def _fit(self, X: np.ndarray, y: np.ndarray) -> NoReturn:
    '\n        Fit Least Squares model to polynomial transformed samples\n\n        Parameters\n        ----------\n        X : ndarray of shape (n_samples, n_features)\n            Input data to fit an estimator for\n\n        y : ndarray of shape (n_samples, )\n            Responses of input data to fit to\n        '
    self.vander_linear_.fit(self.__transform(X), y)
Fit Least Squares model to polynomial transformed samples

Parameters
----------
X : ndarray of shape (n_samples, n_features)
    Input data to fit an estimator for

y : ndarray of shape (n_samples, )
    Responses of input data to fit to
def _fit(self, X: np.ndarray, y: np.ndarray) -> NoReturn:
    '\n        Fit Least Squares model to polynomial transformed samples\n\n        Parameters\n        ----------\n        X : ndarray of shape (n_samples, n_features)\n            Input data to fit an estimator for\n\n        y : ndarray of shape (n_samples, )\n            Responses of input data to fit to\n        '
    self.vander_linear_.fit(self.__transform(X), y)