Method fit

sklearn/preprocessing/_encoders.py:982–1007

Fit OneHotEncoder to X. Parameters ---------- X : array-like of shape (n_samples, n_features) The data to determine the categories of each feature. y : None Ignored. This parameter exists only for compatibility with :clas

(self, X, y=None)

    @_fit_context(prefer_skip_nested_validation=True)
    def fit(self, X, y=None):
        """
        Fit OneHotEncoder to X.

        Parameters
        ----------
        X : array-like of shape (n_samples, n_features)
            The data to determine the categories of each feature.

        y : None
            Ignored. This parameter exists only for compatibility with
            :class:`~sklearn.pipeline.Pipeline`.

        Returns
        -------
        self
            Fitted encoder.
        """
        self._fit(
            X,
            handle_unknown=self.handle_unknown,
            ensure_all_finite="allow-nan",
        )
        self._set_drop_idx()
        self._n_features_outs = self._compute_n_features_outs()
        return self

    def transform(self, X):
        """