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Modified Fuzzy Gap statistic for estimating preferable number of clusters in Fuzzy k-means clustering

Paper ID Volume ID Publish Year Pages File Format Full-Text
22422 43276 2008 9 PDF Available
Title
Modified Fuzzy Gap statistic for estimating preferable number of clusters in Fuzzy k-means clustering
Abstract

In clustering methods, the estimation of the optimal number of clusters is significant for subsequent analysis. Without detailed biological information on the genes involved, the evaluation of the number of clusters becomes difficult, and we have to rely on an internal measure that is based on the distribution of the data of the clustering result. The Gap statistic has been proposed as a superior method for estimating the number of clusters in crisp clustering. In this study, we proposed a modified Fuzzy Gap statistic (MFGS) and applied it to fuzzy k-means clustering. For estimating the number of clusters, fuzzy k-means clustering with the MFGS was applied to two artificial data sets with noise and to two experimentally observed gene expression data sets. For the artificial data sets, compared with other internal measures, the MFGS showed a higher performance in terms of robustness against noise for estimating the optimal number of clusters. Moreover, it could be used to estimate the optimal number of clusters in experimental data sets. It was confirmed that the proposed MFGS is a useful method for estimating the number of clusters for microarray data sets.

Keywords
clustering; validity index; fuzzy k-means; microarray data analysis; estimation of number of clusters
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Modified Fuzzy Gap statistic for estimating preferable number of clusters in Fuzzy k-means clustering
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Publisher
Database: Elsevier - ScienceDirect
Journal: Journal of Bioscience and Bioengineering - Volume 105, Issue 3, March 2008, Pages 273–281
Authors
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Subjects
Physical Sciences and Engineering Chemical Engineering Bioengineering
Get Full-Text Now
Don't Miss Today's Special Offer
Price was $35.95
You save - $31
Price after discount Only $4.95
100% Money Back Guarantee
Full-text PDF Download
Online Support
Any Questions? feel free to contact us