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你好!我最近在做一个医学方面的多实例学习任务,刚好看到你的博客,有一些问题想问一下。 关于多实例学习数据tag的获取,目前的方法是将正例bag中所有实例不论正反实例都给上正例tag,反例bag中所有实例给上反例tag,这样的话不会有数据不平衡的问题吗?因为真实情况中正例bag中的实例有些tag是给错了的,所以这样真实的正实例的数量应该是远小于反实例的。第二,错误的tag网络能从中学到正确的特征吗,还是说我理解的学习策略有问题呢?麻烦有空帮忙解答一下,非常感谢!
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你好,我当时也有这个疑惑,但是从验证集来看,表现还行。因为只是试验,所以未深入研究,其他部分也不是太清楚,抱歉哈
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你好!我最近在做一个医学方面的多实例学习任务,刚好看到你的博客,有一些问题想问一下。
关于多实例学习数据tag的获取,目前的方法是将正例bag中所有实例不论正反实例都给上正例tag,反例bag中所有实例给上反例tag,这样的话不会有数据不平衡的问题吗?因为真实情况中正例bag中的实例有些tag是给错了的,所以这样真实的正实例的数量应该是远小于反实例的。第二,错误的tag网络能从中学到正确的特征吗,还是说我理解的学习策略有问题呢?麻烦有空帮忙解答一下,非常感谢!
The text was updated successfully, but these errors were encountered: