Hierarchical initialization approach for K-Means clustering

被引：57

作者：

Lu, J. F. ^{[1
]}

Tang, J. B. ^{[1
]}

Tang, Z. M. ^{[1
]}

Yang, J. Y. ^{[1
]}

机构：

[1] Nanjing Univ Sci & Technol, Dept Comp Sci, Nanjing 210094, Peoples R China

来源：

PATTERN RECOGNITION LETTERS | 2008年 / 29卷 / 06期

关键词：

K-Means algorithm; K-Means initialization; voronoi tessellation; hierarchical technique;

D O I：

10.1016/j.patrec.2007.12.009

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

A hierarchical initialization approach is proposed to the K-Means clustering problem. The core of the proposed method is to treat the clustering problem as a weighted clustering problem so as to find better initial cluster centers based on the hierarchical approach. The experimental results show that the proposed approach needs less iteration time compared with existing approaches and has better performance in terms of convergence speed and ability to reduce the impact of noises. (c) 2008 Elsevier B.V. All rights reserved.

引用

页码：787 / 795

页数：9

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