[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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