Method fit

sklearn/preprocessing/_data.py:2376–2396

Only validates estimator's parameters. This method allows to: (i) validate the estimator's parameters and (ii) be consistent with the scikit-learn transformer API. Parameters ---------- X : {array-like, sparse matrix} of shape (n_samples, n_features)

(self, X, y=None)

    @_fit_context(prefer_skip_nested_validation=True)
    def fit(self, X, y=None):
        """Only validates estimator's parameters.

        This method allows to: (i) validate the estimator's parameters and
        (ii) be consistent with the scikit-learn transformer API.

        Parameters
        ----------
        X : {array-like, sparse matrix} of shape (n_samples, n_features)
            The data.

        y : None
            Ignored.

        Returns
        -------
        self : object
            Fitted transformer.
        """
        validate_data(self, X, accept_sparse="csr")
        return self

    def transform(self, X, copy=None):
        """Binarize each element of X.