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gamma和epsilon在KL散度计算中的作用是什么?

[英]what is the role of gamma and epsilon in the calculation of K-L divergence?

I was wondering if anyone can explain to me why gamma and epsilon might be used to calculate the KL divergence between two documents?我想知道是否有人可以向我解释为什么可以使用 gamma 和 epsilon 来计算两个文档之间的 KL 散度? What are their roles?他们的角色是什么? I am not really good with maths so if someone can explain to me in simple terms that would be very helpful.我的数学不太好,所以如果有人可以用简单的术语向我解释,那将非常有帮助。

Thank you for the help!感谢您的帮助!

I suppose you are referring to the gamma and epsilon values defined in the paper Using Kullback-Leibler Distance for Text Categorization .我想您指的是论文Using Kullback-Leibler Distance for Text Categorization中定义的 gamma 和 epsilon 值。

epsilon is the probability of a term which is not in a document. epsilon是不在文档中的术语的概率。 It is set to a small value instead of 0 to avoid the distance to be infinite.将其设置为较小的值而不是 0,以避免距离无限。 gamma is a normalization coefficient to account of epsilon , so a probability of a term in a category satisfies the properties of a probability (sum to 1). gamma是考虑epsilon的归一化系数,因此类别中的项的概率满足概率的属性(总和为 1)。

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