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

页码：59 / +

页数：2

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