| 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: 0.653 recall_macro: 0.513 precision_macro: 0.392 f1_macro: 0.381 | |
| === new best GaussianNB() (using recall_macro): | |
| accuracy: 0.653 recall_macro: 0.513 precision_macro: 0.392 f1_macro: 0.381 | |
| Running MultinomialNB() | |
| accuracy: 0.893 recall_macro: 0.344 precision_macro: 0.464 f1_macro: 0.336 | |
| 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: 0.562 recall_macro: 0.514 precision_macro: 0.384 f1_macro: 0.343 | |
| === new best DecisionTreeClassifier(class_weight='balanced', max_depth=5) (using recall_macro): | |
| accuracy: 0.562 recall_macro: 0.514 precision_macro: 0.384 f1_macro: 0.343 | |
| Running DecisionTreeClassifier(class_weight='balanced', min_impurity_decrease=0.01) | |
| accuracy: 0.535 recall_macro: 0.519 precision_macro: 0.382 f1_macro: 0.334 | |
| === new best DecisionTreeClassifier(class_weight='balanced', min_impurity_decrease=0.01) (using recall_macro): | |
| accuracy: 0.535 recall_macro: 0.519 precision_macro: 0.382 f1_macro: 0.334 | |
| Running LogisticRegression(C=0.1, class_weight='balanced', max_iter=1000) | |
| accuracy: 0.736 recall_macro: 0.632 precision_macro: 0.440 f1_macro: 0.458 | |
| === new best LogisticRegression(C=0.1, class_weight='balanced', max_iter=1000) (using recall_macro): | |
| accuracy: 0.736 recall_macro: 0.632 precision_macro: 0.440 f1_macro: 0.458 | |
| Running LogisticRegression(C=1, class_weight='balanced', max_iter=1000) | |
| accuracy: 0.745 recall_macro: 0.619 precision_macro: 0.441 f1_macro: 0.461 | |
| Best model: | |
| LogisticRegression(C=0.1, class_weight='balanced', max_iter=1000) | |
| Best Scores: | |
| accuracy: 0.736 recall_macro: 0.632 precision_macro: 0.440 f1_macro: 0.458 | |