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There can't be any sample like CTR:0 CVR:1 if CVR is 1 that means its CTR is already 1 so I don't think we need to filter out CTR:1 samples. Eventually CVR and CTCVR are just same here isn't it?
按照理解,第二个表格评估的时候,是直接用CVR任务的y_true 和 模型的预测 y_pred 去评估的。
如果是CTCVR的话,评估的时候,应该首先减小数据集,把数据集筛选到只剩下 CTR=1的情况下,然后此时CVR这个label才变成了CTCVR。而相应的模型预测概率,也应该是在看到第一个标签的情况下训练的模型所预测出来的概率,才叫做CTCVR
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