Sum-of-squares based cluster validity index and significance analysis

Authors:
Qinpei Zhao;Mantao Xu;Pasi Fränti
Affiliations:
Department of Computer Science, University of Joensuu, Joensuu, Finland;Department of Computer Science, University of Joensuu, Joensuu, Finland;Department of Computer Science, University of Joensuu, Joensuu, Finland
Venue:
ICANNGA'09 Proceedings of the 9th international conference on Adaptive and natural computing algorithms
Year:
2009

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Abstract

Different clustering algorithms achieve different results with certain data sets because most clustering algorithms are sensitive to the input parameters and the structure of data sets. The way of evaluating the result of the clustering algorithms, cluster validity, is one of the problems in cluster analysis. In this paper, we build a framework for cluster validity process, while proposing a sum-of-squares based index for purpose of cluster validity. We use the resampling method in the framework to analyze the stability of the clustering algorithm, and the certainty of the cluster validity index. For homogeneous data based on independent variables, the proposed clustering validity index is effective in comparison to some other commonly used indexes.