(self, X, y=None, **fit_params)
Train the learnable coefficients of this operator, if any.

        Return a trained version of this operator.  If this operator
        has free learnable coefficients, bind them to values that fit
        the data according to the operator's algorithm.  Do nothing if
        the operator implementation lacks a `fit` method or if the
        operator has been marked as `is_frozen_trained`.

        Parameters
        ----------
        X:
            Features that conform to the X property of input_schema_fit.
        y: optional
            Labels that conform to the y property of input_schema_fit.
            Default is None.
        fit_params: Dictionary, optional
            A dictionary of keyword parameters to be used during training.

        Returns
        -------
        TrainedOperator
            A new copy of this operators that is the same except that its
            learnable coefficients are bound to their trained values.
Train the learnable coefficients of this operator, if any.
Train the learnable coefficients of this operator if any .
def fit(self, X, y=None, **fit_params) -> "TrainedOperator":
        """Train the learnable coefficients of this operator, if any.

        Return a trained version of this operator.  If this operator
        has free learnable coefficients, bind them to values that fit
        the data according to the operator's algorithm.  Do nothing if
        the operator implementation lacks a `fit` method or if the
        operator has been marked as `is_frozen_trained`.

        Parameters
        ----------
        X:
            Features that conform to the X property of input_schema_fit.
        y: optional
            Labels that conform to the y property of input_schema_fit.
            Default is None.
        fit_params: Dictionary, optional
            A dictionary of keyword parameters to be used during training.

        Returns
        -------
        TrainedOperator
            A new copy of this operators that is the same except that its
            learnable coefficients are bound to their trained values.

        """
        pass
def fit ( self , X , y = None , * * fit_params ) -> "TrainedOperator" : pass