(self)
return self._inverse_transform
Apply inverse transformations in reverse order

        All estimators in the pipeline must support ``inverse_transform``.

        Parameters
        ----------

        Xt : array-like, shape (n_samples, n_transformed_features)
            Data samples, where ``n_samples`` is the number of samples and
            ``n_features`` is the number of features. Must fulfill
            input requirements of last step of pipeline's
            ``inverse_transform`` method.

        Returns
        -------
        Xt : array-like, shape (n_samples, n_features)
Apply inverse transformations in reverse order
Apply inverse transformations in reverse order
def inverse_transform(self):
        """Apply inverse transformations in reverse order

        All estimators in the pipeline must support ``inverse_transform``.

        Parameters
        ----------

        Xt : array-like, shape (n_samples, n_transformed_features)
            Data samples, where ``n_samples`` is the number of samples and
            ``n_features`` is the number of features. Must fulfill
            input requirements of last step of pipeline's
            ``inverse_transform`` method.

        Returns
        -------
        Xt : array-like, shape (n_samples, n_features)
        """
        # raise AttributeError if necessary for hasattr behaviour
        for _, _, transform in self._iter():
            transform.inverse_transform
        return self._inverse_transform
def inverse_transform ( self ) : # raise AttributeError if necessary for hasattr behaviour for _ , _ , transform in self . _iter ( ) : transform . inverse_transform return self . _inverse_transform