A tabu clustering method with DHB operation and mergence and partition operation

Authors:
Yongguo Liu;Dong Zheng;Shiqun Li;Libin Wang;Kefei Chen
Affiliations:
College of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, P.R. China;Department of Computer Science and Engineering, Shanghai Jiaotong University, Shanghai, P.R. China;Department of Computer Science and Engineering, Shanghai Jiaotong University, Shanghai, P.R. China;Department of Computer Science and Engineering, Shanghai Jiaotong University, Shanghai, P.R. China;Department of Computer Science and Engineering, Shanghai Jiaotong University, Shanghai, P.R. China
Venue:
DS'05 Proceedings of the 8th international conference on Discovery Science
Year:
2005

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Abstract

A new tabu clustering method called ITCA is developed for the minimum sum of squares clustering problem, where DHB operation and mergence and partition operation are introduced to fine-tune the current solution and create the neighborhood, respectively. Compared with some known clustering methods, ITCA can obtain better performance, which is extensively demonstrated by experimental simulations.