如何计算聚类熵-示例和给出的解决方案，但这是正确的吗? [英] How to calculate clustering entropy - example and my solution given but is it correct?

问题描述

我想计算此示例方案的熵

I would like to calculate entropy of this example scheme

http://nlp.stanford .edu/IR-book/html/htmledition/evaluation-of-clustering-1.html

熵方程

那么熵是(第一行)

因此，熵适用于该方案

For the first cluster - ( (5/6)*Log(5/6) + (1/6)*Log(1/6) ) 
For the second cluster  - ( (1/6)*Log(1/6) + (1/6)*Log(1/6) + (4/6)*Log(4/6) )
For the third cluster  - ( (2/5)*Log(2/5) + (3/5)*Log(3/5) )

最终熵为:

 FirtCluster_Entropy + SecondCluster_Entropy  + ThirdCluster_Entropy  

我正确吗?

推荐答案

非常接近！对于聚类的总熵，您需要通过每个聚类的相对权重对其进行加权.请查看我对上一个问题的回答 https://stackoverflow.com/a/35780505/159646 .

Very close! For the total entropy of the clustering you need need to weight each cluster's entropy by its relative weight. Please see my answer to your previous question https://stackoverflow.com/a/35780505/159646.

此外，它可能应该发布到交叉验证，而不是堆栈溢出.

Also this should probably be posted to Cross Validated instead of Stack Overflow.

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