本文介绍了如何计算聚类熵-示例和给出的解决方案,但这是正确的吗?的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着小编来一起学习吧!

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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10-26 21:56