Method transform

sklearn/preprocessing/_data.py:547–586

Scale features of X according to feature_range. Parameters ---------- X : array-like of shape (n_samples, n_features) Input data that will be transformed. Returns ------- Xt : ndarray of shape (n_samples, n_features) Transform

(self, X)

        return self

    def transform(self, X):
        """Scale features of X according to feature_range.

        Parameters
        ----------
        X : array-like of shape (n_samples, n_features)
            Input data that will be transformed.

        Returns
        -------
        Xt : ndarray of shape (n_samples, n_features)
            Transformed data.
        """
        check_is_fitted(self)

        xp, _ = get_namespace(X)

        X = validate_data(
            self,
            X,
            copy=self.copy,
            dtype=_array_api.supported_float_dtypes(xp, device=device(X)),
            force_writeable=True,
            ensure_all_finite="allow-nan",
            reset=False,
        )

        X *= self.scale_
        X += self.min_
        if self.clip:
            device_ = device(X)
            X = _modify_in_place_if_numpy(
                xp,
                xp.clip,
                X,
                xp.asarray(self.feature_range[0], dtype=X.dtype, device=device_),
                xp.asarray(self.feature_range[1], dtype=X.dtype, device=device_),
                out=X,
            )
        return X

    def inverse_transform(self, X):
        """Undo the scaling of X according to feature_range.