| Logging training | |
| Running DummyClassifier() | |
| accuracy: 0.491 recall_macro: 0.333 precision_macro: 0.164 f1_macro: 0.219 | |
| === new best DummyClassifier() (using recall_macro): | |
| accuracy: 0.491 recall_macro: 0.333 precision_macro: 0.164 f1_macro: 0.219 | |
| Running GaussianNB() | |
| accuracy: 0.218 recall_macro: 0.354 precision_macro: 0.473 f1_macro: 0.176 | |
| === new best GaussianNB() (using recall_macro): | |
| accuracy: 0.218 recall_macro: 0.354 precision_macro: 0.473 f1_macro: 0.176 | |
| Running MultinomialNB() | |
| accuracy: 0.660 recall_macro: 0.614 precision_macro: 0.620 f1_macro: 0.612 | |
| === new best MultinomialNB() (using recall_macro): | |
| accuracy: 0.660 recall_macro: 0.614 precision_macro: 0.620 f1_macro: 0.612 | |
| Running DecisionTreeClassifier(class_weight='balanced', max_depth=1) | |
| accuracy: 0.610 recall_macro: 0.460 precision_macro: 0.466 f1_macro: 0.422 | |
| Running DecisionTreeClassifier(class_weight='balanced', max_depth=5) | |
| accuracy: 0.633 recall_macro: 0.606 precision_macro: 0.634 f1_macro: 0.598 | |
| Running DecisionTreeClassifier(class_weight='balanced', min_impurity_decrease=0.01) | |
| accuracy: 0.604 recall_macro: 0.592 precision_macro: 0.594 f1_macro: 0.574 | |
| Running LogisticRegression(C=0.1, class_weight='balanced', max_iter=1000) | |
| accuracy: 0.693 recall_macro: 0.666 precision_macro: 0.658 f1_macro: 0.657 | |
| === new best LogisticRegression(C=0.1, class_weight='balanced', max_iter=1000) (using recall_macro): | |
| accuracy: 0.693 recall_macro: 0.666 precision_macro: 0.658 f1_macro: 0.657 | |
| Running LogisticRegression(class_weight='balanced', max_iter=1000) | |
| accuracy: 0.694 recall_macro: 0.664 precision_macro: 0.658 f1_macro: 0.656 | |
| Best model: | |
| LogisticRegression(C=0.1, class_weight='balanced', max_iter=1000) | |
| Best Scores: | |
| accuracy: 0.693 recall_macro: 0.666 precision_macro: 0.658 f1_macro: 0.657 | |