def test_plot_feature_importance(self):
"""
Test plot_feature_importance function
"""
sb_clf, cv_gen = self._prepare_clf_data_set(oob_score=True)
oos_score = ml_cross_val_score(sb_clf,
self.X_train,
self.y_train_clf,
cv_gen=cv_gen,
sample_weight_score=None,
scoring=accuracy_score).mean()
sb_clf.fit(self.X_train, self.y_train_clf)
mdi_feat_imp = mean_decrease_impurity(sb_clf, self.X_train.columns)
plot_feature_importance(mdi_feat_imp,
oob_score=sb_clf.oob_score_,
oos_score=oos_score)
plot_feature_importance(mdi_feat_imp,
oob_score=sb_clf.oob_score_,
oos_score=oos_score,
save_fig=True,
output_path='test.png')
os.remove('test.png')
def test_plot_feature_importance(self):
"""
Test plot_feature_importance function
"""
oos_score = cross_val_score(self.bag_clf, self.X, self.y, cv=self.cv_gen, scoring='accuracy').mean()
mdi_feat_imp = mean_decrease_impurity(self.bag_clf, self.X.columns)
plot_feature_importance(mdi_feat_imp, oob_score=self.bag_clf.oob_score_, oos_score=oos_score)
plot_feature_importance(mdi_feat_imp, oob_score=self.bag_clf.oob_score_, oos_score=oos_score,
save_fig=True, output_path='test.png')
os.remove('test.png')
