A Modified Multiobjective EA-based Clustering Algorithm with Automatic Determination of the Number of Clusters

被引:0
|
作者
Tsai, Chun-Wei [1 ]
Chen, Wen-Ling [2 ]
Chiang, Ming-Chao [2 ]
机构
[1] Chia Nan Univ Pharm & Sci, Dept Appl Geoinformat, Tainan 71710, Taiwan
[2] Natl Sun Yat Sen Univ, Dept Comp Sci & Engn, Kaohsiung 80424, Taiwan
来源
PROCEEDINGS 2012 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC) | 2012年
关键词
Clustering; Multiobjective Clustering; Diversity;
D O I
暂无
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Automatically determining the number of clusters without a priori knowledge is a difficult research issue for data clustering problem. An effective multiobjective evolutionary algorithm based clustering algorithm is proposed to not only overcome this problem but also provide a better clustering result in this study. The proposed algorithm differs from the traditional evolutionary algorithm in the sense that instead of a single crossover operator and a single mutation operator, the proposed algorithm uses a pool of crossover operators and a pool of mutation operators that are selected at random to increase the search diversity. To evaluate the performance of the proposed algorithm, several well-known datasets are used. The simulation results show that not only can the proposed algorithm automatically determine the number of clusters, but it can also provide a better clustering result.
引用
收藏
页码:2833 / 2838
页数:6
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