Intra-cluster similarity index based on fuzzy rough sets for fuzzy c-means algorithm

Authors:
Fan Li;Fan Min;Qihe Liu
Affiliations:
School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, P.R. China;School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, P.R. China;School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, P.R. China
Venue:
RSKT'08 Proceedings of the 3rd international conference on Rough sets and knowledge technology
Year:
2008

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Abstract

Cluster validity indices have been used to evaluate the quality of fuzzy partitions. In this paper, we propose a new index, which uses concepts of Fuzzy Rough sets to evaluate the average intra-cluster similarity of fuzzy clusters produced by the fuzzy c-means algorithm. Experimental results show that contrasted with several well-known cluster validity indices, the proposed index can yield more desirable cluster number estimation.