'Perform classification on an array of test vectors X.
Parameters
X : array-like, shape = (n_samples, n_features)
Returns
C : array, shape = (n_samples,)
Predicted target values for X, values are from ``classes_``'

def predict(self, X):

    check_is_fitted(self, ['classes_', 'n_classes_'])
    X = check_array(X)
    return self.base_estimator_.predict(X)
