classification.py 文件源码

 复制代码def load_model(file_path):
        with open(file_path, "r") as f:
            decision_trees, sparse_features, total_feature_count = load(f)

        dts = {}
        for key in decision_trees.keys():
            dts[key] = []
            for dt in decision_trees[key]:
                d = DecisionTree([])
                for k in dt['model'].keys():
                    setattr(d, k, dt['model'][k])
                dt['model'] = d
                dts[key].append(dt)

        return ClassificationEngine(
            decision_trees=dts,
            sparse_features=sparse_features,
            total_feature_count=total_feature_count
        )