Tree-structured Clustering for Mixed Data

被引：0

作者：

Yang, Kyung-Sook ^{[1
]}

Huh, Myung-Hoe ^{[2
]}

机构：

[1] Korea Univ, Brain Korea Educ & Res Grp Korean Studies 21, Anam Dong 5 Ga, Seoul 136701, South Korea

[2] Korea Univ, Dept Stat, Seoul 136701, South Korea

来源：

KOREAN JOURNAL OF APPLIED STATISTICS | 2006年 / 19卷 / 02期

关键词：

Mixed data; Tree-structured clustering; Node splitting; Variable selection;

D O I：

暂无

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 propose a tree-structured clustering for mixed data. We suggest a scaling method to reduce the variable selection bias among categorical variables. In numerical examples such as credit data, German credit data, we note several differences between tree-structured clustering and K-means clustering.

引用

页码：271 / 282

页数：12

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