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ICASSP
2011
IEEE

A mutual information based approach for evaluating the quality of clustering

10 years 5 months ago
A mutual information based approach for evaluating the quality of clustering
In this paper, a new method for evaluating the quality of clustering of genes is proposed based on mutual information criterion. Instead of using the conventional histogram-based modeling method to assess clustering performance, we derive a normalized mutual information criterion utilizing the Gaussian kernel density estimator. In the computation of the mutual information, we propose to use only clustercentroids instead of involving all the members, which offers a huge computational savings. The proposed algorithm not only considers the cluster size but also takes into consideration the homogeneity within a cluster. One major advantage of the proposed algorithm is that, it is capable of estimating an appropriate number of clusters. Extensive experimentation has been carried out on some synthetic data as well as the most widely used Yeast cell cycle gene expression data. Under various clustering conditions it is found that the proposed method provides an excellent performance in terms ...
Shaikh Anowarul Fattah, Chia-Chun Lin, Sun-Yuan Ku
Added 21 Aug 2011
Updated 21 Aug 2011
Type Journal
Year 2011
Where ICASSP
Authors Shaikh Anowarul Fattah, Chia-Chun Lin, Sun-Yuan Kung
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