proximal.py 文件源码

def _fit(self, X, y, warm_start=None):
        if warm_start is None:
            self.coef_ = np.zeros(X.shape[1])
        else:
            self.coef_ = np.asanyarray(warm_start)

        l1l2_proximal = l1l2_regularization
        self.coef_, self.niter_ = l1l2_proximal(X, y,
                                                self.mu, self.tau,
                                                beta=self.coef_,
                                                kmax=self.max_iter,
                                                tolerance=self.tol,
                                                return_iterations=True,
                                                adaptive=self.adaptive_step_size)

        if self.niter_ == self.max_iter:
            warnings.warn('Objective did not converge, you might want'
                          ' to increase the number of iterations')

        return self