('rf', rf_clf),
('mb', mb_clf),
('svm', svm_clf),
('sgd', sgd_clf)]
voting_clf = VotingClassifier(
estimators=estimators,
voting='hard')
for clf in (log_clf,mlp_clf,rf_clf,mb_clf,svm_clf,sgd_clf,voting_clf):
clf.fit(X, labels)
y_pred = clf.predict(X_test)
print(clf.__class__.__name__, accuracy_score(label_test, y_pred))
clf = BaggingClassifier(
LogisticRegression(),
n_estimators=100,
max_samples=2000,
bootstrap=True,
n_jobs=-1,
oob_score=True)
'''
X = X.toarray()
X_test = X_test.toarray()
Y = np.array(labels)
sgd = SGD()
sgd.fit(X, Y)
y_pred = sgd.predict(X_test)
print(accuracy_score(label_test, y_pred))
end = time.time()
print(end - start)
