DocumentCode
2913971
Title
A new fuzzy C-means with priority
Author
Gao, Jun ; Xiang, Lili ; Wang, Jiandong
Author_Institution
Yancheng Inst. of Technol., Yancheng
fYear
2007
fDate
18-20 Nov. 2007
Firstpage
1014
Lastpage
1018
Abstract
As traditional fuzzy C-means (FCM) has its shortages, we present an improved algorithm: M_FCM. The theory of fuzzy equivalency is used to deal with the original samples for getting the number of clusters and the original clustering center. By improving the clustering objective functions, the abilities of C-means are to handle isolated points and to show the significance of each dimension in the samples for clustering effect also enhanced. An experiment is finally conducted to make the MFCM clearer.
Keywords
fuzzy set theory; pattern classification; fuzzy C-means clustering; fuzzy equivalency theory; Clustering algorithms; Equations; Fuzzy control; Fuzzy set theory; Fuzzy sets; Fuzzy systems; Intelligent systems; Lagrangian functions; Space technology; Virtual colonoscopy;
fLanguage
English
Publisher
ieee
Conference_Titel
Grey Systems and Intelligent Services, 2007. GSIS 2007. IEEE International Conference on
Conference_Location
Nanjing
Print_ISBN
978-1-4244-1294-5
Electronic_ISBN
978-1-4244-1294-5
Type
conf
DOI
10.1109/GSIS.2007.4443425
Filename
4443425
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