DocumentCode :
668786
Title :
Improved FCM algorithm based on the initial clustering center selection
Author :
Qinrun Wen ; Lili Yu ; Yingjie Wang ; Weifeng Wang
Author_Institution :
Dept. of Software Eng., Shijiazhuang Inf. Eng. Vocational Coll., Shijiazhuang, China
fYear :
2013
fDate :
20-22 Nov. 2013
Firstpage :
351
Lastpage :
354
Abstract :
Fuzzy C-average algorithm (also known as the FCM algorithm) is a clustering algorithm based on partition. The idea of the algorithm is making is divided into clusters with the similarity between objects as large as possible, and the similarity between objects of different clusters as small as possible. As the algorithm is simple, easy to implement and computer clustering effect, etc., makes this algorithm in many fields has been widely applied. This paper focuses principles of FCM algorithm, the algorithm steps and its problems were described in detail and propose an improved algorithm.
Keywords :
data mining; fuzzy set theory; pattern clustering; FCM algorithm; computer clustering effect; data mining; fuzzy C-average algorithm; fuzzy cluster theory; initial clustering center selection; Algorithm design and analysis; Classification algorithms; Clustering algorithms; Data mining; Linear programming; Partitioning algorithms; Software algorithms; Fuzzy C-average algorithm; Fuzzy Cluster Theory; clustering algorithm; initialization; weighted index;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Consumer Electronics, Communications and Networks (CECNet), 2013 3rd International Conference on
Conference_Location :
Xianning
Print_ISBN :
978-1-4799-2859-0
Type :
conf
DOI :
10.1109/CECNet.2013.6703344
Filename :
6703344
Link To Document :
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