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原论文中,α的作用是增大数量少的类别的权重,即对正样本权重为α=0.25,对负样本权重为1-α=0.75,这样增大对正样本的学习能力。 在这里,模型输出经过sigmoid,然后沿用论文中focal_loss的计算方式,使我不太清楚这里α的意义。 因为,这里的α对于多个类别,是一致无差的,也就不能起到区别对待各个类别的作用。
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原论文中,α的作用是增大数量少的类别的权重,即对正样本权重为α=0.25,对负样本权重为1-α=0.75,这样增大对正样本的学习能力。
在这里,模型输出经过sigmoid,然后沿用论文中focal_loss的计算方式,使我不太清楚这里α的意义。
因为,这里的α对于多个类别,是一致无差的,也就不能起到区别对待各个类别的作用。
The text was updated successfully, but these errors were encountered: