(self, X)
return np.ones(X.shape[0], dtype=np.int64)
A reference implementation of a predicting function.

        Parameters
        ----------
        X : {array-like, sparse matrix}, shape (n_samples, n_features)
            The training input samples.

        Returns
        -------
        y : ndarray, shape (n_samples,)
            Returns an array of ones.
A reference implementation of a predicting function.
A reference implementation of a predicting function .
def predict(self, X):
        """ A reference implementation of a predicting function.

        Parameters
        ----------
        X : {array-like, sparse matrix}, shape (n_samples, n_features)
            The training input samples.

        Returns
        -------
        y : ndarray, shape (n_samples,)
            Returns an array of ones.
        """
        X = check_array(X, accept_sparse=True)
        check_is_fitted(self, 'is_fitted_')
        return np.ones(X.shape[0], dtype=np.int64)
def predict ( self , X ) : X = check_array ( X , accept_sparse = True ) check_is_fitted ( self , 'is_fitted_' ) return np . ones ( X . shape [ 0 ] , dtype = np . int64 )