| Logging training | |
| Running DummyClassifier() | |
| accuracy: 0.894 recall_macro: 0.333 precision_macro: 0.298 f1_macro: 0.315 | |
| === new best DummyClassifier() (using recall_macro): | |
| accuracy: 0.894 recall_macro: 0.333 precision_macro: 0.298 f1_macro: 0.315 | |
| Running GaussianNB() | |
| accuracy: 0.650 recall_macro: 0.492 precision_macro: 0.389 f1_macro: 0.375 | |
| === new best GaussianNB() (using recall_macro): | |
| accuracy: 0.650 recall_macro: 0.492 precision_macro: 0.389 f1_macro: 0.375 | |
| Running MultinomialNB() | |
| accuracy: 0.892 recall_macro: 0.342 precision_macro: 0.443 f1_macro: 0.334 | |
| Running DecisionTreeClassifier(class_weight='balanced', max_depth=1) | |
| accuracy: 0.820 recall_macro: 0.428 precision_macro: 0.320 f1_macro: 0.336 | |
| Running DecisionTreeClassifier(class_weight='balanced', max_depth=5) | |
| accuracy: 0.572 recall_macro: 0.512 precision_macro: 0.387 f1_macro: 0.349 | |
| === new best DecisionTreeClassifier(class_weight='balanced', max_depth=5) (using recall_macro): | |
| accuracy: 0.572 recall_macro: 0.512 precision_macro: 0.387 f1_macro: 0.349 | |
| Running DecisionTreeClassifier(class_weight='balanced', min_impurity_decrease=0.01) | |
| accuracy: 0.649 recall_macro: 0.530 precision_macro: 0.391 f1_macro: 0.377 | |
| === new best DecisionTreeClassifier(class_weight='balanced', min_impurity_decrease=0.01) (using recall_macro): | |
| accuracy: 0.649 recall_macro: 0.530 precision_macro: 0.391 f1_macro: 0.377 | |
| Running LogisticRegression(C=0.1, class_weight='balanced', max_iter=1000) | |
| accuracy: 0.733 recall_macro: 0.630 precision_macro: 0.440 f1_macro: 0.456 | |
| === new best LogisticRegression(C=0.1, class_weight='balanced', max_iter=1000) (using recall_macro): | |
| accuracy: 0.733 recall_macro: 0.630 precision_macro: 0.440 f1_macro: 0.456 | |
| Running LogisticRegression(C=1, class_weight='balanced', max_iter=1000) | |
| accuracy: 0.749 recall_macro: 0.617 precision_macro: 0.442 f1_macro: 0.462 | |
| Best model: | |
| LogisticRegression(C=0.1, class_weight='balanced', max_iter=1000) | |
| Best Scores: | |
| accuracy: 0.733 recall_macro: 0.630 precision_macro: 0.440 f1_macro: 0.456 | |