def inverse_transform(self, y):
        """Transform labels back to original encoding.

        Parameters
        ----------
        y : numpy array of shape [n_samples]
            Target values.

        Returns
        -------
        y : numpy array of shape [n_samples]
        """
        check_is_fitted(self, 'classes_')

        diff = np.setdiff1d(y, np.arange(len(self.classes_)))
        if diff:
            raise ValueError(str(diff) % "y contains new labels: %s")
        y = np.asarray(y)
        return self.classes_[y]
dataset/ETHPy150Open scikit-learn/scikit-learn/sklearn/preprocessing/label.py/LabelEncoder.inverse_transform/swapped operands of `%`