| Logging training | |
| Running DummyClassifier() | |
| accuracy: 0.632 average_precision: 0.368 roc_auc: 0.500 recall_macro: 0.500 f1_macro: 0.387 | |
| === new best DummyClassifier() (using recall_macro): | |
| accuracy: 0.632 average_precision: 0.368 roc_auc: 0.500 recall_macro: 0.500 f1_macro: 0.387 | |
| Running GaussianNB() | |
| accuracy: 0.947 average_precision: 0.966 roc_auc: 0.983 recall_macro: 0.933 f1_macro: 0.942 | |
| === new best GaussianNB() (using recall_macro): | |
| accuracy: 0.947 average_precision: 0.966 roc_auc: 0.983 recall_macro: 0.933 f1_macro: 0.942 | |
| Running MultinomialNB() | |
| accuracy: 0.975 average_precision: 0.984 roc_auc: 0.987 recall_macro: 0.972 f1_macro: 0.973 | |
| === new best MultinomialNB() (using recall_macro): | |
| accuracy: 0.975 average_precision: 0.984 roc_auc: 0.987 recall_macro: 0.972 f1_macro: 0.973 | |
| Running DecisionTreeClassifier(class_weight='balanced', max_depth=1) | |
| accuracy: 0.975 average_precision: 0.949 roc_auc: 0.972 recall_macro: 0.972 f1_macro: 0.973 | |
| Running DecisionTreeClassifier(class_weight='balanced', max_depth=5) | |
| accuracy: 0.956 average_precision: 0.919 roc_auc: 0.957 recall_macro: 0.952 f1_macro: 0.953 | |
| Running DecisionTreeClassifier(class_weight='balanced', min_impurity_decrease=0.01) | |
| accuracy: 0.975 average_precision: 0.949 roc_auc: 0.972 recall_macro: 0.972 f1_macro: 0.973 | |
| Running LogisticRegression(C=0.1, class_weight='balanced', max_iter=1000) | |
| accuracy: 0.975 average_precision: 0.987 roc_auc: 0.990 recall_macro: 0.972 f1_macro: 0.973 | |
| Running LogisticRegression(class_weight='balanced', max_iter=1000) | |
| accuracy: 0.975 average_precision: 0.987 roc_auc: 0.990 recall_macro: 0.972 f1_macro: 0.973 | |
| Best model: | |
| Pipeline(steps=[('minmaxscaler', MinMaxScaler()), ('multinomialnb', MultinomialNB())]) | |
| Best Scores: | |
| accuracy: 0.975 average_precision: 0.984 roc_auc: 0.987 recall_macro: 0.972 f1_macro: 0.973 | |