k*-means:: A new generalized k-means clustering algorithm

被引:126
作者
Cheung, YM [1 ]
机构
[1] Hong Kong Baptist Univ, Dept Comp Sci, Kowloon, Hong Kong, Peoples R China
关键词
clustering analysis; k-means algorithm; cluster number; rival penalization;
D O I
10.1016/S0167-8655(03)00146-6
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper presents a generalized version of the conventional k-means clustering algorithm [Proceedings of 5th Berkeley Symposium on Mathematical Statistics and Probability, 1, University of California Press, Berkeley, 1967, p. 281]. Not only is this new one applicable to ellipse-shaped data clusters without dead-unit problem, but also performs correct clustering without pre-assigning the exact cluster number. We qualitatively analyze its underlying mechanism, and show its outstanding performance through the experiments. (C) 2003 Elsevier B.V. All rights reserved.
引用
收藏
页码:2883 / 2893
页数:11
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