# Ensemble of Models 
estimator = [] 
estimator.append(('LR',LogisticRegression(solver ='lbfgs',multi_class ='multinomial',max_iter = 200))) 
estimator.append(('SVC', SVC(gamma ='auto', probability = True))) 
estimator.append(('DTC', DecisionTreeClassifier())) 

# Voting Classifier with hard voting 
hard_voting = VotingClassifier(estimators = estimator, voting ='hard') 
hard_voting.fit(X_train, y_train) 
y_pred = hard_voting.predict(X_test)   

# accuracy_score metric to predict Accuracy 
score = accuracy_score(y_test, y_pred) 
print("Hard Voting Score % d" % score)

# Voting Classifier with soft voting 
soft_voting = VotingClassifier(estimators = estimator, voting ='soft') 
soft_voting.fit(X_train, y_train) 
y_pred = soft_voting.predict(X_test) 


# Using accuracy_score 
score = accuracy_score(y_test, y_pred) 
print("Soft Voting Score % d" % score)