Method transform

sklearn/preprocessing/_label.py:124–144

Transform labels to normalized encoding. Parameters ---------- y : array-like of shape (n_samples,) Target values. Returns ------- y : array-like of shape (n_samples,) Labels as normalized encodings.

(self, y)

        return y

    def transform(self, y):
        """Transform labels to normalized encoding.

        Parameters
        ----------
        y : array-like of shape (n_samples,)
            Target values.

        Returns
        -------
        y : array-like of shape (n_samples,)
            Labels as normalized encodings.
        """
        check_is_fitted(self)
        xp, _ = get_namespace(y)
        y = column_or_1d(y, dtype=self.classes_.dtype, warn=True)
        # transform of empty array is empty array
        if _num_samples(y) == 0:
            return xp.asarray([])

        return _encode(y, uniques=self.classes_)

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