Hierarchical clustering for boxplot variables

被引：3
|
作者：
Arroyo, Javier [1 ]
Mate, Carlos [2 ]
Roque, Antonio Munoz-San [2 ]
机构：
[1] Univ Complutense Madrid, Dept Sistemas Informat, Prof Garcia Santesmases S-N, E-28040 Madrid, Spain
[2] Univ Pontificia Comillas, ETSI ICAI, Inst Invest Tecnol, E-28015 Madrid, Spain
来源：
DATA SCIENCE AND CLASSIFICATION | 2006年
关键词：
D O I：
10.1007/3-540-34416-0_7
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Boxplots are well-known exploratory charts used to extract meaningful information from batches of data at a glance. Their strength lies in their ability to summarize data retaining the key information, which also is a desirable property of symbolic variables. In this paper, boxplots are presented as a new kind of symbolic variable. In addition, two different approaches to measure distances between boxplot variables are proposed. The usefulness of these distances is illustrated by means of a hierarchical clustering of boxplot data.
引用
收藏
页码：59 / +
页数：2
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