base.py 文件源码

def fit(self, x_, y, sample_weight=None):
        X, y = check_X_y(x_, y, accept_sparse=[], y_numeric=True, multi_output=False)

        x, y, X_offset, y_offset, X_scale = self._preprocess_data(
            x_, y, fit_intercept=self.fit_intercept, normalize=self.normalize,
            copy=self.copy_X, sample_weight=None)

        if sample_weight is not None:
            x, y = _rescale_data(x, y, sample_weight)

        self.iters = 0
        self.ind_ = np.ones(x.shape[1], dtype=bool) # initial guess
        if self.threshold > 0:
            self._reduce(x, y)
        else:
            self.coef_ = self._regress(x[:, self.ind_], y, self.alpha)

        if self.unbias and self.alpha >= 0:
            self._unbias(x, y)

        self._set_intercept(X_offset, y_offset, X_scale)
        return self