optimizer_base.py 文件源码

def get_best_params_and_model(self):
        """
        Returns the best parameters and model after optimization.
        Keyword arguments:
            None
        """
        best_params_idx = np.argmax([score for score, params in self.hyperparam_history])
        best_params = self.hyperparam_history[best_params_idx][1]
        if isinstance(self.model, Pipeline):
            all_params = self.model.get_params()
            all_params.update(best_params)
            best_model = self.model.set_params(**all_params)
        else:
            best_model = self.model.__class__(**dict(self.model.get_params(), **best_params))
        return best_params, best_model