| Logging training | |
| Running DummyClassifier() | |
| accuracy: 0.456 recall_macro: 0.333 precision_macro: 0.152 f1_macro: 0.209 | |
| === new best DummyClassifier() (using recall_macro): | |
| accuracy: 0.456 recall_macro: 0.333 precision_macro: 0.152 f1_macro: 0.209 | |
| Running GaussianNB() | |
| accuracy: 0.456 recall_macro: 0.333 precision_macro: 0.152 f1_macro: 0.209 | |
| Running MultinomialNB() | |
| accuracy: 0.456 recall_macro: 0.333 precision_macro: 0.152 f1_macro: 0.209 | |
| Running DecisionTreeClassifier(class_weight='balanced', max_depth=1) | |
| accuracy: 0.354 recall_macro: 0.345 precision_macro: 0.226 f1_macro: 0.268 | |
| === new best DecisionTreeClassifier(class_weight='balanced', max_depth=1) (using recall_macro): | |
| accuracy: 0.354 recall_macro: 0.345 precision_macro: 0.226 f1_macro: 0.268 | |
| Running DecisionTreeClassifier(class_weight='balanced', max_depth=5) | |
| accuracy: 0.360 recall_macro: 0.352 precision_macro: 0.352 f1_macro: 0.339 | |
| === new best DecisionTreeClassifier(class_weight='balanced', max_depth=5) (using recall_macro): | |
| accuracy: 0.360 recall_macro: 0.352 precision_macro: 0.352 f1_macro: 0.339 | |
| Running DecisionTreeClassifier(class_weight='balanced', min_impurity_decrease=0.01) | |
| accuracy: 0.245 recall_macro: 0.333 precision_macro: 0.082 f1_macro: 0.131 | |
| Running LogisticRegression(C=0.1, class_weight='balanced', max_iter=1000) | |
| accuracy: 0.361 recall_macro: 0.353 precision_macro: 0.241 f1_macro: 0.278 | |
| === new best LogisticRegression(C=0.1, class_weight='balanced', max_iter=1000) (using recall_macro): | |
| accuracy: 0.361 recall_macro: 0.353 precision_macro: 0.241 f1_macro: 0.278 | |
| Running LogisticRegression(class_weight='balanced', max_iter=1000) | |
| accuracy: 0.361 recall_macro: 0.353 precision_macro: 0.241 f1_macro: 0.278 | |
| Best model: | |
| LogisticRegression(C=0.1, class_weight='balanced', max_iter=1000) | |
| Best Scores: | |
| accuracy: 0.361 recall_macro: 0.353 precision_macro: 0.241 f1_macro: 0.278 | |