An ensemble classifier that relies on soft voting.

soft_voting.py

# Out of the three models, 
# only SVC requires some tweaking to output its confidence
# this is done by setting probability=True:
svm_clf_tweaked = SVC(gamma='scale', probability=True, random_state=42)

soft_voting_clf = VotingClassifier(estimators=[('svm', svm_clf_tweaked), ('tree', tree_clf), ('log', log_clf)], 
                             voting='soft')

soft_voting_clf.fit(X_train, y_train) # training
y_pred_voting = soft_voting_clf.predict(X_test) # predicting
accuracy_score(y_test, y_pred_voting) # evaluating

# Output of the evaluation: 0.912