| Logging training | |
| Running DummyClassifier() | |
| accuracy: 0.513 average_precision: 0.487 roc_auc: 0.500 recall_macro: 0.500 f1_macro: 0.339 | |
| === new best DummyClassifier() (using recall_macro): | |
| accuracy: 0.513 average_precision: 0.487 roc_auc: 0.500 recall_macro: 0.500 f1_macro: 0.339 | |
| Running GaussianNB() | |
| accuracy: 0.592 average_precision: 0.669 roc_auc: 0.824 recall_macro: 0.602 f1_macro: 0.534 | |
| === new best GaussianNB() (using recall_macro): | |
| accuracy: 0.592 average_precision: 0.669 roc_auc: 0.824 recall_macro: 0.602 f1_macro: 0.534 | |
| Running MultinomialNB() | |
| accuracy: 0.857 average_precision: 0.934 roc_auc: 0.931 recall_macro: 0.856 f1_macro: 0.856 | |
| === new best MultinomialNB() (using recall_macro): | |
| accuracy: 0.857 average_precision: 0.934 roc_auc: 0.931 recall_macro: 0.856 f1_macro: 0.856 | |
| Running DecisionTreeClassifier(class_weight='balanced', max_depth=1) | |
| accuracy: 0.749 average_precision: 0.680 roc_auc: 0.749 recall_macro: 0.749 f1_macro: 0.749 | |
| Running DecisionTreeClassifier(class_weight='balanced', max_depth=5) | |
| accuracy: 0.883 average_precision: 0.943 roc_auc: 0.940 recall_macro: 0.882 f1_macro: 0.882 | |
| === new best DecisionTreeClassifier(class_weight='balanced', max_depth=5) (using recall_macro): | |
| accuracy: 0.883 average_precision: 0.943 roc_auc: 0.940 recall_macro: 0.882 f1_macro: 0.882 | |
| Running DecisionTreeClassifier(class_weight='balanced', min_impurity_decrease=0.01) | |
| accuracy: 0.833 average_precision: 0.857 roc_auc: 0.878 recall_macro: 0.832 f1_macro: 0.833 | |
| Running LogisticRegression(C=0.1, class_weight='balanced', max_iter=1000) | |
| accuracy: 0.873 average_precision: 0.941 roc_auc: 0.060 recall_macro: 0.872 f1_macro: 0.873 | |
| Running LogisticRegression(class_weight='balanced', max_iter=1000) | |
| accuracy: 0.886 average_precision: 0.949 roc_auc: 0.051 recall_macro: 0.885 f1_macro: 0.886 | |
| === new best LogisticRegression(class_weight='balanced', max_iter=1000) (using recall_macro): | |
| accuracy: 0.886 average_precision: 0.949 roc_auc: 0.051 recall_macro: 0.885 f1_macro: 0.886 | |
| Best model: | |
| LogisticRegression(class_weight='balanced', max_iter=1000) | |
| Best Scores: | |
| accuracy: 0.886 average_precision: 0.949 roc_auc: 0.051 recall_macro: 0.885 f1_macro: 0.886 | |