On fuzzy cluster validity indices

  • Authors:
  • Weina Wang;Yunjie Zhang

  • Affiliations:
  • Department of Mathematics, Dalian Maritime University, Dalian, Liaoning Province, China and Department of Mathematics, Jilin Institute of Chemical Technology, Jilin, Jilin Province, China;Department of Mathematics, Dalian Maritime University, Dalian, Liaoning Province, China

  • Venue:
  • Fuzzy Sets and Systems
  • Year:
  • 2007

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Abstract

Cluster analysis aims at identifying groups of similar objects, and helps to discover distribution of patterns and interesting correlations in large data sets. Especially, fuzzy clustering has been widely studied and applied in a variety of key areas and fuzzy cluster validation plays a very important role in fuzzy clustering. This paper introduces the fundamental concepts of cluster validity, and presents a review of fuzzy cluster validity indices available in the literature. We conducted extensive comparisons of the mentioned indices in conjunction with the Fuzzy C-Means clustering algorithm on a number of widely used data sets, and make a simple analysis of the experimental results.