|
Logging training |
|
Running DummyClassifier() |
|
accuracy: 0.053 recall_macro: 0.001 precision_macro: 0.000 f1_macro: 0.000 |
|
=== new best DummyClassifier() (using recall_macro): |
|
accuracy: 0.053 recall_macro: 0.001 precision_macro: 0.000 f1_macro: 0.000 |
|
|
|
Running GaussianNB() |
|
accuracy: 0.177 recall_macro: 0.184 precision_macro: 0.214 f1_macro: 0.164 |
|
=== new best GaussianNB() (using recall_macro): |
|
accuracy: 0.177 recall_macro: 0.184 precision_macro: 0.214 f1_macro: 0.164 |
|
|
|
Running MultinomialNB() |
|
accuracy: 0.296 recall_macro: 0.029 precision_macro: 0.028 f1_macro: 0.022 |
|
Running DecisionTreeClassifier(class_weight='balanced', max_depth=1) |
|
accuracy: 0.038 recall_macro: 0.001 precision_macro: 0.000 f1_macro: 0.000 |
|
Running DecisionTreeClassifier(class_weight='balanced', max_depth=2249) |
|
accuracy: 0.931 recall_macro: 0.656 precision_macro: 0.641 f1_macro: 0.638 |
|
=== new best DecisionTreeClassifier(class_weight='balanced', max_depth=2249) (using recall_macro): |
|
accuracy: 0.931 recall_macro: 0.656 precision_macro: 0.641 f1_macro: 0.638 |
|
|
|
Running DecisionTreeClassifier(class_weight='balanced', min_impurity_decrease=0.01) |
|
accuracy: 0.037 recall_macro: 0.001 precision_macro: 0.000 f1_macro: 0.000 |
|
Running LogisticRegression(C=0.1, class_weight='balanced', max_iter=1000) |
|
accuracy: 0.087 recall_macro: 0.110 precision_macro: 0.082 f1_macro: 0.072 |
|
Running LogisticRegression(class_weight='balanced', max_iter=1000) |
|
accuracy: 0.188 recall_macro: 0.168 precision_macro: 0.135 f1_macro: 0.127 |
|
|
|
Best model: |
|
DecisionTreeClassifier(class_weight='balanced', max_depth=2249) |
|
Best Scores: |
|
accuracy: 0.931 recall_macro: 0.656 precision_macro: 0.641 f1_macro: 0.638 |
|
|