A modified version of the K-means algorithm with a distance based on cluster symmetry

作     者：Su, MS Chou, CH 

作者机构：Natl Cent Univ Dept Comp Sci & Informat Engn Chungli 320 Taiwan Tamkang Univ Dept Elect Engn Tamsui 25137 Taiwan 

出 版 物：《IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE》 (IEEE Trans Pattern Anal Mach Intell)

年 卷 期：2001年第23卷第6期

页      面：674-680页

核心收录：

学科分类：0808[工学-电气工程] 08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：National Science Council  NSC  (NSC 88-2213-E-032-014) 

主　　题：data clustering pattern recognition k-means algorithm face detection 

摘      要：In this paper, we propose a modified version of the K-means algorithm to cluster data. The proposed algorithm adopts a novel nonmetric distance measure based on the idea of point symmetry. This kind of point symmetry distance can be applied in data clustering and human face detection. Several data sets are used to illustrate its effectiveness.