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题名:
automatic clustering using genetic algorithms
作者: Liu Yongguo ; Wu Xindong ; Shen Yidong
关键词: Genetic algorithms
刊名: Applied Mathematics and Computation
发表日期: 2011
卷: 218, 期:4, 页:1267-1279
收录类别: EI
部门归属: (1) School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China; (2) State Key Laboratory of Computer Science, Institute of Software, Chinese Academy of Sciences, Beijing 100191, China; (3) Key Laboratory of Symbolic Computation and Knowledge Engineering, Ministry of Education, Jilin University, Changchun 130012, China; (4) Department of Computer Science, University of Vermont, Burlington, VT 05405, United States
英文摘要: In face of the clustering problem, many clustering methods usually require the designer to provide the number of clusters as input. Unfortunately, the designer has no idea, in general, about this information beforehand. In this article, we develop a genetic algorithm based clustering method called automatic genetic clustering for unknown K (AGCUK). In the AGCUK algorithm, noising selection and division-absorption mutation are designed to keep a balance between selection pressure and population diversity. In addition, the Davies-Bouldin index is employed to measure the validity of clusters. Experimental results on artificial and real-life data sets are given to illustrate the effectiveness of the AGCUK algorithm in automatically evolving the number of clusters and providing the clustering partition. © 2011 Elsevier Inc. All rights reserved.
WOS记录号: WOS:000294302800013
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内容类型: 期刊论文
URI标识: http://ir.iscas.ac.cn/handle/311060/14059
Appears in Collections:计算机科学国家重点实验室 _期刊论文

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Recommended Citation:
Liu Yongguo,Wu Xindong,Shen Yidong. automatic clustering using genetic algorithms[J]. Applied Mathematics and Computation,2011-01-01,218(4):1267-1279.
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