rankgbm.py 文件源码

def load(file_path):
        with open(file_path + '.params', 'r') as params_file:
            params = json.load(params_file)

        weak_learners = list()
        for wl_id in range(params['n_round']):
            # wl = DecisionTreeRegressor(max_depth=params['max_depth'],
            #                            max_features=params['max_features'],
            #                            min_samples_leaf=params['min_samples_leaf'])
            wl = joblib.load(file_path + '.wl%d' % wl_id)
            weak_learners.append(wl)

        rankgbm = RankGBM(params['vote_k'],
                          n_round=params['n_round'],
                          max_depth=params['max_depth'],
                          max_features=params['max_features'],
                          min_samples_leaf=params['min_samples_leaf'],
                          learn_rate=params['learn_rate'])
        rankgbm.weak_learners = weak_learners

        return rankgbm