def get_loss_info(self, tst_eval_info, val_eval_info): loss_mN = val_eval_info.get_loss() w_km = base.build_bootstrap_matrix(self.k_bootstrap, loss_mN.shape[0], self.essr) prob_N = base.aB_prob(w_km, loss_mN) loss_m = tst_eval_info.test_distr(prob_N) return loss_m
def get_loss_info(self, tst_eval_info, val_eval_info): loss_mN = val_eval_info.get_loss() m, N = loss_mN.shape w_km = base.build_bootstrap_matrix(self.k_bootstrap, m, self.essr) ensemble_d, prob_d = greedy.greedy_ensemble(loss_mN, w_km, self.ensemble_size) prob_N = np.zeros(N) prob_N[ensemble_d] = prob_d loss_m = tst_eval_info.test_distr(prob_N) return loss_m