7d949ddda1c424773171a1db21f68eb8e6bb17cd,doc/examples/xx_applications/plot_haar_extraction_selection_classification.py,,,#,68

Before Change

// Once the feature are extracted, we can train and test the a new classifier.

clf.fit(X_train, y_train)
y_pred = clf.predict(X_test)
print(classification_report(y_test, y_pred))
plt.show()

After Change

clf.fit(X_train, y_train)
time_subset_features = time() - t_start

auc_subset_features = roc_auc_score(y_test, clf.predict_proba(X_test)[:, 1])

summary = ("Training on the full feature set took {:.3f}s and had an "
           "AUC of {:.2f}. Training on the feature subset took {:.3f}s "

Instances