DocumentCode
2436865
Title
A Novel Clustering Algorithm with Ant Colony Optimization
Author
Fu, Hui
Author_Institution
Dept. of Comput. Sci., Guangdong Polytech. Normal Univ., Guangzhou
Volume
2
fYear
2008
fDate
19-20 Dec. 2008
Firstpage
66
Lastpage
69
Abstract
Clustering analysis is an important area of data mining. A kind of new clustering algorithm with ant colony optimization based on cluster center initialization is proposed in this paper. The new algorithm gives initialized cluster centers by different methods, then solves clustering problems by iterated method. Three methods of cluster center initialization are used in clustering algorithm with ant colony optimization - Sacc.Three datasets - butterfly data, iris and wine are chosen for the compare of three algorithms. The results of several times experiments show that the new algorithm is less in running time, is better in clustering effect and more stable than Sacc. Experimental results validate new algorithm´s efficiency.
Keywords
data mining; iterative methods; optimisation; pattern clustering; ant colony optimization; cluster center initialization; clustering algorithm; clustering analysis; data mining; iterated method; Ant colony optimization; Application software; Clustering algorithms; Computational intelligence; Computer industry; Computer science; Conferences; Mining industry; Partitioning algorithms; Pattern analysis;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence and Industrial Application, 2008. PACIIA '08. Pacific-Asia Workshop on
Conference_Location
Wuhan
Print_ISBN
978-0-7695-3490-9
Type
conf
DOI
10.1109/PACIIA.2008.75
Filename
4756736
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