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. © 2008 Springer-Verlag Berlin Heidelberg.
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CITATION STYLE
Li, F., Min, F., & Liu, Q. (2008). Intra-cluster similarity index based on fuzzy rough sets for fuzzy C-means algorithm. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5009 LNAI, pp. 316–323). https://doi.org/10.1007/978-3-540-79721-0_45
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