def normalization(self, X, y=None):
    X = ((X - np.full(X.shape, self.mean_X_train)) / np.full(X.shape, self.std_X_train))
    if (y is not None):
        y = ((y - self.mean_y_train) / self.std_y_train)
        return (X, y)
    else:
        return X
def normalization(self, X, y=None):
    X = ((X - np.full(X.shape, self.mean_X_train)) / np.full(X.shape, self.std_X_train))
    if (y is not None):
        y = ((y - self.mean_y_train) / self.std_y_train)
        return (X, y)
    else:
        return X