## How to implement voting ensemble in Python
## DataSet: skleran.datasets.load_breast_cancer()
def Snippet_184(): 
    print()
    print(format('How to implement voting ensemble in Python','*^82'))    
    
    import warnings
    warnings.filterwarnings("ignore")
    
    # load libraries
    from sklearn import model_selection
    from sklearn.linear_model import LogisticRegression
    from sklearn.tree import DecisionTreeClassifier
    from sklearn.svm import SVC
    from sklearn.ensemble import VotingClassifier
    from sklearn import datasets
    from sklearn.model_selection import train_test_split
    import matplotlib.pyplot as plt    
    
    plt.style.use('ggplot')

    # load datasets
    seed = 42
    dataset = datasets.load_breast_cancer()
    X = dataset.data; y = dataset.target
    X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.25)
    kfold = model_selection.KFold(n_splits=10, random_state=seed)
    
    # create different models
    estimators = []
    model1 = LogisticRegression(); estimators.append(('logistic', model1))
    model2 = DecisionTreeClassifier(); estimators.append(('cart', model2))
    model3 = SVC(); estimators.append(('svm', model3))
    
    # create the ensemble model
    ensemble = VotingClassifier(estimators)
    results = model_selection.cross_val_score(ensemble, X_train, y_train, cv=kfold)
    print(); print(results.mean())
Snippet_184()

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