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Replaced deprecated module (cross_validation) Ch-02 naive_bayes.py #13

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Replaced deprecated module (cross_validation) Ch-02 naive_bayes.py #13

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12 changes: 6 additions & 6 deletions Chapter 02/code/naive_bayes.py
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Original file line number Diff line number Diff line change
@@ -1,7 +1,7 @@
import numpy as np
import matplotlib.pyplot as plt
from sklearn.naive_bayes import GaussianNB
from sklearn import cross_validation
from sklearn import model_selection

from utilities import visualize_classifier

Expand Down Expand Up @@ -32,7 +32,7 @@
# Cross validation

# Split data into training and test data
X_train, X_test, y_train, y_test = cross_validation.train_test_split(X, y, test_size=0.2, random_state=3)
X_train, X_test, y_train, y_test = model_selection.train_test_split(X, y, test_size=0.2, random_state=3)
classifier_new = GaussianNB()
classifier_new.fit(X_train, y_train)
y_test_pred = classifier_new.predict(X_test)
Expand All @@ -48,19 +48,19 @@
# Scoring functions

num_folds = 3
accuracy_values = cross_validation.cross_val_score(classifier,
accuracy_values = model_selection.cross_val_score(classifier,
X, y, scoring='accuracy', cv=num_folds)
print("Accuracy: " + str(round(100*accuracy_values.mean(), 2)) + "%")

precision_values = cross_validation.cross_val_score(classifier,
precision_values = model_selection.cross_val_score(classifier,
X, y, scoring='precision_weighted', cv=num_folds)
print("Precision: " + str(round(100*precision_values.mean(), 2)) + "%")

recall_values = cross_validation.cross_val_score(classifier,
recall_values = model_selection.cross_val_score(classifier,
X, y, scoring='recall_weighted', cv=num_folds)
print("Recall: " + str(round(100*recall_values.mean(), 2)) + "%")

f1_values = cross_validation.cross_val_score(classifier,
f1_values = model_selection.cross_val_score(classifier,
X, y, scoring='f1_weighted', cv=num_folds)
print("F1: " + str(round(100*f1_values.mean(), 2)) + "%")