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除了推荐任务，在二分类任务中，也可以计算该指标，代码如下：
# ndcg def get_dcg(y_pred, y_true, k):
#注意y_pred与y_true必须是一一对应的，并且y_pred越大越接近label=1(用相关性的说法就是，与label=1越相关) df = pd.
DataFrame({"y_pred":y_pred, "y_true":y_true}) df = df.sort_values(by="y_pred",
ascending=False) # 对y_pred进行降序排列，越排在前面的，越接近label=1 df = df.iloc[0:k, :] # 取前K个
dcg= (2 ** df["y_true"] - 1) / np.log2(np.arange(1, df["y_true"].count()+1) + 1)
# 位置从1开始计数 dcg = np.sum(dcg) def get_ndcg(df, k): # df包含y_pred和y_true dcg =
get_dcg(df["y_pred"], df["y_true"], k) idcg = get_dcg(df["y_true"], df["y_true"]
, k) ndcg = dcg / idcg return ndcg
