Logging training
Running DummyClassifier()
accuracy: 0.846 average_precision: 0.154 roc_auc: 0.500 recall_macro: 0.500 f1_macro: 0.458
=== new best DummyClassifier() (using recall_macro):
accuracy: 0.846 average_precision: 0.154 roc_auc: 0.500 recall_macro: 0.500 f1_macro: 0.458

Running GaussianNB()
accuracy: 0.469 average_precision: 0.171 roc_auc: 0.646 recall_macro: 0.550 f1_macro: 0.426
=== new best GaussianNB() (using recall_macro):
accuracy: 0.469 average_precision: 0.171 roc_auc: 0.646 recall_macro: 0.550 f1_macro: 0.426

Running MultinomialNB()
accuracy: 0.826 average_precision: 0.295 roc_auc: 0.680 recall_macro: 0.542 f1_macro: 0.547
Running DecisionTreeClassifier(class_weight='balanced', max_depth=1)
accuracy: 0.872 average_precision: 0.519 roc_auc: 0.883 recall_macro: 0.883 f1_macro: 0.802
=== new best DecisionTreeClassifier(class_weight='balanced', max_depth=1) (using recall_macro):
accuracy: 0.872 average_precision: 0.519 roc_auc: 0.883 recall_macro: 0.883 f1_macro: 0.802

Running DecisionTreeClassifier(class_weight='balanced', max_depth=5)
accuracy: 0.885 average_precision: 0.552 roc_auc: 0.822 recall_macro: 0.816 f1_macro: 0.786
Running DecisionTreeClassifier(class_weight='balanced', min_impurity_decrease=0.01)
accuracy: 0.882 average_precision: 0.603 roc_auc: 0.800 recall_macro: 0.835 f1_macro: 0.789
Running LogisticRegression(C=0.1, class_weight='balanced', max_iter=1000)
accuracy: 0.903 average_precision: 0.782 roc_auc: 0.066 recall_macro: 0.854 f1_macro: 0.820
Running LogisticRegression(C=1, class_weight='balanced', max_iter=1000)
accuracy: 0.913 average_precision: 0.762 roc_auc: 0.083 recall_macro: 0.853 f1_macro: 0.834

Best model:
DecisionTreeClassifier(class_weight='balanced', max_depth=1)
Best Scores:
accuracy: 0.872 average_precision: 0.519 roc_auc: 0.883 recall_macro: 0.883 f1_macro: 0.802