Weighting variables in K-means clustering

被引：13

作者：

Huh, Myung-Hoe ^{[2
]}

Lim, Yong B. ^{[1
]}

机构：

[1] Ewha Womans Univ, Dept Stat, Seoul, South Korea

[2] Korea Univ, Dept Stat, Seoul, South Korea

来源：

JOURNAL OF APPLIED STATISTICS | 2009年 / 36卷 / 01期

关键词：

K-means clustering; variable weighting; penalty constant;

D O I：

10.1080/02664760802382533

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

The aim of this study is to assign weights w1, , wm to m clustering variables Z1, , Zm, so that k groups were uncovered to reveal more meaningful within-group coherence. We propose a new criterion to be minimized, which is the sum of the weighted within-cluster sums of squares and the penalty for the heterogeneity in variable weights w1, , wm. We will present the computing algorithm for such k-means clustering, a working procedure to determine a suitable value of penalty constant and numerical examples, among which one is simulated and the other two are real.

引用

页码：67 / 78

页数：12

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