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