DocumentCode
2439273
Title
A New Validity Index of Fuzzy c-Means Clustering
Author
Zhang, Xin-Bo ; Jiang, Li
Author_Institution
Coll. of Inf. & Electron. Eng., ZheJiang Gongshang Univ., Hangzhou, China
Volume
2
fYear
2009
fDate
26-27 Aug. 2009
Firstpage
218
Lastpage
221
Abstract
FCM algorithm is an important algorithm in fuzzy pattern identification. It has significant application value in theory and practice. And whether clustering results are reasonable or not is belongs to cluster validity problem. In this paper, based on the Shannon entropy and fuzzy variation theory, considering the geometry structure information of data sets, we give a new cluster validity function. Experimental results show that the new method has good classification performance.
Keywords
fuzzy set theory; information theory; pattern clustering; Shannon entropy; cluster validity problem; fuzzy c-Means clustering algorithm; fuzzy pattern identification; fuzzy variation theory; Clustering algorithms; Cybernetics; Data analysis; Educational institutions; Entropy; Fuzzy sets; Fuzzy systems; Intelligent systems; Man machine systems; Partitioning algorithms; fuzzy c-means; fuzzy variation; partition entropy; validity index;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Human-Machine Systems and Cybernetics, 2009. IHMSC '09. International Conference on
Conference_Location
Hangzhou, Zhejiang
Print_ISBN
978-0-7695-3752-8
Type
conf
DOI
10.1109/IHMSC.2009.178
Filename
5336004
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