def predict_proba(self, X):
        if(self.voting_scheme == VotingClassifierDIY.SCHEME_COUNTING):
            raise AttributeError("This call is not supported for counting scheme mode!")
        predictions = []
        for i in range(len(self.clfs)):
            predictions.append(self.clfs[i].predict_proba(X))

        predictions = np.array(predictions)
        total = [np.average(predictions[:,i],axis=0) for i in range(X.shape[0])]

        return np.array(total)

    def predict(self, X):
        predictions = []

        if(self.voting_scheme == VotingClassifierDIY.SCHEME_COUNTING):
            for i in range(len(self.clfs)):
                predictions.append(self.clfs[i].predict(X))

        predictions = np.array(predictions)

        if(self.voting_scheme == VotingClassifierDIY.SCHEME_AVERAGING):
            predictions = self.predict_proba(X)
        total = []
        for i in range(X.shape[0]):
            if(self.voting_scheme == VotingClassifierDIY.SCHEME_AVERAGING):
                total.append(np.argmax(predictions[i]))
            else:
                total.append(np.argmax(np.bincount(predictions[:,i])))
        return np.array(total,dtype=int64)