evaluation.py 文件源码

def average_ndcg(self):
        ndcg = 0.
        for goal, prediction in self.instances:
            if len(prediction) > 0:
                dcg = 0.
                max_dcg = 0.
                for i, p in enumerate(prediction[:min(len(prediction), self.k)]):
                    if i < len(goal):
                        max_dcg += 1. / np.log2(2 + i)

                    if p in goal:
                        dcg += 1. / np.log2(2 + i)

                ndcg += dcg/max_dcg

        return ndcg / len(self.instances)