diff --git a/__pycache__/__init__.cpython-36.pyc b/__pycache__/__init__.cpython-36.pyc new file mode 100644 index 0000000..6056df9 Binary files /dev/null and b/__pycache__/__init__.cpython-36.pyc differ diff --git a/q01_my_decision_regressor/__pycache__/__init__.cpython-36.pyc b/q01_my_decision_regressor/__pycache__/__init__.cpython-36.pyc new file mode 100644 index 0000000..c0b14dc Binary files /dev/null and b/q01_my_decision_regressor/__pycache__/__init__.cpython-36.pyc differ diff --git a/q01_my_decision_regressor/__pycache__/build.cpython-36.pyc b/q01_my_decision_regressor/__pycache__/build.cpython-36.pyc new file mode 100644 index 0000000..ebfaa7e Binary files /dev/null and b/q01_my_decision_regressor/__pycache__/build.cpython-36.pyc differ diff --git a/q01_my_decision_regressor/build.py b/q01_my_decision_regressor/build.py index 5eb1927..48b7650 100644 --- a/q01_my_decision_regressor/build.py +++ b/q01_my_decision_regressor/build.py @@ -1,3 +1,4 @@ +# %load q01_my_decision_regressor/build.py # default imports from sklearn.model_selection import GridSearchCV from sklearn.tree import DecisionTreeRegressor @@ -5,13 +6,30 @@ from sklearn.model_selection import train_test_split import pandas as pd -data = pd.read_csv("./data/house_pricing.csv") +data = pd.read_csv('./data/house_pricing.csv') X = data.iloc[:, :-1] y = data.iloc[:, -1] X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3, random_state=9) -param_grid = {"max_depth": [2, 3, 5, 6, 8, 10, 15, 20, 30, 50], - "max_leaf_nodes": [2, 3, 4, 5, 10, 15, 20], - "max_features": [4, 8, 20, 25]} +param_grid = {'max_depth': [2, 3, 5, 6, 8, 10, 15, 20, 30, 50], + 'max_leaf_nodes': [2, 3, 4, 5, 10, 15, 20], + 'max_features': [4, 8, 20, 25]} # Write your solution here : + +def my_decision_regressor(X_train, X_test, y_train, y_test,Param_grid): + + dtr=DecisionTreeRegressor(random_state=9) + gsv=GridSearchCV(estimator=dtr,param_grid=Param_grid,cv=5) + + gsv.fit(X_train,y_train) + predicted=gsv.predict(X_test) + + r2=r2_score(y_test,predicted) + best=gsv.best_estimator_ + x=dict() + x['max_leaf_nodes']=best.max_leaf_nodes + x['max_features']=best.max_features + x['max_depth']=best.max_depth + return r2,x + diff --git a/q01_my_decision_regressor/tests/__pycache__/__init__.cpython-36.pyc b/q01_my_decision_regressor/tests/__pycache__/__init__.cpython-36.pyc new file mode 100644 index 0000000..3237897 Binary files /dev/null and b/q01_my_decision_regressor/tests/__pycache__/__init__.cpython-36.pyc differ diff --git a/q01_my_decision_regressor/tests/__pycache__/test_q01_my_decision_regressor.cpython-36.pyc b/q01_my_decision_regressor/tests/__pycache__/test_q01_my_decision_regressor.cpython-36.pyc new file mode 100644 index 0000000..1880dcb Binary files /dev/null and b/q01_my_decision_regressor/tests/__pycache__/test_q01_my_decision_regressor.cpython-36.pyc differ diff --git a/q02_decision_regressor_plot/__pycache__/__init__.cpython-36.pyc b/q02_decision_regressor_plot/__pycache__/__init__.cpython-36.pyc new file mode 100644 index 0000000..0c88dde Binary files /dev/null and b/q02_decision_regressor_plot/__pycache__/__init__.cpython-36.pyc differ diff --git a/q02_decision_regressor_plot/__pycache__/build.cpython-36.pyc b/q02_decision_regressor_plot/__pycache__/build.cpython-36.pyc new file mode 100644 index 0000000..de26695 Binary files /dev/null and b/q02_decision_regressor_plot/__pycache__/build.cpython-36.pyc differ diff --git a/q02_decision_regressor_plot/build.py b/q02_decision_regressor_plot/build.py index 020d81e..0fc57a1 100644 --- a/q02_decision_regressor_plot/build.py +++ b/q02_decision_regressor_plot/build.py @@ -1,3 +1,4 @@ +# %load q02_decision_regressor_plot/build.py # default imports from sklearn.model_selection import train_test_split from sklearn.tree import DecisionTreeRegressor @@ -5,13 +6,35 @@ import pandas as pd import matplotlib.pyplot as plt import numpy as np -plt.switch_backend('agg') -data = pd.read_csv("./data/house_pricing.csv") +data = pd.read_csv('./data/house_pricing.csv') X = data.iloc[:, :-1] y = data.iloc[:, -1] X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3, random_state=9) depth_list = [2, 8, 10, 15, 20, 25, 30, 35, 45, 50, 80] - +mse_train=[] +mse_test=[] # Write your solution here : +def decision_regressor_plot(X_train,X_test,y_train,y_test,depths): + fig=plt.figure() + for d in depths: + dtr=DecisionTreeRegressor(max_depth=d) + + dtr.fit(X_train,y_train) + + predicted=dtr.predict(X_train) + mean=mean_squared_error(y_train,predicted) + mse_train.append(mean) + + predicted=dtr.predict(X_test) + mean=mean_squared_error(y_test,predicted) + mse_test.append(mean) + + + plt.plot(depth_list,mse_train) + plt.plot(depth_list,mse_test) + return fig + + + diff --git a/q02_decision_regressor_plot/tests/__pycache__/__init__.cpython-36.pyc b/q02_decision_regressor_plot/tests/__pycache__/__init__.cpython-36.pyc new file mode 100644 index 0000000..ca8d631 Binary files /dev/null and b/q02_decision_regressor_plot/tests/__pycache__/__init__.cpython-36.pyc differ diff --git a/q02_decision_regressor_plot/tests/__pycache__/test_q02_decision_regressor_plot.cpython-36.pyc b/q02_decision_regressor_plot/tests/__pycache__/test_q02_decision_regressor_plot.cpython-36.pyc new file mode 100644 index 0000000..83c7102 Binary files /dev/null and b/q02_decision_regressor_plot/tests/__pycache__/test_q02_decision_regressor_plot.cpython-36.pyc differ diff --git a/q04_decision_classifier_plot/__pycache__/__init__.cpython-36.pyc b/q04_decision_classifier_plot/__pycache__/__init__.cpython-36.pyc new file mode 100644 index 0000000..618a42a Binary files /dev/null and b/q04_decision_classifier_plot/__pycache__/__init__.cpython-36.pyc differ diff --git a/q04_decision_classifier_plot/__pycache__/build.cpython-36.pyc b/q04_decision_classifier_plot/__pycache__/build.cpython-36.pyc new file mode 100644 index 0000000..88db812 Binary files /dev/null and b/q04_decision_classifier_plot/__pycache__/build.cpython-36.pyc differ diff --git a/q04_decision_classifier_plot/build.py b/q04_decision_classifier_plot/build.py index 44e9e87..e17d747 100644 --- a/q04_decision_classifier_plot/build.py +++ b/q04_decision_classifier_plot/build.py @@ -1,3 +1,4 @@ +# %load q04_decision_classifier_plot/build.py # default imports from sklearn.model_selection import RandomizedSearchCV from sklearn.tree import DecisionTreeClassifier @@ -6,9 +7,8 @@ import matplotlib.pyplot as plt import pandas as pd import numpy as np -plt.switch_backend('agg') -data = pd.read_csv("./data/loan_prediction.csv") +data = pd.read_csv('./data/loan_prediction.csv') np.random.seed(9) X = data.iloc[:, :-1] y = data.iloc[:, -1] @@ -18,3 +18,23 @@ # Write your solution here : +def decision_classifier_plot(X_train,X_test,y_train,y_test,depths): + accuracy_fit=[] + accuracy_predict=[] + for a in depths: + dtr=DecisionTreeClassifier(max_depth=a) + dtr.fit(X_train,y_train) + predicted=dtr.predict(X_train) + accuracy_fit.append(accuracy_score(y_train,predicted)) + + predicted=dtr.predict(X_test) + accuracy_predict.append(accuracy_score(y_test,predicted)) + plt.plot(depths,accuracy_fit) + plt.plot(depths,accuracy_predict) + plt.show() + + + + + + diff --git a/q04_decision_classifier_plot/tests/__pycache__/__init__.cpython-36.pyc b/q04_decision_classifier_plot/tests/__pycache__/__init__.cpython-36.pyc new file mode 100644 index 0000000..9e4b8bb Binary files /dev/null and b/q04_decision_classifier_plot/tests/__pycache__/__init__.cpython-36.pyc differ diff --git a/q04_decision_classifier_plot/tests/__pycache__/test_q04_decision_classifier_plot.cpython-36.pyc b/q04_decision_classifier_plot/tests/__pycache__/test_q04_decision_classifier_plot.cpython-36.pyc new file mode 100644 index 0000000..bdd9f97 Binary files /dev/null and b/q04_decision_classifier_plot/tests/__pycache__/test_q04_decision_classifier_plot.cpython-36.pyc differ