parallel.py 文件源码

def _decision_function(self, X):
        """Predict using the linear model

        Parameters
        ----------
        X : {array-like, sparse matrix}, shape (n_samples, n_features)

        Returns
        -------
        array, shape (n_samples,)
           Predicted target values per element in X.
        """
        check_is_fitted(self, ["t_", "coef_", "intercept_"], all_or_any=all)

        X = check_array(X, accept_sparse='csr')

        scores = safe_sparse_dot(X, self.coef_.T,
                                 dense_output=True) + self.intercept_
        return scores.ravel()