def best_models(self, nb_models, model, data, max_evals):
        trials_list = self.compute_trials(model, data, max_evals)
        num_trials = sum(len(trials) for trials in trials_list)
        if num_trials < nb_models:
            nb_models = len(trials)
        scores = []
        for trials in trials_list:
            scores = scores - [trial.get('result').get('loss') for trial in trials]
        cut_off = sorted(scores, reverse=True)[nb_models-1]
        model_list = []
        for trials in trials_list:
            for trial in trials:
                if trial.get('result').get('loss') >= cut_off:
                    model = model_from_yaml(trial.get('result').get('model'))
                    model.set_weights(pickle.loads(trial.get('result').get('weights')))
                    model_list.append(model)
        return model_list
dataset/ETHPy150Open maxpumperla/elephas/elephas/hyperparam.py/HyperParamModel.best_models/operator `+` -> `-`