DocumentCode
501100
Title
A New Validity Function for Fuzzy Clustering
Author
Li, Yang ; Yu, Fusheng
Author_Institution
Lab. of Math. & Complex Syst., Beijing Normal Univ., Beijing, China
Volume
1
fYear
2009
fDate
6-7 June 2009
Firstpage
462
Lastpage
465
Abstract
This paper first gives a new validity function for fuzzy clustering, then presents a method of the optimal selecting of the cluster number in the standard fuzzy c-means clustering algorithm, and finally outlines the fuzzy c-means clustering algorithm with parameters self-adapted. Experimental results carried on synthetic data set and data set based on actual background illustrate the performance of the new validity function and the corresponding fuzzy clustering algorithm.
Keywords
fuzzy set theory; pattern clustering; fuzzy c-means clustering algorithm; optimal selecting method; validity function; Algorithm design and analysis; Clustering algorithms; Computational intelligence; Fuzzy sets; Fuzzy systems; Iterative algorithms; Laboratories; Mathematical programming; Mathematics; Partitioning algorithms; Fuzzy C-Means; cluster number; clustering validity function; fuzzy clustering analysis;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence and Natural Computing, 2009. CINC '09. International Conference on
Conference_Location
Wuhan
Print_ISBN
978-0-7695-3645-3
Type
conf
DOI
10.1109/CINC.2009.100
Filename
5231083
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