Partitional Clustering with a Modified Differential Evolution Algorithm

摘要：

A partitional clustering algorithm based on a modified differential evolution is proposed to determining the optimal number of clusters and finding the optimal partition of a data set. The proposed algotihhm is tested with four artificial and real world data sets. The empirical results show that the proposed clustering algorithm is feasible and effective, moreover, it converges faster than the clustering algorithm based on the basic differential evolution.

关键词： cluster analysis partitional clustering differential evolution

作者: ZHAO Guangquan PENG Xiyuan YANG Ling

作者单位: Department of Automatic Test and Control, Harbin Institute of Technology, Harbin, Heilongjiang 150080, China

会议类型: 国际会议

会议名称: 第七届国际测试技术研讨会

会议地点: 北京

会议语种:英文

在线出版日期: 2007-08-05（万方平台首次上网日期，不代表论文的发表时间）