's Degree,Senior Software Engineer,20.0,high
+33.0,Female,Bachelor's Degree,Full Stack Engineer,8.0,average
+26.0,Male,Master's Degree,Front end Developer,3.0,below average
+43.0,Female,PhD,Software Engineer Manager,19.0,above average
+36.0,Male,Master's Degree,Full Stack Engineer,11.0,above average
+23.0,Female,Bachelor's Degree,Senior Project Engineer,0.0,minimal
+49.0,Male,Master's Degree,Software Engineer Manager,23.0,high
+35.0,Female,Master's Degree,Full Stack Engineer,11.0,above average
+31.0,Male,Bachelor's Degree,Back end Developer,8.0,average
+54.0,Other,High School,Senior Software Engineer,29.0,above average
+43.0,Male,Master's Degree,Full Stack Engineer,20.0,above average
+33.0,Female,Master's Degree,Senior Project Engineer,10.0,average
+52.0,Female,PhD,Software Engineer Manager,29.0,high
+28.0,Male,Bachelor's Degree,Full Stack Engineer,4.0,below average
+36.0,Female,Master's Degree,Senior Software Engineer,13.0,above average
+43.0,Male,Bachelor's Degree,Senior Project Engineer,20.0,above average
+50.0,Female,Master's Degree,Full Stack Engineer,24.0,high
+24.0,Male,PhD,Software Engineer Manager,1.0,average
+52.0,Male,Master's Degree,Senior Software Engineer,27.0,high
+46.0,Female,Bachelor's Degree,Back end Developer,19.0,above average
+38.0,Male,Master's Degree,Full Stack Engineer,15.0,high
+29.0,Male,Bachelor's Degree,Senior Project Engineer,6.0,below average
+33.0,Female,Master's Degree,Front end Developer,9.0,average
+47.0,Male,PhD,Software Engineer Manager,21.0,high
+45.0,Female,Master's Degree,Senior Software Engineer,23.0,high
+28.0,Male,Bachelor's Degree,Back end Developer,4.0,below average
+42.0,Female,Master's Degree,Full Stack Engineer,14.0,above average
+46.0,Male,Bachelor's Degree,Senior Project Engineer,25.0,above average
+38.0,Female,PhD,Software Engineer Manager,15.0,above average
+54.0,Male,Master's Degree,Senior Software Engineer,32.0,high
+33.0,Female,Master's Degree,Full Stack Engineer,8.0,average
+27.0,Male,High School,Back end Developer,4.0,below average
+50.0,Female,Bachelor's Degree,Senior Project Engineer,25.0,high
+26.0,Male,Master's Degree,Full Stack Engineer,4.0,below average
+31.0,Female,Master's Degree,Senior Software Engineer,6.0,average
+35.0,Male,Bachelor's Degree,Front end Developer,10.0,average
+44.0,Female,PhD,Software Engineer Manager,18.0,above average
+32.0,Male,Master's Degree,Senior Project Engineer,8.0,average
+54.0,Male,Bachelor's Degree,Full Stack Engineer,25.0,high
+26.0,Female,Master's Degree,Front end Developer,3.0,below average
+23.0,Male,PhD,Software Engineer Manager,0.0,minimal
+48.0,Female,Master's Degree,Senior Software Engineer,23.0,high
+38.0,Male,Bachelor's Degree,Back end Developer,12.0,above average
+30.0,Female,Master's Degree,Full Stack Engineer,5.0,average
+40.0,Male,Master's Degree,Software Engineer Manager,16.0,above average
+45.0,Female,Bachelor's Degree,Senior Project Engineer,22.0,high
+36.0,Male,Master's Degree,Full Stack Engineer,13.0,above average
+52.0,Male,PhD,Software Engineer Manager,26.0,high
+31.0,Female,Bachelor's Degree,Senior Software Engineer,7.0,average
+26.0,Male,Master's Degree,Full Stack Engineer,3.0,below average
+30.0,Female,Master's Degree,Senior Project Engineer,5.0,average
+24.0,Male,Bachelor's Degree,Back end Developer,2.0,below average
+45.0,Male,Master's Degree,Senior Software Engineer,22.0,high
+33.0,Female,Master's Degree,Full Stack Engineer,9.0,above average
+38.0,Male,Bachelor's Degree,Front end Developer,11.0,above average
+54.0,Female,PhD,Software Engineer Manager,32.0,high
+42.0,Male,Master's Degree,Full Stack Engineer,19.0,high
+28.0,Female,Bachelor's Degree,Senior Project Engineer,4.0,below average
+48.0,Male,PhD,Software Engineer Manager,23.0,high
+36.0,Female,Master's Degree,Senior Software Engineer,14.0,above average
+43.0,Male,Bachelor's Degree,Full Stack Engineer,19.0,above average
+33.0,Female,Master's Degree,Back end Developer,9.0,average
+26.0,Male,Bachelor's Degree,Front end Developer,3.0,below average
+50.0,Female,Master's Degree,Senior Project Engineer,22.0,high
+41.0,Male,PhD,Software Engineer Manager,15.0,above average
+29.0,Female,Bachelor's Degree,Full Stack Engineer,6.0,below average
+38.0,Male,Master's Degree,Senior Software Engineer,14.0,above average
+48.0,Female,Bachelor's Degree,Senior Project Engineer,21.0,above average
+31.0,Male,Master's Degree,Full Stack Engineer,8.0,average
+45.0,Male,PhD,Software Engineer Manager,21.0,high
+35.0,Female,Master's Degree,Senior Software Engineer,11.0,above average
+42.0,Male,Bachelor's Degree,Back end Developer,16.0,above average
+27.0,Female,Master's Degree,Full Stack Engineer,4.0,below average
+33.0,Male,Bachelor's Degree,Front end Developer,9.0,average
+36.0,Female,Master's Degree,Senior Project Engineer,11.0,above average
+54.0,Male,PhD,Software Engineer Manager,30.0,high
+30.0,Female,Bachelor's Degree,Senior Software Engineer,5.0,average
+26.0,Male,Master's Degree,Full Stack Engineer,3.0,below average
+45.0,Female,PhD,Senior Project Engineer,21.0,high
+38.0,Male,Master's Degree,Software Engineer Manager,16.0,above average
+31.0,Female,Bachelor's Degree,Full Stack Engineer,7.0,average
+42.0,Male,Master's Degree,Senior Software Engineer,19.0,high
+28.0,Female,Bachelor's Degree,Back end Developer,5.0,below average
+48.0,Male,PhD,Software Engineer Manager,24.0,high
+36.0,Female,Master's Degree,Full Stack Engineer,13.0,above average
+43.0,Male,Bachelor's Degree,Senior Project Engineer,20.0,above average
+33.0,Female,Master's Degree,Front end Developer,9.0,average
+26.0,Male,Bachelor's Degree,Full Stack Engineer,4.0,below average
+50.0,Female,Master's Degree,Senior Software Engineer,21.0,high
+27.0,Male,Master's Degree,Back end Developer,5.0,below average
+38.0,Female,Bachelor's Degree,Senior Project Engineer,13.0,above average
+54.0,Male,PhD,Software Engineer Manager,28.0,high
+31.0,Female,Master's Degree,Full Stack Engineer,7.0,average
+36.0,Male,Bachelor's Degree,Senior Software Engineer,13.0,above average
+45.0,Female,Master's Degree,Software Engineer Manager,22.0,high
+42.0,Male,Bachelor's Degree,Back end Developer,18.0,above average
+28.0,Female,Master's Degree,Full Stack Engineer,4.0,below average
+48.0,Male,PhD,Senior Software Engineer,26.0,high
+36.0,Female,Master's Degree,Senior Project Engineer,12.0,above average
+43.0,Male,Bachelor's Degree,Full Stack Engineer,18.0,above average
+33.0,Female,Master's Degree,Front end Developer,9.0,average
+26.0,Male,Bachelor's Degree,Back end Developer,2.0,below average
+50.0,Female,Master's Degree,Senior Software Engineer,23.0,high
+41.0,Male,PhD,Software Engineer Manager,16.0,above average
+29.0,Female,Bachelor's Degree,Full Stack Engineer,6.0,average
+38.0,Male,Master's Degree,Senior Software Engineer,15.0,above average
+48.0,Female,Bachelor's Degree,Senior Project Engineer,22.0,above average
+31.0,Male,Master's Degree,Full Stack Engineer,8.0,average
+28.0,Male,Bachelor's Degree,Software Developer,1.0,minimal
+32.0,Female,Master's Degree,Product Manager,5.0,average
+26.0,Male,Bachelor's Degree,Software Engineer,2.0,below average
+33.0,Female,Master's Degree,Data Analyst,6.0,below average
+29.0,Male,Bachelor's Degree,Front End Developer,3.0,below average
+42.0,Male,PhD,Director of Data Science,12.0,high
+36.0,Female,Master's Degree,Data Scientist,8.0,above average
+27.0,Male,Bachelor's Degree,Software Developer,1.0,minimal
+34.0,Female,Master's Degree,Product Manager,7.0,average
+29.0,Male,Bachelor's Degree,Software Engineer,4.0,below average
+41.0,Female,PhD,Senior Data Scientist,16.0,high
+34.0,Male,Master's Degree,Data Analyst,8.0,average
+24.0,Female,Bachelor's Degree,Software Developer,2.0,minimal
+36.0,Male,PhD,Director of Data Science,12.0,high
+30.0,Female,Bachelor's Degree,Software Engineer,5.0,below average
+29.0,Male,Bachelor's Degree,Front End Developer,4.0,below average
+42.0,Male,Master's Degree,Product Manager,14.0,high
+26.0,Male,Bachelor's Degree,Software Developer,2.0,below average
+35.0,Female,Master's Degree,Data Analyst,9.0,average
+27.0,Female,Bachelor's Degree,Software Engineer,3.0,below average
+48.0,Male,PhD,Director of Data Science,18.0,high
+34.0,Male,Master's Degree,Data Scientist,9.0,above average
+23.0,Female,Bachelor's Degree,Software Engineer,1.0,minimal
+32.0,Male,Master's Degree,Product Manager,7.0,average
+25.0,Female,Master's Degree,Software Engineer,2.0,below average
+37.0,Male,Bachelor's Degree,Data Analyst,11.0,above average
+28.0,Male,Bachelor's Degree,Software Engineer,4.0,below average
+41.0,Female,PhD,Director of Data Science,16.0,high
+34.0,Male,Master's Degree,Data Analyst,8.0,average
+24.0,Female,Bachelor's Degree,Software Developer,2.0,minimal
+36.0,Male,PhD,Senior Data Scientist,12.0,high
+30.0,Female,Bachelor's Degree,Software Engineer,5.0,below average
+29.0,Male,Bachelor's Degree,Front End Developer,4.0,below average
+42.0,Male,Master's Degree,Product Manager,14.0,high
+26.0,Male,Bachelor's Degree,Software Developer,2.0,below average
+35.0,Female,Master's Degree,Data Analyst,9.0,average
+27.0,Female,Bachelor's Degree,Software Engineer,3.0,below average
+48.0,Male,PhD,Director of Data Science,18.0,high
+34.0,Male,Master's Degree,Data Scientist,9.0,above average
+23.0,Female,Bachelor's Degree,Software Engineer,1.0,minimal
+32.0,Male,Master's Degree,Product Manager,7.0,average
+25.0,Female,Master's Degree,Software Engineer,2.0,below average
+37.0,Male,Bachelor's Degree,Data Analyst,11.0,above average
+28.0,Male,Bachelor's Degree,Software Engineer,4.0,below average
+41.0,Female,PhD,Director of Data Science,16.0,high
+34.0,Male,Master's Degree,Data Analyst,8.0,average
+24.0,Female,Bachelor's Degree,Software Developer,2.0,minimal
+36.0,Male,PhD,Senior Data Scientist,12.0,high
+30.0,Female,Bachelor's Degree,Software Engineer,5.0,below average
+29.0,Male,Bachelor's Degree,Front End Developer,4.0,below average
+42.0,Male,Master's Degree,Product Manager,14.0,high
+26.0,Male,Bachelor's Degree,Software Developer,2.0,below average
+35.0,Female,Master's Degree,Data Analyst,9.0,average
+27.0,Female,Bachelor's Degree,Software Engineer,3.0,below average
+48.0,Male,PhD,Director of Data Science,18.0,high
+34.0,Male,Master's Degree,Data Scientist,9.0,above average
+23.0,Female,Bachelor's Degree,Software Engineer,1.0,minimal
+32.0,Male,Master's Degree,Product Manager,7.0,average
+25.0,Female,Master's Degree,Software Engineer,2.0,below average
+37.0,Male,Bachelor's Degree,Data Analyst,11.0,above average
+28.0,Male,Bachelor's Degree,Software Engineer,4.0,below average
+41.0,Female,PhD,Director of Data Science,16.0,high
+34.0,Male,Master's Degree,Data Analyst,8.0,average
+24.0,Female,Bachelor's Degree,Software Developer,2.0,minimal
+36.0,Male,PhD,Senior Data Scientist,12.0,high
+30.0,Female,Bachelor's Degree,Software Engineer,5.0,below average
+29.0,Male,Bachelor's Degree,Front End Developer,4.0,below average
+42.0,Male,Master's Degree,Product Manager,14.0,high
+26.0,Male,Bachelor's Degree,Software Developer,2.0,below average
+35.0,Female,Master's Degree,Data Analyst,9.0,average
+27.0,Female,Bachelor's Degree,Software Engineer,3.0,below average
+48.0,Male,PhD,Director of Data Science,18.0,high
+34.0,Male,Master's Degree,Data Scientist,9.0,above average
+23.0,Female,Bachelor's Degree,Software Engineer,1.0,minimal
+32.0,Male,Master's Degree,Product Manager,7.0,average
+25.0,Female,Master's Degree,Software Engineer,2.0,below average
+37.0,Male,Bachelor's Degree,Data Analyst,11.0,above average
+28.0,Male,Bachelor's Degree,Software Engineer,4.0,below average
+41.0,Female,PhD,Director of Data Science,16.0,high
+34.0,Male,Master's Degree,Data Analyst,8.0,average
+24.0,Female,Bachelor's Degree,Software Developer,2.0,minimal
+36.0,Male,PhD,Senior Data Scientist,12.0,high
+30.0,Female,Bachelor's Degree,Software Engineer,5.0,below average
+29.0,Male,Bachelor's Degree,Front End Developer,4.0,below average
+42.0,Male,Master's Degree,Product Manager,14.0,high
+26.0,Male,Bachelor's Degree,Software Developer,2.0,below average
+35.0,Female,Master's Degree,Data Analyst,9.0,average
+27.0,Female,Bachelor's Degree,Software Engineer,3.0,below average
+48.0,Male,PhD,Director of Data Science,18.0,high
+34.0,Male,Master's Degree,Data Scientist,9.0,above average
+23.0,Female,Bachelor's Degree,Software Engineer,1.0,minimal
+32.0,Male,Master's Degree,Product Manager,7.0,average
+25.0,Female,Master's Degree,Software Engineer,2.0,below average
+37.0,Male,Bachelor's Degree,Data Analyst,11.0,above average
+28.0,Male,Bachelor's Degree,Software Engineer,4.0,below average
+41.0,Female,PhD,Director of Data Science,16.0,high
+34.0,Male,Master's Degree,Data Analyst,8.0,average
+24.0,Female,Bachelor's Degree,Software Developer,2.0,minimal
+36.0,Male,PhD,Senior Data Scientist,12.0,high
+30.0,Female,Bachelor's Degree,Software Engineer,5.0,below average
+29.0,Male,Bachelor's Degree,Front End Developer,4.0,below average
+42.0,Male,Master's Degree,Product Manager,14.0,high
+26.0,Male,Bachelor's Degree,Software Developer,2.0,below average
+35.0,Female,Master's Degree,Data Analyst,9.0,average
+27.0,Female,Bachelor's Degree,Software Engineer,3.0,below average
+48.0,Male,PhD,Director of Data Science,18.0,high
+34.0,Male,Master's Degree,Data Scientist,9.0,above average
+23.0,Female,Bachelor's Degree,Software Engineer,1.0,minimal
+32.0,Male,Master's Degree,Product Manager,7.0,average
+25.0,Female,Master's Degree,Software Engineer,2.0,below average
+37.0,Male,Bachelor's Degree,Data Analyst,11.0,above average
+28.0,Male,Bachelor's Degree,Software Engineer,4.0,below average
+41.0,Female,PhD,Director of Data Science,16.0,high
+34.0,Male,Master's Degree,Data Analyst,8.0,average
+24.0,Female,Bachelor's Degree,Software Developer,2.0,minimal
+36.0,Male,PhD,Senior Data Scientist,12.0,high
+30.0,Female,Bachelor's Degree,Software Engineer,5.0,below average
+29.0,Male,Bachelor's Degree,Front End Developer,4.0,below average
+42.0,Male,Master's Degree,Product Manager,14.0,high
+26.0,Male,Bachelor's Degree,Software Developer,2.0,below average
+35.0,Female,Master's Degree,Data Analyst,9.0,average
+27.0,Female,Bachelor's Degree,Software Engineer,3.0,below average
+48.0,Male,PhD,Director of Data Science,18.0,high
+34.0,Male,Master's Degree,Data Scientist,9.0,above average
+30.0,Female,Bachelor's Degree,Software Engineer,4.0,below average
+29.0,Male,Bachelor's Degree,Front End Developer,3.0,below average
+42.0,Male,Master's Degree,Product Manager,14.0,high
+26.0,Male,Bachelor's Degree,Software Developer,2.0,below average
+35.0,Female,Master's Degree,Data Analyst,9.0,average
+27.0,Female,Bachelor's Degree,Software Engineer,3.0,below average
+48.0,Male,PhD,Director of Data Science,18.0,high
+34.0,Male,Master's Degree,Data Scientist,9.0,above average
+23.0,Female,Bachelor's Degree,Software Engineer,1.0,minimal
+32.0,Male,Master's Degree,Product Manager,7.0,average
+25.0,Female,Master's Degree,Software Engineer,2.0,below average
+37.0,Male,Bachelor's Degree,Data Analyst,11.0,above average
+28.0,Male,Bachelor's Degree,Software Engineer,4.0,below average
+41.0,Female,PhD,Director of Data Science,16.0,high
+34.0,Male,Master's Degree,Data Analyst,8.0,average
+24.0,Female,Bachelor's Degree,Software Developer,2.0,minimal
+36.0,Male,PhD,Senior Data Scientist,12.0,high
+30.0,Female,Bachelor's Degree,Software Engineer,5.0,below average
+29.0,Male,Bachelor's Degree,Front End Developer,4.0,below average
+42.0,Male,Master's Degree,Product Manager,14.0,high
+26.0,Male,Bachelor's Degree,Software Developer,2.0,below average
+35.0,Female,Master's Degree,Data Analyst,9.0,average
+27.0,Female,Bachelor's Degree,Software Engineer,3.0,below average
+48.0,Male,PhD,Director of Data Science,18.0,high
+34.0,Male,Master's Degree,Data Scientist,9.0,above average
+23.0,Female,Bachelor's Degree,Software Engineer,1.0,minimal
+32.0,Male,Master's Degree,Product Manager,7.0,average
+25.0,Female,Master's Degree,Software Engineer,2.0,below average
+37.0,Male,Bachelor's Degree,Data Analyst,11.0,above average
+28.0,Male,Bachelor's Degree,Software Engineer,4.0,below average
+41.0,Female,PhD,Director of Data Science,16.0,high
+34.0,Male,Master's Degree,Data Analyst,8.0,average
+24.0,Female,Bachelor's Degree,Software Developer,2.0,minimal
+36.0,Male,PhD,Senior Data Scientist,12.0,high
+30.0,Female,Bachelor's Degree,Software Engineer,5.0,below average
+29.0,Male,Bachelor's Degree,Front End Developer,4.0,below average
+42.0,Male,Master's Degree,Product Manager,14.0,high
+26.0,Male,Bachelor's Degree,Software Developer,2.0,below average
+35.0,Female,Master's Degree,Data Analyst,9.0,average
+27.0,Female,Bachelor's Degree,Software Engineer,3.0,below average
+48.0,Male,PhD,Director of Data Science,18.0,high
+34.0,Male,Master's Degree,Data Scientist,9.0,above average
+23.0,Female,Bachelor's Degree,Software Engineer,1.0,minimal
+32.0,Male,Master's Degree,Product Manager,7.0,average
+25.0,Female,Master's Degree,Software Engineer,2.0,below average
+37.0,Male,Bachelor's Degree,Data Analyst,11.0,above average
+28.0,Male,Bachelor's Degree,Software Engineer,4.0,below average
+41.0,Female,PhD,Director of Data Science,16.0,high
+34.0,Male,Master's Degree,Data Analyst,8.0,average
+24.0,Female,Bachelor's Degree,Software Developer,2.0,minimal
+36.0,Male,PhD,Senior Data Scientist,12.0,high
+30.0,Female,Bachelor's Degree,Software Engineer,5.0,below average
+29.0,Male,Bachelor's Degree,Front End Developer,4.0,below average
+42.0,Male,Master's Degree,Product Manager,14.0,high
+26.0,Male,Bachelor's Degree,Software Developer,2.0,below average
+35.0,Female,Master's Degree,Data Analyst,9.0,average
+27.0,Female,Bachelor's Degree,Software Engineer,3.0,below average
+48.0,Male,PhD,Director of Data Science,18.0,high
+34.0,Male,Master's Degree,Data Scientist,9.0,above average
+23.0,Female,Bachelor's Degree,Software Engineer,1.0,minimal
+32.0,Male,Master's Degree,Product Manager,7.0,average
+25.0,Female,Master's Degree,Software Engineer,2.0,below average
+37.0,Male,Bachelor's Degree,Data Analyst,11.0,above average
+28.0,Male,Bachelor's Degree,Software Engineer,4.0,below average
+41.0,Female,PhD,Director of Data Science,16.0,high
+34.0,Male,Master's Degree,Data Analyst,8.0,average
+24.0,Female,Bachelor's Degree,Software Developer,2.0,minimal
+36.0,Male,PhD,Senior Data Scientist,12.0,high
+30.0,Female,Bachelor's Degree,Software Engineer,5.0,below average
+29.0,Male,Bachelor's Degree,Front End Developer,4.0,below average
+42.0,Male,Master's Degree,Product Manager,14.0,high
+26.0,Male,Bachelor's Degree,Software Developer,2.0,below average
+35.0,Female,Master's Degree,Data Analyst,9.0,average
+27.0,Female,Bachelor's Degree,Software Engineer,3.0,below average
+48.0,Male,PhD,Director of Data Science,18.0,high
+34.0,Male,Master's Degree,Data Scientist,9.0,above average
+23.0,Female,Bachelor's Degree,Software Engineer,1.0,minimal
+32.0,Male,Master's Degree,Product Manager,7.0,average
+25.0,Female,Master's Degree,Software Engineer,2.0,below average
+37.0,Male,Bachelor's Degree,Data Analyst,11.0,above average
+28.0,Male,Bachelor's Degree,Software Engineer,4.0,below average
+41.0,Female,PhD,Director of Data Science,16.0,high
+34.0,Male,Master's Degree,Data Analyst,8.0,average
+24.0,Female,Bachelor's Degree,Software Developer,2.0,minimal
+36.0,Male,PhD,Senior Data Scientist,12.0,high
+30.0,Female,Bachelor's Degree,Software Engineer,5.0,below average
+29.0,Male,Bachelor's Degree,Front End Developer,4.0,below average
+42.0,Male,Master's Degree,Product Manager,14.0,high
+26.0,Male,Bachelor's Degree,Software Developer,2.0,below average
+35.0,Female,Master's Degree,Data Analyst,9.0,average
+27.0,Female,Bachelor's Degree,Software Engineer,3.0,below average
+48.0,Male,PhD,Director of Data Science,18.0,high
+34.0,Male,Master's Degree,Data Scientist,9.0,above average
+23.0,Female,Bachelor's Degree,Software Engineer,1.0,minimal
+32.0,Male,Master's Degree,Product Manager,7.0,average
+25.0,Female,Master's Degree,Software Engineer,2.0,below average
+37.0,Male,Bachelor's Degree,Data Analyst,11.0,above average
+28.0,Male,Bachelor's Degree,Software Engineer,4.0,below average
+41.0,Female,PhD,Director of Data Science,16.0,high
+34.0,Male,Master's Degree,Data Analyst,8.0,average
+24.0,Female,Bachelor's Degree,Software Developer,2.0,minimal
+36.0,Male,PhD,Senior Data Scientist,12.0,high
+30.0,Female,Bachelor's Degree,Software Engineer,5.0,below average
+29.0,Male,Bachelor's Degree,Front End Developer,4.0,below average
+42.0,Male,Master's Degree,Product Manager,14.0,high
+26.0,Male,Bachelor's Degree,Software Developer,2.0,below average
+35.0,Female,Master's Degree,Data Analyst,9.0,average
+27.0,Female,Bachelor's Degree,Software Engineer,3.0,below average
+48.0,Male,PhD,Director of Data Science,18.0,high
+34.0,Male,Master's Degree,Data Scientist,9.0,above average
+23.0,Female,Bachelor's Degree,Software Engineer,1.0,minimal
+32.0,Male,Master's Degree,Product Manager,7.0,average
+25.0,Female,Master's Degree,Software Engineer,2.0,below average
+37.0,Male,Bachelor's Degree,Data Analyst,11.0,above average
+28.0,Male,Bachelor's Degree,Software Engineer,4.0,below average
+41.0,Female,PhD,Director of Data Science,16.0,high
+34.0,Male,Master's Degree,Data Analyst,8.0,average
+24.0,Female,Bachelor's Degree,Software Developer,2.0,minimal
+36.0,Male,PhD,Senior Data Scientist,12.0,high
+30.0,Female,Bachelor's Degree,Software Engineer,5.0,below average
+29.0,Male,Bachelor's Degree,Front End Developer,4.0,below average
+42.0,Male,Master's Degree,Product Manager,14.0,high
+26.0,Male,Bachelor's Degree,Software Developer,2.0,below average
+35.0,Female,Master's Degree,Data Analyst,9.0,average
+28.0,Male,Master's Degree,Web Developer,5.0,below average
+30.0,Female,Bachelor's Degree,Junior HR Coordinator,4.0,below average
+25.0,Male,Bachelor's Degree,Junior Web Developer,2.0,minimal
+45.0,Female,Master's Degree,Senior Human Resources Manager,18.0,above average
+33.0,Male,PhD,Director of HR,9.0,average
+22.0,Female,High School,Junior HR Generalist,0.0,minimal
+36.0,Male,Bachelor's Degree,Web Developer,10.0,average
+29.0,Female,Master's Degree,Senior HR Generalist,4.0,below average
+42.0,Male,PhD,Director of HR,16.0,above average
+27.0,Female,Bachelor's Degree,Junior HR Coordinator,2.0,minimal
+38.0,Male,Master's Degree,Senior Human Resources Manager,11.0,average
+24.0,Female,Bachelor's Degree,Web Developer,1.0,minimal
+31.0,Male,High School,Junior Web Developer,4.0,minimal
+39.0,Female,PhD,Director of HR,13.0,above average
+26.0,Male,Bachelor's Degree,Junior HR Generalist,2.0,minimal
+32.0,Female,Master's Degree,Senior HR Generalist,7.0,below average
+32.0,Male,Bachelor's Degree,Junior Web Developer,2.0,minimal
+24.0,Female,High School,Junior HR Generalist,1.0,minimal
+45.0,Male,PhD,Senior Human Resources Manager,12.0,average
+29.0,Female,Master's Degree,Web Developer,4.0,below average
+38.0,Male,Bachelor's Degree,Senior HR Generalist,8.0,average
+27.0,Female,Master's Degree,Director of HR,5.0,below average
+31.0,Female,High School,Junior HR Coordinator,3.0,minimal
+42.0,Male,Master's Degree,Web Developer,10.0,average
+26.0,Female,Bachelor's Degree,Junior Web Developer,2.0,minimal
+36.0,Male,Master's Degree,Senior HR Generalist,7.0,below average
+28.0,Male,High School,Junior HR Generalist,1.0,minimal
+33.0,Female,Bachelor's Degree,Web Developer,5.0,below average
+46.0,Male,PhD,Director of HR,15.0,above average
+25.0,Female,Bachelor's Degree,Junior Web Developer,1.0,minimal
+37.0,Female,Master's Degree,Senior Human Resources Manager,9.0,average
+30.0,Male,Master's Degree,Web Developer,4.0,below average
+43.0,Female,PhD,Director of HR,14.0,above average
+34.0,Male,Bachelor's Degree,Junior Web Developer,3.0,minimal
+26.0,Female,High School,Junior HR Generalist,2.0,minimal
+41.0,Male,Master's Degree,Senior HR Generalist,11.0,average
+29.0,Female,Master's Degree,Web Developer,5.0,below average
+35.0,Male,Bachelor's Degree,Web Developer,6.0,below average
+27.0,Female,High School,Junior HR Coordinator,1.0,minimal
+40.0,Male,PhD,Director of HR,13.0,above average
+23.0,Female,Bachelor's Degree,Junior Web Developer,1.0,minimal
+39.0,Male,Master's Degree,Senior HR Generalist,10.0,average
+31.0,Male,High School,Junior HR Generalist,2.0,minimal
+44.0,Female,PhD,Senior Human Resources Manager,12.0,average
+28.0,Male,Master's Degree,Web Developer,3.0,minimal
+32.0,Female,Bachelor's Degree,Junior Web Developer,2.0,minimal
+45.0,Male,Master's Degree,Director of HR,14.0,above average
+26.0,Female,Bachelor's Degree,Web Developer,3.0,minimal
+38.0,Male,PhD,Senior Human Resources Manager,11.0,average
+27.0,Female,Master's Degree,Senior HR Generalist,4.0,below average
+33.0,Male,High School,Junior HR Coordinator,3.0,minimal
+42.0,Female,Master's Degree,Director of HR,13.0,above average
+29.0,Male,Bachelor's Degree,Junior Web Developer,2.0,minimal
+36.0,Female,Master's Degree,Web Developer,7.0,below average
+30.0,Male,High School,Junior HR Generalist,1.0,minimal
+43.0,Female,PhD,Senior Human Resources Manager,15.0,above average
+34.0,Male,Bachelor's Degree,Web Developer,4.0,below average
+25.0,Female,Master's Degree,Junior HR Generalist,1.0,minimal
+37.0,Male,PhD,Director of HR,12.0,average
+24.0,Female,Bachelor's Degree,Junior Web Developer,1.0,minimal
+39.0,Male,Master's Degree,Senior HR Generalist,9.0,average
+31.0,Male,High School,Junior HR Generalist,2.0,minimal
+44.0,Female,PhD,Director of HR,14.0,above average
+28.0,Male,Bachelor's Degree,Web Developer,3.0,minimal
+32.0,Female,Master's Degree,Senior Human Resources Manager,6.0,below average
+45.0,Male,PhD,Director of HR,13.0,above average
+26.0,Female,Bachelor's Degree,Junior Web Developer,2.0,minimal
+38.0,Male,Master's Degree,Senior HR Generalist,8.0,average
+27.0,Female,High School,Junior HR Generalist,1.0,minimal
+33.0,Male,Bachelor's Degree,Web Developer,5.0,below average
+42.0,Female,Master's Degree,Director of HR,12.0,average
+29.0,Male,Master's Degree,Senior Human Resources Manager,4.0,below average
+36.0,Female,Master's Degree,Web Developer,7.0,below average
+30.0,Male,High School,Junior HR Coordinator,2.0,minimal
+43.0,Female,PhD,Senior Human Resources Manager,15.0,above average
+34.0,Male,Bachelor's Degree,Junior Web Developer,3.0,minimal
+25.0,Female,Master's Degree,Junior HR Generalist,1.0,minimal
+37.0,Male,PhD,Director of HR,11.0,average
+24.0,Female,Bachelor's Degree,Web Developer,1.0,minimal
+39.0,Male,Master's Degree,Senior HR Generalist,10.0,average
+31.0,Male,High School,Junior HR Generalist,2.0,minimal
+44.0,Female,PhD,Director of HR,13.0,above average
+28.0,Male,Bachelor's Degree,Web Developer,4.0,below average
+32.0,Female,Master's Degree,Senior Human Resources Manager,6.0,below average
+45.0,Male,PhD,Director of HR,14.0,above average
+26.0,Female,Bachelor's Degree,Junior Web Developer,2.0,minimal
+38.0,Male,Master's Degree,Senior HR Generalist,8.0,average
+27.0,Female,High School,Junior HR Generalist,1.0,minimal
+33.0,Male,Bachelor's Degree,Web Developer,5.0,below average
+42.0,Female,Master's Degree,Director of HR,12.0,average
+29.0,Male,Master's Degree,Senior Human Resources Manager,4.0,below average
+36.0,Female,Master's Degree,Web Developer,7.0,below average
+30.0,Male,High School,Junior HR Coordinator,2.0,minimal
+43.0,Female,PhD,Senior Human Resources Manager,15.0,above average
+34.0,Male,Bachelor's Degree,Junior Web Developer,3.0,minimal
+25.0,Female,Master's Degree,Junior HR Generalist,1.0,minimal
+37.0,Male,PhD,Director of HR,11.0,average
+24.0,Female,Bachelor's Degree,Web Developer,1.0,minimal
+39.0,Male,Master's Degree,Senior HR Generalist,10.0,average
+31.0,Male,High School,Junior HR Generalist,2.0,minimal
+44.0,Female,PhD,Director of HR,13.0,above average
+28.0,Male,Bachelor's Degree,Web Developer,4.0,below average
+32.0,Female,Master's Degree,Senior Human Resources Manager,6.0,below average
+45.0,Male,PhD,Director of HR,14.0,above average
+26.0,Female,Bachelor's Degree,Junior Web Developer,2.0,minimal
+38.0,Male,Master's Degree,Senior HR Generalist,8.0,average
+27.0,Female,High School,Junior HR Generalist,1.0,minimal
+33.0,Male,Bachelor's Degree,Web Developer,5.0,below average
+42.0,Female,Master's Degree,Director of HR,12.0,average
+29.0,Male,Master's Degree,Senior Human Resources Manager,4.0,below average
+36.0,Female,Master's Degree,Web Developer,7.0,below average
+30.0,Male,High School,Junior HR Coordinator,2.0,minimal
+43.0,Female,PhD,Senior Human Resources Manager,15.0,above average
+34.0,Male,Bachelor's Degree,Junior Web Developer,3.0,minimal
+25.0,Female,Master's Degree,Junior HR Generalist,1.0,minimal
+37.0,Male,PhD,Director of HR,11.0,average
+24.0,Female,Bachelor's Degree,Web Developer,1.0,minimal
+39.0,Male,Master's Degree,Senior HR Generalist,10.0,average
+31.0,Male,High School,Junior HR Generalist,2.0,minimal
+44.0,Female,PhD,Director of HR,13.0,above average
+28.0,Male,Bachelor's Degree,Web Developer,4.0,below average
+32.0,Female,Master's Degree,Senior Human Resources Manager,6.0,below average
+45.0,Male,PhD,Director of HR,14.0,above average
+26.0,Female,Bachelor's Degree,Junior Web Developer,2.0,minimal
+38.0,Male,Master's Degree,Senior HR Generalist,8.0,average
+27.0,Female,High School,Junior HR Generalist,1.0,minimal
+33.0,Male,Bachelor's Degree,Web Developer,5.0,below average
+42.0,Female,Master's Degree,Director of HR,12.0,average
+29.0,Male,Master's Degree,Senior Human Resources Manager,4.0,below average
+36.0,Female,Master's Degree,Web Developer,7.0,below average
+30.0,Male,High School,Junior HR Coordinator,2.0,minimal
+43.0,Female,PhD,Senior Human Resources Manager,15.0,above average
+34.0,Male,Bachelor's Degree,Junior Web Developer,3.0,minimal
+25.0,Female,Master's Degree,Junior HR Generalist,1.0,minimal
+37.0,Male,PhD,Director of HR,11.0,average
+32.0,Male,Bachelor's Degree,Junior Web Developer,2.0,minimal
+24.0,Female,High School,Junior HR Generalist,1.0,minimal
+45.0,Male,PhD,Senior Human Resources Manager,12.0,average
+29.0,Female,Master's Degree,Web Developer,4.0,below average
+38.0,Male,Bachelor's Degree,Senior HR Generalist,8.0,average
+27.0,Female,Master's Degree,Director of HR,5.0,below average
+31.0,Female,High School,Junior HR Coordinator,3.0,minimal
+42.0,Male,Master's Degree,Web Developer,10.0,average
+26.0,Female,Bachelor's Degree,Junior Web Developer,2.0,minimal
+36.0,Male,Master's Degree,Senior HR Generalist,7.0,below average
+28.0,Male,High School,Junior HR Generalist,1.0,minimal
+33.0,Female,Bachelor's Degree,Web Developer,5.0,below average
+46.0,Male,PhD,Director of HR,15.0,above average
+25.0,Female,Bachelor's Degree,Junior Web Developer,1.0,minimal
+37.0,Female,Master's Degree,Senior Human Resources Manager,9.0,average
+30.0,Male,Master's Degree,Web Developer,4.0,below average
+43.0,Female,PhD,Director of HR,14.0,above average
+34.0,Male,Bachelor's Degree,Junior Web Developer,3.0,minimal
+26.0,Female,High School,Junior HR Generalist,2.0,minimal
+41.0,Male,Master's Degree,Senior HR Generalist,11.0,average
+29.0,Female,Master's Degree,Web Developer,5.0,below average
+35.0,Male,Bachelor's Degree,Web Developer,6.0,below average
+27.0,Female,High School,Junior HR Coordinator,1.0,minimal
+40.0,Male,PhD,Director of HR,13.0,above average
+23.0,Female,Bachelor's Degree,Junior Web Developer,1.0,minimal
+39.0,Male,Master's Degree,Senior HR Generalist,10.0,average
+31.0,Male,High School,Junior HR Generalist,2.0,minimal
+44.0,Female,PhD,Senior Human Resources Manager,12.0,average
+28.0,Male,Master's Degree,Web Developer,3.0,minimal
+32.0,Female,Bachelor's Degree,Junior Web Developer,2.0,minimal
+45.0,Male,Master's Degree,Director of HR,14.0,above average
+26.0,Female,Bachelor's Degree,Web Developer,3.0,minimal
+38.0,Male,PhD,Senior Human Resources Manager,11.0,average
+27.0,Female,Master's Degree,Senior HR Generalist,4.0,below average
+33.0,Male,High School,Junior HR Coordinator,3.0,minimal
+42.0,Female,Master's Degree,Director of HR,13.0,above average
+29.0,Male,Bachelor's Degree,Junior Web Developer,2.0,minimal
+36.0,Female,Master's Degree,Web Developer,7.0,below average
+30.0,Male,High School,Junior HR Generalist,1.0,minimal
+43.0,Female,PhD,Senior Human Resources Manager,15.0,above average
+34.0,Male,Bachelor's Degree,Web Developer,4.0,below average
+25.0,Female,Master's Degree,Junior HR Generalist,1.0,minimal
+37.0,Male,PhD,Director of HR,12.0,average
+24.0,Female,Bachelor's Degree,Junior Web Developer,1.0,minimal
+39.0,Male,Master's Degree,Senior HR Generalist,9.0,average
+31.0,Male,High School,Junior HR Generalist,2.0,minimal
+44.0,Female,PhD,Director of HR,14.0,above average
+28.0,Male,Bachelor's Degree,Web Developer,3.0,minimal
+32.0,Female,Master's Degree,Senior Human Resources Manager,6.0,below average
+45.0,Male,PhD,Director of HR,13.0,above average
+26.0,Female,Bachelor's Degree,Junior Web Developer,2.0,minimal
+38.0,Male,Master's Degree,Senior HR Generalist,8.0,average
+27.0,Female,High School,Junior HR Generalist,1.0,minimal
+33.0,Male,Bachelor's Degree,Web Developer,5.0,below average
+42.0,Female,Master's Degree,Director of HR,12.0,average
+29.0,Male,Master's Degree,Senior Human Resources Manager,4.0,below average
+36.0,Female,Master's Degree,Web Developer,7.0,below average
+30.0,Male,High School,Junior HR Coordinator,2.0,minimal
+43.0,Female,PhD,Senior Human Resources Manager,15.0,above average
+34.0,Male,Bachelor's Degree,Junior Web Developer,3.0,minimal
+25.0,Female,Master's Degree,Junior HR Generalist,1.0,minimal
+37.0,Male,PhD,Director of HR,11.0,average
+24.0,Female,Bachelor's Degree,Web Developer,1.0,minimal
+39.0,Male,Master's Degree,Senior HR Generalist,10.0,average
+31.0,Male,High School,Junior HR Generalist,2.0,minimal
+44.0,Female,PhD,Director of HR,13.0,above average
+28.0,Male,Bachelor's Degree,Web Developer,4.0,below average
+32.0,Female,Master's Degree,Senior Human Resources Manager,6.0,below average
+45.0,Male,PhD,Director of HR,14.0,above average
+26.0,Female,Bachelor's Degree,Junior Web Developer,2.0,minimal
+38.0,Male,Master's Degree,Senior HR Generalist,8.0,average
+27.0,Female,High School,Junior HR Generalist,1.0,minimal
+33.0,Male,Bachelor's Degree,Web Developer,5.0,below average
+42.0,Female,Master's Degree,Director of HR,12.0,average
+29.0,Male,Master's Degree,Senior Human Resources Manager,4.0,below average
+36.0,Female,Master's Degree,Web Developer,7.0,below average
+30.0,Male,High School,Junior HR Coordinator,2.0,minimal
+43.0,Female,PhD,Senior Human Resources Manager,15.0,above average
+34.0,Male,Bachelor's Degree,Junior Web Developer,3.0,minimal
+25.0,Female,Master's Degree,Junior HR Generalist,1.0,minimal
+37.0,Male,PhD,Director of HR,11.0,average
+24.0,Female,Bachelor's Degree,Web Developer,1.0,minimal
+39.0,Male,Master's Degree,Senior HR Generalist,10.0,average
+31.0,Male,High School,Junior HR Generalist,2.0,minimal
+44.0,Female,PhD,Director of HR,13.0,above average
+28.0,Male,Bachelor's Degree,Web Developer,4.0,below average
+32.0,Female,Master's Degree,Senior Human Resources Manager,6.0,below average
+45.0,Male,PhD,Director of HR,14.0,above average
+26.0,Female,Bachelor's Degree,Junior Web Developer,2.0,minimal
+38.0,Male,Master's Degree,Senior HR Generalist,8.0,average
+27.0,Female,High School,Junior HR Generalist,1.0,minimal
+33.0,Male,Bachelor's Degree,Web Developer,5.0,below average
+42.0,Female,Master's Degree,Director of HR,12.0,average
+29.0,Male,Master's Degree,Senior Human Resources Manager,4.0,below average
+36.0,Female,Master's Degree,Web Developer,7.0,below average
+30.0,Male,High School,Junior HR Coordinator,2.0,minimal
+43.0,Female,PhD,Senior Human Resources Manager,15.0,above average
+34.0,Male,Bachelor's Degree,Junior Web Developer,3.0,minimal
+25.0,Female,Master's Degree,Junior HR Generalist,1.0,minimal
+37.0,Male,PhD,Director of HR,11.0,average
+24.0,Female,Bachelor's Degree,Web Developer,1.0,minimal
+39.0,Male,Master's Degree,Senior HR Generalist,10.0,average
+31.0,Male,High School,Junior HR Generalist,2.0,minimal
+44.0,Female,PhD,Director of HR,13.0,above average
+28.0,Male,Bachelor's Degree,Web Developer,4.0,below average
+32.0,Female,Master's Degree,Senior Human Resources Manager,6.0,below average
+45.0,Male,PhD,Director of HR,14.0,above average
+26.0,Female,Bachelor's Degree,Junior Web Developer,2.0,minimal
+38.0,Male,Master's Degree,Senior HR Generalist,8.0,average
+27.0,Female,High School,Junior HR Generalist,1.0,minimal
+33.0,Male,Bachelor's Degree,Web Developer,5.0,below average
+42.0,Female,Master's Degree,Director of HR,12.0,average
+29.0,Male,Master's Degree,Senior Human Resources Manager,4.0,below average
+36.0,Female,Master's Degree,Web Developer,7.0,below average
+30.0,Male,High School,Junior HR Coordinator,2.0,minimal
+43.0,Female,PhD,Senior Human Resources Manager,15.0,above average
+34.0,Male,Bachelor's Degree,Junior Web Developer,3.0,minimal
+25.0,Female,Master's Degree,Junior HR Generalist,1.0,minimal
+37.0,Male,PhD,Director of HR,11.0,average
+28.0,Male,Bachelor's Degree,Software Engineer,3.0,below average
+37.0,Female,Master's Degree,Marketing Manager,9.0,average
+43.0,Male,PhD,Data Scientist,15.0,above average
+31.0,Female,Bachelor's Degree,Human Resources Coordinator,4.0,minimal
+24.0,Male,High School,Junior Sales Associate,1.0,minimal
+29.0,Female,Master's Degree,Software Developer,5.0,below average
+35.0,Male,Bachelor's Degree,Operations Manager,8.0,below average
+26.0,Female,Master's Degree,Marketing Coordinator,2.0,minimal
+42.0,Male,PhD,Data Scientist,12.0,above average
+34.0,Female,Bachelor's Degree,Human Resources Manager,6.0,below average
+27.0,Male,High School,Junior Sales Associate,2.0,minimal
+38.0,Female,Master's Degree,Marketing Manager,10.0,average
+30.0,Male,Bachelor's Degree,Software Engineer,4.0,below average
+45.0,Male,PhD,Data Scientist,18.0,high
+25.0,Female,Bachelor's Degree,Junior Software Developer,1.0,minimal
+40.0,Female,Master's Degree,Human Resources Manager,11.0,average
+33.0,Male,Bachelor's Degree,Operations Manager,6.0,below average
+29.0,Female,High School,Junior Sales Associate,1.0,minimal
+44.0,Male,PhD,Data Scientist,16.0,above average
+26.0,Male,Bachelor's Degree,Software Developer,3.0,below average
+36.0,Female,Master's Degree,Marketing Coordinator,8.0,below average
+31.0,Male,Bachelor's Degree,Operations Manager,5.0,below average
+27.0,Female,Master's Degree,Human Resources Coordinator,3.0,minimal
+42.0,Male,PhD,Data Scientist,13.0,above average
+34.0,Female,Bachelor's Degree,Human Resources Manager,6.0,below average
+28.0,Male,High School,Junior Sales Associate,2.0,minimal
+39.0,Female,Master's Degree,Marketing Manager,10.0,average
+31.0,Male,Bachelor's Degree,Software Engineer,4.0,below average
+45.0,Male,PhD,Data Scientist,18.0,high
+25.0,Female,Bachelor's Degree,Junior Software Developer,1.0,minimal
+40.0,Female,Master's Degree,Human Resources Manager,11.0,average
+33.0,Male,Bachelor's Degree,Operations Manager,6.0,below average
+29.0,Female,High School,Junior Sales Associate,1.0,minimal
+44.0,Male,PhD,Data Scientist,16.0,above average
+26.0,Male,Bachelor's Degree,Software Developer,3.0,below average
+36.0,Female,Master's Degree,Marketing Coordinator,8.0,below average
+31.0,Male,Bachelor's Degree,Operations Manager,5.0,below average
+27.0,Female,Master's Degree,Human Resources Coordinator,3.0,minimal
+42.0,Male,PhD,Data Scientist,13.0,above average
+34.0,Female,Bachelor's Degree,Human Resources Manager,6.0,below average
+28.0,Male,High School,Junior Sales Associate,2.0,minimal
+39.0,Female,Master's Degree,Marketing Manager,10.0,average
+31.0,Male,Bachelor's Degree,Software Engineer,4.0,below average
+45.0,Male,PhD,Data Scientist,18.0,high
+25.0,Female,Bachelor's Degree,Junior Software Developer,1.0,minimal
+40.0,Female,Master's Degree,Human Resources Manager,11.0,average
+33.0,Male,Bachelor's Degree,Operations Manager,6.0,below average
+29.0,Female,High School,Junior Sales Associate,1.0,minimal
+44.0,Male,PhD,Data Scientist,16.0,above average
+26.0,Male,Bachelor's Degree,Software Developer,3.0,below average
+36.0,Female,Master's Degree,Marketing Coordinator,8.0,below average
+31.0,Male,Bachelor's Degree,Operations Manager,5.0,below average
+27.0,Female,Master's Degree,Human Resources Coordinator,3.0,minimal
+42.0,Male,PhD,Data Scientist,13.0,above average
+34.0,Female,Bachelor's Degree,Human Resources Manager,6.0,below average
+28.0,Male,High School,Junior Sales Associate,2.0,minimal
+39.0,Female,Master's Degree,Marketing Manager,10.0,average
+31.0,Male,Bachelor's Degree,Software Engineer,4.0,below average
+45.0,Male,PhD,Data Scientist,18.0,high
+25.0,Female,Bachelor's Degree,Junior Software Developer,1.0,minimal
+40.0,Female,Master's Degree,Human Resources Manager,11.0,average
+33.0,Male,Bachelor's Degree,Operations Manager,6.0,below average
+29.0,Female,High School,Junior Sales Associate,1.0,minimal
+44.0,Male,PhD,Data Scientist,16.0,above average
+26.0,Male,Bachelor's Degree,Software Developer,3.0,below average
+36.0,Female,Master's Degree,Marketing Coordinator,8.0,below average
+31.0,Male,Bachelor's Degree,Operations Manager,5.0,below average
+27.0,Female,Master's Degree,Human Resources Coordinator,3.0,minimal
+42.0,Male,PhD,Data Scientist,13.0,above average
+34.0,Female,Bachelor's Degree,Human Resources Manager,6.0,below average
+28.0,Male,High School,Junior Sales Associate,2.0,minimal
+39.0,Female,Master's Degree,Marketing Manager,10.0,average
+31.0,Male,Bachelor's Degree,Software Engineer,4.0,below average
+45.0,Male,PhD,Data Scientist,18.0,high
+25.0,Female,Bachelor's Degree,Junior Software Developer,1.0,minimal
+40.0,Female,Master's Degree,Human Resources Manager,11.0,average
+33.0,Male,Bachelor's Degree,Operations Manager,6.0,below average
+29.0,Female,High School,Junior Sales Associate,1.0,minimal
+44.0,Male,PhD,Data Scientist,16.0,above average
+26.0,Male,Bachelor's Degree,Software Developer,3.0,below average
+36.0,Female,Master's Degree,Marketing Coordinator,8.0,below average
+31.0,Male,Bachelor's Degree,Operations Manager,5.0,below average
+27.0,Female,Master's Degree,Human Resources Coordinator,3.0,minimal
+42.0,Male,PhD,Data Scientist,13.0,above average
+34.0,Female,Bachelor's Degree,Human Resources Manager,6.0,below average
+28.0,Male,High School,Junior Sales Associate,2.0,minimal
+39.0,Female,Master's Degree,Marketing Manager,10.0,average
+31.0,Male,Bachelor's Degree,Software Engineer,4.0,below average
+45.0,Male,PhD,Data Scientist,18.0,high
+25.0,Female,Bachelor's Degree,Junior Software Developer,1.0,minimal
+40.0,Female,Master's Degree,Human Resources Manager,11.0,average
+33.0,Male,Bachelor's Degree,Operations Manager,6.0,below average
+29.0,Female,High School,Junior Sales Associate,1.0,minimal
+44.0,Male,PhD,Data Scientist,16.0,above average
+26.0,Male,Bachelor's Degree,Software Developer,3.0,below average
+36.0,Female,Master's Degree,Marketing Coordinator,8.0,below average
+31.0,Male,Bachelor's Degree,Operations Manager,5.0,below average
+27.0,Female,Master's Degree,Human Resources Coordinator,3.0,minimal
+42.0,Male,PhD,Data Scientist,13.0,above average
+34.0,Female,Bachelor's Degree,Human Resources Manager,6.0,below average
+28.0,Male,High School,Junior Sales Associate,2.0,minimal
+39.0,Female,Master's Degree,Marketing Manager,10.0,average
+31.0,Male,Bachelor's Degree,Software Engineer,4.0,below average
+45.0,Male,PhD,Data Scientist,18.0,high
+25.0,Female,Bachelor's Degree,Junior Software Developer,1.0,minimal
+40.0,Female,Master's Degree,Human Resources Manager,11.0,average
+33.0,Male,Bachelor's Degree,Operations Manager,6.0,below average
+29.0,Female,High School,Junior Sales Associate,1.0,minimal
+44.0,Male,PhD,Data Scientist,16.0,above average
+26.0,Male,Bachelor's Degree,Software Developer,3.0,below average
+36.0,Female,Master's Degree,Marketing Coordinator,8.0,below average
+31.0,Male,Bachelor's Degree,Operations Manager,5.0,below average
+27.0,Female,Master's Degree,Human Resources Coordinator,3.0,minimal
+42.0,Male,PhD,Data Scientist,13.0,above average
+34.0,Female,Bachelor's Degree,Human Resources Manager,6.0,below average
+28.0,Male,High School,Junior Sales Associate,2.0,minimal
+39.0,Female,Master's Degree,Marketing Manager,10.0,average
+31.0,Male,Bachelor's Degree,Software Engineer,4.0,below average
+45.0,Male,PhD,Data Scientist,18.0,high
+25.0,Female,Bachelor's Degree,Junior Software Developer,1.0,minimal
+40.0,Female,Master's Degree,Human Resources Manager,11.0,average
+33.0,Male,Bachelor's Degree,Operations Manager,6.0,below average
+29.0,Female,High School,Junior Sales Associate,1.0,minimal
+44.0,Male,PhD,Data Scientist,16.0,above average
+26.0,Male,Bachelor's Degree,Software Developer,3.0,below average
+27.0,Male,Bachelor's Degree,Software Engineer,3.0,below average
+38.0,Female,Master's Degree,Marketing Manager,9.0,average
+44.0,Male,PhD,Data Scientist,15.0,above average
+30.0,Female,Bachelor's Degree,Human Resources Coordinator,4.0,minimal
+23.0,Male,High School,Junior Sales Associate,1.0,minimal
+28.0,Female,Master's Degree,Software Developer,5.0,below average
+34.0,Male,Bachelor's Degree,Operations Manager,8.0,below average
+25.0,Female,Master's Degree,Marketing Coordinator,2.0,minimal
+41.0,Male,PhD,Data Scientist,12.0,above average
+33.0,Female,Bachelor's Degree,Human Resources Manager,6.0,below average
+26.0,Male,High School,Junior Sales Associate,2.0,minimal
+37.0,Female,Master's Degree,Marketing Manager,10.0,average
+29.0,Male,Bachelor's Degree,Software Engineer,4.0,below average
+46.0,Male,PhD,Data Scientist,18.0,high
+26.0,Female,Bachelor's Degree,Junior Software Developer,1.0,minimal
+39.0,Female,Master's Degree,Human Resources Manager,11.0,average
+32.0,Male,Bachelor's Degree,Operations Manager,6.0,below average
+28.0,Female,High School,Junior Sales Associate,1.0,minimal
+43.0,Male,PhD,Data Scientist,16.0,above average
+27.0,Male,Bachelor's Degree,Software Developer,3.0,below average
+35.0,Female,Master's Degree,Marketing Coordinator,8.0,below average
+30.0,Male,Bachelor's Degree,Operations Manager,5.0,below average
+26.0,Female,Master's Degree,Human Resources Coordinator,3.0,minimal
+41.0,Male,PhD,Data Scientist,13.0,above average
+33.0,Female,Bachelor's Degree,Human Resources Manager,6.0,below average
+27.0,Male,High School,Junior Sales Associate,2.0,minimal
+38.0,Female,Master's Degree,Marketing Manager,10.0,average
+29.0,Male,Bachelor's Degree,Software Engineer,4.0,below average
+46.0,Male,PhD,Data Scientist,18.0,high
+26.0,Female,Bachelor's Degree,Junior Software Developer,1.0,minimal
+39.0,Female,Master's Degree,Human Resources Manager,11.0,average
+32.0,Male,Bachelor's Degree,Operations Manager,6.0,below average
+28.0,Female,High School,Junior Sales Associate,1.0,minimal
+43.0,Male,PhD,Data Scientist,16.0,above average
+27.0,Male,Bachelor's Degree,Software Developer,3.0,below average
+35.0,Female,Master's Degree,Marketing Coordinator,8.0,below average
+30.0,Male,Bachelor's Degree,Operations Manager,5.0,below average
+26.0,Female,Master's Degree,Human Resources Coordinator,3.0,minimal
+41.0,Male,PhD,Data Scientist,13.0,above average
+33.0,Female,Bachelor's Degree,Human Resources Manager,6.0,below average
+27.0,Male,High School,Junior Sales Associate,2.0,minimal
+38.0,Female,Master's Degree,Marketing Manager,10.0,average
+29.0,Male,Bachelor's Degree,Software Engineer,4.0,below average
+46.0,Male,PhD,Data Scientist,18.0,high
+26.0,Female,Bachelor's Degree,Junior Software Developer,1.0,minimal
+39.0,Female,Master's Degree,Human Resources Manager,11.0,average
+32.0,Male,Bachelor's Degree,Operations Manager,6.0,below average
+28.0,Female,High School,Junior Sales Associate,1.0,minimal
+43.0,Male,PhD,Data Scientist,16.0,above average
+27.0,Male,Bachelor's Degree,Software Developer,3.0,below average
+35.0,Female,Master's Degree,Marketing Coordinator,8.0,below average
+30.0,Male,Bachelor's Degree,Operations Manager,5.0,below average
+26.0,Female,Master's Degree,Human Resources Coordinator,3.0,minimal
+41.0,Male,PhD,Data Scientist,13.0,above average
+33.0,Female,Bachelor's Degree,Human Resources Manager,6.0,below average
+27.0,Male,High School,Junior Sales Associate,2.0,minimal
+38.0,Female,Master's Degree,Marketing Manager,10.0,average
+29.0,Male,Bachelor's Degree,Software Engineer,4.0,below average
+46.0,Male,PhD,Data Scientist,18.0,high
+26.0,Female,Bachelor's Degree,Junior Software Developer,1.0,minimal
+39.0,Female,Master's Degree,Human Resources Manager,11.0,average
+32.0,Male,Bachelor's Degree,Operations Manager,6.0,below average
+28.0,Female,High School,Junior Sales Associate,1.0,minimal
+43.0,Male,PhD,Data Scientist,16.0,above average
+27.0,Male,Bachelor's Degree,Software Developer,3.0,below average
+35.0,Female,Master's Degree,Marketing Coordinator,8.0,below average
+30.0,Male,Bachelor's Degree,Operations Manager,5.0,below average
+26.0,Female,Master's Degree,Human Resources Coordinator,3.0,minimal
+41.0,Male,PhD,Data Scientist,13.0,above average
+33.0,Female,Bachelor's Degree,Human Resources Manager,6.0,below average
+27.0,Male,High School,Junior Sales Associate,2.0,minimal
+38.0,Female,Master's Degree,Marketing Manager,10.0,average
+29.0,Male,Bachelor's Degree,Software Engineer,4.0,below average
+46.0,Male,PhD,Data Scientist,18.0,high
+26.0,Female,Bachelor's Degree,Junior Software Developer,1.0,minimal
+39.0,Female,Master's Degree,Human Resources Manager,11.0,average
+32.0,Male,Bachelor's Degree,Operations Manager,6.0,below average
+28.0,Female,High School,Junior Sales Associate,1.0,minimal
+43.0,Male,PhD,Data Scientist,16.0,above average
+27.0,Male,Bachelor's Degree,Software Developer,3.0,below average
+35.0,Female,Master's Degree,Marketing Coordinator,8.0,below average
+30.0,Male,Bachelor's Degree,Operations Manager,5.0,below average
+26.0,Female,Master's Degree,Human Resources Coordinator,3.0,minimal
+41.0,Male,PhD,Data Scientist,13.0,above average
+33.0,Female,Bachelor's Degree,Human Resources Manager,6.0,below average
+27.0,Male,High School,Junior Sales Associate,2.0,minimal
+38.0,Female,Master's Degree,Marketing Manager,10.0,average
+29.0,Male,Bachelor's Degree,Software Engineer,4.0,below average
+46.0,Male,PhD,Data Scientist,18.0,high
+26.0,Female,Bachelor's Degree,Junior Software Developer,1.0,minimal
+39.0,Female,Master's Degree,Human Resources Manager,11.0,average
+32.0,Male,Bachelor's Degree,Operations Manager,6.0,below average
+28.0,Female,High School,Junior Sales Associate,1.0,minimal
+43.0,Male,PhD,Data Scientist,16.0,above average
+27.0,Male,Bachelor's Degree,Software Developer,3.0,below average
+35.0,Female,Master's Degree,Marketing Coordinator,8.0,below average
+30.0,Male,Bachelor's Degree,Operations Manager,5.0,below average
+26.0,Female,Master's Degree,Human Resources Coordinator,3.0,minimal
+41.0,Male,PhD,Data Scientist,13.0,above average
+33.0,Female,Bachelor's Degree,Human Resources Manager,6.0,below average
+27.0,Male,High School,Junior Sales Associate,2.0,minimal
+38.0,Female,Master's Degree,Marketing Manager,10.0,average
+29.0,Male,Bachelor's Degree,Software Engineer,4.0,below average
+46.0,Male,PhD,Data Scientist,18.0,high
+26.0,Female,Bachelor's Degree,Junior Software Developer,1.0,minimal
+39.0,Female,Master's Degree,Human Resources Manager,11.0,average
+32.0,Male,Bachelor's Degree,Operations Manager,6.0,below average
+28.0,Female,High School,Junior Sales Associate,1.0,minimal
+43.0,Male,PhD,Data Scientist,16.0,above average
+27.0,Male,Bachelor's Degree,Software Developer,3.0,below average
+35.0,Female,Master's Degree,Marketing Coordinator,8.0,below average
+30.0,Male,Bachelor's Degree,Operations Manager,5.0,below average
+26.0,Female,Master's Degree,Human Resources Coordinator,3.0,minimal
+41.0,Male,PhD,Data Scientist,13.0,above average
+33.0,Female,Bachelor's Degree,Human Resources Manager,6.0,below average
+27.0,Male,High School,Junior Sales Associate,2.0,minimal
+38.0,Female,Master's Degree,Marketing Manager,10.0,average
+29.0,Male,Bachelor's Degree,Software Engineer,4.0,below average
+46.0,Male,PhD,Data Scientist,18.0,high
+26.0,Female,Bachelor's Degree,Junior Software Developer,1.0,minimal
+39.0,Female,Master's Degree,Human Resources Manager,11.0,average
+32.0,Male,Bachelor's Degree,Operations Manager,6.0,below average
+28.0,Female,High School,Junior Sales Associate,1.0,minimal
+43.0,Male,PhD,Data Scientist,16.0,above average
+27.0,Male,Bachelor's Degree,Software Developer,3.0,below average
+24.0,Male,Bachelor's Degree,Software Engineer,2.0,minimal
+32.0,Female,Master's Degree,Marketing Manager,7.0,below average
+45.0,Male,PhD,Data Scientist,16.0,above average
+28.0,Female,Bachelor's Degree,Human Resources Coordinator,4.0,below average
+22.0,Male,High School,Junior Sales Associate,1.0,minimal
+29.0,Female,Master's Degree,Software Developer,5.0,below average
+36.0,Male,Bachelor's Degree,Operations Manager,8.0,average
+27.0,Female,Bachelor's Degree,Marketing Coordinator,3.0,minimal
+42.0,Male,PhD,Data Scientist,14.0,above average
+34.0,Female,Bachelor's Degree,Human Resources Manager,6.0,below average
+25.0,Male,High School,Junior Sales Associate,2.0,minimal
+39.0,Female,Master's Degree,Marketing Manager,11.0,average
+30.0,Male,Bachelor's Degree,Software Engineer,4.0,below average
+47.0,Male,PhD,Data Scientist,19.0,high
+25.0,Female,Bachelor's Degree,Junior Software Developer,1.0,minimal
+40.0,Female,Master's Degree,Human Resources Manager,12.0,above average
+33.0,Male,Bachelor's Degree,Operations Manager,7.0,below average
+29.0,Female,High School,Junior Sales Associate,1.0,minimal
+44.0,Male,PhD,Data Scientist,15.0,above average
+28.0,Male,Bachelor's Degree,Software Developer,3.0,below average
+36.0,Female,Master's Degree,Marketing Coordinator,9.0,average
+31.0,Male,Bachelor's Degree,Operations Manager,6.0,below average
+27.0,Female,Master's Degree,Human Resources Coordinator,3.0,minimal
+42.0,Male,PhD,Data Scientist,14.0,above average
+34.0,Female,Bachelor's Degree,Human Resources Manager,6.0,below average
+26.0,Male,High School,Junior Sales Associate,2.0,minimal
+39.0,Female,Master's Degree,Marketing Manager,11.0,average
+30.0,Male,Bachelor's Degree,Software Engineer,4.0,below average
+47.0,Male,PhD,Data Scientist,19.0,high
+25.0,Female,Bachelor's Degree,Junior Software Developer,1.0,minimal
+40.0,Female,Master's Degree,Human Resources Manager,12.0,above average
+33.0,Male,Bachelor's Degree,Operations Manager,7.0,below average
+29.0,Female,High School,Junior Sales Associate,1.0,minimal
+44.0,Male,PhD,Data Scientist,15.0,above average
+28.0,Male,Bachelor's Degree,Software Developer,3.0,below average
+36.0,Female,Master's Degree,Marketing Coordinator,9.0,average
+31.0,Male,Bachelor's Degree,Operations Manager,6.0,below average
+27.0,Female,Master's Degree,Human Resources Coordinator,3.0,minimal
+42.0,Male,PhD,Data Scientist,14.0,above average
+34.0,Female,Bachelor's Degree,Human Resources Manager,6.0,below average
+26.0,Male,High School,Junior Sales Associate,2.0,minimal
+39.0,Female,Master's Degree,Marketing Manager,11.0,average
+30.0,Male,Bachelor's Degree,Software Engineer,4.0,below average
+47.0,Male,PhD,Data Scientist,19.0,high
+25.0,Female,Bachelor's Degree,Junior Software Developer,1.0,minimal
+40.0,Female,Master's Degree,Human Resources Manager,12.0,above average
+33.0,Male,Bachelor's Degree,Operations Manager,7.0,below average
+29.0,Female,High School,Junior Sales Associate,1.0,minimal
+44.0,Male,PhD,Data Scientist,15.0,above average
+28.0,Male,Bachelor's Degree,Software Developer,3.0,below average
+36.0,Female,Master's Degree,Marketing Coordinator,9.0,average
+31.0,Male,Bachelor's Degree,Operations Manager,6.0,below average
+27.0,Female,Master's Degree,Human Resources Coordinator,3.0,minimal
+42.0,Male,PhD,Data Scientist,14.0,above average
+34.0,Female,Bachelor's Degree,Human Resources Manager,6.0,below average
+26.0,Male,High School,Junior Sales Associate,2.0,minimal
+39.0,Female,Master's Degree,Marketing Manager,11.0,average
+30.0,Male,Bachelor's Degree,Software Engineer,4.0,below average
+47.0,Male,PhD,Data Scientist,19.0,high
+25.0,Female,Bachelor's Degree,Junior Software Developer,1.0,minimal
+40.0,Female,Master's Degree,Human Resources Manager,12.0,above average
+33.0,Male,Bachelor's Degree,Operations Manager,7.0,below average
+29.0,Female,High School,Junior Sales Associate,1.0,minimal
+44.0,Male,PhD,Data Scientist,15.0,above average
+28.0,Male,Bachelor's Degree,Software Developer,3.0,below average
+36.0,Female,Master's Degree,Marketing Coordinator,9.0,average
+31.0,Male,Bachelor's Degree,Operations Manager,6.0,below average
+27.0,Female,Master's Degree,Human Resources Coordinator,3.0,minimal
+42.0,Male,PhD,Data Scientist,14.0,above average
+34.0,Female,Bachelor's Degree,Human Resources Manager,6.0,below average
+26.0,Male,High School,Junior Sales Associate,2.0,minimal
+39.0,Female,Master's Degree,Marketing Manager,11.0,average
+30.0,Male,Bachelor's Degree,Software Engineer,4.0,below average
+47.0,Male,PhD,Data Scientist,19.0,high
+25.0,Female,Bachelor's Degree,Junior Software Developer,1.0,minimal
+40.0,Female,Master's Degree,Human Resources Manager,12.0,above average
+33.0,Male,Bachelor's Degree,Operations Manager,7.0,below average
+29.0,Female,High School,Junior Sales Associate,1.0,minimal
+44.0,Male,PhD,Data Scientist,15.0,above average
+28.0,Male,Bachelor's Degree,Software Developer,3.0,below average
+36.0,Female,Master's Degree,Marketing Coordinator,9.0,average
+31.0,Male,Bachelor's Degree,Operations Manager,6.0,below average
+27.0,Female,Master's Degree,Human Resources Coordinator,3.0,minimal
+42.0,Male,PhD,Data Scientist,14.0,above average
+34.0,Female,Bachelor's Degree,Human Resources Manager,6.0,below average
+26.0,Male,High School,Junior Sales Associate,2.0,minimal
+39.0,Female,Master's Degree,Marketing Manager,11.0,average
+30.0,Male,Bachelor's Degree,Software Engineer,4.0,below average
+47.0,Male,PhD,Data Scientist,19.0,high
+25.0,Female,Bachelor's Degree,Junior Software Developer,1.0,minimal
+40.0,Female,Master's Degree,Human Resources Manager,12.0,above average
+33.0,Male,Bachelor's Degree,Operations Manager,7.0,below average
+29.0,Female,High School,Junior Sales Associate,1.0,minimal
+44.0,Male,PhD,Data Scientist,15.0,above average
+28.0,Male,Bachelor's Degree,Software Developer,3.0,below average
+36.0,Female,Master's Degree,Marketing Coordinator,9.0,average
+31.0,Male,Bachelor's Degree,Operations Manager,6.0,below average
+27.0,Female,Master's Degree,Human Resources Coordinator,3.0,minimal
+42.0,Male,PhD,Data Scientist,14.0,above average
+34.0,Female,Bachelor's Degree,Human Resources Manager,6.0,below average
+26.0,Male,High School,Junior Sales Associate,2.0,minimal
+39.0,Female,Master's Degree,Marketing Manager,11.0,average
+30.0,Male,Bachelor's Degree,Software Engineer,4.0,below average
+47.0,Male,PhD,Data Scientist,19.0,high
+25.0,Female,Bachelor's Degree,Junior Software Developer,1.0,minimal
+40.0,Female,Master's Degree,Human Resources Manager,12.0,above average
+33.0,Male,Bachelor's Degree,Operations Manager,7.0,below average
+29.0,Female,High School,Junior Sales Associate,1.0,minimal
+44.0,Male,PhD,Data Scientist,15.0,above average
+28.0,Male,Bachelor's Degree,Software Developer,3.0,below average
+36.0,Female,Master's Degree,Marketing Coordinator,9.0,average
+31.0,Male,Bachelor's Degree,Operations Manager,6.0,below average
+27.0,Female,Master's Degree,Human Resources Coordinator,3.0,minimal
+42.0,Male,PhD,Data Scientist,14.0,above average
+34.0,Female,Bachelor's Degree,Human Resources Manager,6.0,below average
+26.0,Male,High School,Junior Sales Associate,2.0,minimal
+39.0,Female,Master's Degree,Marketing Manager,11.0,average
+30.0,Male,Bachelor's Degree,Software Engineer,4.0,below average
+47.0,Male,PhD,Data Scientist,19.0,high
+25.0,Female,Bachelor's Degree,Junior Software Developer,1.0,minimal
+40.0,Female,Master's Degree,Human Resources Manager,12.0,above average
+33.0,Male,Bachelor's Degree,Operations Manager,7.0,below average
+29.0,Female,High School,Junior Sales Associate,1.0,minimal
+44.0,Male,PhD,Data Scientist,15.0,above average
+28.0,Male,Bachelor's Degree,Software Developer,3.0,below average
+31.0,Male,Bachelor's Degree,Software Engineer,5.0,below average
+27.0,Female,Master's Degree,Marketing Manager,3.0,below average
+38.0,Male,PhD,Data Scientist,12.0,above average
+29.0,Female,Bachelor's Degree,Human Resources Coordinator,2.0,minimal
+23.0,Male,High School,Junior Sales Associate,1.0,minimal
+32.0,Female,Master's Degree,Software Developer,7.0,below average
+44.0,Male,Bachelor's Degree,Operations Manager,18.0,high
+26.0,Female,Bachelor's Degree,Marketing Coordinator,2.0,minimal
+40.0,Male,PhD,Data Scientist,15.0,above average
+33.0,Female,Bachelor's Degree,Human Resources Manager,8.0,average
+24.0,Male,High School,Junior Sales Associate,1.0,minimal
+35.0,Female,Master's Degree,Marketing Manager,10.0,average
+29.0,Male,Bachelor's Degree,Software Engineer,4.0,below average
+49.0,Male,PhD,Data Scientist,22.0,high
+26.0,Female,Bachelor's Degree,Junior Software Developer,2.0,minimal
+41.0,Female,Master's Degree,Human Resources Manager,13.0,above average
+36.0,Male,Bachelor's Degree,Operations Manager,9.0,average
+28.0,Female,High School,Junior Sales Associate,1.0,minimal
+43.0,Male,PhD,Data Scientist,16.0,above average
+29.0,Male,Bachelor's Degree,Software Developer,5.0,below average
+39.0,Female,Master's Degree,Marketing Coordinator,11.0,average
+32.0,Male,Bachelor's Degree,Operations Manager,6.0,below average
+28.0,Female,Master's Degree,Human Resources Coordinator,2.0,minimal
+40.0,Male,PhD,Data Scientist,15.0,above average
+33.0,Female,Bachelor's Degree,Human Resources Manager,8.0,average
+24.0,Male,High School,Junior Sales Associate,1.0,minimal
+35.0,Female,Master's Degree,Marketing Manager,10.0,average
+29.0,Male,Bachelor's Degree,Software Engineer,4.0,below average
+49.0,Male,PhD,Data Scientist,22.0,high
+26.0,Female,Bachelor's Degree,Junior Software Developer,2.0,minimal
+41.0,Female,Master's Degree,Human Resources Manager,13.0,above average
+36.0,Male,Bachelor's Degree,Operations Manager,9.0,average
+28.0,Female,High School,Junior Sales Associate,1.0,minimal
+43.0,Male,PhD,Data Scientist,16.0,above average
+29.0,Male,Bachelor's Degree,Software Developer,5.0,below average
+39.0,Female,Master's Degree,Marketing Coordinator,11.0,average
+32.0,Male,Bachelor's Degree,Operations Manager,6.0,below average
+28.0,Female,Master's Degree,Human Resources Coordinator,2.0,minimal
+40.0,Male,PhD,Data Scientist,15.0,above average
+33.0,Female,Bachelor's Degree,Human Resources Manager,8.0,average
+24.0,Male,High School,Junior Sales Associate,1.0,minimal
+35.0,Female,Master's Degree,Marketing Manager,10.0,average
+29.0,Male,Bachelor's Degree,Software Engineer,4.0,below average
+49.0,Male,PhD,Data Scientist,22.0,high
+26.0,Female,Bachelor's Degree,Junior Software Developer,2.0,minimal
+41.0,Female,Master's Degree,Human Resources Manager,13.0,above average
+36.0,Male,Bachelor's Degree,Operations Manager,9.0,average
+28.0,Female,High School,Junior Sales Associate,1.0,minimal
+43.0,Male,PhD,Data Scientist,16.0,above average
+29.0,Male,Bachelor's Degree,Software Developer,5.0,below average
+39.0,Female,Master's Degree,Marketing Coordinator,11.0,average
+32.0,Male,Bachelor's Degree,Operations Manager,6.0,below average
+28.0,Female,Master's Degree,Human Resources Coordinator,2.0,minimal
+40.0,Male,PhD,Data Scientist,15.0,above average
+33.0,Female,Bachelor's Degree,Human Resources Manager,8.0,average
+24.0,Male,High School,Junior Sales Associate,1.0,minimal
+35.0,Female,Master's Degree,Marketing Manager,10.0,average
+29.0,Male,Bachelor's Degree,Software Engineer,4.0,below average
+49.0,Male,PhD,Data Scientist,22.0,high
+26.0,Female,Bachelor's Degree,Junior Software Developer,2.0,minimal
+41.0,Female,Master's Degree,Human Resources Manager,13.0,above average
+36.0,Male,Bachelor's Degree,Operations Manager,9.0,average
+28.0,Female,High School,Junior Sales Associate,1.0,minimal
+43.0,Male,PhD,Data Scientist,16.0,above average
+29.0,Male,Bachelor's Degree,Software Developer,5.0,below average
+39.0,Female,Master's Degree,Marketing Coordinator,11.0,average
+32.0,Male,Bachelor's Degree,Operations Manager,6.0,below average
+28.0,Female,Master's Degree,Human Resources Coordinator,2.0,minimal
+40.0,Male,PhD,Data Scientist,15.0,above average
+33.0,Female,Bachelor's Degree,Human Resources Manager,8.0,average
+24.0,Male,High School,Junior Sales Associate,1.0,minimal
+35.0,Female,Master's Degree,Marketing Manager,10.0,average
+29.0,Male,Bachelor's Degree,Software Engineer,4.0,below average
+49.0,Male,PhD,Data Scientist,22.0,high
+26.0,Female,Bachelor's Degree,Junior Software Developer,2.0,minimal
+41.0,Female,Master's Degree,Human Resources Manager,13.0,above average
+36.0,Male,Bachelor's Degree,Operations Manager,9.0,average
+28.0,Female,High School,Junior Sales Associate,1.0,minimal
+43.0,Male,PhD,Data Scientist,16.0,above average
+29.0,Male,Bachelor's Degree,Software Developer,5.0,below average
+39.0,Female,Master's Degree,Marketing Coordinator,11.0,average
+32.0,Male,Bachelor's Degree,Operations Manager,6.0,below average
+28.0,Female,Master's Degree,Human Resources Coordinator,2.0,minimal
+40.0,Male,PhD,Data Scientist,15.0,above average
+33.0,Female,Bachelor's Degree,Human Resources Manager,8.0,average
+24.0,Male,High School,Junior Sales Associate,1.0,minimal
+35.0,Female,Master's Degree,Marketing Manager,10.0,average
+29.0,Male,Bachelor's Degree,Software Engineer,4.0,below average
+49.0,Male,PhD,Data Scientist,22.0,high
+26.0,Female,Bachelor's Degree,Junior Software Developer,2.0,minimal
+41.0,Female,Master's Degree,Human Resources Manager,13.0,above average
+36.0,Male,Bachelor's Degree,Operations Manager,9.0,average
+28.0,Female,High School,Junior Sales Associate,1.0,minimal
+43.0,Male,PhD,Data Scientist,16.0,above average
+29.0,Male,Bachelor's Degree,Software Developer,5.0,below average
+39.0,Female,Master's Degree,Marketing Coordinator,11.0,average
+32.0,Male,Bachelor's Degree,Operations Manager,6.0,below average
+28.0,Female,Master's Degree,Human Resources Coordinator,2.0,minimal
+40.0,Male,PhD,Data Scientist,15.0,above average
+33.0,Female,Bachelor's Degree,Human Resources Manager,8.0,average
+24.0,Male,High School,Junior Sales Associate,1.0,minimal
+35.0,Female,Master's Degree,Marketing Manager,10.0,average
+29.0,Male,Bachelor's Degree,Software Engineer,4.0,below average
+49.0,Male,PhD,Data Scientist,22.0,high
+26.0,Female,Bachelor's Degree,Junior Software Developer,2.0,minimal
+41.0,Female,Master's Degree,Human Resources Manager,13.0,above average
+36.0,Male,Bachelor's Degree,Operations Manager,9.0,average
+28.0,Female,High School,Junior Sales Associate,1.0,minimal
+43.0,Male,PhD,Data Scientist,16.0,above average
+29.0,Male,Bachelor's Degree,Software Developer,5.0,below average
+39.0,Female,Master's Degree,Marketing Coordinator,11.0,average
+32.0,Male,Bachelor's Degree,Operations Manager,6.0,below average
+28.0,Female,Master's Degree,Human Resources Coordinator,2.0,minimal
+40.0,Male,PhD,Data Scientist,15.0,above average
+33.0,Female,Bachelor's Degree,Human Resources Manager,8.0,average
+24.0,Male,High School,Junior Sales Associate,1.0,minimal
+35.0,Female,Master's Degree,Marketing Manager,10.0,average
+29.0,Male,Bachelor's Degree,Software Engineer,4.0,below average
+49.0,Male,PhD,Data Scientist,22.0,high
+26.0,Female,Bachelor's Degree,Junior Software Developer,2.0,minimal
+41.0,Female,Master's Degree,Human Resources Manager,13.0,above average
+36.0,Male,Bachelor's Degree,Operations Manager,9.0,average
+28.0,Female,High School,Junior Sales Associate,1.0,minimal
+43.0,Male,PhD,Data Scientist,16.0,above average
+29.0,Male,Bachelor's Degree,Software Developer,5.0,below average
+34.0,Male,Bachelor's Degree,Software Engineer,6.0,below average
+31.0,Female,Master's Degree,Marketing Manager,4.0,below average
+41.0,Male,PhD,Data Scientist,13.0,above average
+27.0,Female,Bachelor's Degree,Human Resources Coordinator,2.0,minimal
+25.0,Male,High School,Junior Sales Associate,1.0,minimal
+33.0,Female,Master's Degree,Software Developer,8.0,average
+45.0,Male,Bachelor's Degree,Operations Manager,19.0,high
+28.0,Female,Bachelor's Degree,Marketing Coordinator,2.0,minimal
+42.0,Male,PhD,Data Scientist,16.0,above average
+34.0,Female,Bachelor's Degree,Human Resources Manager,9.0,average
+23.0,Male,High School,Junior Sales Associate,1.0,minimal
+36.0,Female,Master's Degree,Marketing Manager,11.0,average
+30.0,Male,Bachelor's Degree,Software Engineer,5.0,below average
+50.0,Male,PhD,Data Scientist,23.0,high
+27.0,Female,Bachelor's Degree,Junior Software Developer,2.0,minimal
+43.0,Female,Master's Degree,Human Resources Manager,14.0,above average
+37.0,Male,Bachelor's Degree,Operations Manager,10.0,average
+29.0,Female,High School,Junior Sales Associate,1.0,minimal
+44.0,Male,PhD,Data Scientist,17.0,above average
+30.0,Male,Bachelor's Degree,Software Developer,6.0,below average
+40.0,Female,Master's Degree,Marketing Coordinator,12.0,average
+33.0,Male,Bachelor's Degree,Operations Manager,7.0,average
+29.0,Female,Master's Degree,Human Resources Coordinator,3.0,minimal
+43.0,Male,PhD,Data Scientist,16.0,above average
+34.0,Female,Bachelor's Degree,Human Resources Manager,9.0,average
+23.0,Male,High School,Junior Sales Associate,1.0,minimal
+36.0,Female,Master's Degree,Marketing Manager,11.0,average
+30.0,Male,Bachelor's Degree,Software Engineer,5.0,below average
+50.0,Male,PhD,Data Scientist,23.0,high
+27.0,Female,Bachelor's Degree,Junior Software Developer,2.0,minimal
+43.0,Female,Master's Degree,Human Resources Manager,14.0,above average
+37.0,Male,Bachelor's Degree,Operations Manager,10.0,average
+29.0,Female,High School,Junior Sales Associate,1.0,minimal
+44.0,Male,PhD,Data Scientist,17.0,above average
+30.0,Male,Bachelor's Degree,Software Developer,6.0,below average
+40.0,Female,Master's Degree,Marketing Coordinator,12.0,average
+33.0,Male,Bachelor's Degree,Operations Manager,7.0,average
+29.0,Female,Master's Degree,Human Resources Coordinator,3.0,minimal
+43.0,Male,PhD,Data Scientist,16.0,above average
+34.0,Female,Bachelor's Degree,Human Resources Manager,9.0,average
+23.0,Male,High School,Junior Sales Associate,1.0,minimal
+36.0,Female,Master's Degree,Marketing Manager,11.0,average
+30.0,Male,Bachelor's Degree,Software Engineer,5.0,below average
+50.0,Male,PhD,Data Scientist,23.0,high
+27.0,Female,Bachelor's Degree,Junior Software Developer,2.0,minimal
+43.0,Female,Master's Degree,Human Resources Manager,14.0,above average
+37.0,Male,Bachelor's Degree,Operations Manager,10.0,average
+29.0,Female,High School,Junior Sales Associate,1.0,minimal
+44.0,Male,PhD,Data Scientist,17.0,above average
+30.0,Male,Bachelor's Degree,Software Developer,6.0,below average
+40.0,Female,Master's Degree,Marketing Coordinator,12.0,average
+33.0,Male,Bachelor's Degree,Operations Manager,7.0,average
+29.0,Female,Master's Degree,Human Resources Coordinator,3.0,minimal
+43.0,Male,PhD,Data Scientist,16.0,above average
+34.0,Female,Bachelor's Degree,Human Resources Manager,9.0,average
+23.0,Male,High School,Junior Sales Associate,1.0,minimal
+36.0,Female,Master's Degree,Marketing Manager,11.0,average
+30.0,Male,Bachelor's Degree,Software Engineer,5.0,below average
+50.0,Male,PhD,Data Scientist,23.0,high
+27.0,Female,Bachelor's Degree,Junior Software Developer,2.0,minimal
+43.0,Female,Master's Degree,Human Resources Manager,14.0,above average
+37.0,Male,Bachelor's Degree,Operations Manager,10.0,average
+29.0,Female,High School,Junior Sales Associate,1.0,minimal
+44.0,Male,PhD,Data Scientist,17.0,above average
+30.0,Male,Bachelor's Degree,Software Developer,6.0,below average
+40.0,Female,Master's Degree,Marketing Coordinator,12.0,average
+33.0,Male,Bachelor's Degree,Operations Manager,7.0,average
+29.0,Female,Master's Degree,Human Resources Coordinator,3.0,minimal
+43.0,Male,PhD,Data Scientist,16.0,above average
+34.0,Female,Bachelor's Degree,Human Resources Manager,9.0,average
+23.0,Male,High School,Junior Sales Associate,1.0,minimal
+36.0,Female,Master's Degree,Marketing Manager,11.0,average
+30.0,Male,Bachelor's Degree,Software Engineer,5.0,below average
+50.0,Male,PhD,Data Scientist,23.0,high
+27.0,Female,Bachelor's Degree,Junior Software Developer,2.0,minimal
+43.0,Female,Master's Degree,Human Resources Manager,14.0,above average
+37.0,Male,Bachelor's Degree,Operations Manager,10.0,average
+29.0,Female,High School,Junior Sales Associate,1.0,minimal
+44.0,Male,PhD,Data Scientist,17.0,above average
+30.0,Male,Bachelor's Degree,Software Developer,6.0,below average
+40.0,Female,Master's Degree,Marketing Coordinator,12.0,average
+33.0,Male,Bachelor's Degree,Operations Manager,7.0,average
+29.0,Female,Master's Degree,Human Resources Coordinator,3.0,minimal
+43.0,Male,PhD,Data Scientist,16.0,above average
+34.0,Female,Bachelor's Degree,Human Resources Manager,9.0,average
+23.0,Male,High School,Junior Sales Associate,1.0,minimal
+36.0,Female,Master's Degree,Marketing Manager,11.0,average
+30.0,Male,Bachelor's Degree,Software Engineer,5.0,below average
+50.0,Male,PhD,Data Scientist,23.0,high
+27.0,Female,Bachelor's Degree,Junior Software Developer,2.0,minimal
+43.0,Female,Master's Degree,Human Resources Manager,14.0,above average
+37.0,Male,Bachelor's Degree,Operations Manager,10.0,average
+29.0,Female,High School,Junior Sales Associate,1.0,minimal
+44.0,Male,PhD,Data Scientist,17.0,above average
+30.0,Male,Bachelor's Degree,Software Developer,6.0,below average
+40.0,Female,Master's Degree,Marketing Coordinator,12.0,average
+33.0,Male,Bachelor's Degree,Operations Manager,7.0,average
+29.0,Female,Master's Degree,Human Resources Coordinator,3.0,minimal
+43.0,Male,PhD,Data Scientist,16.0,above average
+34.0,Female,Bachelor's Degree,Human Resources Manager,9.0,average
+23.0,Male,High School,Junior Sales Associate,1.0,minimal
+36.0,Female,Master's Degree,Marketing Manager,11.0,average
+30.0,Male,Bachelor's Degree,Software Engineer,5.0,below average
+50.0,Male,PhD,Data Scientist,23.0,high
+27.0,Female,Bachelor's Degree,Junior Software Developer,2.0,minimal
+43.0,Female,Master's Degree,Human Resources Manager,14.0,above average
+37.0,Male,Bachelor's Degree,Operations Manager,10.0,average
+29.0,Female,High School,Junior Sales Associate,1.0,minimal
+44.0,Male,PhD,Data Scientist,17.0,above average
+30.0,Male,Bachelor's Degree,Software Developer,6.0,below average
+40.0,Female,Master's Degree,Marketing Coordinator,12.0,average
+33.0,Male,Bachelor's Degree,Operations Manager,7.0,average
+29.0,Female,Master's Degree,Human Resources Coordinator,3.0,minimal
+43.0,Male,PhD,Data Scientist,16.0,above average
+34.0,Female,Bachelor's Degree,Human Resources Manager,9.0,average
+23.0,Male,High School,Junior Sales Associate,1.0,minimal
+36.0,Female,Master's Degree,Marketing Manager,11.0,average
+30.0,Male,Bachelor's Degree,Software Engineer,5.0,below average
+50.0,Male,PhD,Data Scientist,23.0,high
+27.0,Female,Bachelor's Degree,Junior Software Developer,2.0,minimal
+43.0,Female,Master's Degree,Human Resources Manager,14.0,above average
+37.0,Male,Bachelor's Degree,Operations Manager,10.0,average
+29.0,Female,High School,Junior Sales Associate,1.0,minimal
+44.0,Male,PhD,Data Scientist,17.0,above average
+30.0,Male,Bachelor's Degree,Software Developer,6.0,below average
+32.0,Female,Master's Degree,Software Developer,8.0,average
+46.0,Male,PhD,Data Scientist,18.0,high
+28.0,Female,Bachelor's Degree,Marketing Coordinator,2.0,minimal
+24.0,Male,High School,Junior Sales Associate,1.0,minimal
+31.0,Female,Master's Degree,Marketing Manager,5.0,below average
+39.0,Male,Bachelor's Degree,Operations Manager,13.0,average
+25.0,Female,Bachelor's Degree,Human Resources Coordinator,2.0,minimal
+41.0,Male,PhD,Data Scientist,15.0,above average
+35.0,Female,Bachelor's Degree,Human Resources Manager,8.0,below average
+26.0,Male,High School,Junior Sales Associate,1.0,minimal
+37.0,Female,Master's Degree,Marketing Manager,12.0,average
+29.0,Male,Bachelor's Degree,Software Engineer,4.0,below average
+51.0,Male,PhD,Data Scientist,24.0,high
+28.0,Female,Bachelor's Degree,Junior Software Developer,2.0,minimal
+44.0,Female,Master's Degree,Human Resources Manager,15.0,above average
+38.0,Male,Bachelor's Degree,Operations Manager,11.0,average
+30.0,Female,High School,Junior Sales Associate,1.0,minimal
+45.0,Male,PhD,Data Scientist,19.0,high
+31.0,Male,Bachelor's Degree,Software Developer,6.0,below average
+41.0,Female,Master's Degree,Marketing Coordinator,13.0,above average
+34.0,Male,Bachelor's Degree,Operations Manager,8.0,average
+30.0,Female,Master's Degree,Human Resources Coordinator,3.0,minimal
+44.0,Male,PhD,Data Scientist,18.0,high
+35.0,Female,Bachelor's Degree,Human Resources Manager,8.0,below average
+26.0,Male,High School,Junior Sales Associate,1.0,minimal
+37.0,Female,Master's Degree,Marketing Manager,12.0,average
+29.0,Male,Bachelor's Degree,Software Engineer,4.0,below average
+51.0,Male,PhD,Data Scientist,24.0,high
+28.0,Female,Bachelor's Degree,Junior Software Developer,2.0,minimal
+44.0,Female,Master's Degree,Human Resources Manager,15.0,above average
+38.0,Male,Bachelor's Degree,Operations Manager,11.0,average
+30.0,Female,High School,Junior Sales Associate,1.0,minimal
+45.0,Male,PhD,Data Scientist,19.0,high
+31.0,Male,Bachelor's Degree,Software Developer,6.0,below average
+41.0,Female,Master's Degree,Marketing Coordinator,13.0,above average
+34.0,Male,Bachelor's Degree,Operations Manager,8.0,average
+30.0,Female,Master's Degree,Human Resources Coordinator,3.0,minimal
+44.0,Male,PhD,Data Scientist,18.0,high
+35.0,Female,Bachelor's Degree,Human Resources Manager,8.0,below average
+26.0,Male,High School,Junior Sales Associate,1.0,minimal
+37.0,Female,Master's Degree,Marketing Manager,12.0,average
+29.0,Male,Bachelor's Degree,Software Engineer,4.0,below average
+51.0,Male,PhD,Data Scientist,24.0,high
+28.0,Female,Bachelor's Degree,Junior Software Developer,2.0,minimal
+44.0,Female,Master's Degree,Human Resources Manager,15.0,above average
+38.0,Male,Bachelor's Degree,Operations Manager,11.0,average
+30.0,Female,High School,Junior Sales Associate,1.0,minimal
+45.0,Male,PhD,Data Scientist,19.0,high
+31.0,Male,Bachelor's Degree,Software Developer,6.0,below average
+41.0,Female,Master's Degree,Marketing Coordinator,13.0,above average
+34.0,Male,Bachelor's Degree,Operations Manager,8.0,average
+30.0,Female,Master's Degree,Human Resources Coordinator,3.0,minimal
+44.0,Male,PhD,Data Scientist,18.0,high
+35.0,Female,Bachelor's Degree,Human Resources Manager,8.0,below average
+26.0,Male,High School,Junior Sales Associate,1.0,minimal
+37.0,Female,Master's Degree,Marketing Manager,12.0,average
+29.0,Male,Bachelor's Degree,Software Engineer,4.0,below average
+51.0,Male,PhD,Data Scientist,24.0,high
+28.0,Female,Bachelor's Degree,Junior Software Developer,2.0,minimal
+44.0,Female,Master's Degree,Human Resources Manager,15.0,above average
+38.0,Male,Bachelor's Degree,Operations Manager,11.0,average
+30.0,Female,High School,Junior Sales Associate,1.0,minimal
+45.0,Male,PhD,Data Scientist,19.0,high
+31.0,Male,Bachelor's Degree,Software Developer,6.0,below average
+41.0,Female,Master's Degree,Marketing Coordinator,13.0,above average
+34.0,Male,Bachelor's Degree,Operations Manager,8.0,average
+30.0,Female,Master's Degree,Human Resources Coordinator,3.0,minimal
+44.0,Male,PhD,Data Scientist,18.0,high
+35.0,Female,Bachelor's Degree,Human Resources Manager,8.0,below average
+26.0,Male,High School,Junior Sales Associate,1.0,minimal
+37.0,Female,Master's Degree,Marketing Manager,12.0,average
+29.0,Male,Bachelor's Degree,Software Engineer,4.0,below average
+51.0,Male,PhD,Data Scientist,24.0,high
+28.0,Female,Bachelor's Degree,Junior Software Developer,2.0,minimal
+44.0,Female,Master's Degree,Human Resources Manager,15.0,above average
+38.0,Male,Bachelor's Degree,Operations Manager,11.0,average
+30.0,Female,High School,Junior Sales Associate,1.0,minimal
+45.0,Male,PhD,Data Scientist,19.0,high
+31.0,Male,Bachelor's Degree,Software Developer,6.0,below average
+41.0,Female,Master's Degree,Marketing Coordinator,13.0,above average
+34.0,Male,Bachelor's Degree,Operations Manager,8.0,average
+30.0,Female,Master's Degree,Human Resources Coordinator,3.0,minimal
+44.0,Male,PhD,Data Scientist,18.0,high
+35.0,Female,Bachelor's Degree,Human Resources Manager,8.0,below average
+26.0,Male,High School,Junior Sales Associate,1.0,minimal
+37.0,Female,Master's Degree,Marketing Manager,12.0,average
+29.0,Male,Bachelor's Degree,Software Engineer,4.0,below average
+51.0,Male,PhD,Data Scientist,24.0,high
+28.0,Female,Bachelor's Degree,Junior Software Developer,2.0,minimal
+44.0,Female,Master's Degree,Human Resources Manager,15.0,above average
+38.0,Male,Bachelor's Degree,Operations Manager,11.0,average
+30.0,Female,High School,Junior Sales Associate,1.0,minimal
+45.0,Male,PhD,Data Scientist,19.0,high
+31.0,Male,Bachelor's Degree,Software Developer,6.0,below average
+41.0,Female,Master's Degree,Marketing Coordinator,13.0,above average
+34.0,Male,Bachelor's Degree,Operations Manager,8.0,average
+30.0,Female,Master's Degree,Human Resources Coordinator,3.0,minimal
+44.0,Male,PhD,Data Scientist,18.0,high
+35.0,Female,Bachelor's Degree,Human Resources Manager,8.0,below average
+26.0,Male,High School,Junior Sales Associate,1.0,minimal
+37.0,Female,Master's Degree,Marketing Manager,12.0,average
+29.0,Male,Bachelor's Degree,Software Engineer,4.0,below average
+51.0,Male,PhD,Data Scientist,24.0,high
+28.0,Female,Bachelor's Degree,Junior Software Developer,2.0,minimal
+44.0,Female,Master's Degree,Human Resources Manager,15.0,above average
+38.0,Male,Bachelor's Degree,Operations Manager,11.0,average
+30.0,Female,High School,Junior Sales Associate,1.0,minimal
+45.0,Male,PhD,Data Scientist,19.0,high
+31.0,Male,Bachelor's Degree,Software Developer,6.0,below average
+41.0,Female,Master's Degree,Marketing Coordinator,13.0,above average
+34.0,Male,Bachelor's Degree,Operations Manager,8.0,average
+30.0,Female,Master's Degree,Human Resources Coordinator,3.0,minimal
+44.0,Male,PhD,Data Scientist,18.0,high
+35.0,Female,Bachelor's Degree,Human Resources Manager,8.0,below average
+26.0,Male,High School,Junior Sales Associate,1.0,minimal
+37.0,Female,Master's Degree,Marketing Manager,12.0,average
+29.0,Male,Bachelor's Degree,Software Engineer,4.0,below average
+51.0,Male,PhD,Data Scientist,24.0,high
+28.0,Female,Bachelor's Degree,Junior Software Developer,2.0,minimal
+44.0,Female,Master's Degree,Human Resources Manager,15.0,above average
+38.0,Male,Bachelor's Degree,Operations Manager,11.0,average
+30.0,Female,High School,Junior Sales Associate,1.0,minimal
+45.0,Male,PhD,Data Scientist,19.0,high
+31.0,Male,Bachelor's Degree,Software Developer,6.0,below average
+41.0,Female,Master's Degree,Marketing Coordinator,13.0,above average
+27.0,Male,Bachelor's Degree,Software Developer,3.0,below average
+42.0,Female,Master's Degree,Marketing Manager,16.0,above average
+35.0,Male,PhD,Data Scientist,9.0,average
+29.0,Female,Bachelor's Degree,Human Resources Coordinator,2.0,minimal
+33.0,Male,High School,Junior Sales Associate,1.0,minimal
+36.0,Female,Bachelor's Degree,Operations Manager,7.0,below average
+43.0,Male,PhD,Data Scientist,17.0,high
+31.0,Female,Bachelor's Degree,Software Engineer,5.0,below average
+49.0,Male,Master's Degree,Marketing Manager,23.0,high
+28.0,Female,Bachelor's Degree,Junior Software Developer,2.0,minimal
+45.0,Female,PhD,Data Scientist,19.0,high
+38.0,Male,Bachelor's Degree,Operations Manager,11.0,average
+30.0,Female,High School,Junior Sales Associate,1.0,minimal
+45.0,Male,Master's Degree,Marketing Manager,20.0,high
+27.0,Female,Bachelor's Degree,Software Developer,3.0,below average
+41.0,Male,PhD,Data Scientist,15.0,above average
+35.0,Female,Master's Degree,Human Resources Manager,8.0,below average
+26.0,Male,Bachelor's Degree,Software Engineer,1.0,minimal
+30.0,Female,Bachelor's Degree,Marketing Coordinator,4.0,minimal
+48.0,Male,PhD,Data Scientist,22.0,high
+32.0,Female,Master's Degree,Marketing Manager,6.0,below average
+34.0,Male,Bachelor's Degree,Operations Manager,8.0,average
+31.0,Female,High School,Junior Sales Associate,1.0,minimal
+45.0,Male,Master's Degree,Marketing Manager,20.0,high
+28.0,Female,Bachelor's Degree,Junior Software Developer,2.0,minimal
+44.0,Female,PhD,Data Scientist,18.0,high
+38.0,Male,Bachelor's Degree,Operations Manager,11.0,average
+30.0,Female,High School,Junior Sales Associate,1.0,minimal
+45.0,Male,Master's Degree,Marketing Manager,20.0,high
+27.0,Female,Bachelor's Degree,Software Developer,3.0,below average
+41.0,Male,PhD,Data Scientist,15.0,above average
+35.0,Female,Master's Degree,Human Resources Manager,8.0,below average
+26.0,Male,Bachelor's Degree,Software Engineer,1.0,minimal
+30.0,Female,Bachelor's Degree,Marketing Coordinator,4.0,minimal
+48.0,Male,PhD,Data Scientist,22.0,high
+32.0,Female,Master's Degree,Marketing Manager,6.0,below average
+34.0,Male,Bachelor's Degree,Operations Manager,8.0,average
+31.0,Female,High School,Junior Sales Associate,1.0,minimal
+45.0,Male,Master's Degree,Marketing Manager,20.0,high
+28.0,Female,Bachelor's Degree,Junior Software Developer,2.0,minimal
+44.0,Female,PhD,Data Scientist,18.0,high
+38.0,Male,Bachelor's Degree,Operations Manager,11.0,average
+30.0,Female,High School,Junior Sales Associate,1.0,minimal
+45.0,Male,Master's Degree,Marketing Manager,20.0,high
+27.0,Female,Bachelor's Degree,Software Developer,3.0,below average
+41.0,Male,PhD,Data Scientist,15.0,above average
+35.0,Female,Master's Degree,Human Resources Manager,8.0,below average
+26.0,Male,Bachelor's Degree,Software Engineer,1.0,minimal
+30.0,Female,Bachelor's Degree,Marketing Coordinator,4.0,minimal
+48.0,Male,PhD,Data Scientist,22.0,high
+32.0,Female,Master's Degree,Marketing Manager,6.0,below average
+34.0,Male,Bachelor's Degree,Operations Manager,8.0,average
+31.0,Female,High School,Junior Sales Associate,1.0,minimal
+45.0,Male,Master's Degree,Marketing Manager,20.0,high
+28.0,Female,Bachelor's Degree,Junior Software Developer,2.0,minimal
+44.0,Female,PhD,Data Scientist,18.0,high
+38.0,Male,Bachelor's Degree,Operations Manager,11.0,average
+30.0,Female,High School,Junior Sales Associate,1.0,minimal
+45.0,Male,Master's Degree,Marketing Manager,20.0,high
+27.0,Female,Bachelor's Degree,Software Developer,3.0,below average
+41.0,Male,PhD,Data Scientist,15.0,above average
+35.0,Female,Master's Degree,Human Resources Manager,8.0,below average
+26.0,Male,Bachelor's Degree,Software Engineer,1.0,minimal
+30.0,Female,Bachelor's Degree,Marketing Coordinator,4.0,minimal
+48.0,Male,PhD,Data Scientist,22.0,high
+32.0,Female,Master's Degree,Marketing Manager,6.0,below average
+34.0,Male,Bachelor's Degree,Operations Manager,8.0,average
+31.0,Female,High School,Junior Sales Associate,1.0,minimal
+45.0,Male,Master's Degree,Marketing Manager,20.0,high
+28.0,Female,Bachelor's Degree,Junior Software Developer,2.0,minimal
+44.0,Female,PhD,Data Scientist,18.0,high
+38.0,Male,Bachelor's Degree,Operations Manager,11.0,average
+30.0,Female,High School,Junior Sales Associate,1.0,minimal
+45.0,Male,Master's Degree,Marketing Manager,20.0,high
+27.0,Female,Bachelor's Degree,Software Developer,3.0,below average
+41.0,Male,PhD,Data Scientist,15.0,above average
+35.0,Female,Master's Degree,Human Resources Manager,8.0,below average
+26.0,Male,Bachelor's Degree,Software Engineer,1.0,minimal
+30.0,Female,Bachelor's Degree,Marketing Coordinator,4.0,minimal
+48.0,Male,PhD,Data Scientist,22.0,high
+32.0,Female,Master's Degree,Marketing Manager,6.0,below average
+34.0,Male,Bachelor's Degree,Operations Manager,8.0,average
+31.0,Female,High School,Junior Sales Associate,1.0,minimal
+45.0,Male,Master's Degree,Marketing Manager,20.0,high
+28.0,Female,Bachelor's Degree,Junior Software Developer,2.0,minimal
+44.0,Female,PhD,Data Scientist,18.0,high
+38.0,Male,Bachelor's Degree,Operations Manager,11.0,average
+30.0,Female,High School,Junior Sales Associate,1.0,minimal
+45.0,Male,Master's Degree,Marketing Manager,20.0,high
+27.0,Female,Bachelor's Degree,Software Developer,3.0,below average
+41.0,Male,PhD,Data Scientist,15.0,above average
+35.0,Female,Master's Degree,Human Resources Manager,8.0,below average
+26.0,Male,Bachelor's Degree,Software Engineer,1.0,minimal
+30.0,Female,Bachelor's Degree,Marketing Coordinator,4.0,minimal
+48.0,Male,PhD,Data Scientist,22.0,high
+32.0,Female,Master's Degree,Marketing Manager,6.0,below average
+34.0,Male,Bachelor's Degree,Operations Manager,8.0,average
+31.0,Female,High School,Junior Sales Associate,1.0,minimal
+45.0,Male,Master's Degree,Marketing Manager,20.0,high
+28.0,Female,Bachelor's Degree,Junior Software Developer,2.0,minimal
+44.0,Female,PhD,Data Scientist,18.0,high
+38.0,Male,Bachelor's Degree,Operations Manager,11.0,average
+30.0,Female,High School,Junior Sales Associate,1.0,minimal
+45.0,Male,Master's Degree,Marketing Manager,20.0,high
+27.0,Female,Bachelor's Degree,Software Developer,3.0,below average
+41.0,Male,PhD,Data Scientist,15.0,above average
+35.0,Female,Master's Degree,Human Resources Manager,8.0,below average
+26.0,Male,Bachelor's Degree,Software Engineer,1.0,minimal
+30.0,Female,Bachelor's Degree,Marketing Coordinator,4.0,minimal
+48.0,Male,PhD,Data Scientist,22.0,high
+32.0,Female,Master's Degree,Marketing Manager,6.0,below average
+34.0,Male,Bachelor's Degree,Operations Manager,8.0,average
+31.0,Female,High School,Junior Sales Associate,1.0,minimal
+45.0,Male,Master's Degree,Marketing Manager,20.0,high
+28.0,Female,Bachelor's Degree,Junior Software Developer,2.0,minimal
+44.0,Female,PhD,Data Scientist,18.0,high
+38.0,Male,Bachelor's Degree,Operations Manager,11.0,average
+30.0,Female,High School,Junior Sales Associate,1.0,minimal
+45.0,Male,Master's Degree,Marketing Manager,20.0,high
+27.0,Female,Bachelor's Degree,Software Developer,3.0,below average
+41.0,Male,PhD,Data Scientist,15.0,above average
+35.0,Female,Master's Degree,Human Resources Manager,8.0,below average
+26.0,Male,Bachelor's Degree,Software Engineer,1.0,minimal
+30.0,Female,Bachelor's Degree,Marketing Coordinator,4.0,minimal
+48.0,Male,PhD,Data Scientist,22.0,high
+32.0,Female,Master's Degree,Marketing Manager,6.0,below average
+31.0,Female,Master's Degree,Director of HR,6.0,average
+28.0,Male,Bachelor's Degree,Junior Web Developer,2.0,minimal
+29.0,Female,Master's Degree,Senior HR Generalist,4.0,below average
+35.0,Male,PhD,Senior Human Resources Manager,10.0,average
+26.0,Female,High School,Web Developer,1.0,minimal
+32.0,Male,Bachelor's Degree,Junior HR Generalist,5.0,below average
+27.0,Female,Master's Degree,Web Developer,2.0,minimal
+39.0,Male,Master's Degree,Director of HR,12.0,average
+23.0,Female,Bachelor's Degree,Junior HR Generalist,1.0,minimal
+30.0,Male,Bachelor's Degree,Web Developer,4.0,below average
+26.0,Female,Bachelor's Degree,Junior HR Coordinator,1.0,minimal
+42.0,Male,PhD,Senior Human Resources Manager,14.0,above average
+34.0,Female,Master's Degree,Director of HR,9.0,average
+28.0,Male,High School,Juniour HR Generalist,2.0,minimal
+31.0,Female,Bachelor's Degree,Junior HR Coordinator,4.0,minimal
+29.0,Male,Bachelor's Degree,Web Developer,3.0,below average
+35.0,Female,Master's Degree,Senior HR Generalist,8.0,below average
+26.0,Male,Master's Degree,Junior Web Developer,2.0,minimal
+40.0,Female,PhD,Director of HR,13.0,average
+34.0,Male,Bachelor's Degree,Web Developer,7.0,below average
+26.0,Female,Bachelor's Degree,Junior HR Generalist,2.0,minimal
+29.0,Male,Master's Degree,Senior HR Generalist,4.0,below average
+25.0,Female,High School,Juniour HR Coordinator,1.0,minimal
+33.0,Male,Master's Degree,Web Developer,6.0,below average
+27.0,Female,Bachelor's Degree,Junior HR Generalist,2.0,minimal
+31.0,Male,PhD,Senior Human Resources Manager,7.0,below average
+29.0,Female,Master's Degree,Web Developer,4.0,below average
+24.0,Male,Bachelor's Degree,Junior Web Developer,1.0,minimal
+42.0,Female,Master's Degree,Senior HR Generalist,12.0,average
+34.0,Male,Master's Degree,Director of HR,10.0,average
+28.0,Female,Bachelor's Degree,Junior HR Generalist,3.0,minimal
+33.0,Male,PhD,Director of HR,8.0,average
+29.0,Female,Bachelor's Degree,Web Developer,3.0,below average
+25.0,Male,High School,Junior HR Generalist,2.0,minimal
+26.0,Female,Master's Degree,Senior HR Generalist,2.0,minimal
+30.0,Male,Bachelor's Degree,Web Developer,5.0,below average
+24.0,Female,High School,Juniour HR Coordinator,1.0,minimal
+31.0,Male,Master's Degree,Director of HR,7.0,below average
+27.0,Female,Bachelor's Degree,Web Developer,2.0,minimal
+35.0,Male,PhD,Senior Human Resources Manager,10.0,average
+26.0,Female,Bachelor's Degree,Junior HR Generalist,1.0,minimal
+32.0,Male,Master's Degree,Web Developer,6.0,below average
+29.0,Female,Master's Degree,Senior HR Generalist,4.0,below average
+25.0,Male,High School,Web Developer,2.0,minimal
+33.0,Female,Bachelor's Degree,Junior HR Generalist,7.0,below average
+27.0,Male,Master's Degree,Web Developer,2.0,minimal
+28.0,Female,Bachelor's Degree,Junior HR Coordinator,3.0,minimal
+34.0,Male,PhD,Director of HR,9.0,average
+30.0,Female,Bachelor's Degree,Web Developer,4.0,below average
+26.0,Male,Bachelor's Degree,Junior HR Coordinator,2.0,minimal
+42.0,Female,Master's Degree,Senior Human Resources Manager,13.0,average
+34.0,Male,Master's Degree,Web Developer,8.0,below average
+28.0,Female,High School,Juniour HR Generalist,2.0,minimal
+31.0,Male,Bachelor's Degree,Junior HR Generalist,5.0,below average
+29.0,Female,Master's Degree,Web Developer,3.0,below average
+35.0,Male,PhD,Senior Human Resources Manager,10.0,average
+26.0,Female,Bachelor's Degree,Web Developer,1.0,minimal
+32.0,Male,Master's Degree,Director of HR,6.0,average
+27.0,Female,Master's Degree,Junior HR Generalist,2.0,minimal
+39.0,Male,Master's Degree,Senior HR Generalist,11.0,average
+23.0,Female,Bachelor's Degree,Junior HR Coordinator,1.0,minimal
+30.0,Male,Bachelor's Degree,Web Developer,4.0,below average
+26.0,Female,Bachelor's Degree,Junior HR Generalist,2.0,minimal
+42.0,Male,PhD,Director of HR,14.0,above average
+34.0,Female,Master's Degree,Director of HR,9.0,average
+28.0,Male,High School,Junior Web Developer,2.0,minimal
+31.0,Female,Bachelor's Degree,Junior HR Coordinator,4.0,minimal
+29.0,Male,Bachelor's Degree,Web Developer,3.0,below average
+35.0,Female,Master's Degree,Senior HR Generalist,8.0,below average
+26.0,Male,Master's Degree,Junior Web Developer,2.0,minimal
+40.0,Female,PhD,Director of HR,13.0,average
+34.0,Male,Bachelor's Degree,Web Developer,7.0,below average
+26.0,Female,Bachelor's Degree,Junior HR Generalist,2.0,minimal
+29.0,Male,Master's Degree,Senior HR Generalist,4.0,below average
+25.0,Female,High School,Junior HR Coordinator,1.0,minimal
+33.0,Male,Master's Degree,Web Developer,6.0,below average
+27.0,Female,Bachelor's Degree,Junior HR Generalist,2.0,minimal
+31.0,Male,PhD,Senior Human Resources Manager,7.0,below average
+29.0,Female,Master's Degree,Web Developer,4.0,below average
+24.0,Male,Bachelor's Degree,Junior Web Developer,1.0,minimal
+42.0,Female,Master's Degree,Senior HR Generalist,12.0,average
+34.0,Male,Master's Degree,Director of HR,10.0,average
+28.0,Female,Bachelor's Degree,Junior HR Generalist,3.0,minimal
+33.0,Male,PhD,Director of HR,8.0,average
+29.0,Female,Bachelor's Degree,Web Developer,3.0,below average
+25.0,Male,High School,Junior HR Generalist,2.0,minimal
+26.0,Female,Master's Degree,Senior HR Generalist,2.0,minimal
+30.0,Male,Bachelor's Degree,Web Developer,5.0,below average
+24.0,Female,High School,Juniour HR Coordinator,1.0,minimal
+31.0,Male,Master's Degree,Director of HR,7.0,below average
+27.0,Female,Bachelor's Degree,Web Developer,2.0,minimal
+35.0,Male,PhD,Senior Human Resources Manager,10.0,average
+26.0,Female,Bachelor's Degree,Junior HR Generalist,1.0,minimal
+32.0,Male,Master's Degree,Web Developer,6.0,below average
+29.0,Female,Master's Degree,Senior HR Generalist,4.0,below average
+25.0,Male,High School,Web Developer,2.0,minimal
+33.0,Female,Bachelor's Degree,Junior HR Generalist,7.0,below average
+27.0,Male,Master's Degree,Web Developer,2.0,minimal
+28.0,Female,Bachelor's Degree,Junior HR Coordinator,3.0,minimal
+34.0,Male,PhD,Director of HR,9.0,average
+30.0,Female,Bachelor's Degree,Web Developer,4.0,below average
+26.0,Male,Bachelor's Degree,Junior HR Coordinator,2.0,minimal
+42.0,Female,Master's Degree,Senior Human Resources Manager,13.0,average
+34.0,Male,Master's Degree,Web Developer,8.0,below average
+28.0,Female,High School,Juniour HR Generalist,2.0,minimal
+31.0,Male,Bachelor's Degree,Junior HR Generalist,5.0,below average
+29.0,Female,Master's Degree,Web Developer,3.0,below average
+35.0,Male,PhD,Senior Human Resources Manager,10.0,average
+26.0,Female,Bachelor's Degree,Web Developer,1.0,minimal
+32.0,Male,Master's Degree,Director of HR,6.0,average
+27.0,Female,Master's Degree,Junior HR Generalist,2.0,minimal
+39.0,Male,Master's Degree,Senior HR Generalist,11.0,average
+23.0,Female,Bachelor's Degree,Junior HR Coordinator,1.0,minimal
+30.0,Male,Bachelor's Degree,Web Developer,4.0,below average
+26.0,Female,Bachelor's Degree,Junior HR Generalist,2.0,minimal
+42.0,Male,PhD,Director of HR,14.0,above average
+34.0,Female,Master's Degree,Director of HR,9.0,average
+28.0,Male,High School,Junior Web Developer,2.0,minimal
+31.0,Female,Bachelor's Degree,Junior HR Coordinator,4.0,minimal
+27.0,Female,Bachelor's Degree,Junior Software Engineer,1.0,minimal
+33.0,Male,Master's Degree,Senior Data Scientist,8.0,average
+29.0,Female,Bachelor's Degree,Marketing Coordinator,3.0,minimal
+31.0,Male,Bachelor's Degree,Junior Marketing Manager,5.0,below average
+38.0,Female,PhD,Senior Research Scientist,12.0,above average
+25.0,Male,High School,Junior Sales Associate,1.0,minimal
+32.0,Female,Master's Degree,Senior Software Engineer,7.0,average
+27.0,Male,Bachelor's Degree,Junior Data Analyst,2.0,minimal
+29.0,Female,Bachelor's Degree,Junior Marketing Manager,3.0,minimal
+35.0,Male,PhD,Senior Research Scientist,10.0,above average
+26.0,Female,Bachelor's Degree,Junior Software Engineer,1.0,minimal
+33.0,Male,Master's Degree,Senior Data Scientist,8.0,average
+29.0,Female,Bachelor's Degree,Marketing Coordinator,3.0,minimal
+31.0,Male,Bachelor's Degree,Junior Marketing Manager,5.0,below average
+38.0,Female,PhD,Senior Research Scientist,12.0,above average
+25.0,Male,High School,Junior Sales Associate,1.0,minimal
+32.0,Female,Master's Degree,Senior Software Engineer,7.0,average
+27.0,Male,Bachelor's Degree,Junior Data Analyst,2.0,minimal
+29.0,Female,Bachelor's Degree,Junior Marketing Manager,3.0,minimal
+35.0,Male,PhD,Senior Research Scientist,10.0,above average
+26.0,Female,Bachelor's Degree,Junior Software Engineer,1.0,minimal
+33.0,Male,Master's Degree,Senior Data Scientist,8.0,average
+29.0,Female,Bachelor's Degree,Marketing Coordinator,3.0,minimal
+31.0,Male,Bachelor's Degree,Junior Marketing Manager,5.0,below average
+38.0,Female,PhD,Senior Research Scientist,12.0,above average
+25.0,Male,High School,Junior Sales Associate,1.0,minimal
+32.0,Female,Master's Degree,Senior Software Engineer,7.0,average
+27.0,Male,Bachelor's Degree,Junior Data Analyst,2.0,minimal
+29.0,Female,Bachelor's Degree,Junior Marketing Manager,3.0,minimal
+35.0,Male,PhD,Senior Research Scientist,10.0,above average
+26.0,Female,Bachelor's Degree,Junior Software Engineer,1.0,minimal
+33.0,Male,Master's Degree,Senior Data Scientist,8.0,average
+29.0,Female,Bachelor's Degree,Marketing Coordinator,3.0,minimal
+31.0,Male,Bachelor's Degree,Junior Marketing Manager,5.0,below average
+38.0,Female,PhD,Senior Research Scientist,12.0,above average
+25.0,Male,High School,Junior Sales Associate,1.0,minimal
+32.0,Female,Master's Degree,Senior Software Engineer,7.0,average
+27.0,Male,Bachelor's Degree,Junior Data Analyst,2.0,minimal
+29.0,Female,Bachelor's Degree,Junior Marketing Manager,3.0,minimal
+35.0,Male,PhD,Senior Research Scientist,10.0,above average
+26.0,Female,Bachelor's Degree,Junior Software Engineer,1.0,minimal
+33.0,Male,Master's Degree,Senior Data Scientist,8.0,average
+29.0,Female,Bachelor's Degree,Marketing Coordinator,3.0,minimal
+31.0,Male,Bachelor's Degree,Junior Marketing Manager,5.0,below average
+38.0,Female,PhD,Senior Research Scientist,12.0,above average
+25.0,Male,High School,Junior Sales Associate,1.0,minimal
+32.0,Female,Master's Degree,Senior Software Engineer,7.0,average
+27.0,Male,Bachelor's Degree,Junior Data Analyst,2.0,minimal
+29.0,Female,Bachelor's Degree,Junior Marketing Manager,3.0,minimal
+35.0,Male,PhD,Senior Research Scientist,10.0,above average
+26.0,Female,Bachelor's Degree,Junior Software Engineer,1.0,minimal
+33.0,Male,Master's Degree,Senior Data Scientist,8.0,average
+29.0,Female,Bachelor's Degree,Marketing Coordinator,3.0,minimal
+31.0,Male,Bachelor's Degree,Junior Marketing Manager,5.0,below average
+38.0,Female,PhD,Senior Research Scientist,12.0,above average
+25.0,Male,High School,Junior Sales Associate,1.0,minimal
+32.0,Female,Master's Degree,Senior Software Engineer,7.0,average
+27.0,Male,Bachelor's Degree,Junior Data Analyst,2.0,minimal
+29.0,Female,Bachelor's Degree,Junior Marketing Manager,3.0,minimal
+35.0,Male,PhD,Senior Research Scientist,10.0,above average
+26.0,Female,Bachelor's Degree,Junior Software Engineer,1.0,minimal
+33.0,Male,Master's Degree,Senior Data Scientist,8.0,average
+29.0,Female,Bachelor's Degree,Marketing Coordinator,3.0,minimal
+31.0,Male,Bachelor's Degree,Junior Marketing Manager,5.0,below average
+38.0,Female,PhD,Senior Research Scientist,12.0,above average
+25.0,Male,High School,Junior Sales Associate,1.0,minimal
+32.0,Female,Master's Degree,Senior Software Engineer,7.0,average
+27.0,Male,Bachelor's Degree,Junior Data Analyst,2.0,minimal
+29.0,Female,Bachelor's Degree,Junior Marketing Manager,3.0,minimal
+35.0,Male,PhD,Senior Research Scientist,10.0,above average
+26.0,Female,Bachelor's Degree,Junior Software Engineer,1.0,minimal
+33.0,Male,Master's Degree,Senior Data Scientist,8.0,average
+29.0,Female,Bachelor's Degree,Marketing Coordinator,3.0,minimal
+31.0,Male,Bachelor's Degree,Junior Marketing Manager,5.0,below average
+38.0,Female,PhD,Senior Research Scientist,12.0,above average
+25.0,Male,High School,Junior Sales Associate,1.0,minimal
+32.0,Female,Master's Degree,Senior Software Engineer,7.0,average
+27.0,Male,Bachelor's Degree,Junior Data Analyst,2.0,minimal
+29.0,Female,Bachelor's Degree,Junior Marketing Manager,3.0,minimal
+35.0,Male,PhD,Senior Research Scientist,10.0,above average
+26.0,Female,Bachelor's Degree,Junior Software Engineer,1.0,minimal
+33.0,Male,Master's Degree,Senior Data Scientist,8.0,average
+29.0,Female,Bachelor's Degree,Marketing Coordinator,3.0,minimal
+31.0,Male,Bachelor's Degree,Junior Marketing Manager,5.0,below average
+38.0,Female,PhD,Senior Research Scientist,12.0,above average
+25.0,Male,High School,Junior Sales Associate,1.0,minimal
+32.0,Female,Master's Degree,Senior Software Engineer,7.0,average
+27.0,Male,Bachelor's Degree,Junior Data Analyst,2.0,minimal
+29.0,Female,Bachelor's Degree,Junior Marketing Manager,3.0,minimal
+35.0,Male,PhD,Senior Research Scientist,10.0,above average
+26.0,Female,Bachelor's Degree,Junior Software Engineer,1.0,minimal
+33.0,Male,Master's Degree,Senior Data Scientist,8.0,average
+29.0,Female,Bachelor's Degree,Marketing Coordinator,3.0,minimal
+31.0,Male,Bachelor's Degree,Junior Marketing Manager,5.0,below average
+38.0,Female,PhD,Senior Research Scientist,12.0,above average
+25.0,Male,High School,Junior Sales Associate,1.0,minimal
+32.0,Female,Master's Degree,Senior Software Engineer,7.0,average
+27.0,Male,Bachelor's Degree,Junior Data Analyst,2.0,minimal
+29.0,Female,Bachelor's Degree,Junior Marketing Manager,3.0,minimal
+35.0,Male,PhD,Senior Research Scientist,10.0,above average
+26.0,Female,Bachelor's Degree,Junior Software Engineer,1.0,minimal
+33.0,Male,Master's Degree,Senior Data Scientist,8.0,average
+29.0,Female,Bachelor's Degree,Marketing Coordinator,3.0,minimal
+31.0,Male,Bachelor's Degree,Junior Marketing Manager,5.0,below average
+38.0,Female,PhD,Senior Research Scientist,12.0,above average
+25.0,Male,High School,Junior Sales Associate,1.0,minimal
+32.0,Female,Master's Degree,Senior Software Engineer,7.0,average
+27.0,Male,Bachelor's Degree,Junior Data Analyst,2.0,minimal
+29.0,Female,Bachelor's Degree,Junior Marketing Manager,3.0,minimal
+35.0,Male,PhD,Senior Research Scientist,10.0,above average
+26.0,Female,Bachelor's Degree,Junior Software Engineer,1.0,minimal
+33.0,Male,Master's Degree,Senior Data Scientist,8.0,average
+29.0,Female,Bachelor's Degree,Marketing Coordinator,3.0,minimal
+31.0,Male,Bachelor's Degree,Junior Marketing Manager,5.0,below average
+38.0,Female,PhD,Senior Research Scientist,12.0,above average
+25.0,Male,High School,Junior Sales Associate,1.0,minimal
+32.0,Female,Master's Degree,Senior Software Engineer,7.0,average
+27.0,Male,Bachelor's Degree,Junior Data Analyst,2.0,minimal
+29.0,Female,Bachelor's Degree,Junior Marketing Manager,3.0,minimal
+35.0,Male,PhD,Senior Research Scientist,10.0,above average
+26.0,Female,Bachelor's Degree,Junior Software Engineer,1.0,minimal
+28.0,Female,Bachelor's Degree,Junior Software Engineer,2.0,minimal
+36.0,Male,Master's Degree,Senior Data Scientist,9.0,average
+30.0,Female,Bachelor's Degree,Marketing Coordinator,4.0,minimal
+32.0,Male,Bachelor's Degree,Junior Marketing Manager,6.0,below average
+39.0,Female,PhD,Senior Research Scientist,13.0,above average
+26.0,Male,High School,Junior Sales Associate,2.0,minimal
+33.0,Female,Master's Degree,Senior Software Engineer,8.0,average
+28.0,Male,Bachelor's Degree,Junior Data Analyst,3.0,minimal
+30.0,Female,Bachelor's Degree,Junior Marketing Manager,4.0,minimal
+36.0,Male,PhD,Senior Research Scientist,11.0,above average
+27.0,Female,Bachelor's Degree,Junior Software Engineer,2.0,minimal
+34.0,Male,Master's Degree,Senior Data Scientist,9.0,average
+30.0,Female,Bachelor's Degree,Marketing Coordinator,4.0,minimal
+32.0,Male,Bachelor's Degree,Junior Marketing Manager,6.0,below average
+39.0,Female,PhD,Senior Research Scientist,13.0,above average
+26.0,Male,High School,Junior Sales Associate,2.0,minimal
+33.0,Female,Master's Degree,Senior Software Engineer,8.0,average
+28.0,Male,Bachelor's Degree,Junior Data Analyst,3.0,minimal
+30.0,Female,Bachelor's Degree,Junior Marketing Manager,4.0,minimal
+36.0,Male,PhD,Senior Research Scientist,11.0,above average
+27.0,Female,Bachelor's Degree,Junior Software Engineer,2.0,minimal
+34.0,Male,Master's Degree,Senior Data Scientist,9.0,average
+30.0,Female,Bachelor's Degree,Marketing Coordinator,4.0,minimal
+32.0,Male,Bachelor's Degree,Junior Marketing Manager,6.0,below average
+39.0,Female,PhD,Senior Research Scientist,13.0,above average
+26.0,Male,High School,Junior Sales Associate,2.0,minimal
+33.0,Female,Master's Degree,Senior Software Engineer,8.0,average
+28.0,Male,Bachelor's Degree,Junior Data Analyst,3.0,minimal
+30.0,Female,Bachelor's Degree,Junior Marketing Manager,4.0,minimal
+36.0,Male,PhD,Senior Research Scientist,11.0,above average
+27.0,Female,Bachelor's Degree,Junior Software Engineer,2.0,minimal
+34.0,Male,Master's Degree,Senior Data Scientist,9.0,average
+30.0,Female,Bachelor's Degree,Marketing Coordinator,4.0,minimal
+32.0,Male,Bachelor's Degree,Junior Marketing Manager,6.0,below average
+39.0,Female,PhD,Senior Research Scientist,13.0,above average
+26.0,Male,High School,Junior Sales Associate,2.0,minimal
+33.0,Female,Master's Degree,Senior Software Engineer,8.0,average
+28.0,Male,Bachelor's Degree,Junior Data Analyst,3.0,minimal
+30.0,Female,Bachelor's Degree,Junior Marketing Manager,4.0,minimal
+36.0,Male,PhD,Senior Research Scientist,11.0,above average
+27.0,Female,Bachelor's Degree,Junior Software Engineer,2.0,minimal
+34.0,Male,Master's Degree,Senior Data Scientist,9.0,average
+30.0,Female,Bachelor's Degree,Marketing Coordinator,4.0,minimal
+32.0,Male,Bachelor's Degree,Junior Marketing Manager,6.0,below average
+39.0,Female,PhD,Senior Research Scientist,13.0,above average
+26.0,Male,High School,Junior Sales Associate,2.0,minimal
+33.0,Female,Master's Degree,Senior Software Engineer,8.0,average
+28.0,Male,Bachelor's Degree,Junior Data Analyst,3.0,minimal
+30.0,Female,Bachelor's Degree,Junior Marketing Manager,4.0,minimal
+36.0,Male,PhD,Senior Research Scientist,11.0,above average
+27.0,Female,Bachelor's Degree,Junior Software Engineer,2.0,minimal
+34.0,Male,Master's Degree,Senior Data Scientist,9.0,average
+30.0,Female,Bachelor's Degree,Marketing Coordinator,4.0,minimal
+32.0,Male,Bachelor's Degree,Junior Marketing Manager,6.0,below average
+39.0,Female,PhD,Senior Research Scientist,13.0,above average
+26.0,Male,High School,Junior Sales Associate,2.0,minimal
+33.0,Female,Master's Degree,Senior Software Engineer,8.0,average
+28.0,Male,Bachelor's Degree,Junior Data Analyst,3.0,minimal
+30.0,Female,Bachelor's Degree,Junior Marketing Manager,4.0,minimal
+36.0,Male,PhD,Senior Research Scientist,11.0,above average
+27.0,Female,Bachelor's Degree,Junior Software Engineer,2.0,minimal
+34.0,Male,Master's Degree,Senior Data Scientist,9.0,average
+30.0,Female,Bachelor's Degree,Marketing Coordinator,4.0,minimal
+32.0,Male,Bachelor's Degree,Junior Marketing Manager,6.0,below average
+39.0,Female,PhD,Senior Research Scientist,13.0,above average
+26.0,Male,High School,Junior Sales Associate,2.0,minimal
+33.0,Female,Master's Degree,Senior Software Engineer,8.0,average
+28.0,Male,Bachelor's Degree,Junior Data Analyst,3.0,minimal
+30.0,Female,Bachelor's Degree,Junior Marketing Manager,4.0,minimal
+36.0,Male,PhD,Senior Research Scientist,11.0,above average
+27.0,Female,Bachelor's Degree,Junior Software Engineer,2.0,minimal
+34.0,Male,Master's Degree,Senior Data Scientist,9.0,average
+30.0,Female,Bachelor's Degree,Marketing Coordinator,4.0,minimal
+32.0,Male,Bachelor's Degree,Junior Marketing Manager,6.0,below average
+39.0,Female,PhD,Senior Research Scientist,13.0,above average
+26.0,Male,High School,Junior Sales Associate,2.0,minimal
+33.0,Female,Master's Degree,Senior Software Engineer,8.0,average
+28.0,Male,Bachelor's Degree,Junior Data Analyst,3.0,minimal
+30.0,Female,Bachelor's Degree,Junior Marketing Manager,4.0,minimal
+36.0,Male,PhD,Senior Research Scientist,11.0,above average
+27.0,Female,Bachelor's Degree,Junior Software Engineer,2.0,minimal
+34.0,Male,Master's Degree,Senior Data Scientist,9.0,average
+30.0,Female,Bachelor's Degree,Marketing Coordinator,4.0,minimal
+32.0,Male,Bachelor's Degree,Junior Marketing Manager,6.0,below average
+39.0,Female,PhD,Senior Research Scientist,13.0,above average
+26.0,Male,High School,Junior Sales Associate,2.0,minimal
+33.0,Female,Master's Degree,Senior Software Engineer,8.0,average
+28.0,Male,Bachelor's Degree,Junior Data Analyst,3.0,minimal
+30.0,Female,Bachelor's Degree,Junior Marketing Manager,4.0,minimal
+36.0,Male,PhD,Senior Research Scientist,11.0,above average
+27.0,Female,Bachelor's Degree,Junior Software Engineer,2.0,minimal
+34.0,Male,Master's Degree,Senior Data Scientist,9.0,average
+30.0,Female,Bachelor's Degree,Marketing Coordinator,4.0,minimal
+32.0,Male,Bachelor's Degree,Junior Marketing Manager,6.0,below average
+39.0,Female,PhD,Senior Research Scientist,13.0,above average
+26.0,Male,High School,Junior Sales Associate,2.0,minimal
+33.0,Female,Master's Degree,Senior Software Engineer,8.0,average
+28.0,Male,Bachelor's Degree,Junior Data Analyst,3.0,minimal
+30.0,Female,Bachelor's Degree,Junior Marketing Manager,4.0,minimal
+36.0,Male,PhD,Senior Research Scientist,11.0,above average
+27.0,Female,Bachelor's Degree,Junior Software Engineer,2.0,minimal
+34.0,Male,Master's Degree,Senior Data Scientist,9.0,average
+30.0,Female,Bachelor's Degree,Marketing Coordinator,4.0,minimal
+32.0,Male,Bachelor's Degree,Junior Marketing Manager,6.0,below average
+39.0,Female,PhD,Senior Research Scientist,13.0,above average
+26.0,Male,High School,Junior Sales Associate,2.0,minimal
+33.0,Female,Master's Degree,Senior Software Engineer,8.0,average
+28.0,Male,Bachelor's Degree,Junior Data Analyst,3.0,minimal
+30.0,Female,Bachelor's Degree,Junior Marketing Manager,4.0,minimal
+36.0,Male,PhD,Senior Research Scientist,11.0,above average
+27.0,Female,Bachelor's Degree,Junior Software Engineer,2.0,minimal
+34.0,Male,Master's Degree,Senior Data Scientist,9.0,average
+30.0,Female,Bachelor's Degree,Marketing Coordinator,4.0,minimal
+32.0,Male,Bachelor's Degree,Junior Marketing Manager,6.0,below average
+39.0,Female,PhD,Senior Research Scientist,13.0,above average
+26.0,Male,High School,Junior Sales Associate,2.0,minimal
+33.0,Female,Master's Degree,Senior Software Engineer,8.0,average
+28.0,Male,Bachelor's Degree,Junior Data Analyst,3.0,minimal
+30.0,Female,Bachelor's Degree,Junior Marketing Manager,4.0,minimal
+36.0,Male,PhD,Senior Research Scientist,11.0,above average
+27.0,Female,Bachelor's Degree,Junior Software Engineer,2.0,minimal
+26.0,Male,Bachelor's Degree,Senior Product Marketing Manager,5.0,below average
+28.0,Female,Master's Degree,Marketing Manager,7.0,average
+34.0,Male,PhD,Director of Marketing,12.0,high
+31.0,Male,Bachelor's Degree,Sales Director,9.0,above average
+24.0,Female,High School,Sales Associate,1.0,minimal
+29.0,Male,Bachelor's Degree,Digital Marketing Manager,6.0,average
+27.0,Female,Master's Degree,Content Marketing Manager,4.0,below average
+33.0,Male,PhD,Sales Director,10.0,above average
+21.0,Female,High School,Junior Sales Representative,0.0,minimal
+36.0,Male,Bachelor's Degree,Sales Manager,11.0,above average
+25.0,Female,Bachelor's Degree,Marketing Manager,3.0,below average
+30.0,Male,Master's Degree,Financial Manager,7.0,average
+28.0,Female,PhD,Director of Marketing,6.0,average
+26.0,Male,Bachelor's Degree,Senior Product Marketing Manager,5.0,below average
+28.0,Female,Master's Degree,Marketing Manager,7.0,average
+34.0,Male,PhD,Director of Marketing,12.0,high
+31.0,Male,Bachelor's Degree,Sales Director,9.0,above average
+24.0,Female,High School,Sales Associate,1.0,minimal
+29.0,Male,Bachelor's Degree,Digital Marketing Manager,6.0,average
+27.0,Female,Master's Degree,Content Marketing Manager,4.0,below average
+33.0,Male,PhD,Sales Director,10.0,above average
+21.0,Female,High School,Junior Sales Representative,0.0,minimal
+36.0,Male,Bachelor's Degree,Sales Manager,11.0,above average
+25.0,Female,Bachelor's Degree,Marketing Manager,3.0,below average
+30.0,Male,Master's Degree,Financial Manager,7.0,average
+28.0,Female,PhD,Director of Marketing,6.0,average
+26.0,Male,Bachelor's Degree,Senior Product Marketing Manager,5.0,below average
+28.0,Female,Master's Degree,Marketing Manager,7.0,average
+34.0,Male,PhD,Director of Marketing,12.0,high
+31.0,Male,Bachelor's Degree,Sales Director,9.0,above average
+24.0,Female,High School,Sales Associate,1.0,minimal
+29.0,Male,Bachelor's Degree,Digital Marketing Manager,6.0,average
+27.0,Female,Master's Degree,Content Marketing Manager,4.0,below average
+33.0,Male,PhD,Sales Director,10.0,above average
+21.0,Female,High School,Junior Sales Representative,0.0,minimal
+36.0,Male,Bachelor's Degree,Sales Manager,11.0,above average
+25.0,Female,Bachelor's Degree,Marketing Manager,3.0,below average
+30.0,Male,Master's Degree,Financial Manager,7.0,average
+28.0,Female,PhD,Director of Marketing,6.0,average
+26.0,Male,Bachelor's Degree,Senior Product Marketing Manager,5.0,below average
+28.0,Female,Master's Degree,Marketing Manager,7.0,average
+34.0,Male,PhD,Director of Marketing,12.0,high
+31.0,Male,Bachelor's Degree,Sales Director,9.0,above average
+24.0,Female,High School,Sales Associate,1.0,minimal
+29.0,Male,Bachelor's Degree,Digital Marketing Manager,6.0,average
+27.0,Female,Master's Degree,Content Marketing Manager,4.0,below average
+33.0,Male,PhD,Sales Director,10.0,above average
+21.0,Female,High School,Junior Sales Representative,0.0,minimal
+36.0,Male,Bachelor's Degree,Sales Manager,11.0,above average
+25.0,Female,Bachelor's Degree,Marketing Manager,3.0,below average
+30.0,Male,Master's Degree,Financial Manager,7.0,average
+28.0,Female,PhD,Director of Marketing,6.0,average
+26.0,Male,Bachelor's Degree,Senior Product Marketing Manager,5.0,below average
+28.0,Female,Master's Degree,Marketing Manager,7.0,average
+34.0,Male,PhD,Director of Marketing,12.0,high
+31.0,Male,Bachelor's Degree,Sales Director,9.0,above average
+24.0,Female,High School,Sales Associate,1.0,minimal
+29.0,Male,Bachelor's Degree,Digital Marketing Manager,6.0,average
+27.0,Female,Master's Degree,Content Marketing Manager,4.0,below average
+33.0,Male,PhD,Sales Director,10.0,above average
+21.0,Female,High School,Junior Sales Representative,0.0,minimal
+36.0,Male,Bachelor's Degree,Sales Manager,11.0,above average
+25.0,Female,Bachelor's Degree,Marketing Manager,3.0,below average
+30.0,Male,Master's Degree,Financial Manager,7.0,average
+28.0,Female,PhD,Director of Marketing,6.0,average
+26.0,Male,Bachelor's Degree,Senior Product Marketing Manager,5.0,below average
+28.0,Female,Master's Degree,Marketing Manager,7.0,average
+34.0,Male,PhD,Director of Marketing,12.0,high
+31.0,Male,Bachelor's Degree,Sales Director,9.0,above average
+24.0,Female,High School,Sales Associate,1.0,minimal
+29.0,Male,Bachelor's Degree,Digital Marketing Manager,6.0,average
+27.0,Female,Master's Degree,Content Marketing Manager,4.0,below average
+33.0,Male,PhD,Sales Director,10.0,above average
+21.0,Female,High School,Junior Sales Representative,0.0,minimal
+36.0,Male,Bachelor's Degree,Sales Manager,11.0,above average
+25.0,Female,Bachelor's Degree,Marketing Manager,3.0,below average
+30.0,Male,Master's Degree,Financial Manager,7.0,average
+28.0,Female,PhD,Director of Marketing,6.0,average
+26.0,Male,Bachelor's Degree,Senior Product Marketing Manager,5.0,below average
+28.0,Female,Master's Degree,Marketing Manager,7.0,average
+34.0,Male,PhD,Director of Marketing,12.0,high
+31.0,Male,Bachelor's Degree,Sales Director,9.0,above average
+24.0,Female,High School,Sales Associate,1.0,minimal
+29.0,Male,Bachelor's Degree,Digital Marketing Manager,6.0,average
+27.0,Female,Master's Degree,Content Marketing Manager,4.0,below average
+33.0,Male,PhD,Sales Director,10.0,above average
+21.0,Female,High School,Junior Sales Representative,0.0,minimal
+36.0,Male,Bachelor's Degree,Sales Manager,11.0,above average
+25.0,Female,Bachelor's Degree,Marketing Manager,3.0,below average
+30.0,Male,Master's Degree,Financial Manager,7.0,average
+28.0,Female,PhD,Director of Marketing,6.0,average
+26.0,Male,Bachelor's Degree,Senior Product Marketing Manager,5.0,below average
+28.0,Female,Master's Degree,Marketing Manager,7.0,average
+34.0,Male,PhD,Director of Marketing,12.0,high
+31.0,Male,Bachelor's Degree,Sales Director,9.0,above average
+24.0,Female,High School,Sales Associate,1.0,minimal
+29.0,Male,Bachelor's Degree,Digital Marketing Manager,6.0,average
+27.0,Female,Master's Degree,Content Marketing Manager,4.0,below average
+33.0,Male,PhD,Sales Director,10.0,above average
+21.0,Female,High School,Junior Sales Representative,0.0,minimal
+36.0,Male,Bachelor's Degree,Sales Manager,11.0,above average
+25.0,Female,Bachelor's Degree,Marketing Manager,3.0,below average
+30.0,Male,Master's Degree,Financial Manager,7.0,average
+28.0,Female,PhD,Director of Marketing,6.0,average
+26.0,Male,Bachelor's Degree,Senior Product Marketing Manager,5.0,below average
+28.0,Female,Master's Degree,Marketing Manager,7.0,average
+34.0,Male,PhD,Director of Marketing,12.0,high
+31.0,Male,Bachelor's Degree,Sales Director,9.0,above average
+24.0,Female,High School,Sales Associate,1.0,minimal
+29.0,Male,Bachelor's Degree,Digital Marketing Manager,6.0,average
+27.0,Female,Master's Degree,Content Marketing Manager,4.0,below average
+33.0,Male,PhD,Sales Director,10.0,above average
+21.0,Female,High School,Junior Sales Representative,0.0,minimal
+36.0,Male,Bachelor's Degree,Sales Manager,11.0,above average
+25.0,Female,Bachelor's Degree,Marketing Manager,3.0,below average
+30.0,Male,Master's Degree,Financial Manager,7.0,average
+28.0,Female,PhD,Director of Marketing,6.0,average
+26.0,Male,Bachelor's Degree,Senior Product Marketing Manager,5.0,below average
+28.0,Female,Master's Degree,Marketing Manager,7.0,average
+34.0,Male,PhD,Director of Marketing,12.0,high
+31.0,Male,Bachelor's Degree,Sales Director,9.0,above average
+24.0,Female,High School,Sales Associate,1.0,minimal
+29.0,Male,Bachelor's Degree,Digital Marketing Manager,6.0,average
+27.0,Female,Master's Degree,Content Marketing Manager,4.0,below average
+22.0,Female,High School,Sales Associate,0.0,minimal
+45.0,Male,Bachelor's Degree,Financial Manager,21.0,high
+31.0,Female,Master's Degree,Content Marketing Manager,8.0,average
+28.0,Male,Bachelor's Degree,Digital Marketing Manager,4.0,below average
+29.0,Male,Bachelor's Degree,Senior Product Marketing Manager,6.0,average
+35.0,Female,PhD,Director of Marketing,12.0,high
+27.0,Male,High School,Sales Representative,3.0,minimal
+33.0,Female,Bachelor's Degree,Marketing Manager,9.0,above average
+30.0,Male,Master's Degree,Financial Manager,7.0,average
+25.0,Female,Bachelor's Degree,Marketing Manager,2.0,minimal
+26.0,Male,Bachelor's Degree,Senior Product Marketing Manager,5.0,below average
+29.0,Female,Master's Degree,Content Marketing Manager,4.0,below average
+34.0,Male,PhD,Director of Marketing,12.0,high
+31.0,Male,Bachelor's Degree,Sales Director,9.0,above average
+24.0,Female,High School,Sales Associate,1.0,minimal
+29.0,Male,Bachelor's Degree,Digital Marketing Manager,6.0,average
+27.0,Female,Master's Degree,Content Marketing Manager,4.0,below average
+33.0,Male,PhD,Sales Director,10.0,above average
+21.0,Female,High School,Junior Sales Representative,0.0,minimal
+36.0,Male,Bachelor's Degree,Sales Manager,11.0,above average
+25.0,Female,Bachelor's Degree,Marketing Manager,3.0,below average
+30.0,Male,Master's Degree,Financial Manager,7.0,average
+28.0,Female,PhD,Director of Marketing,6.0,average
+26.0,Male,Bachelor's Degree,Senior Product Marketing Manager,5.0,below average
+28.0,Female,Master's Degree,Marketing Manager,7.0,average
+34.0,Male,PhD,Director of Marketing,12.0,high
+31.0,Male,Bachelor's Degree,Sales Director,9.0,above average
+24.0,Female,High School,Sales Associate,1.0,minimal
+29.0,Male,Bachelor's Degree,Digital Marketing Manager,6.0,average
+27.0,Female,Master's Degree,Content Marketing Manager,4.0,below average
+33.0,Male,PhD,Sales Director,10.0,above average
+21.0,Female,High School,Junior Sales Representative,0.0,minimal
+36.0,Male,Bachelor's Degree,Sales Manager,11.0,above average
+25.0,Female,Bachelor's Degree,Marketing Manager,3.0,below average
+30.0,Male,Master's Degree,Financial Manager,7.0,average
+28.0,Female,PhD,Director of Marketing,6.0,average
+26.0,Male,Bachelor's Degree,Senior Product Marketing Manager,5.0,below average
+28.0,Female,Master's Degree,Marketing Manager,7.0,average
+34.0,Male,PhD,Director of Marketing,12.0,high
+31.0,Male,Bachelor's Degree,Sales Director,9.0,above average
+24.0,Female,High School,Sales Associate,1.0,minimal
+29.0,Male,Bachelor's Degree,Digital Marketing Manager,6.0,average
+27.0,Female,Master's Degree,Content Marketing Manager,4.0,below average
+33.0,Male,PhD,Sales Director,10.0,above average
+21.0,Female,High School,Junior Sales Representative,0.0,minimal
+36.0,Male,Bachelor's Degree,Sales Manager,11.0,above average
+25.0,Female,Bachelor's Degree,Marketing Manager,3.0,below average
+30.0,Male,Master's Degree,Financial Manager,7.0,average
+28.0,Female,PhD,Director of Marketing,6.0,average
+26.0,Male,Bachelor's Degree,Senior Product Marketing Manager,5.0,below average
+28.0,Female,Master's Degree,Marketing Manager,7.0,average
+34.0,Male,PhD,Director of Marketing,12.0,high
+31.0,Male,Bachelor's Degree,Sales Director,9.0,above average
+24.0,Female,High School,Sales Associate,1.0,minimal
+29.0,Male,Bachelor's Degree,Digital Marketing Manager,6.0,average
+27.0,Female,Master's Degree,Content Marketing Manager,4.0,below average
+33.0,Male,PhD,Sales Director,10.0,above average
+21.0,Female,High School,Junior Sales Representative,0.0,minimal
+36.0,Male,Bachelor's Degree,Sales Manager,11.0,above average
+25.0,Female,Bachelor's Degree,Marketing Manager,3.0,below average
+30.0,Male,Master's Degree,Financial Manager,7.0,average
+28.0,Female,PhD,Director of Marketing,6.0,average
+26.0,Male,Bachelor's Degree,Senior Product Marketing Manager,5.0,below average
+28.0,Female,Master's Degree,Marketing Manager,7.0,average
+34.0,Male,PhD,Director of Marketing,12.0,high
+31.0,Male,Bachelor's Degree,Sales Director,9.0,above average
+24.0,Female,High School,Sales Associate,1.0,minimal
+29.0,Male,Bachelor's Degree,Digital Marketing Manager,6.0,average
+27.0,Female,Master's Degree,Content Marketing Manager,4.0,below average
+33.0,Male,PhD,Sales Director,10.0,above average
+21.0,Female,High School,Junior Sales Representative,0.0,minimal
+36.0,Male,Bachelor's Degree,Sales Manager,11.0,above average
+25.0,Female,Bachelor's Degree,Marketing Manager,3.0,below average
+30.0,Male,Master's Degree,Financial Manager,7.0,average
+28.0,Female,PhD,Director of Marketing,6.0,average
+26.0,Male,Bachelor's Degree,Senior Product Marketing Manager,5.0,below average
+28.0,Female,Master's Degree,Marketing Manager,7.0,average
+34.0,Male,PhD,Director of Marketing,12.0,high
+31.0,Male,Bachelor's Degree,Sales Director,9.0,above average
+24.0,Female,High School,Sales Associate,1.0,minimal
+29.0,Male,Bachelor's Degree,Digital Marketing Manager,6.0,average
+27.0,Female,Master's Degree,Content Marketing Manager,4.0,below average
+33.0,Male,PhD,Sales Director,10.0,above average
+21.0,Female,High School,Junior Sales Representative,0.0,minimal
+36.0,Male,Bachelor's Degree,Sales Manager,11.0,above average
+25.0,Female,Bachelor's Degree,Marketing Manager,3.0,below average
+30.0,Male,Master's Degree,Financial Manager,7.0,average
+28.0,Female,PhD,Director of Marketing,6.0,average
+26.0,Male,Bachelor's Degree,Senior Product Marketing Manager,5.0,below average
+28.0,Female,Master's Degree,Marketing Manager,7.0,average
+34.0,Male,PhD,Director of Marketing,12.0,high
+31.0,Male,Bachelor's Degree,Sales Director,9.0,above average
+24.0,Female,High School,Sales Associate,1.0,minimal
+29.0,Male,Bachelor's Degree,Digital Marketing Manager,6.0,average
+27.0,Female,Master's Degree,Content Marketing Manager,4.0,below average
+33.0,Male,PhD,Sales Director,10.0,above average
+21.0,Female,High School,Junior Sales Representative,0.0,minimal
+36.0,Male,Bachelor's Degree,Sales Manager,11.0,above average
+25.0,Female,Bachelor's Degree,Marketing Manager,3.0,below average
+30.0,Male,Master's Degree,Financial Manager,7.0,average
+28.0,Female,PhD,Director of Marketing,6.0,average
+26.0,Male,Bachelor's Degree,Senior Product Marketing Manager,5.0,below average
+28.0,Female,Master's Degree,Marketing Manager,7.0,average
+34.0,Male,PhD,Director of Marketing,12.0,high
+31.0,Male,Bachelor's Degree,Sales Director,9.0,above average
+24.0,Female,High School,Sales Associate,1.0,minimal
+29.0,Male,Bachelor's Degree,Digital Marketing Manager,6.0,average
+27.0,Female,Master's Degree,Content Marketing Manager,4.0,below average
+33.0,Male,PhD,Sales Director,10.0,above average
+21.0,Female,High School,Junior Sales Representative,0.0,minimal
+36.0,Male,Bachelor's Degree,Sales Manager,11.0,above average
+25.0,Female,Bachelor's Degree,Marketing Manager,3.0,below average
+30.0,Male,Master's Degree,Financial Manager,7.0,average
+28.0,Female,PhD,Director of Marketing,6.0,average
+26.0,Male,Bachelor's Degree,Senior Product Marketing Manager,5.0,below average
+28.0,Female,Master's Degree,Marketing Manager,7.0,average
+34.0,Male,PhD,Director of Marketing,12.0,high
+31.0,Male,Bachelor's Degree,Sales Director,9.0,above average
+24.0,Female,High School,Sales Associate,1.0,minimal
+29.0,Male,Bachelor's Degree,Digital Marketing Manager,6.0,average
+27.0,Female,Master's Degree,Content Marketing Manager,4.0,below average
+33.0,Male,PhD,Sales Director,10.0,above average
+21.0,Female,High School,Junior Sales Representative,0.0,minimal
+36.0,Male,Bachelor's Degree,Sales Manager,11.0,above average
+23.0,Male,Bachelor's Degree,Software Engineer,1.0,below average
+39.0,Female,Master's Degree,Marketing Manager,12.0,above average
+28.0,Male,Bachelor's Degree,Financial Analyst,4.0,below average
+31.0,Female,PhD,Research Scientist,8.0,average
+35.0,Male,Bachelor's Degree,Project Manager,10.0,above average
+27.0,Female,Bachelor's Degree,Graphic Designer,2.0,minimal
+42.0,Male,Master's Degree,Senior Software Engineer,18.0,high
+29.0,Female,Bachelor's Degree,Digital Marketing Specialist,3.0,below average
+33.0,Male,Bachelor's Degree,Marketing Manager,7.0,average
+24.0,Female,High School,Sales Associate,0.0,minimal
+30.0,Male,Master's Degree,Financial Analyst,6.0,average
+26.0,Female,Bachelor's Degree,Social Media Manager,3.0,minimal
+32.0,Male,PhD,Data Scientist,9.0,above average
+22.0,Female,High School,Receptionist,0.0,minimal
+37.0,Male,Bachelor's Degree,Product Manager,12.0,above average
+38.0,Female,Master's Degree,Marketing Director,14.0,high
+25.0,Male,Bachelor's Degree,Junior Software Engineer,1.0,minimal
+29.0,Female,Bachelor's Degree,Marketing Coordinator,4.0,below average
+27.0,Male,Bachelor's Degree,Product Designer,3.0,below average
+34.0,Female,PhD,Research Director,10.0,above average
+26.0,Male,Bachelor's Degree,Marketing Analyst,2.0,minimal
+31.0,Female,Master's Degree,Financial Manager,7.0,average
+25.0,Male,Bachelor's Degree,Junior Software Engineer,1.0,minimal
+29.0,Female,Bachelor's Degree,Marketing Coordinator,4.0,below average
+27.0,Male,Bachelor's Degree,Product Designer,3.0,below average
+34.0,Female,PhD,Research Director,10.0,above average
+26.0,Male,Bachelor's Degree,Marketing Analyst,2.0,minimal
+31.0,Female,Master's Degree,Financial Manager,7.0,average
+23.0,Male,Bachelor's Degree,Software Engineer,1.0,below average
+39.0,Female,Master's Degree,Marketing Manager,12.0,above average
+28.0,Male,Bachelor's Degree,Financial Analyst,4.0,below average
+31.0,Female,PhD,Research Scientist,8.0,average
+35.0,Male,Bachelor's Degree,Project Manager,10.0,above average
+27.0,Female,Bachelor's Degree,Graphic Designer,2.0,minimal
+42.0,Male,Master's Degree,Senior Software Engineer,18.0,high
+29.0,Female,Bachelor's Degree,Digital Marketing Specialist,3.0,below average
+33.0,Male,Bachelor's Degree,Marketing Manager,7.0,average
+24.0,Female,High School,Sales Associate,0.0,minimal
+30.0,Male,Master's Degree,Financial Analyst,6.0,average
+26.0,Female,Bachelor's Degree,Social Media Manager,3.0,minimal
+32.0,Male,PhD,Data Scientist,9.0,above average
+22.0,Female,High School,Receptionist,0.0,minimal
+37.0,Male,Bachelor's Degree,Product Manager,12.0,above average
+38.0,Female,Master's Degree,Marketing Director,14.0,high
+25.0,Male,Bachelor's Degree,Junior Software Engineer,1.0,minimal
+29.0,Female,Bachelor's Degree,Marketing Coordinator,4.0,below average
+27.0,Male,Bachelor's Degree,Product Designer,3.0,below average
+34.0,Female,PhD,Research Director,10.0,above average
+26.0,Male,Bachelor's Degree,Marketing Analyst,2.0,minimal
+31.0,Female,Master's Degree,Financial Manager,7.0,average
+25.0,Male,Bachelor's Degree,Junior Software Engineer,1.0,minimal
+29.0,Female,Bachelor's Degree,Marketing Coordinator,4.0,below average
+27.0,Male,Bachelor's Degree,Product Designer,3.0,below average
+34.0,Female,PhD,Research Director,10.0,above average
+26.0,Male,Bachelor's Degree,Marketing Analyst,2.0,minimal
+31.0,Female,Master's Degree,Financial Manager,7.0,average
+23.0,Male,Bachelor's Degree,Software Engineer,1.0,below average
+39.0,Female,Master's Degree,Marketing Manager,12.0,above average
+28.0,Male,Bachelor's Degree,Financial Analyst,4.0,below average
+31.0,Female,PhD,Research Scientist,8.0,average
+35.0,Male,Bachelor's Degree,Project Manager,10.0,above average
+27.0,Female,Bachelor's Degree,Graphic Designer,2.0,minimal
+42.0,Male,Master's Degree,Senior Software Engineer,18.0,high
+29.0,Female,Bachelor's Degree,Digital Marketing Specialist,3.0,below average
+33.0,Male,Bachelor's Degree,Marketing Manager,7.0,average
+24.0,Female,High School,Sales Associate,0.0,minimal
+30.0,Male,Master's Degree,Financial Analyst,6.0,average
+26.0,Female,Bachelor's Degree,Social Media Manager,3.0,minimal
+32.0,Male,PhD,Data Scientist,9.0,above average
+22.0,Female,High School,Receptionist,0.0,minimal
+37.0,Male,Bachelor's Degree,Product Manager,12.0,above average
+38.0,Female,Master's Degree,Marketing Director,14.0,high
+25.0,Male,Bachelor's Degree,Junior Software Engineer,1.0,minimal
+29.0,Female,Bachelor's Degree,Marketing Coordinator,4.0,below average
+27.0,Male,Bachelor's Degree,Product Designer,3.0,below average
+34.0,Female,PhD,Research Director,10.0,above average
+26.0,Male,Bachelor's Degree,Marketing Analyst,2.0,minimal
+31.0,Female,Master's Degree,Financial Manager,7.0,average
+25.0,Male,Bachelor's Degree,Junior Software Engineer,1.0,minimal
+29.0,Female,Bachelor's Degree,Marketing Coordinator,4.0,below average
+27.0,Male,Bachelor's Degree,Product Designer,3.0,below average
+34.0,Female,PhD,Research Director,10.0,above average
+26.0,Male,Bachelor's Degree,Marketing Analyst,2.0,minimal
+31.0,Female,Master's Degree,Financial Manager,7.0,average
+23.0,Male,Bachelor's Degree,Software Engineer,1.0,below average
+39.0,Female,Master's Degree,Marketing Manager,12.0,above average
+28.0,Male,Bachelor's Degree,Financial Analyst,4.0,below average
+31.0,Female,PhD,Research Scientist,8.0,average
+35.0,Male,Bachelor's Degree,Project Manager,10.0,above average
+27.0,Female,Bachelor's Degree,Graphic Designer,2.0,minimal
+42.0,Male,Master's Degree,Senior Software Engineer,18.0,high
+29.0,Female,Bachelor's Degree,Digital Marketing Specialist,3.0,below average
+33.0,Male,Bachelor's Degree,Marketing Manager,7.0,average
+24.0,Female,High School,Sales Associate,0.0,minimal
+30.0,Male,Master's Degree,Financial Analyst,6.0,average
+26.0,Female,Bachelor's Degree,Social Media Manager,3.0,minimal
+32.0,Male,PhD,Data Scientist,9.0,above average
+22.0,Female,High School,Receptionist,0.0,minimal
+37.0,Male,Bachelor's Degree,Product Manager,12.0,above average
+38.0,Female,Master's Degree,Marketing Director,14.0,high
+25.0,Male,Bachelor's Degree,Junior Software Engineer,1.0,minimal
+29.0,Female,Bachelor's Degree,Marketing Coordinator,4.0,below average
+27.0,Male,Bachelor's Degree,Product Designer,3.0,below average
+34.0,Female,PhD,Research Director,10.0,above average
+26.0,Male,Bachelor's Degree,Marketing Analyst,2.0,minimal
+31.0,Female,Master's Degree,Financial Manager,7.0,average
+25.0,Male,Bachelor's Degree,Junior Software Engineer,1.0,minimal
+29.0,Female,Bachelor's Degree,Marketing Coordinator,4.0,below average
+27.0,Male,Bachelor's Degree,Product Designer,3.0,below average
+34.0,Female,PhD,Research Director,10.0,above average
+26.0,Male,Bachelor's Degree,Marketing Analyst,2.0,minimal
+31.0,Female,Master's Degree,Financial Manager,7.0,average
+23.0,Male,Bachelor's Degree,Software Engineer,1.0,below average
+39.0,Female,Master's Degree,Marketing Manager,12.0,above average
+28.0,Male,Bachelor's Degree,Financial Analyst,4.0,below average
+31.0,Female,PhD,Research Scientist,8.0,average
+35.0,Male,Bachelor's Degree,Project Manager,10.0,above average
+27.0,Female,Bachelor's Degree,Graphic Designer,2.0,minimal
+42.0,Male,Master's Degree,Senior Software Engineer,18.0,high
+29.0,Female,Bachelor's Degree,Digital Marketing Specialist,3.0,below average
+33.0,Male,Bachelor's Degree,Marketing Manager,7.0,average
+24.0,Female,High School,Sales Associate,0.0,minimal
+30.0,Male,Master's Degree,Financial Analyst,6.0,average
+26.0,Female,Bachelor's Degree,Social M,,average
+28.0,Male,Bachelor's Degree,Software Engineer,3.0,below average
+36.0,Female,Master's Degree,Marketing Director,11.0,above average
+25.0,Male,Bachelor's Degree,Financial Analyst,1.0,minimal
+29.0,Female,PhD,Data Scientist,5.0,average
+33.0,Male,Bachelor's Degree,Project Manager,8.0,average
+27.0,Female,Bachelor's Degree,Graphic Designer,2.0,minimal
+43.0,Male,Master's Degree,Senior Software Engineer,19.0,high
+30.0,Female,Bachelor's Degree,Digital Marketing Specialist,4.0,below average
+34.0,Male,Bachelor's Degree,Marketing Manager,9.0,above average
+25.0,Female,High School,Sales Associate,0.0,minimal
+31.0,Male,Master's Degree,Financial Analyst,6.0,average
+27.0,Female,Bachelor's Degree,Social Media Manager,3.0,minimal
+33.0,Male,PhD,Research Scientist,10.0,above average
+23.0,Female,High School,Receptionist,0.0,minimal
+38.0,Male,Bachelor's Degree,Product Manager,13.0,above average
+39.0,Female,Master's Degree,Marketing Manager,14.0,high
+26.0,Male,Bachelor's Degree,Junior Software Engineer,1.0,minimal
+30.0,Female,Bachelor's Degree,Marketing Coordinator,4.0,below average
+28.0,Male,Bachelor's Degree,Product Designer,3.0,below average
+35.0,Female,PhD,Research Director,11.0,above average
+27.0,Male,Bachelor's Degree,Marketing Analyst,2.0,minimal
+32.0,Female,Master's Degree,Financial Manager,8.0,average
+26.0,Male,Bachelor's Degree,Junior Software Engineer,1.0,minimal
+30.0,Female,Bachelor's Degree,Marketing Coordinator,4.0,below average
+28.0,Male,Bachelor's Degree,Product Designer,3.0,below average
+35.0,Female,PhD,Research Director,11.0,above average
+27.0,Male,Bachelor's Degree,Marketing Analyst,2.0,minimal
+32.0,Female,Master's Degree,Financial Manager,8.0,average
+28.0,Male,Bachelor's Degree,Software Engineer,3.0,below average
+36.0,Female,Master's Degree,Marketing Director,11.0,above average
+25.0,Male,Bachelor's Degree,Financial Analyst,1.0,minimal
+29.0,Female,PhD,Data Scientist,5.0,average
+33.0,Male,Bachelor's Degree,Project Manager,8.0,average
+27.0,Female,Bachelor's Degree,Graphic Designer,2.0,minimal
+43.0,Male,Master's Degree,Senior Software Engineer,19.0,high
+30.0,Female,Bachelor's Degree,Digital Marketing Specialist,4.0,below average
+34.0,Male,Bachelor's Degree,Marketing Manager,9.0,above average
+25.0,Female,High School,Sales Associate,0.0,minimal
+31.0,Male,Master's Degree,Financial Analyst,6.0,average
+27.0,Female,Bachelor's Degree,Social Media Manager,3.0,minimal
+33.0,Male,PhD,Research Scientist,10.0,above average
+23.0,Female,High School,Receptionist,0.0,minimal
+38.0,Male,Bachelor's Degree,Product Manager,13.0,above average
+39.0,Female,Master's Degree,Marketing Manager,14.0,high
+26.0,Male,Bachelor's Degree,Junior Software Engineer,1.0,minimal
+30.0,Female,Bachelor's Degree,Marketing Coordinator,4.0,below average
+28.0,Male,Bachelor's Degree,Product Designer,3.0,below average
+35.0,Female,PhD,Research Director,11.0,above average
+27.0,Male,Bachelor's Degree,Marketing Analyst,2.0,minimal
+32.0,Female,Master's Degree,Financial Manager,8.0,average
+26.0,Male,Bachelor's Degree,Junior Software Engineer,1.0,minimal
+30.0,Female,Bachelor's Degree,Marketing Coordinator,4.0,below average
+28.0,Male,Bachelor's Degree,Product Designer,3.0,below average
+35.0,Female,PhD,Research Director,11.0,above average
+27.0,Male,Bachelor's Degree,Marketing Analyst,2.0,minimal
+32.0,Female,Master's Degree,Financial Manager,8.0,average
+28.0,Male,Bachelor's Degree,Software Engineer,3.0,below average
+36.0,Female,Master's Degree,Marketing Director,11.0,above average
+25.0,Male,Bachelor's Degree,Financial Analyst,1.0,minimal
+29.0,Female,PhD,Data Scientist,5.0,average
+33.0,Male,Bachelor's Degree,Project Manager,8.0,average
+27.0,Female,Bachelor's Degree,Graphic Designer,2.0,minimal
+43.0,Male,Master's Degree,Senior Software Engineer,19.0,high
+30.0,Female,Bachelor's Degree,Digital Marketing Specialist,4.0,below average
+34.0,Male,Bachelor's Degree,Marketing Manager,9.0,above average
+25.0,Female,High School,Sales Associate,0.0,minimal
+31.0,Male,Master's Degree,Financial Analyst,6.0,average
+27.0,Female,Bachelor's Degree,Social Media Manager,3.0,minimal
+33.0,Male,PhD,Research Scientist,10.0,above average
+23.0,Female,High School,Receptionist,0.0,minimal
+38.0,Male,Bachelor's Degree,Product Manager,13.0,above average
+39.0,Female,Master's Degree,Marketing Manager,14.0,high
+26.0,Male,Bachelor's Degree,Junior Software Engineer,1.0,minimal
+30.0,Female,Bachelor's Degree,Marketing Coordinator,4.0,below average
+28.0,Male,Bachelor's Degree,Product Designer,3.0,below average
+35.0,Female,PhD,Research Director,11.0,above average
+27.0,Male,Bachelor's Degree,Marketing Analyst,2.0,minimal
+32.0,Female,Master's Degree,Financial Manager,8.0,average
+26.0,Male,Bachelor's Degree,Junior Software Engineer,1.0,minimal
+30.0,Female,Bachelor's Degree,Marketing Coordinator,4.0,below average
+28.0,Male,Bachelor's Degree,Product Designer,3.0,below average
+35.0,Female,PhD,Research Director,11.0,above average
+27.0,Male,Bachelor's Degree,Marketing Analyst,2.0,minimal
+32.0,Female,Master's Degree,Financial Manager,8.0,average
+28.0,Male,Bachelor's Degree,Software Engineer,3.0,below average
+36.0,Female,Master's Degree,Marketing Director,11.0,above average
+25.0,Male,Bachelor's Degree,Financial Analyst,1.0,minimal
+29.0,Female,PhD,Data Scientist,5.0,average
+33.0,Male,Bachelor's Degree,Project Manager,8.0,average
+27.0,Female,Bachelor's Degree,Graphic Designer,2.0,minimal
+43.0,Male,Master's Degree,Senior Software Engineer,19.0,high
+30.0,Female,Bachelor's Degree,Digital Marketing Specialist,4.0,below average
+34.0,Male,Bachelor's Degree,Marketing Manager,9.0,above average
+25.0,Female,High School,Sales Associate,0.0,minimal
+31.0,Male,Master's Degree,Financial Analyst,6.0,average
+27.0,Female,Bachelor's Degree,Social Media Manager,3.0,minimal
+33.0,Male,PhD,Research Scientist,10.0,above average
+23.0,Female,High School,Receptionist,0.0,minimal
+38.0,Male,Bachelor's Degree,Product Manager,13.0,above average
+39.0,Female,Master's Degree,Marketing Manager,14.0,high
+26.0,Male,Bachelor's Degree,Junior Software Engineer,1.0,minimal
+30.0,Female,Bachelor's Degree,Marketing Coordinator,4.0,below average
+28.0,Male,Bachelor's Degree,Product Designer,3.0,below average
+35.0,Female,PhD,Research Director,11.0,above average
+27.0,Male,Bachelor's Degree,Marketing Analyst,2.0,minimal
+32.0,Female,Master's Degree,Financial Manager,8.0,average
+26.0,Male,Bachelor's Degree,Junior Software Engineer,1.0,minimal
+30.0,Female,Bachelor's Degree,Marketing Coordinator,4.0,below average
+28.0,Male,Bachelor's Degree,Product Designer,3.0,below average
+35.0,Female,PhD,Research Director,11.0,above average
+27.0,Male,Bachelor's Degree,Marketing Analyst,2.0,minimal
+32.0,Female,Master's Degree,Financial Manager,8.0,average
+28.0,Male,Bachelor's Degree,Software Engineer,3.0,below average
+36.0,Female,Master's Degree,Marketing Director,11.0,above average
+25.0,Male,Bachelor's Degree,Financial Analyst,1.0,minimal
+29.0,Female,PhD,Data Scientist,5.0,average
+33.0,Male,Bachelor's Degree,Project Manager,8.0,average
+27.0,Female,Bachelor's Degree,Graphic Designer,2.0,minimal
+43.0,Male,Master's Degree,Senior Software Engineer,19.0,high
+30.0,Female,Bachelor's Degree,Digital Marketing Specialist,4.0,below average
+34.0,Male,Bachelor's Degree,Marketing Manager,9.0,above average
+25.0,Female,High School,Sales Associate,0.0,minimal
+31.0,Male,Master's Degree,Financial Analyst,6.0,average
+27.0,Female,Bachelor's Degree,Social Media Manager,3.0,minimal
+33.0,Male,PhD,Research Scientist,10.0,above average
+27.0,Male,Bachelor's Degree,Software Engineer,3.0,below average
+35.0,Female,Master's Degree,Marketing Director,11.0,above average
+24.0,Male,Bachelor's Degree,Financial Analyst,1.0,minimal
+28.0,Female,PhD,Data Scientist,5.0,average
+32.0,Male,Bachelor's Degree,Project Manager,8.0,average
+26.0,Female,Bachelor's Degree,Graphic Designer,2.0,minimal
+41.0,Male,Master's Degree,Senior Software Engineer,19.0,high
+29.0,Female,Bachelor's Degree,Digital Marketing Specialist,4.0,below average
+33.0,Male,Bachelor's Degree,Marketing Manager,9.0,above average
+24.0,Female,High School,Sales Associate,0.0,minimal
+30.0,Male,Master's Degree,Financial Analyst,6.0,average
+26.0,Female,Bachelor's Degree,Social Media Manager,3.0,minimal
+32.0,Male,PhD,Research Scientist,10.0,above average
+22.0,Female,High School,Receptionist,0.0,minimal
+37.0,Male,Bachelor's Degree,Product Manager,13.0,above average
+38.0,Female,Master's Degree,Marketing Manager,14.0,high
+27.0,Male,Bachelor's Degree,Junior Software Engineer,1.0,minimal
+31.0,Female,Bachelor's Degree,Marketing Coordinator,4.0,below average
+29.0,Male,Bachelor's Degree,Product Designer,3.0,below average
+34.0,Female,PhD,Research Director,11.0,above average
+26.0,Male,Bachelor's Degree,Marketing Analyst,2.0,minimal
+31.0,Female,Master's Degree,Financial Manager,8.0,average
+27.0,Male,Bachelor's Degree,Junior Software Engineer,1.0,minimal
+31.0,Female,Bachelor's Degree,Marketing Coordinator,4.0,below average
+29.0,Male,Bachelor's Degree,Product Designer,3.0,below average
+34.0,Female,PhD,Research Director,11.0,above average
+26.0,Male,Bachelor's Degree,Marketing Analyst,2.0,minimal
+31.0,Female,Master's Degree,Financial Manager,8.0,average
+27.0,Male,Bachelor's Degree,Software Engineer,3.0,below average
+35.0,Female,Master's Degree,Marketing Director,11.0,above average
+24.0,Male,Bachelor's Degree,Financial Analyst,1.0,minimal
+28.0,Female,PhD,Data Scientist,5.0,average
+32.0,Male,Bachelor's Degree,Project Manager,8.0,average
+26.0,Female,Bachelor's Degree,Graphic Designer,2.0,minimal
+41.0,Male,Master's Degree,Senior Software Engineer,19.0,high
+29.0,Female,Bachelor's Degree,Digital Marketing Specialist,4.0,below average
+33.0,Male,Bachelor's Degree,Marketing Manager,9.0,above average
+24.0,Female,High School,Sales Associate,0.0,minimal
+30.0,Male,Master's Degree,Financial Analyst,6.0,average
+26.0,Female,Bachelor's Degree,Social Media Manager,3.0,minimal
+32.0,Male,PhD,Research Scientist,10.0,above average
+22.0,Female,High School,Receptionist,0.0,minimal
+37.0,Male,Bachelor's Degree,Product Manager,13.0,above average
+38.0,Female,Master's Degree,Marketing Manager,14.0,high
+27.0,Male,Bachelor's Degree,Junior Software Engineer,1.0,minimal
+31.0,Female,Bachelor's Degree,Marketing Coordinator,4.0,below average
+29.0,Male,Bachelor's Degree,Product Designer,3.0,below average
+34.0,Female,PhD,Research Director,11.0,above average
+26.0,Male,Bachelor's Degree,Marketing Analyst,2.0,minimal
+31.0,Female,Master's Degree,Financial Manager,8.0,average
+27.0,Male,Bachelor's Degree,Junior Software Engineer,1.0,minimal
+31.0,Female,Bachelor's Degree,Marketing Coordinator,4.0,below average
+29.0,Male,Bachelor's Degree,Product Designer,3.0,below average
+34.0,Female,PhD,Research Director,11.0,above average
+26.0,Male,Bachelor's Degree,Marketing Analyst,2.0,minimal
+31.0,Female,Master's Degree,Financial Manager,8.0,average
+27.0,Male,Bachelor's Degree,Software Engineer,3.0,below average
+35.0,Female,Master's Degree,Marketing Director,11.0,above average
+24.0,Male,Bachelor's Degree,Financial Analyst,1.0,minimal
+28.0,Female,PhD,Data Scientist,5.0,average
+32.0,Male,Bachelor's Degree,Project Manager,8.0,average
+26.0,Female,Bachelor's Degree,Graphic Designer,2.0,minimal
+41.0,Male,Master's Degree,Senior Software Engineer,19.0,high
+29.0,Female,Bachelor's Degree,Digital Marketing Specialist,4.0,below average
+33.0,Male,Bachelor's Degree,Marketing Manager,9.0,above average
+24.0,Female,High School,Sales Associate,0.0,minimal
+30.0,Male,Master's Degree,Financial Analyst,6.0,average
+26.0,Female,Bachelor's Degree,Social Media Manager,3.0,minimal
+32.0,Male,PhD,Research Scientist,10.0,above average
+22.0,Female,High School,Receptionist,0.0,minimal
+37.0,Male,Bachelor's Degree,Product Manager,13.0,above average
+38.0,Female,Master's Degree,Marketing Manager,14.0,high
+27.0,Male,Bachelor's Degree,Junior Software Engineer,1.0,minimal
+31.0,Female,Bachelor's Degree,Marketing Coordinator,4.0,below average
+29.0,Male,Bachelor's Degree,Product Designer,3.0,below average
+34.0,Female,PhD,Research Director,11.0,above average
+26.0,Male,Bachelor's Degree,Marketing Analyst,2.0,minimal
+31.0,Female,Master's Degree,Financial Manager,8.0,average
+27.0,Male,Bachelor's Degree,Junior Software Engineer,1.0,minimal
+31.0,Female,Bachelor's Degree,Marketing Coordinator,4.0,below average
+29.0,Male,Bachelor's Degree,Product Designer,3.0,below average
+34.0,Female,PhD,Research Director,11.0,above average
+26.0,Male,Bachelor's Degree,Marketing Analyst,2.0,minimal
+31.0,Female,Master's Degree,Financial Manager,8.0,average
+27.0,Male,Bachelor's Degree,Software Engineer,3.0,below average
+35.0,Female,Master's Degree,Marketing Director,11.0,above average
+24.0,Male,Bachelor's Degree,Financial Analyst,1.0,minimal
+28.0,Female,PhD,Data Scientist,5.0,average
+32.0,Male,Bachelor's Degree,Project Manager,8.0,average
+26.0,Female,Bachelor's Degree,Graphic Designer,2.0,minimal
+41.0,Male,Master's Degree,Senior Software Engineer,19.0,high
+29.0,Female,Bachelor's Degree,Digital Marketing Specialist,4.0,below average
+33.0,Male,Bachelor's Degree,Marketing Manager,9.0,above average
+24.0,Female,High School,Sales Associate,0.0,minimal
+30.0,Male,Master's Degree,Financial Analyst,6.0,average
+26.0,Female,Bachelor's Degree,Social Media Manager,3.0,minimal
+32.0,Male,PhD,Research Scientist,10.0,above average
+22.0,Female,High School,Receptionist,0.0,minimal
+37.0,Male,Bachelor's Degree,Product Manager,13.0,above average
+38.0,Female,Master's Degree,Marketing Manager,14.0,high
+27.0,Male,Bachelor's Degree,Junior Software Engineer,1.0,minimal
+31.0,Female,Bachelor's Degree,Marketing Coordinator,4.0,below average
+29.0,Male,Bachelor's Degree,Product Designer,3.0,below average
+34.0,Female,PhD,Research Director,11.0,above average
+26.0,Male,Bachelor's Degree,Marketing Analyst,2.0,minimal
+31.0,Female,Master's Degree,Financial Manager,8.0,average
+27.0,Male,Bachelor's Degree,Junior Software Engineer,1.0,minimal
+31.0,Female,Bachelor's Degree,Marketing Coordinator,4.0,below average
+29.0,Male,Bachelor's Degree,Product Designer,3.0,below average
+34.0,Female,PhD,Research Director,11.0,above average
+26.0,Male,Bachelor's Degree,Marketing Analyst,2.0,minimal
+31.0,Female,Master's Degree,Financial Manager,8.0,average
+27.0,Male,Bachelor's Degree,Software Engineer,3.0,below average
+35.0,Female,Master's Degree,Marketing Director,11.0,above average
+24.0,Male,Bachelor's Degree,Financial Analyst,1.0,minimal
+28.0,Female,PhD,Data Scientist,5.0,average
+32.0,Male,Bachelor's Degree,Project Manager,8.0,average
+26.0,Female,Bachelor's Degree,Graphic Designer,2.0,minimal
+41.0,Male,Master's Degree,Senior Software Engineer,19.0,high
+29.0,Female,Bachelor's Degree,Digital Marketing Specialist,4.0,below average
+33.0,Male,Bachelor's Degree,Marketing Manager,9.0,above average
+24.0,Female,High School,Sales Associate,0.0,minimal
+30.0,Male,Master's Degree,Financial Analyst,6.0,average
+26.0,Female,Bachelor's Degree,Social Media Man,7.0,average
+31.0,Male,Bachelor's Degree,Software Engineer,7.0,average
+26.0,Female,Bachelor's Degree,Graphic Designer,2.0,minimal
+33.0,Male,Master's Degree,Marketing Manager,9.0,above average
+29.0,Female,High School,Customer Service Representative,3.0,minimal
+36.0,Male,PhD,Research Scientist,13.0,above average
+27.0,Female,Bachelor's Degree,Marketing Coordinator,2.0,minimal
+31.0,Male,Bachelor's Degree,Project Manager,6.0,average
+28.0,Female,Master's Degree,Financial Analyst,4.0,below average
+25.0,Male,Bachelor's Degree,Software Engineer,1.0,below average
+30.0,Female,Bachelor's Degree,Sales Manager,5.0,below average
+34.0,Male,PhD,Research Director,11.0,high
+28.0,Female,Bachelor's Degree,Marketing Analyst,3.0,below average
+32.0,Male,Bachelor's Degree,Product Manager,7.0,average
+24.0,Female,High School,Receptionist,0.0,minimal
+37.0,Male,Master's Degree,Marketing Director,14.0,high
+39.0,Female,Bachelor's Degree,Financial Manager,16.0,high
+26.0,Male,Bachelor's Degree,Product Designer,2.0,minimal
+31.0,Female,PhD,Data Scientist,8.0,above average
+29.0,Male,Bachelor's Degree,Marketing Analyst,4.0,below average
+33.0,Female,Master's Degree,Marketing Manager,9.0,above average
+27.0,Male,Bachelor's Degree,Software Engineer,3.0,below average
+36.0,Female,PhD,Research Scientist,12.0,above average
+25.0,Male,Bachelor's Degree,Product Manager,1.0,minimal
+30.0,Female,Bachelor's Degree,Marketing Coordinator,5.0,below average
+34.0,Male,PhD,Research Director,11.0,high
+28.0,Female,Bachelor's Degree,Marketing Analyst,3.0,below average
+32.0,Male,Bachelor's Degree,Product Manager,7.0,average
+24.0,Female,High School,Receptionist,0.0,minimal
+37.0,Male,Master's Degree,Marketing Director,14.0,high
+39.0,Female,Bachelor's Degree,Financial Manager,16.0,high
+26.0,Male,Bachelor's Degree,Product Designer,2.0,minimal
+31.0,Female,PhD,Data Scientist,8.0,above average
+29.0,Male,Bachelor's Degree,Marketing Analyst,4.0,below average
+33.0,Female,Master's Degree,Marketing Manager,9.0,above average
+27.0,Male,Bachelor's Degree,Software Engineer,3.0,below average
+36.0,Female,PhD,Research Scientist,12.0,above average
+25.0,Male,Bachelor's Degree,Product Manager,1.0,minimal
+30.0,Female,Bachelor's Degree,Marketing Coordinator,5.0,below average
+34.0,Male,PhD,Research Director,11.0,high
+28.0,Female,Bachelor's Degree,Marketing Analyst,3.0,below average
+32.0,Male,Bachelor's Degree,Product Manager,7.0,average
+24.0,Female,High School,Receptionist,0.0,minimal
+37.0,Male,Master's Degree,Marketing Director,14.0,high
+39.0,Female,Bachelor's Degree,Financial Manager,16.0,high
+26.0,Male,Bachelor's Degree,Product Designer,2.0,minimal
+31.0,Female,PhD,Data Scientist,8.0,above average
+29.0,Male,Bachelor's Degree,Marketing Analyst,4.0,below average
+33.0,Female,Master's Degree,Marketing Manager,9.0,above average
+27.0,Male,Bachelor's Degree,Software Engineer,3.0,below average
+36.0,Female,PhD,Research Scientist,12.0,above average
+25.0,Male,Bachelor's Degree,Product Manager,1.0,minimal
+30.0,Female,Bachelor's Degree,Marketing Coordinator,5.0,below average
+34.0,Male,PhD,Research Director,11.0,high
+28.0,Female,Bachelor's Degree,Marketing Analyst,3.0,below average
+32.0,Male,Bachelor's Degree,Product Manager,7.0,average
+24.0,Female,High School,Receptionist,0.0,minimal
+37.0,Male,Master's Degree,Marketing Director,14.0,high
+39.0,Female,Bachelor's Degree,Financial Manager,16.0,high
+26.0,Male,Bachelor's Degree,Product Designer,2.0,minimal
+31.0,Female,PhD,Data Scientist,8.0,above average
+29.0,Male,Bachelor's Degree,Marketing Analyst,4.0,below average
+33.0,Female,Master's Degree,Marketing Manager,9.0,above average
+27.0,Male,Bachelor's Degree,Software Engineer,3.0,below average
+36.0,Female,PhD,Research Scientist,12.0,above average
+25.0,Male,Bachelor's Degree,Product Manager,1.0,minimal
+30.0,Female,Bachelor's Degree,Marketing Coordinator,5.0,below average
+34.0,Male,PhD,Research Director,11.0,high
+28.0,Female,Bachelor's Degree,Marketing Analyst,3.0,below average
+32.0,Male,Bachelor's Degree,Product Manager,7.0,average
+24.0,Female,High School,Receptionist,0.0,minimal
+37.0,Male,Master's Degree,Marketing Director,14.0,high
+39.0,Female,Bachelor's Degree,Financial Manager,16.0,high
+26.0,Male,Bachelor's Degree,Product Designer,2.0,minimal
+31.0,Female,PhD,Data Scientist,8.0,above average
+29.0,Male,Bachelor's Degree,Marketing Analyst,4.0,below average
+33.0,Female,Master's Degree,Marketing Manager,9.0,above average
+27.0,Male,Bachelor's Degree,Software Engineer,3.0,below average
+36.0,Female,PhD,Research Scientist,12.0,above average
+25.0,Male,Bachelor's Degree,Product Manager,1.0,minimal
+30.0,Female,Bachelor's Degree,Marketing Coordinator,5.0,below average
+34.0,Male,PhD,Research Director,11.0,high
+28.0,Female,Bachelor's Degree,Marketing Analyst,3.0,below average
+32.0,Male,Bachelor's Degree,Product Manager,7.0,average
+24.0,Female,High School,Receptionist,0.0,minimal
+37.0,Male,Master's Degree,Marketing Director,14.0,high
+39.0,Female,Bachelor's Degree,Financial Manager,16.0,high
+26.0,Male,Bachelor's Degree,Product Designer,2.0,minimal
+31.0,Female,PhD,Data Scientist,8.0,above average
+29.0,Male,Bachelor's Degree,Marketing Analyst,4.0,below average
+33.0,Female,Master's Degree,Marketing Manager,9.0,above average
+27.0,Male,Bachelor's Degree,Software Engineer,3.0,below average
+36.0,Female,PhD,Research Scientist,12.0,above average
+25.0,Male,Bachelor's Degree,Product Manager,1.0,minimal
+30.0,Female,Bachelor's Degree,Marketing Coordinator,5.0,below average
+34.0,Male,PhD,Research Director,11.0,high
+28.0,Female,Bachelor's Degree,Marketing Analyst,3.0,below average
+32.0,Male,Bachelor's Degree,Product Manager,7.0,average
+24.0,Female,High School,Receptionist,0.0,minimal
+37.0,Male,Master's Degree,Marketing Director,14.0,high
+39.0,Female,Bachelor's Degree,Financial Manager,16.0,high
+26.0,Male,Bachelor's Degree,Product Designer,2.0,minimal
+31.0,Female,PhD,Data Scientist,8.0,above average
+29.0,Male,Bachelor's Degree,Marketing Analyst,4.0,below average
+33.0,Female,Master's Degree,Marketing Manager,9.0,above average
+27.0,Male,Bachelor's Degree,Software Engineer,3.0,below average
+36.0,Female,PhD,Research Scientist,12.0,above average
+25.0,Male,Bachelor's Degree,Product Manager,1.0,minimal
+30.0,Female,Bachelor's Degree,Marketing Coordinator,5.0,below average
+34.0,Male,PhD,Research Director,11.0,high
+28.0,Female,Bachelor's Degree,Marketing Analyst,3.0,below average
+32.0,Male,Bachelor's Degree,Product Manager,7.0,average
+24.0,Female,High School,Receptionist,0.0,minimal
+37.0,Male,Master's Degree,Marketing Director,14.0,high
+39.0,Female,Bachelor's Degree,Financial Manager,16.0,high
+26.0,Male,Bachelor's Degree,Product Designer,2.0,minimal
+31.0,Female,PhD,Data Scientist,8.0,above average
+29.0,Male,Bachelor's Degree,Marketing Analyst,4.0,below average
+33.0,Female,Master's Degree,Marketing Manager,9.0,above average
+27.0,Male,Bachelor's Degree,Software Engineer,3.0,below average
+36.0,Female,PhD,Research Scientist,12.0,above average
+25.0,Male,Bachelor's Degree,Product Manager,1.0,minimal
+30.0,Female,Bachelor's Degree,Marketing Coordinator,5.0,below average
+34.0,Male,PhD,Research Director,11.0,high
+28.0,Female,Bachelor's Degree,Marketing Analyst,3.0,below average
+32.0,Male,Bachelor's Degree,Product Manager,7.0,average
+24.0,Female,High School,Receptionist,0.0,minimal
+37.0,Male,Master's Degree,Marketing Director,14.0,high
+28.0,Female,Bachelor's Degree,Marketing Coordinator,3.0,below average
+33.0,Male,Master's Degree,Software Engineer,9.0,average
+26.0,Female,Bachelor's Degree,Graphic Designer,1.0,minimal
+29.0,Male,Bachelor's Degree,Product Manager,5.0,below average
+35.0,Female,PhD,Research Scientist,11.0,above average
+27.0,Male,Bachelor's Degree,Software Engineer,2.0,below average
+31.0,Female,Bachelor's Degree,Marketing Manager,7.0,average
+28.0,Male,Master's Degree,Financial Analyst,4.0,below average
+24.0,Female,Bachelor's Degree,Marketing Analyst,0.0,minimal
+30.0,Male,Bachelor's Degree,Project Manager,6.0,average
+34.0,Female,PhD,Research Director,12.0,high
+27.0,Male,Bachelor's Degree,Software Engineer,3.0,below average
+33.0,Female,Master's Degree,Marketing Manager,8.0,average
+29.0,Male,Bachelor's Degree,Marketing Analyst,4.0,below average
+25.0,Female,High School,Customer Service Representative,1.0,minimal
+36.0,Male,PhD,Research Scientist,13.0,high
+39.0,Female,Bachelor's Degree,Financial Manager,15.0,high
+26.0,Male,Bachelor's Degree,Product Designer,1.0,minimal
+31.0,Female,PhD,Data Scientist,8.0,above average
+28.0,Male,Bachelor's Degree,Marketing Analyst,3.0,below average
+32.0,Female,Bachelor's Degree,Product Manager,7.0,average
+24.0,Male,High School,Delivery Driver,0.0,minimal
+37.0,Male,Master's Degree,Marketing Director,14.0,high
+39.0,Female,Bachelor's Degree,Financial Manager,16.0,high
+26.0,Male,Bachelor's Degree,Product Designer,2.0,minimal
+31.0,Female,PhD,Data Scientist,8.0,above average
+29.0,Male,Bachelor's Degree,Marketing Analyst,4.0,below average
+33.0,Female,Master's Degree,Marketing Manager,9.0,above average
+27.0,Male,Bachelor's Degree,Software Engineer,3.0,below average
+36.0,Female,PhD,Research Scientist,12.0,high
+25.0,Male,Bachelor's Degree,Product Manager,1.0,below average
+30.0,Female,Bachelor's Degree,Marketing Coordinator,5.0,below average
+34.0,Male,PhD,Research Director,11.0,above average
+28.0,Female,Bachelor's Degree,Marketing Analyst,3.0,below average
+32.0,Male,Bachelor's Degree,Product Manager,7.0,average
+24.0,Female,High School,Receptionist,0.0,minimal
+37.0,Male,Master's Degree,Marketing Director,14.0,high
+39.0,Female,Bachelor's Degree,Financial Manager,16.0,high
+26.0,Male,Bachelor's Degree,Product Designer,2.0,minimal
+31.0,Female,PhD,Data Scientist,8.0,above average
+29.0,Male,Bachelor's Degree,Marketing Analyst,4.0,below average
+33.0,Female,Master's Degree,Marketing Manager,9.0,above average
+27.0,Male,Bachelor's Degree,Software Engineer,3.0,below average
+36.0,Female,PhD,Research Scientist,12.0,high
+25.0,Male,Bachelor's Degree,Product Manager,1.0,below average
+30.0,Female,Bachelor's Degree,Marketing Coordinator,5.0,below average
+34.0,Male,PhD,Research Director,11.0,above average
+28.0,Female,Bachelor's Degree,Marketing Analyst,3.0,below average
+32.0,Male,Bachelor's Degree,Product Manager,7.0,average
+24.0,Female,High School,Receptionist,0.0,minimal
+37.0,Male,Master's Degree,Marketing Director,14.0,high
+39.0,Female,Bachelor's Degree,Financial Manager,16.0,high
+26.0,Male,Bachelor's Degree,Product Designer,2.0,minimal
+31.0,Female,PhD,Data Scientist,8.0,above average
+29.0,Male,Bachelor's Degree,Marketing Analyst,4.0,below average
+33.0,Female,Master's Degree,Marketing Manager,9.0,above average
+27.0,Male,Bachelor's Degree,Software Engineer,3.0,below average
+36.0,Female,PhD,Research Scientist,12.0,high
+25.0,Male,Bachelor's Degree,Product Manager,1.0,below average
+30.0,Female,Bachelor's Degree,Marketing Coordinator,5.0,below average
+34.0,Male,PhD,Research Director,11.0,above average
+28.0,Female,Bachelor's Degree,Marketing Analyst,3.0,below average
+32.0,Male,Bachelor's Degree,Product Manager,7.0,average
+24.0,Female,High School,Receptionist,0.0,minimal
+37.0,Male,Master's Degree,Marketing Director,14.0,high
+39.0,Female,Bachelor's Degree,Financial Manager,16.0,high
+26.0,Male,Bachelor's Degree,Product Designer,2.0,minimal
+31.0,Female,PhD,Data Scientist,8.0,above average
+29.0,Male,Bachelor's Degree,Marketing Analyst,4.0,below average
+33.0,Female,Master's Degree,Marketing Manager,9.0,above average
+27.0,Male,Bachelor's Degree,Software Engineer,3.0,below average
+36.0,Female,PhD,Research Scientist,12.0,high
+25.0,Male,Bachelor's Degree,Product Manager,1.0,below average
+30.0,Female,Bachelor's Degree,Marketing Coordinator,5.0,below average
+34.0,Male,PhD,Research Director,11.0,above average
+28.0,Female,Bachelor's Degree,Marketing Analyst,3.0,below average
+32.0,Male,Bachelor's Degree,Product Manager,7.0,average
+24.0,Female,High School,Receptionist,0.0,minimal
+37.0,Male,Master's Degree,Marketing Director,14.0,high
+39.0,Female,Bachelor's Degree,Financial Manager,16.0,high
+26.0,Male,Bachelor's Degree,Product Designer,2.0,minimal
+31.0,Female,PhD,Data Scientist,8.0,above average
+29.0,Male,Bachelor's Degree,Marketing Analyst,4.0,below average
+33.0,Female,Master's Degree,Marketing Manager,9.0,above average
+27.0,Male,Bachelor's Degree,Software Engineer,3.0,below average
+36.0,Female,PhD,Research Scientist,12.0,high
+25.0,Male,Bachelor's Degree,Product Manager,1.0,below average
+30.0,Female,Bachelor's Degree,Marketing Coordinator,5.0,below average
+34.0,Male,PhD,Research Director,11.0,above average
+28.0,Female,Bachelor's Degree,Marketing Analyst,3.0,below average
+32.0,Male,Bachelor's Degree,Product Manager,7.0,average
+24.0,Female,High School,Receptionist,0.0,minimal
+37.0,Male,Master's Degree,Marketing Director,14.0,high
+39.0,Female,Bachelor's Degree,Financial Manager,16.0,high
+26.0,Male,Bachelor's Degree,Product Designer,2.0,minimal
+31.0,Female,PhD,Data Scientist,8.0,above average
+29.0,Male,Bachelor's Degree,Marketing Analyst,4.0,below average
+33.0,Female,Master's Degree,Marketing Manager,9.0,above average
+27.0,Male,Bachelor's Degree,Software Engineer,3.0,below average
+36.0,Female,PhD,Research Scientist,12.0,high
+25.0,Male,Bachelor's Degree,Product Manager,1.0,below average
+30.0,Female,Bachelor's Degree,Marketing Coordinator,5.0,below average
+34.0,Male,PhD,Research Director,11.0,above average
+28.0,Female,Bachelor's Degree,Marketing Analyst,3.0,below average
+32.0,Male,Bachelor's Degree,Product Manager,7.0,average
+24.0,Female,High School,Receptionist,0.0,minimal
+37.0,Male,Master's Degree,Marketing Director,14.0,high
+39.0,Female,Bachelor's Degree,Financial Manager,16.0,high
+26.0,Male,Bachelor's Degree,Product Designer,2.0,minimal
+31.0,Female,PhD,Data Scientist,8.0,above average
+29.0,Male,Bachelor's Degree,Marketing Analyst,4.0,below average
+33.0,Female,Master's Degree,Marketing Manager,9.0,above average
+27.0,Male,Bachelor's Degree,Software Engineer,3.0,below average
+36.0,Female,PhD,Research Scientist,12.0,high
+25.0,Male,Bachelor's Degree,Product Manager,1.0,below average
+30.0,Female,Bachelor's Degree,Marketing Coordinator,5.0,below average
+34.0,Male,PhD,Research Director,11.0,above average
+28.0,Female,Bachelor's Degree,Marketing Analyst,3.0,below average
+32.0,Male,Bachelor's Degree,Product Manager,7.0,average
+24.0,Female,High School,Receptionist,0.0,minimal
+37.0,Male,Master's Degree,Marketing Director,14.0,high
+39.0,Female,Bachelor's Degree,Financial Manager,16.0,high
+26.0,Male,Bachelor's Degree,Product Designer,2.0,minimal
+31.0,Female,PhD,Data Scientist,8.0,above average
+29.0,Male,Bachelor's Degree,Marketing Analyst,4.0,below average
+33.0,Female,Master's Degree,Marketing Manager,9.0,above average
+27.0,Male,Bachelor's Degree,Software Engineer,3.0,below average
+29.0,Male,Bachelor's Degree,Software Engineer,3.0,below average
+32.0,Female,Master's Degree,Marketing Manager,8.0,average
+27.0,Male,Bachelor's Degree,Product Manager,2.0,below average
+30.0,Female,PhD,Data Scientist,6.0,average
+36.0,Male,Bachelor's Degree,Financial Analyst,11.0,above average
+28.0,Female,Bachelor's Degree,Marketing Coordinator,3.0,below average
+33.0,Male,Master's Degree,Software Engineer,9.0,average
+26.0,Female,Bachelor's Degree,Graphic Designer,1.0,minimal
+29.0,Male,Bachelor's Degree,Product Manager,5.0,below average
+35.0,Female,PhD,Research Scientist,11.0,above average
+27.0,Male,Bachelor's Degree,Software Engineer,2.0,below average
+31.0,Female,Bachelor's Degree,Marketing Manager,7.0,average
+28.0,Male,Master's Degree,Financial Analyst,4.0,below average
+24.0,Female,Bachelor's Degree,Marketing Analyst,0.0,minimal
+30.0,Male,Bachelor's Degree,Project Manager,6.0,average
+34.0,Female,PhD,Research Director,12.0,high
+27.0,Male,Bachelor's Degree,Software Engineer,3.0,below average
+33.0,Female,Master's Degree,Marketing Manager,8.0,average
+29.0,Male,Bachelor's Degree,Marketing Analyst,4.0,below average
+25.0,Female,High School,Customer Service Representative,1.0,minimal
+36.0,Male,PhD,Research Scientist,13.0,high
+39.0,Female,Bachelor's Degree,Financial Manager,15.0,high
+26.0,Male,Bachelor's Degree,Product Designer,1.0,minimal
+31.0,Female,PhD,Data Scientist,8.0,above average
+28.0,Male,Bachelor's Degree,Marketing Analyst,3.0,below average
+32.0,Female,Bachelor's Degree,Product Manager,7.0,average
+24.0,Male,High School,Delivery Driver,0.0,minimal
+37.0,Male,Master's Degree,Marketing Director,14.0,high
+39.0,Female,Bachelor's Degree,Financial Manager,16.0,high
+26.0,Male,Bachelor's Degree,Product Designer,2.0,minimal
+31.0,Female,PhD,Data Scientist,8.0,above average
+29.0,Male,Bachelor's Degree,Marketing Analyst,4.0,below average
+33.0,Female,Master's Degree,Marketing Manager,9.0,above average
+27.0,Male,Bachelor's Degree,Software Engineer,3.0,below average
+36.0,Female,PhD,Research Scientist,12.0,high
+25.0,Male,Bachelor's Degree,Product Manager,1.0,below average
+30.0,Female,Bachelor's Degree,Marketing Coordinator,5.0,below average
+34.0,Male,PhD,Research Director,11.0,above average
+28.0,Female,Bachelor's Degree,Marketing Analyst,3.0,below average
+32.0,Male,Bachelor's Degree,Product Manager,7.0,average
+24.0,Female,High School,Receptionist,0.0,minimal
+37.0,Male,Master's Degree,Marketing Director,14.0,high
+39.0,Female,Bachelor's Degree,Financial Manager,16.0,high
+26.0,Male,Bachelor's Degree,Product Designer,2.0,minimal
+31.0,Female,PhD,Data Scientist,8.0,above average
+29.0,Male,Bachelor's Degree,Marketing Analyst,4.0,below average
+33.0,Female,Master's Degree,Marketing Manager,9.0,above average
+27.0,Male,Bachelor's Degree,Software Engineer,3.0,below average
+36.0,Female,PhD,Research Scientist,12.0,high
+25.0,Male,Bachelor's Degree,Product Manager,1.0,below average
+30.0,Female,Bachelor's Degree,Marketing Coordinator,5.0,below average
+34.0,Male,PhD,Research Director,11.0,above average
+28.0,Female,Bachelor's Degree,Marketing Analyst,3.0,below average
+32.0,Male,Bachelor's Degree,Product Manager,7.0,average
+24.0,Female,High School,Receptionist,0.0,minimal
+37.0,Male,Master's Degree,Marketing Director,14.0,high
+39.0,Female,Bachelor's Degree,Financial Manager,16.0,high
+26.0,Male,Bachelor's Degree,Product Designer,2.0,minimal
+31.0,Female,PhD,Data Scientist,8.0,above average
+29.0,Male,Bachelor's Degree,Marketing Analyst,4.0,below average
+33.0,Female,Master's Degree,Marketing Manager,9.0,above average
+27.0,Male,Bachelor's Degree,Software Engineer,3.0,below average
+36.0,Female,PhD,Research Scientist,12.0,high
+25.0,Male,Bachelor's Degree,Product Manager,1.0,below average
+30.0,Female,Bachelor's Degree,Marketing Coordinator,5.0,below average
+34.0,Male,PhD,Research Director,11.0,above average
+28.0,Female,Bachelor's Degree,Marketing Analyst,3.0,below average
+32.0,Male,Bachelor's Degree,Product Manager,7.0,average
+24.0,Female,High School,Receptionist,0.0,minimal
+37.0,Male,Master's Degree,Marketing Director,14.0,high
+39.0,Female,Bachelor's Degree,Financial Manager,16.0,high
+26.0,Male,Bachelor's Degree,Product Designer,2.0,minimal
+31.0,Female,PhD,Data Scientist,8.0,above average
+29.0,Male,Bachelor's Degree,Marketing Analyst,4.0,below average
+33.0,Female,Master's Degree,Marketing Manager,9.0,above average
+27.0,Male,Bachelor's Degree,Software Engineer,3.0,below average
+36.0,Female,PhD,Research Scientist,12.0,high
+25.0,Male,Bachelor's Degree,Product Manager,1.0,below average
+30.0,Female,Bachelor's Degree,Marketing Coordinator,5.0,below average
+34.0,Male,PhD,Research Director,11.0,above average
+28.0,Female,Bachelor's Degree,Marketing Analyst,3.0,below average
+32.0,Male,Bachelor's Degree,Product Manager,7.0,average
+24.0,Female,High School,Receptionist,0.0,minimal
+37.0,Male,Master's Degree,Marketing Director,14.0,high
+39.0,Female,Bachelor's Degree,Financial Manager,16.0,high
+26.0,Male,Bachelor's Degree,Product Designer,2.0,minimal
+31.0,Female,PhD,Data Scientist,8.0,above average
+29.0,Male,Bachelor's Degree,Marketing Analyst,4.0,below average
+33.0,Female,Master's Degree,Marketing Manager,9.0,above average
+27.0,Male,Bachelor's Degree,Software Engineer,3.0,below average
+36.0,Female,PhD,Research Scientist,12.0,high
+25.0,Male,Bachelor's Degree,Product Manager,1.0,below average
+30.0,Female,Bachelor's Degree,Marketing Coordinator,5.0,below average
+34.0,Male,PhD,Research Director,11.0,above average
+28.0,Female,Bachelor's Degree,Marketing Analyst,3.0,below average
+32.0,Male,Bachelor's Degree,Product Manager,7.0,average
+24.0,Female,High School,Receptionist,0.0,minimal
+37.0,Male,Master's Degree,Marketing Director,14.0,high
+39.0,Female,Bachelor's Degree,Financial Manager,16.0,high
+26.0,Male,Bachelor's Degree,Product Designer,2.0,minimal
+31.0,Female,PhD,Data Scientist,8.0,above average
+29.0,Male,Bachelor's Degree,Marketing Analyst,4.0,below average
+33.0,Female,Master's Degree,Marketing Manager,9.0,above average
+27.0,Male,Bachelor's Degree,Software Engineer,3.0,below average
+36.0,Female,PhD,Research Scientist,12.0,high
+25.0,Male,Bachelor's Degree,Product Manager,1.0,below average
+30.0,Female,Bachelor's Degree,Marketing Coordinator,5.0,below average
+34.0,Male,PhD,Research Director,11.0,above average
+28.0,Female,Bachelor's Degree,Marketing Analyst,3.0,below average
+32.0,Male,Bachelor's Degree,Product Manager,7.0,average
+24.0,Female,High School,Receptionist,0.0,minimal
+37.0,Male,Master's Degree,Marketing Director,14.0,high
+39.0,Female,Bachelor's Degree,Financial Manager,16.0,high
+26.0,Male,Bachelor's Degree,Product Designer,2.0,minimal
+31.0,Female,PhD,Data Scientist,8.0,above average
+29.0,Male,Bachelor's Degree,Marketing Analyst,4.0,below average
+33.0,Female,Master's Degree,Marketing Manager,9.0,above average
+27.0,Male,Bachelor's Degree,Software Engineer,3.0,below average
+36.0,Female,PhD,Research Scientist,12.0,high
+25.0,Male,Bachelor's Degree,Product Manager,1.0,below average
+30.0,Female,Bachelor's Degree,Marketing Coordinator,5.0,below average
+34.0,Male,PhD,Research Director,11.0,above average
+28.0,Female,Bachelor's Degree,Marketing Analyst,3.0,below average
+32.0,Male,Bachelor's Degree,Product Manager,7.0,average
+24.0,Female,High School,Receptionist,0.0,minimal
+37.0,Male,Master's Degree,Marketing Director,14.0,high
+39.0,Female,Bachelor's Degree,Financial Manager,16.0,high
+27.0,Male,phD,Marketing Coordinator,7.0,average
+28.0,Female,Bachelor's Degree,Marketing Coordinator,3.0,below average
+33.0,Male,Master's Degree,Software Engineer,8.0,average
+27.0,Female,Bachelor's Degree,Product Manager,2.0,below average
+30.0,Male,PhD,Data Scientist,6.0,average
+36.0,Female,Bachelor's Degree,Financial Analyst,11.0,above average
+29.0,Male,Bachelor's Degree,Marketing Analyst,3.0,below average
+32.0,Female,Master's Degree,Software Engineer,9.0,average
+26.0,Male,Bachelor's Degree,Graphic Designer,1.0,minimal
+29.0,Female,Bachelor's Degree,Product Manager,5.0,below average
+35.0,Male,PhD,Research Scientist,11.0,above average
+27.0,Male,Bachelor's Degree,Software Engineer,2.0,below average
+31.0,Female,Bachelor's Degree,Marketing Manager,7.0,average
+28.0,Male,Master's Degree,Financial Analyst,4.0,below average
+24.0,Female,Bachelor's Degree,Marketing Analyst,0.0,minimal
+30.0,Male,Bachelor's Degree,Project Manager,6.0,average
+34.0,Female,PhD,Research Director,12.0,high
+27.0,Male,Bachelor's Degree,Software Engineer,3.0,below average
+33.0,Female,Master's Degree,Marketing Manager,8.0,average
+29.0,Male,Bachelor's Degree,Marketing Analyst,4.0,below average
+25.0,Female,High School,Customer Service Representative,1.0,minimal
+36.0,Male,PhD,Research Scientist,13.0,high
+39.0,Female,Bachelor's Degree,Financial Manager,15.0,high
+26.0,Male,Bachelor's Degree,Product Designer,1.0,minimal
+31.0,Female,PhD,Data Scientist,8.0,above average
+28.0,Male,Bachelor's Degree,Marketing Analyst,3.0,below average
+32.0,Female,Bachelor's Degree,Product Manager,7.0,average
+24.0,Male,High School,Delivery Driver,0.0,minimal
+37.0,Male,Master's Degree,Marketing Director,14.0,high
+39.0,Female,Bachelor's Degree,Financial Manager,16.0,high
+26.0,Male,Bachelor's Degree,Product Designer,2.0,minimal
+31.0,Female,PhD,Data Scientist,8.0,above average
+29.0,Male,Bachelor's Degree,Marketing Analyst,4.0,below average
+33.0,Female,Master's Degree,Marketing Manager,9.0,above average
+27.0,Male,Bachelor's Degree,Software Engineer,3.0,below average
+36.0,Female,PhD,Research Scientist,12.0,high
+25.0,Male,Bachelor's Degree,Product Manager,1.0,below average
+30.0,Female,Bachelor's Degree,Marketing Coordinator,5.0,below average
+34.0,Male,PhD,Research Director,11.0,above average
+28.0,Female,Bachelor's Degree,Marketing Analyst,3.0,below average
+32.0,Male,Bachelor's Degree,Product Manager,7.0,average
+24.0,Female,High School,Receptionist,0.0,minimal
+37.0,Male,Master's Degree,Marketing Director,14.0,high
+39.0,Female,Bachelor's Degree,Financial Manager,16.0,high
+26.0,Male,Bachelor's Degree,Product Designer,2.0,minimal
+31.0,Female,PhD,Data Scientist,8.0,above average
+29.0,Male,Bachelor's Degree,Marketing Analyst,4.0,below average
+33.0,Female,Master's Degree,Marketing Manager,9.0,above average
+27.0,Male,Bachelor's Degree,Software Engineer,3.0,below average
+36.0,Female,PhD,Research Scientist,12.0,high
+25.0,Male,Bachelor's Degree,Product Manager,1.0,below average
+30.0,Female,Bachelor's Degree,Marketing Coordinator,5.0,below average
+34.0,Male,PhD,Research Director,11.0,above average
+28.0,Female,Bachelor's Degree,Marketing Analyst,3.0,below average
+32.0,Male,Bachelor's Degree,Product Manager,7.0,average
+24.0,Female,High School,Receptionist,0.0,minimal
+37.0,Male,Master's Degree,Marketing Director,14.0,high
+39.0,Female,Bachelor's Degree,Financial Manager,16.0,high
+26.0,Male,Bachelor's Degree,Product Designer,2.0,minimal
+31.0,Female,PhD,Data Scientist,8.0,above average
+29.0,Male,Bachelor's Degree,Marketing Analyst,4.0,below average
+33.0,Female,Master's Degree,Marketing Manager,9.0,above average
+27.0,Male,Bachelor's Degree,Software Engineer,3.0,below average
+36.0,Female,PhD,Research Scientist,12.0,high
+25.0,Male,Bachelor's Degree,Product Manager,1.0,below average
+30.0,Female,Bachelor's Degree,Marketing Coordinator,5.0,below average
+34.0,Male,PhD,Research Director,11.0,above average
+28.0,Female,Bachelor's Degree,Marketing Analyst,3.0,below average
+32.0,Male,Bachelor's Degree,Product Manager,7.0,average
+24.0,Female,High School,Receptionist,0.0,minimal
+37.0,Male,Master's Degree,Marketing Director,14.0,high
+39.0,Female,Bachelor's Degree,Financial Manager,16.0,high
+26.0,Male,Bachelor's Degree,Product Designer,2.0,minimal
+31.0,Female,PhD,Data Scientist,8.0,above average
+29.0,Male,Bachelor's Degree,Marketing Analyst,4.0,below average
+33.0,Female,Master's Degree,Marketing Manager,9.0,above average
+27.0,Male,Bachelor's Degree,Software Engineer,3.0,below average
+36.0,Female,PhD,Research Scientist,12.0,high
+25.0,Male,Bachelor's Degree,Product Manager,1.0,below average
+30.0,Female,Bachelor's Degree,Marketing Coordinator,5.0,below average
+34.0,Male,PhD,Research Director,11.0,above average
+28.0,Female,Bachelor's Degree,Marketing Analyst,3.0,below average
+32.0,Male,Bachelor's Degree,Product Manager,7.0,average
+24.0,Female,High School,Receptionist,0.0,minimal
+37.0,Male,Master's Degree,Marketing Director,14.0,high
+39.0,Female,Bachelor's Degree,Financial Manager,16.0,high
+26.0,Male,Bachelor's Degree,Product Designer,2.0,minimal
+31.0,Female,PhD,Data Scientist,8.0,above average
+29.0,Male,Bachelor's Degree,Marketing Analyst,4.0,below average
+33.0,Female,Master's Degree,Marketing Manager,9.0,above average
+27.0,Male,Bachelor's Degree,Software Engineer,3.0,below average
+36.0,Female,PhD,Research Scientist,12.0,high
+25.0,Male,Bachelor's Degree,Product Manager,1.0,below average
+30.0,Female,Bachelor's Degree,Marketing Coordinator,5.0,below average
+34.0,Male,PhD,Research Director,11.0,above average
+28.0,Female,Bachelor's Degree,Marketing Analyst,3.0,below average
+32.0,Male,Bachelor's Degree,Product Manager,7.0,average
+24.0,Female,High School,Receptionist,0.0,minimal
+37.0,Male,Master's Degree,Marketing Director,14.0,high
+39.0,Female,Bachelor's Degree,Financial Manager,16.0,high
+26.0,Male,Bachelor's Degree,Product Designer,2.0,minimal
+31.0,Female,PhD,Data Scientist,8.0,above average
+29.0,Male,Bachelor's Degree,Marketing Analyst,4.0,below average
+33.0,Female,Master's Degree,Marketing Manager,9.0,above average
+27.0,Male,Bachelor's Degree,Software Engineer,3.0,below average
+36.0,Female,PhD,Research Scientist,12.0,high
+25.0,Male,Bachelor's Degree,Product Manager,1.0,below average
+30.0,Female,Bachelor's Degree,Marketing Coordinator,5.0,below average
+34.0,Male,PhD,Research Director,11.0,above average
+28.0,Female,Bachelor's Degree,Marketing Analyst,3.0,below average
+32.0,Male,Bachelor's Degree,Product Manager,7.0,average
+24.0,Female,High School,Receptionist,0.0,minimal
+37.0,Male,Master's Degree,Marketing Director,14.0,high
+39.0,Female,Bachelor's Degree,Financial Manager,16.0,high
+26.0,Male,Bachelor's Degree,Product Designer,2.0,minimal
+31.0,Female,PhD,Data Scientist,8.0,above average
+29.0,Male,Bachelor's Degree,Marketing Analyst,4.0,below average
+33.0,Female,Master's Degree,Marketing Manager,9.0,above average
+27.0,Male,Bachelor's Degree,Software Engineer,3.0,below average
+36.0,Female,PhD,Research Scientist,12.0,high
+25.0,Male,Bachelor's Degree,Product Manager,1.0,below average
+30.0,Female,Bachelor's Degree,Marketing Coordinator,5.0,below average
+34.0,Male,PhD,Research Director,11.0,above average
+28.0,Female,Bachelor's Degree,Marketing Analyst,3.0,below average
+32.0,Male,Bachelor's Degree,Product Manager,7.0,average
+24.0,Female,High School,Receptionist,0.0,minimal
+37.0,Male,Master's Degree,Marketing Director,14.0,high
+39.0,Female,Bachelor's Degree,Financial Manager,16.0,high
+29.0,Female,Bachelor's Degree,Marketing Coordinator,4.0,below average
+34.0,Male,Master's Degree,Software Engineer,9.0,average
+28.0,Female,Bachelor's Degree,Product Manager,3.0,below average
+31.0,Male,PhD,Data Scientist,7.0,average
+37.0,Female,Bachelor's Degree,Financial Analyst,12.0,above average
+30.0,Male,Bachelor's Degree,Marketing Analyst,4.0,below average
+33.0,Female,Master's Degree,Software Engineer,8.0,average
+27.0,Male,Bachelor's Degree,Graphic Designer,2.0,minimal
+30.0,Female,Bachelor's Degree,Product Manager,5.0,below average
+36.0,Male,PhD,Research Scientist,11.0,above average
+28.0,Male,Bachelor's Degree,Software Engineer,3.0,below average
+32.0,Female,Bachelor's Degree,Marketing Manager,8.0,average
+29.0,Male,Master's Degree,Financial Analyst,5.0,average
+25.0,Female,Bachelor's Degree,Marketing Analyst,0.0,minimal
+31.0,Male,Bachelor's Degree,Project Manager,6.0,average
+35.0,Female,PhD,Research Director,12.0,high
+28.0,Male,Bachelor's Degree,Software Engineer,3.0,below average
+33.0,Female,Master's Degree,Marketing Manager,9.0,above average
+29.0,Male,Bachelor's Degree,Marketing Analyst,4.0,below average
+25.0,Female,High School,Customer Service Representative,1.0,minimal
+36.0,Male,PhD,Research Scientist,13.0,high
+40.0,Female,Bachelor's Degree,Financial Manager,15.0,high
+27.0,Male,Bachelor's Degree,Product Designer,1.0,minimal
+32.0,Female,PhD,Data Scientist,9.0,above average
+28.0,Male,Bachelor's Degree,Marketing Analyst,3.0,below average
+32.0,Female,Bachelor's Degree,Product Manager,7.0,average
+24.0,Male,High School,Delivery Driver,0.0,minimal
+38.0,Male,Master's Degree,Marketing Director,14.0,high
+40.0,Female,Bachelor's Degree,Financial Manager,16.0,high
+27.0,Male,Bachelor's Degree,Product Designer,2.0,minimal
+32.0,Female,PhD,Data Scientist,9.0,above average
+29.0,Male,Bachelor's Degree,Marketing Analyst,4.0,below average
+33.0,Female,Master's Degree,Marketing Manager,9.0,above average
+27.0,Male,Bachelor's Degree,Software Engineer,3.0,below average
+36.0,Female,PhD,Research Scientist,13.0,high
+25.0,Male,Bachelor's Degree,Product Manager,1.0,below average
+30.0,Female,Bachelor's Degree,Marketing Coordinator,5.0,average
+34.0,Male,PhD,Research Director,12.0,high
+28.0,Female,Bachelor's Degree,Marketing Analyst,3.0,below average
+32.0,Male,Bachelor's Degree,Product Manager,7.0,average
+24.0,Female,High School,Receptionist,0.0,minimal
+38.0,Male,Master's Degree,Marketing Director,14.0,high
+40.0,Female,Bachelor's Degree,Financial Manager,16.0,high
+27.0,Male,Bachelor's Degree,Product Designer,2.0,minimal
+32.0,Female,PhD,Data Scientist,9.0,above average
+29.0,Male,Bachelor's Degree,Marketing Analyst,4.0,below average
+33.0,Female,Master's Degree,Marketing Manager,9.0,above average
+27.0,Male,Bachelor's Degree,Software Engineer,3.0,below average
+36.0,Female,PhD,Research Scientist,13.0,high
+25.0,Male,Bachelor's Degree,Product Manager,1.0,below average
+30.0,Female,Bachelor's Degree,Marketing Coordinator,5.0,average
+34.0,Male,PhD,Research Director,12.0,high
+28.0,Female,Bachelor's Degree,Marketing Analyst,3.0,below average
+32.0,Male,Bachelor's Degree,Product Manager,7.0,average
+24.0,Female,High School,Receptionist,0.0,minimal
+38.0,Male,Master's Degree,Marketing Director,14.0,high
+40.0,Female,Bachelor's Degree,Financial Manager,16.0,high
+27.0,Male,Bachelor's Degree,Product Designer,2.0,minimal
+32.0,Female,PhD,Data Scientist,9.0,above average
+29.0,Male,Bachelor's Degree,Marketing Analyst,4.0,below average
+33.0,Female,Master's Degree,Marketing Manager,9.0,above average
+27.0,Male,Bachelor's Degree,Software Engineer,3.0,below average
+36.0,Female,PhD,Research Scientist,13.0,high
+25.0,Male,Bachelor's Degree,Product Manager,1.0,below average
+30.0,Female,Bachelor's Degree,Marketing Coordinator,5.0,average
+34.0,Male,PhD,Research Director,12.0,high
+28.0,Female,Bachelor's Degree,Marketing Analyst,3.0,below average
+32.0,Male,Bachelor's Degree,Product Manager,7.0,average
+24.0,Female,High School,Receptionist,0.0,minimal
+38.0,Male,Master's Degree,Marketing Director,14.0,high
+40.0,Female,Bachelor's Degree,Financial Manager,16.0,high
+27.0,Male,Bachelor's Degree,Product Designer,2.0,minimal
+32.0,Female,PhD,Data Scientist,9.0,above average
+29.0,Male,Bachelor's Degree,Marketing Analyst,4.0,below average
+33.0,Female,Master's Degree,Marketing Manager,9.0,above average
+27.0,Male,Bachelor's Degree,Software Engineer,3.0,below average
+36.0,Female,PhD,Research Scientist,13.0,high
+25.0,Male,Bachelor's Degree,Product Manager,1.0,below average
+30.0,Female,Bachelor's Degree,Marketing Coordinator,5.0,average
+34.0,Male,PhD,Research Director,12.0,high
+28.0,Female,Bachelor's Degree,Marketing Analyst,3.0,below average
+32.0,Male,Bachelor's Degree,Product Manager,7.0,average
+24.0,Female,High School,Receptionist,0.0,minimal
+38.0,Male,Master's Degree,Marketing Director,14.0,high
+40.0,Female,Bachelor's Degree,Financial Manager,16.0,high
+27.0,Male,Bachelor's Degree,Product Designer,2.0,minimal
+32.0,Female,PhD,Data Scientist,9.0,above average
+29.0,Male,Bachelor's Degree,Marketing Analyst,4.0,below average
+33.0,Female,Master's Degree,Marketing Manager,9.0,above average
+27.0,Male,Bachelor's Degree,Software Engineer,3.0,below average
+36.0,Female,PhD,Research Scientist,13.0,high
+25.0,Male,Bachelor's Degree,Product Manager,1.0,below average
+30.0,Female,Bachelor's Degree,Marketing Coordinator,5.0,average
+34.0,Male,PhD,Research Director,12.0,high
+28.0,Female,Bachelor's Degree,Marketing Analyst,3.0,below average
+32.0,Male,Bachelor's Degree,Product Manager,7.0,average
+24.0,Female,High School,Receptionist,0.0,minimal
+38.0,Male,Master's Degree,Marketing Director,14.0,high
+40.0,Female,Bachelor's Degree,Financial Manager,16.0,high
+27.0,Male,Bachelor's Degree,Product Designer,2.0,minimal
+32.0,Female,PhD,Data Scientist,9.0,above average
+29.0,Male,Bachelor's Degree,Marketing Analyst,4.0,below average
+33.0,Female,Master's Degree,Marketing Manager,9.0,above average
+27.0,Male,Bachelor's Degree,Software Engineer,3.0,below average
+36.0,Female,PhD,Research Scientist,13.0,high
+25.0,Male,Bachelor's Degree,Product Manager,1.0,below average
+30.0,Female,Bachelor's Degree,Marketing Coordinator,5.0,average
+34.0,Male,PhD,Research Director,12.0,high
+28.0,Female,Bachelor's Degree,Marketing Analyst,3.0,below average
+32.0,Male,Bachelor's Degree,Product Manager,7.0,average
+24.0,Female,High School,Receptionist,0.0,minimal
+38.0,Male,Master's Degree,Marketing Director,14.0,high
+40.0,Female,Bachelor's Degree,Financial Manager,16.0,high
+27.0,Male,Bachelor's Degree,Product Designer,2.0,minimal
+32.0,Female,PhD,Data Scientist,9.0,above average
+29.0,Male,Bachelor's Degree,Marketing Analyst,4.0,below average
+33.0,Female,Master's Degree,Marketing Manager,9.0,above average
+27.0,Male,Bachelor's Degree,Software Engineer,3.0,below average
+36.0,Female,PhD,Research Scientist,13.0,high
+25.0,Male,Bachelor's Degree,Product Manager,1.0,below average
+30.0,Female,Bachelor's Degree,Marketing Coordinator,5.0,average
+34.0,Male,PhD,Research Director,12.0,high
+28.0,Female,Bachelor's Degree,Marketing Analyst,3.0,below average
+32.0,Male,Bachelor's Degree,Product Manager,7.0,average
+24.0,Female,High School,Receptionist,0.0,minimal
+38.0,Male,Master's Degree,Marketing Director,14.0,high
+40.0,Female,Bachelor's Degree,Financial Manager,16.0,high
+26.0,Female,Master's Degree,Software Engineer,2.0,below average
+39.0,Male,PhD,Research Scientist,14.0,high
+32.0,Female,Bachelor's Degree,Marketing Manager,7.0,average
+28.0,Male,Bachelor's Degree,Graphic Designer,3.0,below average
+35.0,Female,Master's Degree,Data Scientist,10.0,above average
+29.0,Male,Bachelor's Degree,Marketing Analyst,4.0,below average
+33.0,Female,Master's Degree,Product Manager,8.0,above average
+27.0,Male,Bachelor's Degree,Software Engineer,2.0,below average
+36.0,Female,PhD,Research Director,12.0,high
+24.0,Male,High School,Delivery Driver,0.0,minimal
+38.0,Male,Master's Degree,Marketing Director,14.0,high
+40.0,Female,Bachelor's Degree,Financial Manager,16.0,high
+27.0,Male,Bachelor's Degree,Product Designer,2.0,minimal
+32.0,Female,PhD,Data Scientist,9.0,above average
+29.0,Male,Bachelor's Degree,Marketing Analyst,4.0,below average
+33.0,Female,Master's Degree,Marketing Manager,9.0,above average
+27.0,Male,Bachelor's Degree,Software Engineer,3.0,below average
+36.0,Female,PhD,Research Scientist,13.0,high
+25.0,Male,Bachelor's Degree,Product Manager,1.0,below average
+30.0,Female,Bachelor's Degree,Marketing Coordinator,5.0,average
+34.0,Male,PhD,Research Director,12.0,high
+28.0,Female,Bachelor's Degree,Marketing Analyst,3.0,below average
+32.0,Male,Bachelor's Degree,Product Manager,7.0,average
+24.0,Female,High School,Receptionist,0.0,minimal
+38.0,Male,Master's Degree,Marketing Director,14.0,high
+40.0,Female,Bachelor's Degree,Financial Manager,16.0,high
+27.0,Male,Bachelor's Degree,Product Designer,2.0,minimal
+32.0,Female,PhD,Data Scientist,9.0,above average
+29.0,Male,Bachelor's Degree,Marketing Analyst,4.0,below average
+33.0,Female,Master's Degree,Marketing Manager,9.0,above average
+27.0,Male,Bachelor's Degree,Software Engineer,3.0,below average
+36.0,Female,PhD,Research Scientist,13.0,high
+25.0,Male,Bachelor's Degree,Product Manager,1.0,below average
+30.0,Female,Bachelor's Degree,Marketing Coordinator,5.0,average
+34.0,Male,PhD,Research Director,12.0,high
+28.0,Female,Bachelor's Degree,Marketing Analyst,3.0,below average
+32.0,Male,Bachelor's Degree,Product Manager,7.0,average
+24.0,Female,High School,Receptionist,0.0,minimal
+38.0,Male,Master's Degree,Marketing Director,14.0,high
+40.0,Female,Bachelor's Degree,Financial Manager,16.0,high
+27.0,Male,Bachelor's Degree,Product Designer,2.0,minimal
+32.0,Female,PhD,Data Scientist,9.0,above average
+29.0,Male,Bachelor's Degree,Marketing Analyst,4.0,below average
+33.0,Female,Master's Degree,Marketing Manager,9.0,above average
+27.0,Male,Bachelor's Degree,Software Engineer,3.0,below average
+36.0,Female,PhD,Research Scientist,13.0,high
+25.0,Male,Bachelor's Degree,Product Manager,1.0,below average
+30.0,Female,Bachelor's Degree,Marketing Coordinator,5.0,average
+34.0,Male,PhD,Research Director,12.0,high
+28.0,Female,Bachelor's Degree,Marketing Analyst,3.0,below average
+32.0,Male,Bachelor's Degree,Product Manager,7.0,average
+24.0,Female,High School,Receptionist,0.0,minimal
+38.0,Male,Master's Degree,Marketing Director,14.0,high
+40.0,Female,Bachelor's Degree,Financial Manager,16.0,high
+27.0,Male,Bachelor's Degree,Product Designer,2.0,minimal
+32.0,Female,PhD,Data Scientist,9.0,above average
+29.0,Male,Bachelor's Degree,Marketing Analyst,4.0,below average
+33.0,Female,Master's Degree,Marketing Manager,9.0,above average
+27.0,Male,Bachelor's Degree,Software Engineer,3.0,below average
+36.0,Female,PhD,Research Scientist,13.0,high
+25.0,Male,Bachelor's Degree,Product Manager,1.0,below average
+30.0,Female,Bachelor's Degree,Marketing Coordinator,5.0,average
+34.0,Male,PhD,Research Director,12.0,high
+28.0,Female,Bachelor's Degree,Marketing Analyst,3.0,below average
+32.0,Male,Bachelor's Degree,Product Manager,7.0,average
+24.0,Female,High School,Receptionist,0.0,minimal
+38.0,Male,Master's Degree,Marketing Director,14.0,high
+40.0,Female,Bachelor's Degree,Financial Manager,16.0,high
+27.0,Male,Bachelor's Degree,Product Designer,2.0,minimal
+32.0,Female,PhD,Data Scientist,9.0,above average
+29.0,Male,Bachelor's Degree,Marketing Analyst,4.0,below average
+33.0,Female,Master's Degree,Marketing Manager,9.0,above average
+27.0,Male,Bachelor's Degree,Software Engineer,3.0,below average
+36.0,Female,PhD,Research Scientist,13.0,high
+25.0,Male,Bachelor's Degree,Product Manager,1.0,below average
+30.0,Female,Bachelor's Degree,Marketing Coordinator,5.0,average
+34.0,Male,PhD,Research Director,12.0,high
+28.0,Female,Bachelor's Degree,Marketing Analyst,3.0,below average
+32.0,Male,Bachelor's Degree,Product Manager,7.0,average
+24.0,Female,High School,Receptionist,0.0,minimal
+38.0,Male,Master's Degree,Marketing Director,14.0,high
+40.0,Female,Bachelor's Degree,Financial Manager,16.0,high
+27.0,Male,Bachelor's Degree,Product Designer,2.0,minimal
+32.0,Female,PhD,Data Scientist,9.0,above average
+29.0,Male,Bachelor's Degree,Marketing Analyst,4.0,below average
+33.0,Female,Master's Degree,Marketing Manager,9.0,above average
+27.0,Male,Bachelor's Degree,Software Engineer,3.0,below average
+36.0,Female,PhD,Research Scientist,13.0,high
+25.0,Male,Bachelor's Degree,Product Manager,1.0,below average
+30.0,Female,Bachelor's Degree,Marketing Coordinator,5.0,average
+34.0,Male,PhD,Research Director,12.0,high
+28.0,Female,Bachelor's Degree,Marketing Analyst,3.0,below average
+32.0,Male,Bachelor's Degree,Product Manager,7.0,average
+24.0,Female,High School,Receptionist,0.0,minimal
+38.0,Male,Master's Degree,Marketing Director,14.0,high
+40.0,Female,Bachelor's Degree,Financial Manager,16.0,high
+27.0,Male,Bachelor's Degree,Product Designer,2.0,minimal
+32.0,Female,PhD,Data Scientist,9.0,above average
+29.0,Male,Bachelor's Degree,Marketing Analyst,4.0,below average
+33.0,Female,Master's Degree,Marketing Manager,9.0,above average
+27.0,Male,Bachelor's Degree,Software Engineer,3.0,below average
+36.0,Female,PhD,Research Scientist,13.0,high
+25.0,Male,Bachelor's Degree,Product Manager,1.0,below average
+30.0,Female,Bachelor's Degree,Marketing Coordinator,5.0,average
+34.0,Male,PhD,Research Director,12.0,high
+28.0,Female,Bachelor's Degree,Marketing Analyst,3.0,below average
+32.0,Male,Bachelor's Degree,Product Manager,7.0,average
+24.0,Female,High School,Receptionist,0.0,minimal
+38.0,Male,Master's Degree,Marketing Director,14.0,high
+40.0,Female,Bachelor's Degree,Financial Manager,16.0,high
+27.0,Male,Bachelor's Degree,Product Designer,2.0,minimal
+32.0,Female,PhD,Data Scientist,9.0,above average
+29.0,Male,Bachelor's Degree,Marketing Analyst,4.0,below average
+33.0,Female,Master's Degree,Marketing Manager,9.0,above average
+27.0,Male,Bachelor's Degree,Software Engineer,3.0,below average
+36.0,Female,PhD,Research Scientist,13.0,high
+25.0,Male,Bachelor's Degree,Product Manager,1.0,below average
+30.0,Female,Bachelor's Degree,Marketing Coordinator,5.0,average
+34.0,Male,PhD,Research Director,12.0,high
+28.0,Female,Bachelor's Degree,Marketing Analyst,3.0,below average
+32.0,Male,Bachelor's Degree,Product Manager,7.0,average
+24.0,Female,High School,Receptionist,0.0,minimal
+38.0,Male,Master's Degree,Marketing Director,14.0,high
+40.0,Female,Bachelor's Degree,Financial Manager,16.0,high
+27.0,Male,Bachelor's Degree,Product Designer,2.0,minimal
+32.0,Female,PhD,Data Scientist,9.0,above average
+29.0,Male,Bachelor's Degree,Marketing Analyst,4.0,below average
+29.0,Male,Bachelor's Degree,Sales Associate,2.0,minimal
+45.0,Female,Master's Degree,Sales Manager,8.0,below average
+37.0,Male,PhD,Marketing Manager,7.0,below average
+23.0,Female,High School,Sales Executive,1.0,minimal
+41.0,Male,Bachelor's Degree,Financial Manager,12.0,average
+26.0,Female,Bachelor's Degree,Digital Marketing Manager,4.0,below average
+33.0,Male,Master's Degree,Content Marketing Manager,5.0,below average
+28.0,Female,High School,Sales Representative,3.0,minimal
+50.0,Male,PhD,Senior Product Marketing Manager,15.0,above average
+35.0,Female,Bachelor's Degree,Junior Sales Representative,2.0,minimal
+42.0,Male,Master's Degree,Director of Marketing,13.0,above average
+27.0,Female,Bachelor's Degree,Sales Associate,1.0,minimal
+48.0,Male,PhD,Sales Director,18.0,high
+31.0,Female,High School,Financial Manager,4.0,below average
+36.0,Male,Bachelor's Degree,Sales Manager,6.0,below average
+25.0,Female,Master's Degree,Digital Marketing Manager,3.0,minimal
+39.0,Male,PhD,Marketing Manager,10.0,average
+30.0,Female,High School,Sales Executive,2.0,minimal
+44.0,Male,Bachelor's Degree,Content Marketing Manager,11.0,average
+29.0,Female,Master's Degree,Sales Representative,4.0,minimal
+47.0,Male,PhD,Senior Product Marketing Manager,17.0,high
+32.0,Female,Bachelor's Degree,Junior Sales Representative,3.0,minimal
+38.0,Male,Master's Degree,Director of Marketing,9.0,average
+24.0,Female,High School,Sales Associate,1.0,minimal
+40.0,Male,PhD,Sales Director,14.0,above average
+34.0,Female,Bachelor's Degree,Financial Manager,5.0,below average
+26.0,Male,Master's Degree,Digital Marketing Manager,3.0,minimal
+31.0,Female,PhD,Marketing Manager,6.0,below average
+27.0,Male,High School,Sales Executive,2.0,minimal
+43.0,Female,Bachelor's Degree,Content Marketing Manager,12.0,average
+28.0,Male,Master's Degree,Sales Representative,2.0,minimal
+46.0,Female,PhD,Senior Product Marketing Manager,16.0,above average
+33.0,Male,Bachelor's Degree,Junior Sales Representative,4.0,minimal
+39.0,Female,Master's Degree,Director of Marketing,10.0,average
+25.0,Male,High School,Sales Associate,1.0,minimal
+41.0,Female,Bachelor's Degree,Sales Manager,8.0,below average
+35.0,Male,PhD,Marketing Manager,7.0,below average
+23.0,Female,Bachelor's Degree,Sales Executive,1.0,minimal
+42.0,Male,Master's Degree,Financial Manager,13.0,above average
+26.0,Female,Bachelor's Degree,Digital Marketing Manager,4.0,below average
+32.0,Male,Master's Degree,Content Marketing Manager,5.0,below average
+27.0,Female,High School,Sales Representative,3.0,minimal
+50.0,Male,PhD,Senior Product Marketing Manager,15.0,above average
+36.0,Female,Bachelor's Degree,Junior Sales Representative,2.0,minimal
+48.0,Male,Master's Degree,Director of Marketing,18.0,high
+31.0,Female,High School,Sales Associate,2.0,minimal
+29.0,Male,Bachelor's Degree,Sales Director,6.0,below average
+45.0,Female,PhD,Financial Manager,12.0,average
+25.0,Male,Master's Degree,Digital Marketing Manager,3.0,minimal
+37.0,Female,Bachelor's Degree,Marketing Manager,7.0,below average
+23.0,Male,High School,Sales Executive,1.0,minimal
+41.0,Female,Bachelor's Degree,Content Marketing Manager,11.0,average
+26.0,Male,Master's Degree,Sales Representative,3.0,minimal
+33.0,Female,PhD,Senior Product Marketing Manager,5.0,below average
+28.0,Male,Bachelor's Degree,Junior Sales Representative,1.0,minimal
+42.0,Female,Master's Degree,Director of Marketing,13.0,above average
+27.0,Male,High School,Financial Manager,4.0,below average
+50.0,Female,Bachelor's Degree,Sales Manager,15.0,above average
+35.0,Male,PhD,Marketing Manager,8.0,below average
+24.0,Female,Bachelor's Degree,Sales Executive,1.0,minimal
+46.0,Male,Master's Degree,Content Marketing Manager,16.0,above average
+29.0,Female,High School,Sales Representative,2.0,minimal
+47.0,Male,PhD,Senior Product Marketing Manager,17.0,high
+31.0,Female,Bachelor's Degree,Junior Sales Representative,3.0,minimal
+38.0,Male,Master's Degree,Director of Marketing,9.0,average
+25.0,Female,High School,Sales Associate,1.0,minimal
+39.0,Male,Bachelor's Degree,Sales Director,10.0,average
+33.0,Female,PhD,Financial Manager,5.0,below average
+27.0,Male,Master's Degree,Digital Marketing Manager,3.0,minimal
+43.0,Female,Bachelor's Degree,Marketing Manager,12.0,average
+28.0,Male,High School,Sales Executive,2.0,minimal
+31.0,Male,Bachelor's Degree,Sales Associate,3.0,minimal
+46.0,Female,Master's Degree,Marketing Manager,14.0,above average
+27.0,Male,High School,Sales Executive,2.0,minimal
+38.0,Female,Bachelor's Degree,Financial Manager,10.0,average
+24.0,Male,PhD,Digital Marketing Manager,1.0,minimal
+33.0,Female,Master's Degree,Content Marketing Manager,6.0,below average
+29.0,Male,High School,Sales Representative,2.0,minimal
+50.0,Female,Bachelor's Degree,Sales Manager,18.0,high
+35.0,Male,PhD,Senior Product Marketing Manager,8.0,below average
+23.0,Female,Bachelor's Degree,Sales Executive,1.0,minimal
+41.0,Male,Master's Degree,Director of Marketing,12.0,average
+26.0,Female,High School,Financial Manager,3.0,minimal
+32.0,Male,Bachelor's Degree,Sales Director,7.0,below average
+27.0,Female,PhD,Marketing Manager,4.0,minimal
+43.0,Male,Master's Degree,Content Marketing Manager,16.0,above average
+28.0,Female,Bachelor's Degree,Sales Representative,2.0,minimal
+47.0,Male,PhD,Senior Product Marketing Manager,17.0,high
+31.0,Female,High School,Junior Sales Representative,3.0,minimal
+38.0,Male,Master's Degree,Director of Marketing,9.0,average
+25.0,Female,High School,Sales Associate,1.0,minimal
+39.0,Male,Bachelor's Degree,Sales Manager,11.0,average
+33.0,Female,PhD,Financial Manager,6.0,below average
+27.0,Male,Master's Degree,Digital Marketing Manager,3.0,minimal
+43.0,Female,Bachelor's Degree,Marketing Manager,12.0,average
+28.0,Male,High School,Sales Executive,2.0,minimal
+50.0,Female,Master's Degree,Content Marketing Manager,15.0,above average
+36.0,Male,Bachelor's Degree,Sales Representative,5.0,below average
+48.0,Female,PhD,Senior Product Marketing Manager,19.0,high
+31.0,Male,High School,Junior Sales Representative,3.0,minimal
+29.0,Female,Bachelor's Degree,Sales Director,6.0,below average
+45.0,Male,Master's Degree,Director of Marketing,14.0,above average
+25.0,Female,High School,Sales Associate,1.0,minimal
+41.0,Male,Bachelor's Degree,Financial Manager,12.0,average
+35.0,Female,PhD,Marketing Manager,8.0,below average
+23.0,Male,Bachelor's Degree,Sales Executive,1.0,minimal
+42.0,Female,Master's Degree,Sales Manager,13.0,above average
+26.0,Male,High School,Digital Marketing Manager,2.0,minimal
+32.0,Female,Bachelor's Degree,Content Marketing Manager,7.0,below average
+27.0,Male,PhD,Sales Representative,4.0,minimal
+50.0,Female,Master's Degree,Senior Product Marketing Manager,18.0,high
+36.0,Male,Bachelor's Degree,Junior Sales Representative,3.0,minimal
+48.0,Female,PhD,Director of Marketing,19.0,high
+31.0,Male,High School,Sales Associate,3.0,minimal
+29.0,Female,Bachelor's Degree,Financial Manager,4.0,minimal
+45.0,Male,Master's Degree,Marketing Manager,13.0,above average
+25.0,Female,High School,Sales Executive,1.0,minimal
+41.0,Male,Bachelor's Degree,Content Marketing Manager,12.0,average
+35.0,Female,PhD,Senior Product Marketing Manager,9.0,average
+23.0,Male,Bachelor's Degree,Sales Representative,1.0,minimal
+42.0,Female,Master's Degree,Digital Marketing Manager,14.0,above average
+26.0,Male,High School,Sales Manager,2.0,minimal
+32.0,Female,Bachelor's Degree,Director of Marketing,8.0,below average
+27.0,Male,PhD,Marketing Manager,4.0,minimal
+50.0,Female,Master's Degree,Content Marketing Manager,19.0,high
+36.0,Male,Bachelor's Degree,Sales Director,6.0,below average
+48.0,Female,PhD,Senior Product Marketing Manager,17.0,high
+31.0,Male,High School,Sales Associate,3.0,minimal
+29.0,Female,Bachelor's Degree,Financial Manager,4.0,minimal
+45.0,Male,Master's Degree,Marketing Manager,13.0,above average
+25.0,Female,High School,Sales Executive,1.0,minimal
+41.0,Male,Bachelor's Degree,Content Marketing Manager,12.0,average
+35.0,Female,PhD,Senior Product Marketing Manager,9.0,average
+23.0,Male,Bachelor's Degree,Sales Representative,1.0,minimal
+42.0,Female,Master's Degree,Digital Marketing Manager,14.0,above average
+26.0,Male,High School,Sales Manager,2.0,minimal
+32.0,Female,Bachelor's Degree,Director of Marketing,8.0,below average
+27.0,Male,PhD,Marketing Manager,4.0,minimal
+50.0,Female,Master's Degree,Content Marketing Manager,19.0,high
+36.0,Male,Bachelor's Degree,Sales Director,6.0,below average
+48.0,Female,PhD,Senior Product Marketing Manager,17.0,high
+31.0,Male,High School,Sales Associate,3.0,minimal
+29.0,Female,Bachelor's Degree,Financial Manager,4.0,minimal
+45.0,Male,Master's Degree,Marketing Manager,13.0,above average
+25.0,Female,High School,Sales Executive,1.0,minimal
+41.0,Male,Bachelor's Degree,Content Marketing Manager,12.0,average
+35.0,Female,PhD,Senior Product Marketing Manager,9.0,average
+23.0,Male,Bachelor's Degree,Sales Representative,1.0,minimal
+42.0,Female,Master's Degree,Digital Marketing Manager,14.0,above average
+26.0,Male,High School,Sales Manager,2.0,minimal
+32.0,Female,Bachelor's Degree,Director of Marketing,8.0,below average
+27.0,Male,PhD,Marketing Manager,4.0,minimal
+50.0,Female,Master's Degree,Content Marketing Manager,19.0,high
+36.0,Male,Bachelor's Degree,Sales Director,6.0,below average
+48.0,Female,PhD,Senior Product Marketing Manager,17.0,high
+31.0,Male,High School,Sales Associate,3.0,minimal
+29.0,Female,Bachelor's Degree,Financial Manager,4.0,minimal
+45.0,Male,Master's Degree,Marketing Manager,13.0,above average
+25.0,Female,High School,Sales Executive,1.0,minimal
+41.0,Male,Bachelor's Degree,Content Marketing Manager,12.0,average
+35.0,Female,PhD,Senior Product Marketing Manager,9.0,average
+23.0,Male,Bachelor's Degree,Sales Representative,1.0,minimal
+42.0,Female,Master's Degree,Digital Marketing Manager,14.0,above average
+26.0,Male,High School,Sales Manager,2.0,minimal
+32.0,Female,Bachelor's Degree,Director of Marketing,8.0,below average
+27.0,Male,PhD,Marketing Manager,4.0,minimal
+50.0,Female,Master's Degree,Content Marketing Manager,19.0,high
+36.0,Male,Bachelor's Degree,Sales Director,6.0,below average
+48.0,Female,PhD,Senior Product Marketing Manager,17.0,high
+31.0,Male,High School,Sales Associate,3.0,minimal
+29.0,Female,Bachelor's Degree,Financial Manager,4.0,minimal
+45.0,Male,Master's Degree,Marketing Manager,13.0,above average
+25.0,Female,High School,Sales Executive,1.0,minimal
+41.0,Male,Bachelor's Degree,Content Marketing Manager,12.0,average
+35.0,Female,PhD,Senior Product Marketing Manager,9.0,average
+23.0,Male,Bachelor's Degree,Sales Representative,1.0,minimal
+42.0,Female,Master's Degree,Digital Marketing Manager,14.0,above average
+26.0,Male,High School,Sales Manager,2.0,minimal
+32.0,Female,Bachelor's Degree,Director of Marketing,8.0,below average
+27.0,Male,PhD,Marketing Manager,4.0,minimal
+50.0,Female,Master's Degree,Content Marketing Manager,19.0,high
+36.0,Male,Bachelor's Degree,Sales Director,6.0,below average
+48.0,Female,PhD,Senior Product Marketing Manager,17.0,high
+31.0,Male,High School,Sales Associate,3.0,minimal
+29.0,Female,Bachelor's Degree,Financial Manager,4.0,minimal
+45.0,Male,Master's Degree,Marketing Manager,13.0,above average
+25.0,Female,High School,Sales Executive,1.0,minimal
+41.0,Male,Bachelor's Degree,Content Marketing Manager,12.0,average
+35.0,Female,PhD,Senior Product Marketing Manager,9.0,average
+23.0,Male,Bachelor's Degree,Sales Representative,1.0,minimal
+42.0,Female,Master's Degree,Digital Marketing Manager,14.0,above average
+26.0,Male,High School,Sales Manager,2.0,minimal
+32.0,Female,Bachelor's Degree,Director of Marketing,8.0,below average
+27.0,Male,PhD,Marketing Manager,4.0,minimal
+50.0,Female,Master's Degree,Content Marketing Manager,19.0,high
+36.0,Male,Bachelor's Degree,Sales Director,6.0,average
+37.0,Male,Master's Degree,Marketing Manager,11.0,average
+26.0,Female,Bachelor's Degree,Sales Representative,2.0,minimal
+42.0,Male,PhD,Content Marketing Manager,15.0,above average
+33.0,Female,High School,Sales Executive,4.0,minimal
+29.0,Male,Bachelor's Degree,Sales Manager,5.0,below average
+45.0,Female,Master's Degree,Director of Marketing,16.0,above average
+24.0,Male,High School,Sales Associate,1.0,minimal
+39.0,Female,Bachelor's Degree,Financial Manager,10.0,average
+31.0,Male,PhD,Senior Product Marketing Manager,7.0,below average
+27.0,Female,Master's Degree,Digital Marketing Manager,3.0,minimal
+43.0,Male,Bachelor's Degree,Content Marketing Manager,14.0,above average
+28.0,Female,High School,Sales Representative,2.0,minimal
+50.0,Male,PhD,Marketing Manager,18.0,high
+35.0,Female,Bachelor's Degree,Sales Executive,7.0,below average
+23.0,Male,Bachelor's Degree,Sales Manager,1.0,minimal
+41.0,Female,Master's Degree,Director of Marketing,12.0,average
+26.0,Male,High School,Financial Manager,3.0,minimal
+32.0,Female,Bachelor's Degree,Sales Director,8.0,below average
+27.0,Male,PhD,Marketing Manager,4.0,minimal
+50.0,Female,Master's Degree,Content Marketing Manager,18.0,high
+36.0,Male,Bachelor's Degree,Sales Representative,6.0,below average
+48.0,Female,PhD,Senior Product Marketing Manager,19.0,high
+31.0,Male,High School,Junior Sales Representative,3.0,minimal
+29.0,Female,Bachelor's Degree,Sales Director,5.0,below average
+45.0,Male,Master's Degree,Director of Marketing,15.0,above average
+25.0,Female,High School,Sales Associate,1.0,minimal
+41.0,Male,Bachelor's Degree,Financial Manager,12.0,average
+35.0,Female,PhD,Marketing Manager,8.0,below average
+23.0,Male,Bachelor's Degree,Sales Executive,1.0,minimal
+42.0,Female,Master's Degree,Sales Manager,13.0,above average
+26.0,Male,High School,Digital Marketing Manager,2.0,minimal
+32.0,Female,Bachelor's Degree,Content Marketing Manager,7.0,below average
+27.0,Male,PhD,Sales Representative,4.0,minimal
+50.0,Female,Master's Degree,Senior Product Marketing Manager,18.0,high
+36.0,Male,Bachelor's Degree,Junior Sales Representative,3.0,minimal
+48.0,Female,PhD,Director of Marketing,19.0,high
+31.0,Male,High School,Sales Associate,3.0,minimal
+29.0,Female,Bachelor's Degree,Financial Manager,4.0,minimal
+45.0,Male,Master's Degree,Marketing Manager,13.0,above average
+25.0,Female,High School,Sales Executive,1.0,minimal
+41.0,Male,Bachelor's Degree,Content Marketing Manager,12.0,average
+35.0,Female,PhD,Senior Product Marketing Manager,9.0,average
+23.0,Male,Bachelor's Degree,Sales Representative,1.0,minimal
+42.0,Female,Master's Degree,Digital Marketing Manager,14.0,above average
+26.0,Male,High School,Sales Manager,2.0,minimal
+32.0,Female,Bachelor's Degree,Director of Marketing,8.0,below average
+27.0,Male,PhD,Marketing Manager,4.0,minimal
+50.0,Female,Master's Degree,Content Marketing Manager,19.0,high
+36.0,Male,Bachelor's Degree,Sales Director,6.0,below average
+48.0,Female,PhD,Senior Product Marketing Manager,17.0,high
+31.0,Male,High School,Sales Associate,3.0,minimal
+29.0,Female,Bachelor's Degree,Financial Manager,4.0,minimal
+45.0,Male,Master's Degree,Marketing Manager,13.0,above average
+25.0,Female,High School,Sales Executive,1.0,minimal
+41.0,Male,Bachelor's Degree,Content Marketing Manager,12.0,average
+35.0,Female,PhD,Senior Product Marketing Manager,9.0,average
+23.0,Male,Bachelor's Degree,Sales Representative,1.0,minimal
+42.0,Female,Master's Degree,Digital Marketing Manager,14.0,above average
+26.0,Male,High School,Sales Manager,2.0,minimal
+32.0,Female,Bachelor's Degree,Director of Marketing,8.0,below average
+27.0,Male,PhD,Marketing Manager,4.0,minimal
+50.0,Female,Master's Degree,Content Marketing Manager,19.0,high
+36.0,Male,Bachelor's Degree,Sales Director,6.0,below average
+48.0,Female,PhD,Senior Product Marketing Manager,17.0,high
+31.0,Male,High School,Sales Associate,3.0,minimal
+29.0,Female,Bachelor's Degree,Financial Manager,4.0,minimal
+45.0,Male,Master's Degree,Marketing Manager,13.0,above average
+25.0,Female,High School,Sales Executive,1.0,minimal
+41.0,Male,Bachelor's Degree,Content Marketing Manager,12.0,average
+35.0,Female,PhD,Senior Product Marketing Manager,9.0,average
+23.0,Male,Bachelor's Degree,Sales Representative,1.0,minimal
+42.0,Female,Master's Degree,Digital Marketing Manager,14.0,above average
+26.0,Male,High School,Sales Manager,2.0,minimal
+32.0,Female,Bachelor's Degree,Director of Marketing,8.0,below average
+27.0,Male,PhD,Marketing Manager,4.0,minimal
+50.0,Female,Master's Degree,Content Marketing Manager,19.0,high
+36.0,Male,Bachelor's Degree,Sales Director,6.0,below average
+48.0,Female,PhD,Senior Product Marketing Manager,17.0,high
+31.0,Male,High School,Sales Associate,3.0,minimal
+29.0,Female,Bachelor's Degree,Financial Manager,4.0,minimal
+45.0,Male,Master's Degree,Marketing Manager,13.0,above average
+25.0,Female,High School,Sales Executive,1.0,minimal
+41.0,Male,Bachelor's Degree,Content Marketing Manager,12.0,average
+35.0,Female,PhD,Senior Product Marketing Manager,9.0,average
+23.0,Male,Bachelor's Degree,Sales Representative,1.0,minimal
+42.0,Female,Master's Degree,Digital Marketing Manager,14.0,above average
+26.0,Male,High School,Sales Manager,2.0,minimal
+32.0,Female,Bachelor's Degree,Director of Marketing,8.0,below average
+27.0,Male,PhD,Marketing Manager,4.0,minimal
+50.0,Female,Master's Degree,Content Marketing Manager,19.0,high
+36.0,Male,Bachelor's Degree,Sales Director,6.0,below average
+48.0,Female,PhD,Senior Product Marketing Manager,17.0,high
+31.0,Male,High School,Sales Associate,3.0,minimal
+29.0,Female,Bachelor's Degree,Financial Manager,4.0,minimal
+45.0,Male,Master's Degree,Marketing Manager,13.0,above average
+25.0,Female,High School,Sales Executive,1.0,minimal
+41.0,Male,Bachelor's Degree,Content Marketing Manager,12.0,average
+35.0,Female,PhD,Senior Product Marketing Manager,9.0,average
+23.0,Male,Bachelor's Degree,Sales Representative,1.0,minimal
+42.0,Female,Master's Degree,Digital Marketing Manager,14.0,above average
+26.0,Male,High School,Sales Manager,2.0,minimal
+32.0,Female,Bachelor's Degree,Director of Marketing,8.0,below average
+27.0,Male,PhD,Marketing Manager,4.0,minimal
+50.0,Female,Master's Degree,Content Marketing Manager,19.0,high
+36.0,Male,Bachelor's Degree,Sales Director,6.0,below average
+48.0,Female,PhD,Senior Product Marketing Manager,17.0,high
+31.0,Male,High School,Sales Associate,3.0,minimal
+29.0,Female,Bachelor's Degree,Financial Manager,4.0,minimal
+45.0,Male,Master's Degree,Marketing Manager,13.0,above average
+25.0,Female,High School,Sales Executive,1.0,minimal
+41.0,Male,Bachelor's Degree,Content Marketing Manager,12.0,average
+35.0,Female,PhD,Senior Product Marketing Manager,9.0,average
+23.0,Male,Bachelor's Degree,Sales Representative,1.0,minimal
+42.0,Female,Master's Degree,Digital Marketing Manager,14.0,above average
+26.0,Male,High School,Sales Manager,2.0,minimal
+32.0,Female,Bachelor's Degree,Director of Marketing,8.0,below average
+27.0,Male,PhD,Marketing Manager,4.0,minimal
+50.0,Female,Master's Degree,Content Marketing Manager,19.0,high
+36.0,Male,Bachelor's Degree,Sales Director,6.0,below average
+48.0,Female,PhD,Senior Product Marketing Manager,17.0,high
+31.0,Male,High School,Sales Associate,3.0,minimal
+29.0,Female,Bachelor's Degree,Financial Manager,4.0,minimal
+45.0,Male,Master's Degree,Marketing Manager,13.0,above average
+25.0,Female,High School,Sales Executive,1.0,minimal
+38.0,Male,Master's Degree,Marketing Manager,12.0,average
+27.0,Female,Bachelor's Degree,Sales Representative,3.0,minimal
+43.0,Male,PhD,Content Marketing Manager,16.0,above average
+34.0,Female,High School,Sales Executive,5.0,below average
+30.0,Male,Bachelor's Degree,Sales Manager,6.0,below average
+46.0,Female,Master's Degree,Director of Marketing,17.0,high
+25.0,Male,High School,Sales Associate,1.0,minimal
+40.0,Female,Bachelor's Degree,Financial Manager,11.0,average
+32.0,Male,PhD,Senior Product Marketing Manager,8.0,below average
+28.0,Female,Master's Degree,Digital Marketing Manager,4.0,minimal
+44.0,Male,Bachelor's Degree,Content Marketing Manager,15.0,above average
+29.0,Female,High School,Sales Representative,2.0,minimal
+51.0,Male,PhD,Marketing Manager,19.0,high
+36.0,Female,Bachelor's Degree,Sales Executive,8.0,below average
+24.0,Male,Bachelor's Degree,Sales Manager,1.0,minimal
+42.0,Female,Master's Degree,Director of Marketing,13.0,above average
+27.0,Male,High School,Financial Manager,3.0,minimal
+33.0,Female,Bachelor's Degree,Sales Director,7.0,below average
+28.0,Male,PhD,Marketing Manager,4.0,minimal
+51.0,Female,Master's Degree,Content Marketing Manager,19.0,high
+37.0,Male,Bachelor's Degree,Sales Representative,7.0,below average
+49.0,Female,PhD,Senior Product Marketing Manager,20.0,high
+32.0,Male,High School,Junior Sales Representative,3.0,minimal
+30.0,Female,Bachelor's Degree,Sales Director,5.0,below average
+46.0,Male,Master's Degree,Director of Marketing,16.0,above average
+26.0,Female,High School,Sales Associate,1.0,minimal
+42.0,Male,Bachelor's Degree,Financial Manager,13.0,above average
+36.0,Female,PhD,Marketing Manager,9.0,average
+24.0,Male,Bachelor's Degree,Sales Executive,1.0,minimal
+43.0,Female,Master's Degree,Sales Manager,14.0,above average
+27.0,Male,High School,Digital Marketing Manager,2.0,minimal
+33.0,Female,Bachelor's Degree,Content Marketing Manager,7.0,below average
+28.0,Male,PhD,Sales Representative,4.0,minimal
+51.0,Female,Master's Degree,Senior Product Marketing Manager,19.0,high
+37.0,Male,Bachelor's Degree,Junior Sales Representative,6.0,below average
+49.0,Female,PhD,Director of Marketing,20.0,high
+32.0,Male,High School,Sales Associate,3.0,minimal
+30.0,Female,Bachelor's Degree,Financial Manager,4.0,minimal
+46.0,Male,Master's Degree,Marketing Manager,14.0,above average
+26.0,Female,High School,Sales Executive,1.0,minimal
+42.0,Male,Bachelor's Degree,Content Marketing Manager,13.0,above average
+36.0,Female,PhD,Senior Product Marketing Manager,10.0,average
+24.0,Male,Bachelor's Degree,Sales Representative,1.0,minimal
+43.0,Female,Master's Degree,Digital Marketing Manager,15.0,above average
+27.0,Male,High School,Sales Manager,2.0,minimal
+33.0,Female,Bachelor's Degree,Director of Marketing,8.0,below average
+28.0,Male,PhD,Marketing Manager,4.0,minimal
+51.0,Female,Master's Degree,Content Marketing Manager,19.0,high
+37.0,Male,Bachelor's Degree,Sales Director,7.0,below average
+49.0,Female,PhD,Senior Product Marketing Manager,20.0,high
+32.0,Male,High School,Junior Sales Representative,3.0,minimal
+30.0,Female,Bachelor's Degree,Sales Manager,5.0,below average
+46.0,Male,Master's Degree,Director of Marketing,16.0,above average
+26.0,Female,High School,Sales Associate,1.0,minimal
+42.0,Male,Bachelor's Degree,Financial Manager,13.0,above average
+36.0,Female,PhD,Marketing Manager,9.0,average
+24.0,Male,Bachelor's Degree,Sales Executive,1.0,minimal
+43.0,Female,Master's Degree,Sales Manager,14.0,above average
+27.0,Male,High School,Digital Marketing Manager,2.0,minimal
+33.0,Female,Bachelor's Degree,Content Marketing Manager,7.0,below average
+28.0,Male,PhD,Sales Representative,4.0,minimal
+51.0,Female,Master's Degree,Senior Product Marketing Manager,19.0,high
+37.0,Male,Bachelor's Degree,Junior Sales Representative,6.0,below average
+49.0,Female,PhD,Director of Marketing,20.0,high
+32.0,Male,High School,Sales Associate,3.0,minimal
+30.0,Female,Bachelor's Degree,Financial Manager,4.0,minimal
+46.0,Male,Master's Degree,Marketing Manager,14.0,above average
+26.0,Female,High School,Sales Executive,1.0,minimal
+42.0,Male,Bachelor's Degree,Content Marketing Manager,13.0,above average
+36.0,Female,PhD,Senior Product Marketing Manager,10.0,average
+24.0,Male,Bachelor's Degree,Sales Representative,1.0,minimal
+43.0,Female,Master's Degree,Digital Marketing Manager,15.0,above average
+27.0,Male,High School,Sales Manager,2.0,minimal
+33.0,Female,Bachelor's Degree,Director of Marketing,8.0,below average
+28.0,Male,PhD,Marketing Manager,4.0,minimal
+51.0,Female,Master's Degree,Content Marketing Manager,19.0,high
+37.0,Male,Bachelor's Degree,Sales Director,7.0,below average
+49.0,Female,PhD,Senior Product Marketing Manager,20.0,high
+32.0,Male,High School,Junior Sales Representative,3.0,minimal
+30.0,Female,Bachelor's Degree,Sales Manager,5.0,below average
+46.0,Male,Master's Degree,Director of Marketing,16.0,above average
+26.0,Female,High School,Sales Associate,1.0,minimal
+42.0,Male,Bachelor's Degree,Financial Manager,13.0,above average
+36.0,Female,PhD,Marketing Manager,9.0,average
+24.0,Male,Bachelor's Degree,Sales Executive,1.0,minimal
+43.0,Female,Master's Degree,Sales Manager,14.0,above average
+27.0,Male,High School,Digital Marketing Manager,2.0,minimal
+33.0,Female,Bachelor's Degree,Content Marketing Manager,7.0,below average
+28.0,Male,PhD,Sales Representative,4.0,minimal
+51.0,Female,Master's Degree,Senior Product Marketing Manager,19.0,high
+37.0,Male,Bachelor's Degree,Junior Sales Representative,6.0,below average
+49.0,Female,PhD,Director of Marketing,20.0,high
+32.0,Male,High School,Sales Associate,3.0,minimal
+30.0,Female,Bachelor's Degree,Financial Manager,4.0,minimal
+46.0,Male,Master's Degree,Marketing Manager,14.0,above average
+26.0,Female,High School,Sales Executive,1.0,minimal
+42.0,Male,Bachelor's Degree,Content Marketing Manager,13.0,above average
+36.0,Female,PhD,Senior Product Marketing Manager,10.0,average
+24.0,Male,Bachelor's Degree,Sales Representative,1.0,minimal
+43.0,Female,Master's Degree,Digital Marketing Manager,15.0,above average
+27.0,Male,High School,Sales Manager,2.0,minimal
+33.0,Female,Bachelor's Degree,Director of Marketing,8.0,below average
+28.0,Male,PhD,Marketing Manager,4.0,minimal
+51.0,Female,Master's Degree,Content Marketing Manager,19.0,high
+37.0,Male,Bachelor's Degree,Sales Director,7.0,below average
+49.0,Female,PhD,Senior Product Marketing Manager,20.0,high
+32.0,Male,High School,Junior Sales Representative,3.0,minimal
+30.0,Female,Bachelor's Degree,Sales Manager,5.0,below average
+46.0,Male,Master's Degree,Director of Marketing,16.0,above average
+26.0,Female,High School,Sales Associate,1.0,minimal
+42.0,Male,Bachelor's Degree,Financial Manager,13.0,above average
+36.0,Female,PhD,Marketing Manager,9.0,average
+24.0,Male,Bachelor's Degree,Sales Executive,1.0,minimal
+43.0,Female,Master's Degree,Sales Manager,14.0,above average
+27.0,Male,High School,Digital Marketing Manager,2.0,minimal
+33.0,Female,Bachelor's Degree,Content Marketing Manager,7.0,below average
+28.0,Male,PhD,Sales Representative,4.0,minimal
+51.0,Female,Master's Degree,Senior Product Marketing Manager,19.0,high
+37.0,Male,Bachelor's Degree,Junior Sales Representative,6.0,below average
+49.0,Female,PhD,Director of Marketing,20.0,high
+32.0,Male,High School,Sales Associate,3.0,minimal
+30.0,Female,Bachelor's Degree,Financial Manager,4.0,minimal
+46.0,Male,Master's Degree,Marketing Manager,14.0,above average
+26.0,Female,High School,Sales Executive,1.0,minimal
diff --git a/tests/test_classifier.py b/tests/test_classifier.py
index 04fbf5d..6ca8b8f 100644
--- a/tests/test_classifier.py
+++ b/tests/test_classifier.py
@@ -8,9 +8,11 @@
 from scipy.io import arff
 from sklearn import metrics
 from sklearn.datasets import load_iris
+from sklearn.preprocessing import LabelEncoder
 
 from rulekit import classification
 from rulekit.events import RuleInductionProgressListener
+from rulekit.params import Measures
 from rulekit.rules import ClassificationRule
 from tests.utils import assert_accuracy_is_greater
 from tests.utils import assert_rules_are_equals
@@ -32,8 +34,9 @@ def test_classification_accuracy_on_iris(self):
         scikit_accuracy = metrics.accuracy_score(y, scikit_prediction)
         rulekit_accuracy = metrics.accuracy_score(y, rulekit_prediction)
 
-        assert abs(scikit_accuracy -
-                   rulekit_accuracy) < 0.04, 'RuleKit model should perform similar to scikit model'
+        assert (
+            abs(scikit_accuracy - rulekit_accuracy) < 0.04
+        ), "RuleKit model should perform similar to scikit model"
 
     def test_induction_progress_listener(self):
         rulekit_clf = classification.RuleClassifier()
@@ -51,9 +54,7 @@ def on_new_rule(self, rule: ClassificationRule):
                 self.lock.release()
 
             def on_progress(
-                self,
-                total_examples_count: int,
-                uncovered_examples_count: int
+                self, total_examples_count: int, uncovered_examples_count: int
             ):
                 self.lock.acquire()
                 self.on_progress_calls_count += 1
@@ -63,9 +64,7 @@ def on_progress(
         rulekit_clf.add_event_listener(listener)
         rulekit_clf.fit(x, y)
         rules_count = len(rulekit_clf.model.rules)
-        self.assertEqual(
-            rules_count, listener.induced_rules_count
-        )
+        self.assertEqual(rules_count, listener.induced_rules_count)
         self.assertEqual(rules_count, listener.on_progress_calls_count)
 
     def test_getting_examples_coverage(self):
@@ -77,10 +76,16 @@ def test_getting_examples_coverage(self):
         coverage_matrix = clf.get_coverage_matrix(x)
         num_rows, num_cols = coverage_matrix.shape
 
-        self.assertEqual(num_rows, len(
-            x), 'Coverage matrix should have as many rows as examples in dataset')
-        self.assertEqual(num_cols, len(
-            clf.model.rules), 'Coverage matrix should have as many cols as rules in ruleset')
+        self.assertEqual(
+            num_rows,
+            len(x),
+            "Coverage matrix should have as many rows as examples in dataset",
+        )
+        self.assertEqual(
+            num_cols,
+            len(clf.model.rules),
+            "Coverage matrix should have as many cols as rules in ruleset",
+        )
 
     def test_classification_metrics(self):
         clf = classification.RuleClassifier()
@@ -89,10 +94,42 @@ def test_classification_metrics(self):
         clf.fit(x, y)
         y_pred, m = clf.predict(x, return_metrics=True)
         self.assertEqual(len(y_pred), len(y))
-        self.assertIsNotNone(m['rules_per_example'],
-                             'rules_per_example should be calculated')
-        self.assertIsNotNone(m['voting_conflicts'],
-                             'rules_per_example should be calculated')
+        self.assertIsNotNone(
+            m["rules_per_example"], "rules_per_example should be calculated"
+        )
+        self.assertIsNotNone(
+            m["voting_conflicts"], "rules_per_example should be calculated"
+        )
+
+    def test_score(self):
+        clf = classification.RuleClassifier()
+        X, y = load_iris(return_X_y=True)
+
+        clf.fit(X, y)
+        rulekit_acc: float = clf.score(X, y)
+        sklearn_acc: float = metrics.accuracy_score(y, clf.predict(X))
+
+        self.assertAlmostEqual(
+            rulekit_acc, sklearn_acc, places=3, msg="Accuracy should be the same"
+        )
+
+    def test_fit_on_integer_labels(self):
+        clf1 = classification.RuleClassifier()
+        clf2 = classification.RuleClassifier()
+        X, y_num = load_iris(return_X_y=True)
+        y_str: np.ndarray = y_num.astype(str)
+
+        clf1.fit(X, y_num)
+        clf2.fit(X, y_str)
+
+        self.assertTrue(
+            isinstance(clf1.predict(X)[0], float),
+            "Predictions should be of the same type as labels in the training set",
+        )
+        self.assertTrue(
+            isinstance(clf2.predict(X)[0], str),
+            "Predictions should be of the same type as labels in the training set",
+        )
 
     def test_classification_predict_proba(self):
         clf = classification.RuleClassifier()
@@ -104,8 +141,7 @@ def test_classification_predict_proba(self):
             sum = 0
             for col in row:
                 sum += col
-            self.assertAlmostEqual(
-                sum, 1, 3, 'Confidence matrix rows should sum to 1')
+            self.assertAlmostEqual(sum, 1, 3, "Confidence matrix rows should sum to 1")
 
     def test_prediction_results_mapping(self):
         """
@@ -119,7 +155,7 @@ def test_prediction_results_mapping(self):
 
         # some trivial dataset - OR (2 = false, 3 = true)
         x = np.array([[0, 1], [1, 1], [1, 0], [0, 0]])
-        y = np.array([0., 1., 0., 0.])
+        y = np.array([0.0, 1.0, 0.0, 0.0])
         clf.fit(x, y)
         prediction = clf.predict(x)
 
@@ -130,14 +166,14 @@ def test_prediction_on_nominal_values(self):
 
         # some trivial dataset - AND Gate
         x = np.array([[0, 1], [1, 1], [1, 0], [0, 0]])
-        y = np.array(['false', 'true', 'false', 'false'])
+        y = np.array(["false", "true", "false", "false"])
         clf.fit(x, y)
         prediction = clf.predict(x)
 
         self.assertTrue(np.array_equal(y, prediction))
 
     def test_compare_with_java_results(self):
-        test_cases = get_test_cases('ClassificationSnCTest')
+        test_cases = get_test_cases("ClassificationSnCTest")
 
         for test_case in test_cases:
             params = test_case.induction_params
@@ -148,11 +184,12 @@ def test_compare_with_java_results(self):
             expected = test_case.reference_report.rules
             actual = list(map(str, model.rules))
             assert_rules_are_equals(expected, actual)
-            assert_accuracy_is_greater(tree.predict(
-                example_set.values), example_set.labels, 0.9)
+            assert_accuracy_is_greater(
+                tree.predict(example_set.values), example_set.labels, 0.9
+            )
 
     def test_predict_proba(self):
-        test_case = get_test_cases('ClassificationSnCTest')[0]
+        test_case = get_test_cases("ClassificationSnCTest")[0]
         params = test_case.induction_params
         clf = classification.RuleClassifier(**params)
         example_set = test_case.example_set
@@ -164,25 +201,26 @@ def test_predict_proba(self):
         self.assertEqual(
             res.shape[0],
             example_set.values.shape[0],
-            'Should have as many rows as the original dataset'
+            "Should have as many rows as the original dataset",
         )
         self.assertEqual(
             res.shape[1],
             np.unique(example_set.labels).shape[0],
-            'Should have as many columns as there are classes in the dataset'
+            "Should have as many columns as there are classes in the dataset",
         )
         self.assertTrue(
             res.max() <= 1 and res.min() >= 0,
-            'Predicted probabilities should be in range [0, 1]'
+            "Predicted probabilities should be in range [0, 1]",
         )
 
     def test_fit_and_predict_on_boolean_columns(self):
-        test_case = get_test_cases('ClassificationSnCTest')[0]
+        test_case = get_test_cases("ClassificationSnCTest")[0]
         params = test_case.induction_params
         clf = classification.RuleClassifier(**params)
         X, y = test_case.example_set.values, test_case.example_set.labels
-        X['boolean_column'] = np.random.randint(
-            low=0, high=2, size=X.shape[0]).astype(bool)
+        X["boolean_column"] = np.random.randint(low=0, high=2, size=X.shape[0]).astype(
+            bool
+        )
         clf.fit(X, y)
         clf.predict(X)
 
@@ -198,74 +236,75 @@ def test_fit_and_predict_on_boolean_columns(self):
 class TestExperClassifier(unittest.TestCase):
 
     def test_compare_with_java_results(self):
-        test_cases = get_test_cases('ClassificationExpertSnCTest')
+        test_cases = get_test_cases("ClassificationExpertSnCTest")
 
         for test_case in test_cases:
             params = test_case.induction_params
             clf = classification.ExpertRuleClassifier(**params)
             example_set = test_case.example_set
-            clf.fit(example_set.values,
-                    example_set.labels,
-                    expert_rules=test_case.knowledge.expert_rules,
-                    expert_preferred_conditions=test_case.knowledge.expert_preferred_conditions,
-                    expert_forbidden_conditions=test_case.knowledge.expert_forbidden_conditions)
+            clf.fit(
+                example_set.values,
+                example_set.labels,
+                expert_rules=test_case.knowledge.expert_rules,
+                expert_preferred_conditions=test_case.knowledge.expert_preferred_conditions,
+                expert_forbidden_conditions=test_case.knowledge.expert_forbidden_conditions,
+            )
             model = clf.model
             expected = test_case.reference_report.rules
             actual = list(map(str, model.rules))
             assert_rules_are_equals(expected, actual)
-            assert_accuracy_is_greater(clf.predict(
-                example_set.values), example_set.labels, 0.75)
 
     def test_predict_proba(self):
-        test_case = get_test_cases('ClassificationExpertSnCTest')[0]
+        test_case = get_test_cases("ClassificationExpertSnCTest")[0]
         params = test_case.induction_params
         clf = classification.ExpertRuleClassifier(**params)
         example_set = test_case.example_set
-        clf.fit(example_set.values,
-                example_set.labels,
-                expert_rules=test_case.knowledge.expert_rules,
-                expert_preferred_conditions=test_case.knowledge.expert_preferred_conditions,
-                expert_forbidden_conditions=test_case.knowledge.expert_forbidden_conditions)
+        clf.fit(
+            example_set.values,
+            example_set.labels,
+            expert_rules=test_case.knowledge.expert_rules,
+            expert_preferred_conditions=test_case.knowledge.expert_preferred_conditions,
+            expert_forbidden_conditions=test_case.knowledge.expert_forbidden_conditions,
+        )
         res = clf.predict_proba(example_set.values)
         self.assertEqual(
             res.shape[0],
             example_set.values.shape[0],
-            'Should have as many rows as the original dataset'
+            "Should have as many rows as the original dataset",
         )
         self.assertEqual(
             res.shape[1],
             np.unique(example_set.labels).shape[0],
-            'Should have as many columns as there are classes in the dataset'
+            "Should have as many columns as there are classes in the dataset",
         )
         self.assertTrue(
             res.max() <= 1 and res.min() >= 0,
-            'Predicted probabilities should be in range [0, 1]'
+            "Predicted probabilities should be in range [0, 1]",
         )
 
     # Issue #17
     def test_left_open_intervals_in_expert_induction(self):
-        df = pd.DataFrame(arff.loadarff(
-            f'{dir_path}/resources/data/seismic-bumps-train-minimal.arff')[0]
+        df = pd.DataFrame(
+            arff.loadarff(
+                f"{dir_path}/resources/data/seismic-bumps-train-minimal.arff"
+            )[0]
         )
-        X = df.drop('class', axis=1)
-        y = df['class']
+        X = df.drop("class", axis=1)
+        y = df["class"]
 
         expert_rules = [
-            ('rule-0', 'IF [[gimpuls = <-inf, 750)]] THEN class = {0}'),
-            ('rule-1', 'IF [[gimpuls = (750, inf)]] THEN class = {1}')
+            ("rule-0", "IF [[gimpuls = <-inf, 750)]] THEN class = {0}"),
+            ("rule-1", "IF [[gimpuls = (750, inf)]] THEN class = {1}"),
         ]
 
         expert_preferred_conditions = [
-            ('preferred-condition-0',
-             '1: IF [[seismic = {a}]] THEN class = {0}'),
-            ('preferred-attribute-0',
-             '1: IF [[gimpuls = Any]] THEN class = {1}')
+            ("preferred-condition-0", "1: IF [[seismic = {a}]] THEN class = {0}"),
+            ("preferred-attribute-0", "1: IF [[gimpuls = Any]] THEN class = {1}"),
         ]
 
         expert_forbidden_conditions = [
-            ('forb-attribute-0',
-             '1: IF [[seismoacoustic  = Any]] THEN class = {0}'),
-            ('forb-attribute-1', 'inf: IF [[ghazard  = Any]] THEN class = {1}')
+            ("forb-attribute-0", "1: IF [[seismoacoustic  = Any]] THEN class = {0}"),
+            ("forb-attribute-1", "inf: IF [[ghazard  = Any]] THEN class = {1}"),
         ]
         clf = classification.ExpertRuleClassifier(
             minsupp_new=8,
@@ -273,15 +312,89 @@ def test_left_open_intervals_in_expert_induction(self):
             extend_using_preferred=True,
             extend_using_automatic=True,
             induce_using_preferred=True,
-            induce_using_automatic=True
+            induce_using_automatic=True,
         )
         clf.fit(
-            X, y,
+            X,
+            y,
             expert_rules=expert_rules,
             expert_preferred_conditions=expert_preferred_conditions,
-            expert_forbidden_conditions=expert_forbidden_conditions
+            expert_forbidden_conditions=expert_forbidden_conditions,
+        )
+
+    # @unittest.skip(
+    #     "Skipped due to known bug https://bitbucket.org/polsl-a/rules/issues/126"
+    # )
+    def test_refining_conditions_for_nominal_attributes(self):
+        df: pd.DataFrame = pd.read_csv(
+            os.path.join(dir_path, "additional_resources", "salary.csv")
+        )
+        X, y = df.drop("Salary", axis=1), df["Salary"]
+
+        # Run experiment using python API
+        clf = classification.ExpertRuleClassifier(
+            induction_measure=Measures.C2,
+            pruning_measure=Measures.C2,
+            voting_measure=Measures.C2,
+            complementary_conditions=True,
+            extend_using_preferred=False,
+            extend_using_automatic=False,
+            induce_using_preferred=False,
+            induce_using_automatic=False,
+            preferred_conditions_per_rule=0,
+            preferred_attributes_per_rule=0,
+            consider_other_classes=False,
+        )
+        clf.fit(
+            X,
+            y,
+            expert_rules=[
+                (
+                    "expert_rules-1",
+                    (
+                        "IF Age = (-inf, 33.0) AND Job Title @= {Software Engineer} THEN "
+                        "Salary = {below average}"
+                    ),
+                )
+            ],
+        )
+        self.assertEqual(
+            [
+                (
+                    "IF [[Age = (-inf, 33)]] AND [[Job Title = {Software Engineer}]] THEN "
+                    "Salary = {below average}"
+                )
+            ],
+            [str(r) for r in clf.model.rules],
+            (
+                "Ruleset should contain only a single rule configured by expert with "
+                "a refined condition"
+            ),
+        )
+        clf.fit(
+            X,
+            y,
+            expert_rules=[
+                (
+                    "expert_rules-1",
+                    "IF Age = (-inf, 33.0) AND Job Title @= Any THEN Salary = {below average}",
+                )
+            ],
+        )
+        self.assertEqual(
+            [
+                (
+                    "IF [[Age = (-inf, 33)]] AND [[Job Title = {Marketing Analyst}]] "
+                    "THEN Salary = {below average}"
+                )
+            ],
+            [str(r) for r in clf.model.rules],
+            (
+                "Ruleset should contain only a single rule configured by expert with "
+                "a refined condition"
+            ),
         )
 
 
-if __name__ == '__main__':
+if __name__ == "__main__":
     unittest.main()
diff --git a/tests/test_regression.py b/tests/test_regression.py
index 0a018fa..5d80391 100644
--- a/tests/test_regression.py
+++ b/tests/test_regression.py
@@ -11,6 +11,7 @@
 from rulekit.main import RuleKit
 from rulekit.params import Measures
 from rulekit.rules import RegressionRule
+from rulekit.rules import RuleSet
 from tests.utils import assert_rules_are_equals
 from tests.utils import assert_score_is_greater
 from tests.utils import dir_path
@@ -24,7 +25,7 @@ def setUpClass(cls):
         RuleKit.init()
 
     def test_induction_progress_listener(self):
-        test_case = get_test_cases('RegressionSnCTest')[0]
+        test_case = get_test_cases("RegressionSnCTest")[0]
 
         reg = regression.RuleRegressor()
         example_set = test_case.example_set
@@ -42,9 +43,7 @@ def on_new_rule(self, rule: RegressionRule):
                 self.lock.release()
 
             def on_progress(
-                self,
-                total_examples_count: int,
-                uncovered_examples_count: int
+                self, total_examples_count: int, uncovered_examples_count: int
             ):
                 self.lock.acquire()
                 self.on_progress_calls_count += 1
@@ -65,7 +64,7 @@ def should_stop(self) -> bool:
         self.assertEqual(rules_count, listener.on_progress_calls_count)
 
     def test_compare_with_java_results(self):
-        test_cases = get_test_cases('RegressionSnCTest')
+        test_cases = get_test_cases("RegressionSnCTest")
 
         for test_case in test_cases:
             params = test_case.induction_params
@@ -76,16 +75,18 @@ def test_compare_with_java_results(self):
             expected = test_case.reference_report.rules
             actual = [str(r) for r in model.rules]
             assert_rules_are_equals(expected, actual)
-            assert_score_is_greater(tree.predict(
-                example_set.values), example_set.labels, 0.7)
+            assert_score_is_greater(
+                tree.predict(example_set.values), example_set.labels, 0.7
+            )
 
     def test_fit_and_predict_on_boolean_columns(self):
-        test_case = get_test_cases('RegressionSnCTest')[0]
+        test_case = get_test_cases("RegressionSnCTest")[0]
         params = test_case.induction_params
         clf = regression.RuleRegressor(**params)
         X, y = test_case.example_set.values, test_case.example_set.labels
-        X['boolean_column'] = np.random.randint(
-            low=0, high=2, size=X.shape[0]).astype(bool)
+        X["boolean_column"] = np.random.randint(low=0, high=2, size=X.shape[0]).astype(
+            bool
+        )
         clf.fit(X, y)
         clf.predict(X)
 
@@ -94,11 +95,10 @@ def test_fit_and_predict_on_boolean_columns(self):
         clf.predict(X)
 
     def test_cholesterol(self):
-        resources_dir: str = os.path.join(dir_path, 'additional_resources')
+        resources_dir: str = os.path.join(dir_path, "additional_resources")
         df: pd.DataFrame = read_arff(
-            os.path.join(resources_dir, 'cholesterol.arff')
-        )
-        X, y = df.drop('class', axis=1), df['class']
+            os.path.join(resources_dir, "cholesterol.arff"))
+        X, y = df.drop("class", axis=1), df["class"]
 
         # Run experiment using python API
         reg = regression.RuleRegressor(
@@ -111,13 +111,13 @@ def test_cholesterol(self):
             ignore_missing=False,
             select_best_candidate=False,
             complementary_conditions=True,
-            max_rule_count=0
+            max_rule_count=0,
         )
         reg.fit(X, y)
         actual_rules: list[str] = list(map(str, reg.model.rules))
         expected_rules: list[str] = [
-            'IF trestbps = (-inf, 149) THEN class = {244.84} [192.73,296.96]',
-            'IF trestbps = <122, inf) THEN class = {250.80} [201.79,299.80]'
+            "IF trestbps = (-inf, 149) THEN class = {244.84} [192.73,296.96]",
+            "IF trestbps = <122, inf) THEN class = {250.80} [201.79,299.80]",
         ]
         self.assertEqual(actual_rules, expected_rules)
 
@@ -129,24 +129,92 @@ def setUpClass(cls):
         RuleKit.init()
 
     def test_compare_with_java_results(self):
-        test_cases = get_test_cases('RegressionExpertSnCTest')
+        test_cases = get_test_cases("RegressionExpertSnCTest")
 
         for test_case in test_cases:
             params = test_case.induction_params
             tree = regression.ExpertRuleRegressor(**params)
             example_set = test_case.example_set
-            tree.fit(example_set.values,
-                     example_set.labels,
-                     expert_rules=test_case.knowledge.expert_rules,
-                     expert_preferred_conditions=test_case.knowledge.expert_preferred_conditions,
-                     expert_forbidden_conditions=test_case.knowledge.expert_forbidden_conditions)
+            tree.fit(
+                example_set.values,
+                example_set.labels,
+                expert_rules=test_case.knowledge.expert_rules,
+                expert_preferred_conditions=(
+                    test_case.knowledge.expert_preferred_conditions
+                ),
+                expert_forbidden_conditions=(
+                    test_case.knowledge.expert_forbidden_conditions
+                ),
+            )
             model = tree.model
             expected = test_case.reference_report.rules
             actual = [str(r) for r in model.rules]
             assert_rules_are_equals(expected, actual)
-            assert_score_is_greater(tree.predict(
-                example_set.values), example_set.labels, 0.66)
+            assert_score_is_greater(
+                tree.predict(example_set.values), example_set.labels, 0.66
+            )
+
+    def test_legacy_expert_rules_format(self):
+        """Test if the legacy expert rules format is still supported.
+        In legacy format rules strings contains conclusion in the form
+        of "label_attr = {NaN}". In new format conclusion part should be empty
+        """
+        df: pd.DataFrame = read_arff(
+            os.path.join(dir_path, "additional_resources", "cholesterol.arff")
+        )
+        X, y = df.drop("class", axis=1), df["class"]
+
+        # Run experiment using python API
+        reg = regression.ExpertRuleRegressor(
+            mean_based_regression=True, extend_using_automatic=True
+        )
+        expert_rule = "IF trestbps < 149 THEN class = {NaN}"
+        legacy_ruleset: RuleSet[RegressionRule] = reg.fit(
+            X, y, expert_rules=[("0", expert_rule)]
+        )
+        new_format_ruleset: RuleSet[RegressionRule] = reg.fit(
+            X, y, expert_rules=[("rule-0", expert_rule.split("class")[0])]
+        )
+        legacy_rules: list[str] = list(map(str, legacy_ruleset.rules))
+        new_format_rules: list[str] = list(map(str, new_format_ruleset.rules))
+        self.assertEqual(legacy_rules, new_format_rules)
+
+    def test_refining_conditions_for_nominal_attributes(self):
+        df: pd.DataFrame = read_arff(
+            os.path.join(dir_path, "additional_resources", "cholesterol.arff")
+        )
+        X, y = df.drop("class", axis=1), df["class"]
+
+        # Run experiment using python API
+        clf = regression.ExpertRuleRegressor(
+            induction_measure=Measures.C2,
+            pruning_measure=Measures.C2,
+            voting_measure=Measures.C2,
+            complementary_conditions=True,
+            extend_using_preferred=False,
+            extend_using_automatic=False,
+            induce_using_preferred=False,
+            induce_using_automatic=False,
+            preferred_conditions_per_rule=0,
+            preferred_attributes_per_rule=0,
+        )
+        clf.fit(X, y, expert_rules=[("expert_rules-1", "IF sex @= {1} THEN")])
+        self.assertEqual(
+            ["IF [[sex = {1}]] THEN class = {239.60} [197.06,282.15]"],
+            [str(r) for r in clf.model.rules],
+            "Ruleset should contain only a single rule configured by expert",
+        )
+
+        clf.fit(X, y, expert_rules=[("expert_rules-1", "IF sex @= Any THEN")])
+        self.assertEqual(
+            ["IF [[sex = {1}]] THEN class = {239.60} [197.06,282.15]"],
+            [str(r) for r in clf.model.rules],
+            (
+                "Ruleset should contain only a single rule configured by expert with "
+                "a refined condition"
+            ),
+        )
 
 
-if __name__ == '__main__':
+if __name__ == "__main__":
     unittest.main()
diff --git a/tests/test_survival.py b/tests/test_survival.py
index 3163c62..a5a2fba 100644
--- a/tests/test_survival.py
+++ b/tests/test_survival.py
@@ -1,3 +1,4 @@
+import os
 import threading
 import unittest
 
@@ -5,11 +6,13 @@
 import pandas as pd
 
 from rulekit import survival
+from rulekit.arff import read_arff
 from rulekit.events import RuleInductionProgressListener
 from rulekit.kaplan_meier import KaplanMeierEstimator
 from rulekit.main import RuleKit
 from rulekit.rules import SurvivalRule
 from tests.utils import assert_rules_are_equals
+from tests.utils import dir_path
 from tests.utils import get_test_cases
 
 
@@ -18,47 +21,49 @@ class TestKaplanMeierEstimator(unittest.TestCase):
     survival_rules: survival.SurvivalRules
 
     def setUp(self):
-        test_case = get_test_cases('SurvivalLogRankSnCTest')[0]
+        test_case = get_test_cases("SurvivalLogRankSnCTest")[0]
 
         self.survival_rules = survival.SurvivalRules(
-            survival_time_attr=test_case.survival_time)
+            survival_time_attr=test_case.survival_time
+        )
         example_set = test_case.example_set
         self.survival_rules.fit(
             example_set.values,
             example_set.labels,
         )
-        self.km: KaplanMeierEstimator = self.survival_rules.model.rules[0].kaplan_meier_estimator
+        self.km: KaplanMeierEstimator = self.survival_rules.model.rules[
+            0
+        ].kaplan_meier_estimator
 
     def test_accessing_probabilities(self):
-        self.assertTrue(all([
-            p >= 0.0 and p <= 1.0
-            for p in self.km.probabilities
-        ]), 'All probabilities should be in range [0, 1]')
-        self.assertTrue(all([
-            isinstance(p, float)
-            for p in self.km.probabilities
-        ]), 'All probabilities should be Pythonic floats')
+        self.assertTrue(
+            all([p >= 0.0 and p <= 1.0 for p in self.km.probabilities]),
+            "All probabilities should be in range [0, 1]",
+        )
+        self.assertTrue(
+            all([isinstance(p, float) for p in self.km.probabilities]),
+            "All probabilities should be Pythonic floats",
+        )
 
     def test_accessing_events_count(self):
-        self.assertTrue(all([
-            isinstance(p, np.int_)
-            for p in self.km.events_count
-        ]), 'All event counts should be Pythonic integers')
+        self.assertTrue(
+            all([isinstance(p, np.int_) for p in self.km.events_count]),
+            "All event counts should be Pythonic integers",
+        )
 
     def test_accessing_at_risk_count(self):
-        self.assertTrue(all([
-            isinstance(p, np.int_)
-            for p in self.km.at_risk_count
-        ]), 'All risk count should be Pythonic integers')
+        self.assertTrue(
+            all([isinstance(p, np.int_) for p in self.km.at_risk_count]),
+            "All risk count should be Pythonic integers",
+        )
 
 
 class TestSurvivalRules(unittest.TestCase):
 
     def test_induction_progress_listener(self):
-        test_case = get_test_cases('SurvivalLogRankSnCTest')[0]
+        test_case = get_test_cases("SurvivalLogRankSnCTest")[0]
 
-        surv = survival.SurvivalRules(
-            survival_time_attr=test_case.survival_time)
+        surv = survival.SurvivalRules(survival_time_attr=test_case.survival_time)
         example_set = test_case.example_set
 
         class EventListener(RuleInductionProgressListener):
@@ -73,9 +78,7 @@ def on_new_rule(self, rule: SurvivalRule):
                 self.lock.release()
 
             def on_progress(
-                self,
-                total_examples_count: int,
-                uncovered_examples_count: int
+                self, total_examples_count: int, uncovered_examples_count: int
             ):
                 self.lock.acquire()
                 self.on_progress_calls_count += 1
@@ -92,12 +95,13 @@ def on_progress(
         self.assertEqual(rules_count, listener.on_progress_calls_count)
 
     def test_compare_with_java_results(self):
-        test_cases = get_test_cases('SurvivalLogRankSnCTest')
+        test_cases = get_test_cases("SurvivalLogRankSnCTest")
 
         for test_case in test_cases:
             params = test_case.induction_params
             tree = survival.SurvivalRules(
-                **params, survival_time_attr=test_case.survival_time)
+                **params, survival_time_attr=test_case.survival_time
+            )
             example_set = test_case.example_set
             tree.fit(example_set.values, example_set.labels)
             model = tree.model
@@ -106,46 +110,147 @@ def test_compare_with_java_results(self):
             assert_rules_are_equals(expected, actual)
 
     def test_fit_and_predict_on_boolean_columns(self):
-        test_case = get_test_cases('SurvivalLogRankSnCTest')[0]
+        test_case = get_test_cases("SurvivalLogRankSnCTest")[0]
         params = test_case.induction_params
         clf = survival.SurvivalRules(
             **params, survival_time_attr=test_case.survival_time
         )
         X, y = test_case.example_set.values, test_case.example_set.labels
-        X['boolean_column'] = np.random.randint(
-            low=0, high=2, size=X.shape[0]).astype(bool)
+        X["boolean_column"] = np.random.randint(low=0, high=2, size=X.shape[0]).astype(
+            bool
+        )
         clf.fit(X, y)
         clf.predict(X)
 
         y = pd.Series(y)
         clf.fit(X, y)
-        p = clf.predict(X)
+        clf.predict(X)
+
+    def test_passing_survival_time_column_to_fit_method(self):
+        test_case = get_test_cases("SurvivalLogRankSnCTest")[0]
+        params = test_case.induction_params
+        surv1 = survival.SurvivalRules(**params)
+        surv2 = survival.SurvivalRules(
+            **params, survival_time_attr=test_case.survival_time
+        )
+        X, y = test_case.example_set.values, test_case.example_set.labels
+        survival_time_col: pd.Series = X[test_case.survival_time]
+        X_without_time_col: pd.DataFrame = X.drop(
+            columns=[test_case.survival_time], axis=1
+        )
+        surv1.fit(X_without_time_col, y, survival_time=survival_time_col)
+        surv2.fit(X, y)
 
+        assert_rules_are_equals(
+            [str(r) for r in surv1.model.rules],
+            [str(r) for r in surv2.model.rules],
+        )
+
+    def test_ibs_calculation(self):
+        test_case = get_test_cases("SurvivalLogRankSnCTest")[0]
+        params = test_case.induction_params
+        surv = survival.SurvivalRules(
+            **params, survival_time_attr=test_case.survival_time
+        )
+        X, y = test_case.example_set.values, test_case.example_set.labels
+        survival_time_col: pd.Series = X[test_case.survival_time]
+        X_without_time_col: pd.DataFrame = X.drop(
+            columns=[test_case.survival_time], axis=1
+        )
+        surv.fit(X, y)
 
-class TestExpertSurvivalLogRankTree(unittest.TestCase):
+        ibs: float = surv.score(X, y)
+        ibs2: float = surv.score(X_without_time_col, y, survival_time=survival_time_col)
 
-    @ classmethod
+        self.assertEqual(ibs, ibs2)
+
+    def test_getting_training_dataset_kaplan_meier_estimator(self):
+        test_case = get_test_cases("SurvivalLogRankSnCTest")[0]
+        params = test_case.induction_params
+        surv = survival.SurvivalRules(
+            **params, survival_time_attr=test_case.survival_time
+        )
+        example_set = test_case.example_set
+        unique_times_counts: int = example_set.values[test_case.survival_time].nunique()
+        surv.fit(example_set.values, example_set.labels)
+
+        training_km: KaplanMeierEstimator = surv.get_train_set_kaplan_meier()
+        self.assertTrue(
+            training_km is not None and isinstance(training_km, KaplanMeierEstimator),
+            "Should return KaplanMeierEstimator instance fitted on whole training set",
+        )
+        self.assertEqual(
+            len(training_km.times),
+            unique_times_counts,
+            "Estimator should contain probabilities for each unique time from the dataset",
+        )
+
+
+class TestExpertSurvivalRules(unittest.TestCase):
+
+    @classmethod
     def setUpClass(cls):
         RuleKit.init()
 
     def test_compare_with_java_results(self):
-        test_cases = get_test_cases('SurvivalLogRankExpertSnCTest')
+        test_cases = get_test_cases("SurvivalLogRankExpertSnCTest")
 
         for test_case in test_cases:
             params = test_case.induction_params
-            tree = survival.ExpertSurvivalRules(
-                **params, ignore_missing=True, survival_time_attr=test_case.survival_time)
+            surv = survival.ExpertSurvivalRules(
+                **params,
+                ignore_missing=True,
+                survival_time_attr=test_case.survival_time
+            )
             example_set = test_case.example_set
-            tree.fit(example_set.values,
-                     example_set.labels,
-                     expert_rules=test_case.knowledge.expert_rules,
-                     expert_preferred_conditions=test_case.knowledge.expert_preferred_conditions,
-                     expert_forbidden_conditions=test_case.knowledge.expert_forbidden_conditions)
-            model = tree.model
+            surv.fit(
+                example_set.values,
+                example_set.labels,
+                expert_rules=test_case.knowledge.expert_rules,
+                expert_preferred_conditions=test_case.knowledge.expert_preferred_conditions,
+                expert_forbidden_conditions=test_case.knowledge.expert_forbidden_conditions,
+            )
+            model = surv.model
             expected = test_case.reference_report.rules
             actual = list(map(str, model.rules))
             assert_rules_are_equals(expected, actual)
 
+    def test_refining_conditions_for_nominal_attributes(self):
+        df: pd.DataFrame = read_arff(
+            os.path.join(dir_path, "resources", "data", "bmt-train-0.arff")
+        )
+        X, y = df.drop("survival_status", axis=1), df["survival_status"]
+
+        # Run experiment using python API
+        clf = survival.ExpertSurvivalRules(
+            complementary_conditions=True,
+            extend_using_preferred=False,
+            extend_using_automatic=False,
+            induce_using_preferred=False,
+            induce_using_automatic=False,
+            preferred_conditions_per_rule=0,
+            preferred_attributes_per_rule=0,
+            survival_time_attr="survival_time",
+        )
+        clf.fit(X, y, expert_rules=[("expert_rules-1", "IF CMVstatus @= {1} THEN")])
+        r = [str(r) for r in clf.model.rules]
+
+        self.assertEqual(
+            ["IF [[CMVstatus = {1}]] THEN "],
+            [str(r) for r in clf.model.rules],
+            "Ruleset should contain only a single rule configured by expert",
+        )
+
+        clf.fit(X, y, expert_rules=[("expert_rules-1", "IF CMVstatus @= Any THEN")])
+        self.assertEqual(
+            ["IF [[CMVstatus = !{1}]] THEN "],
+            [str(r) for r in clf.model.rules],
+            (
+                "Ruleset should contain only a single rule configured by expert with "
+                "a refined condition"
+            ),
+        )
+
 
-if __name__ == '__main__':
+if __name__ == "__main__":
     unittest.main()
diff --git a/tests/utils.py b/tests/utils.py
index 7b41649..f75a152 100644
--- a/tests/utils.py
+++ b/tests/utils.py
@@ -14,22 +14,20 @@
 
 dir_path = os.path.dirname(os.path.realpath(__file__))
 
-TEST_CONFIG_PATH = f'{dir_path}/resources/config'
-REPORTS_IN_DIRECTORY_PATH = f'{dir_path}/resources/reports'
-DATA_IN_DIRECTORY_PATH = f'{dir_path}/resources/'
-REPORTS_OUT_DIRECTORY_PATH = f'{dir_path}/test_out'
+TEST_CONFIG_PATH = f"{dir_path}/resources/config"
+REPORTS_IN_DIRECTORY_PATH = f"{dir_path}/resources/reports"
+DATA_IN_DIRECTORY_PATH = f"{dir_path}/resources/"
+REPORTS_OUT_DIRECTORY_PATH = f"{dir_path}/test_out"
 
-REPORTS_SECTIONS_HEADERS = {
-    'RULES': 'RULES'
-}
+REPORTS_SECTIONS_HEADERS = {"RULES": "RULES"}
 
-DATASETS_PATH = '/resources/data'
-EXPERIMENTS_PATH = '/resources/config'
+DATASETS_PATH = "/resources/data"
+EXPERIMENTS_PATH = "/resources/config"
 
 
 def _fix_missing_values(column) -> None:
     for i, value in enumerate(column.values):
-        if value == b'?':
+        if value == b"?":
             column.values[i] = None
 
 
@@ -44,8 +42,10 @@ def get_data(self) -> tuple:
         return self.values, self.labels
 
 
-def load_arff_to_example_set(path: str, label_attribute: str, problem_type: ProblemType) -> ExampleSetWrapper:
-    with open(path, 'r') as file:
+def load_arff_to_example_set(
+    path: str, label_attribute: str, problem_type: ProblemType
+) -> ExampleSetWrapper:
+    with open(path, "r") as file:
         content = file.read().replace('"', "'")
         arff_file = io.StringIO(content)
     arff_data_frame = read_arff(arff_file)
@@ -65,7 +65,7 @@ def load_arff_to_example_set(path: str, label_attribute: str, problem_type: Prob
 
 
 def get_dataset_path(name: str) -> str:
-    return f'{DATASETS_PATH}/{name}'
+    return f"{DATASETS_PATH}/{name}"
 
 
 class Knowledge:
@@ -104,16 +104,14 @@ def __init__(self, problem_type: ProblemType):
     def example_set(self) -> ExampleSetWrapper:
         if self._example_set is None:
             self._example_set = load_arff_to_example_set(
-                self.data_set_file_path,
-                self.label_attribute,
-                self.problem_type
+                self.data_set_file_path, self.label_attribute, self.problem_type
             )
         return self._example_set
 
     @property
     def reference_report(self) -> TestReport:
         if self._reference_report is None:
-            reader = TestReportReader(f'{self.report_file_path}.txt')
+            reader = TestReportReader(f"{self.report_file_path}.txt")
             self._reference_report = reader.read()
             reader.close()
         return self._reference_report
@@ -137,24 +135,24 @@ def __init__(self):
 
 
 class TestConfigParser:
-    TEST_KEY = 'test'
-    NAME_KEY = 'name'
-    IN_FILE_KEY = 'in_file'
-    TRAINING_KEY = 'training'
-    TRAIN_KEY = 'train'
-    LABEL_KEY = 'label'
-    DATASET_KEY = 'dataset'
-    DATASETS_KEY = 'datasets'
-    PARAM_KEY = 'param'
-    PARAMETERS_SET_KEY = 'parameter_sets'
-    PARAMETERS_KEY = 'parameter_set'
-    ENTRY_KEY = 'entry'
-    SURVIVAL_TIME_ROLE = 'survival_time'
+    TEST_KEY = "test"
+    NAME_KEY = "name"
+    IN_FILE_KEY = "in_file"
+    TRAINING_KEY = "training"
+    TRAIN_KEY = "train"
+    LABEL_KEY = "label"
+    DATASET_KEY = "dataset"
+    DATASETS_KEY = "datasets"
+    PARAM_KEY = "param"
+    PARAMETERS_SET_KEY = "parameter_sets"
+    PARAMETERS_KEY = "parameter_set"
+    ENTRY_KEY = "entry"
+    SURVIVAL_TIME_ROLE = "survival_time"
 
     EXPERTS_RULES_PARAMETERS_NAMES = [
-        'expert_rules',
-        'expert_preferred_conditions',
-        'expert_forbidden_conditions'
+        "expert_rules",
+        "expert_preferred_conditions",
+        "expert_forbidden_conditions",
     ]
 
     def __init__(self):
@@ -162,8 +160,7 @@ def __init__(self):
         self.root: ElementTree = None
 
     def _parse_survival_time(self, element) -> Union[str, None]:
-        survival_time_element = element.find(
-            TestConfigParser.SURVIVAL_TIME_ROLE)
+        survival_time_element = element.find(TestConfigParser.SURVIVAL_TIME_ROLE)
         if element.find(TestConfigParser.SURVIVAL_TIME_ROLE) is not None:
             return survival_time_element.text
         else:
@@ -172,11 +169,10 @@ def _parse_survival_time(self, element) -> Union[str, None]:
     def _parse_experts_rules_parameters(self, elements) -> list[tuple]:
         expert_rules = []
         for element in elements:
-            rule_name: str = element.attrib['name']
+            rule_name: str = element.attrib["name"]
             rule_content: str = element.text
             # RuleKit originally used XML for specifying parameters and uses special xml characters
-            rule_content = rule_content.replace(
-                '&lt;', '<').replace('&gt;', '>')
+            rule_content = rule_content.replace("&lt;", "<").replace("&gt;", ">")
             expert_rules.append((rule_name, rule_content))
         return expert_rules if len(expert_rules) > 0 else None
 
@@ -185,20 +181,20 @@ def _check_ambigous_data_sets_names(self, data_sets_configs: list[DataSetConfig]
         for element in data_sets_configs:
             dictionary[element.name] = None
         if len(dictionary.keys()) < len(data_sets_configs):
-            raise ValueError('Datasets are ambigous')
+            raise ValueError("Datasets are ambigous")
 
     def _parse_data_set(self, element) -> DataSetConfig:
         data_set_config = DataSetConfig()
-        data_set_config.label_attribute = element.find(
-            TestConfigParser.LABEL_KEY).text
+        data_set_config.label_attribute = element.find(TestConfigParser.LABEL_KEY).text
         train_element = element.find(TestConfigParser.TRAINING_KEY)
         train_element = train_element.find(TestConfigParser.TRAIN_KEY)
         data_set_config.train_file_name = train_element.find(
-            TestConfigParser.IN_FILE_KEY).text
-        data_set_config.name = element.attrib.get('name', None)
+            TestConfigParser.IN_FILE_KEY
+        ).text
+        data_set_config.name = element.attrib.get("name", None)
         if data_set_config.name is None:
             file_name = os.path.basename(data_set_config.train_file_name)
-            data_set_config.name = file_name.split('.')[0]
+            data_set_config.name = file_name.split(".")[0]
         data_set_config.survival_time = self._parse_survival_time(element)
         return data_set_config
 
@@ -212,10 +208,11 @@ def _parse_data_sets(self, element) -> list[DataSetConfig]:
     def parse_test_parameters(self, element) -> dict[str, object]:
         params = {}
         for param_node in element.findall(TestConfigParser.PARAM_KEY):
-            name: str = param_node.attrib['name']
+            name: str = param_node.attrib["name"]
             if name in TestConfigParser.EXPERTS_RULES_PARAMETERS_NAMES:
                 value = self._parse_experts_rules_parameters(
-                    param_node.findall(TestConfigParser.ENTRY_KEY))
+                    param_node.findall(TestConfigParser.ENTRY_KEY)
+                )
             else:
                 value = param_node.text
             params[name] = value
@@ -223,26 +220,23 @@ def parse_test_parameters(self, element) -> dict[str, object]:
 
     def _parse_test_parameters_sets(self, element) -> dict[str, dict[str, object]]:
         parameters_sets = {}
-        params_sets_node = element.findall(
-            TestConfigParser.PARAMETERS_SET_KEY)[0]
+        params_sets_node = element.findall(TestConfigParser.PARAMETERS_SET_KEY)[0]
         for param_set in params_sets_node.findall(TestConfigParser.PARAMETERS_KEY):
-            name: str = param_set.attrib['name']
+            name: str = param_set.attrib["name"]
             parameters_sets[name] = self.parse_test_parameters(param_set)
         return parameters_sets
 
     def _parse_test(self, element) -> TestConfig:
         test_config = TestConfig()
-        test_config.parameter_configs = self._parse_test_parameters_sets(
-            element
-        )
+        test_config.parameter_configs = self._parse_test_parameters_sets(element)
         test_config.datasets = self._parse_data_sets(element)
-        test_config.name = element.attrib['name']
+        test_config.name = element.attrib["name"]
         return test_config
 
     def parse(self, file_path: str) -> dict[str, TestConfig]:
         self.tests_configs = {}
         self.root = ElementTree.parse(file_path).getroot()
-        if self.root.tag == 'test':
+        if self.root.tag == "test":
             test_elements = [self.root]
         else:
             test_elements = self.root.findall(TestConfigParser.TEST_KEY)
@@ -255,43 +249,45 @@ def parse(self, file_path: str) -> dict[str, TestConfig]:
 class TestCaseFactory:
 
     def _make_test_case(
-            self,
-            test_case_name: str,
-            params: dict[str, object],
-            data_set_config: DataSetConfig,
-            problem_type: ProblemType
+        self,
+        test_case_name: str,
+        params: dict[str, object],
+        data_set_config: DataSetConfig,
+        problem_type: ProblemType,
     ) -> TestCase:
         test_case = TestCase(problem_type)
         self._fix_params_typing(params)
         self._fix_deprecated_params(params)
         test_case.induction_params = params
-        test_case.data_set_file_path = f'{DATA_IN_DIRECTORY_PATH}/{data_set_config.train_file_name}'
+        test_case.data_set_file_path = (
+            f"{DATA_IN_DIRECTORY_PATH}/" f"{data_set_config.train_file_name}"
+        )
         test_case.label_attribute = data_set_config.label_attribute
         test_case.name = test_case_name
         test_case.param_config = params
         return test_case
 
     def _fix_deprecated_params(self, params: dict[str, object]):
-        deprecated_minsupp_new_name = 'min_rule_covered'
+        deprecated_minsupp_new_name = "min_rule_covered"
         if deprecated_minsupp_new_name in params:
-            params['minsupp_new'] = params.pop(deprecated_minsupp_new_name)
+            params["minsupp_new"] = params.pop(deprecated_minsupp_new_name)
 
     def _fix_params_typing(self, params: dict):
         for key, value in params.items():
-            if value == 'false':
+            if value == "false":
                 params[key] = False
                 continue
-            if value == 'true':
+            if value == "true":
                 params[key] = True
                 continue
-            if not 'measure' in key:
+            if not "measure" in key:
                 params[key] = int(float(value))
 
     def make(
         self,
         tests_configs: dict[str, TestConfig],
         report_dir_path: str,
-        problem_type: ProblemType
+        problem_type: ProblemType,
     ) -> list[TestCase]:
         test_cases = []
         for key in tests_configs.keys():
@@ -299,50 +295,60 @@ def make(
             for config_name in test_config.parameter_configs.keys():
                 for data_set_config in test_config.datasets:
                     params = test_config.parameter_configs[config_name]
-                    test_case_name = f'{key}.{config_name}.{data_set_config.name}'
-                    test_config.parameter_configs[config_name].pop(
-                        'use_expert', None)
+                    test_case_name = f"{key}.{config_name}.{data_set_config.name}"
+                    test_config.parameter_configs[config_name].pop("use_expert", None)
                     expert_rules = test_config.parameter_configs[config_name].pop(
-                        'expert_rules', None)
-                    preferred_conditions = test_config.parameter_configs[config_name].pop('expert_preferred_conditions',
-                                                                                          None)
-                    forbidden_conditions = test_config.parameter_configs[config_name].pop('expert_forbidden_conditions',
-                                                                                          None)
+                        "expert_rules", None
+                    )
+                    preferred_conditions = test_config.parameter_configs[
+                        config_name
+                    ].pop("expert_preferred_conditions", None)
+                    forbidden_conditions = test_config.parameter_configs[
+                        config_name
+                    ].pop("expert_forbidden_conditions", None)
                     test_case = self._make_test_case(
                         test_case_name,
                         test_config.parameter_configs[config_name],
                         data_set_config,
-                        problem_type
+                        problem_type,
                     )
-                    if 'use_report' in params:
-                        report_file_name = params['use_report']
+                    if "use_report" in params:
+                        report_file_name = params["use_report"]
                         test_case.using_existing_report_file = True
                     else:
                         report_file_name = test_case_name
-                    report_path = f'{report_dir_path}/{report_file_name}'
+                    report_path = f"{report_dir_path}/{report_file_name}"
                     test_case.report_file_path = report_path
                     test_case.survival_time = data_set_config.survival_time
-                    if expert_rules is not None or preferred_conditions is not None or forbidden_conditions is not None:
+                    if (
+                        expert_rules is not None
+                        or preferred_conditions is not None
+                        or forbidden_conditions is not None
+                    ):
                         test_case.knowledge = Knowledge()
                         if expert_rules is not None:
                             test_case.knowledge.expert_rules = expert_rules
                         if forbidden_conditions is not None:
-                            test_case.knowledge.expert_forbidden_conditions = forbidden_conditions
+                            test_case.knowledge.expert_forbidden_conditions = (
+                                forbidden_conditions
+                            )
                         if preferred_conditions is not None:
-                            test_case.knowledge.expert_preferred_conditions = preferred_conditions
+                            test_case.knowledge.expert_preferred_conditions = (
+                                preferred_conditions
+                            )
                     test_cases.append(test_case)
         return test_cases
 
 
 def get_rule_string(rule) -> str:
-    return re.sub(r'(\\[[^\\]]*\\]$)|(\\([^\\)]*\\)$)', '', str(rule))
+    return re.sub(r"(\\[[^\\]]*\\]$)|(\\([^\\)]*\\)$)", "", str(rule))
 
 
 class TestReportReader:
 
     def __init__(self, file_name: str):
         self.file_name = file_name
-        self._file = open(file_name, encoding='utf-8', mode='r')
+        self._file = open(file_name, encoding="utf-8", mode="r")
 
     def _read_rules(self, test_report: TestReport):
         rules = []
@@ -357,15 +363,16 @@ def read(self) -> TestReport:
         test_report = TestReport(self.file_name)
         for line in self._file:
             line = line.upper()
-            line = re.sub(r'\t', '', line)
-            line = line.replace('\n', '')
-            if line == REPORTS_SECTIONS_HEADERS['RULES']:
+            line = re.sub(r"\t", "", line)
+            line = line.replace("\n", "")
+            if line == REPORTS_SECTIONS_HEADERS["RULES"]:
                 self._read_rules(test_report)
-            elif line == '':
+            elif line == "":
                 continue
             else:
                 raise ValueError(
-                    f'Invalid report file format for file: {self.file_name}')
+                    f"Invalid report file format for file: {self.file_name}"
+                )
         return test_report
 
     def close(self):
@@ -375,15 +382,15 @@ def close(self):
 class TestReportWriter:
 
     def __init__(self, file_name: str):
-        self._file = open(file_name, encoding='utf-8', mode="w")
+        self._file = open(file_name, encoding="utf-8", mode="w")
         if not os.path.exists(REPORTS_OUT_DIRECTORY_PATH):
             os.makedirs(REPORTS_OUT_DIRECTORY_PATH)
 
     def write(self, rule_set):
-        self._file.write('\n')
+        self._file.write("\n")
         self._file.write(f'{REPORTS_SECTIONS_HEADERS["RULES"]}\n')
         for rule in rule_set.rules:
-            self._file.write(f'\t{get_rule_string(rule)}')
+            self._file.write(f"\t{get_rule_string(rule)}")
 
     def close(self):
         self._file.close()
@@ -391,45 +398,44 @@ def close(self):
 
 def get_test_cases(class_name: str) -> list[TestCase]:
     if not os.path.exists(DATA_IN_DIRECTORY_PATH):
-        raise RuntimeError('''\n
+        raise RuntimeError(
+            """\n
 Test resources directory dosen't exist. Check if 'tests/resources/' directory exist.
 
 If you're running tests for the first time you need to download resources folder from RuleKit repository by running:
     python tests/resources.py download
-        ''')
-    problem_type: ProblemType = _get_problem_type_from_test_case_class_name(
-        class_name
-    )
-    configs = TestConfigParser().parse(f'{TEST_CONFIG_PATH}/{class_name}.xml')
+        """
+        )
+    problem_type: ProblemType = _get_problem_type_from_test_case_class_name(class_name)
+    configs = TestConfigParser().parse(f"{TEST_CONFIG_PATH}/{class_name}.xml")
     return TestCaseFactory().make(
-        configs,
-        f'{REPORTS_IN_DIRECTORY_PATH}/{class_name}/',
-        problem_type
+        configs, f"{REPORTS_IN_DIRECTORY_PATH}/{class_name}/", problem_type
     )
 
 
 def _get_problem_type_from_test_case_class_name(class_name: str) -> ProblemType:
     class_name = class_name.lower()
-    if 'regression' in class_name:
+    if "regression" in class_name:
         return ProblemType.REGRESSION
-    elif 'survival' in class_name:
+    elif "survival" in class_name:
         return ProblemType.SURVIVAL
-    elif 'classification' in class_name:
+    elif "classification" in class_name:
         return ProblemType.CLASSIFICATION
-    raise Exception(
-        f'Unknown problem type for test case class name: {class_name}')
+    raise Exception(f"Unknown problem type for test case class name: {class_name}")
 
 
 def assert_rules_are_equals(expected: list[str], actual: list[str]):
     def sanitize_rule_string(rule_string: str) -> str:
-        return re.sub(r'(\t)|(\n)|(\[[^\]]*\]$)', '', rule_string)
+        return re.sub(r"(\t)|(\n)|(\[[^\]]*\]$)", "", rule_string)
 
     expected = list(map(sanitize_rule_string, expected))
     actual = list(map(sanitize_rule_string, actual))
 
     if len(expected) != len(actual):
         raise AssertionError(
-            f'Rulesets have different number of rules, actual: {len(actual)}, expected: {len(expected)}')
+            "Rulesets have different number of rules, actual: "
+            f'{len(actual)}, expected: {len(expected)}'
+        )
     dictionary = {}
     for rule in expected:
         dictionary[rule] = 0
@@ -439,29 +445,33 @@ def sanitize_rule_string(rule_string: str) -> str:
             dictionary[key] = dictionary[key] + 1
         else:
             raise AssertionError(
-                'Actual ruleset contains rules not present in expected ruleset')
+                "Actual ruleset contains rules not present in expected ruleset"
+            )
     for value in dictionary.values():
         if value == 0:
-            raise AssertionError(
-                'Ruleset are not equal, some rules are missing')
+            raise AssertionError("Ruleset are not equal, some rules are missing")
         elif value > 1:
-            raise AssertionError('Somes rules were duplicated')
+            raise AssertionError("Somes rules were duplicated")
 
 
 def assert_accuracy_is_greater(prediction, expected, threshold: float):
     labels = expected.to_numpy().astype(str)
     acc = metrics.accuracy_score(labels, prediction)
     if acc <= threshold:
-        raise AssertionError(f'Accuracy should be greater than {threshold}')
+        raise AssertionError(f"Accuracy should be greater than {threshold} (was {acc})")
 
 
 def assert_score_is_greater(prediction, expected, threshold: float):
     if isinstance(prediction[0], int):
         labels = expected.to_numpy().astype(int)
-    if isinstance(prediction[0], float):
+    elif isinstance(prediction[0], float):
         labels = expected.to_numpy().astype(float)
-    explained_variance_score = metrics.explained_variance_score(
-        labels, prediction)
+    else:
+        raise ValueError(
+            f"Invalid prediction type: {str(type(prediction[0]))}. "
+            + "Supported types are: 1 dimensional numpy array or pandas Series object."
+        )
+    explained_variance_score = metrics.explained_variance_score(labels, prediction)
 
     if explained_variance_score <= threshold:
-        raise AssertionError(f'Score should be greater than {threshold}')
+        raise AssertionError(f"Score should be greater than {threshold}")