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
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;
Conference_Titel :
Computational Intelligence and Natural Computing, 2009. CINC '09. International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-0-7695-3645-3
DOI :
10.1109/CINC.2009.100
