Techniques of Cluster Algorithms in Data Mining

被引：0
|
作者：
Johannes Grabmeier
Andreas Rudolph
机构：
[1] University of Applied Sciences,
[2] Universität der Bundeswehr München,undefined
来源：
Data Mining and Knowledge Discovery | 2002年 / 6卷
关键词：
data mining; cluster algorithm; Condorcet's criterion; demographic clustering;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
An overview of cluster analysis techniques from a data mining point of view is given. This is done by a strict separation of the questions of various similarity and distance measures and related optimization criteria for clusterings from the methods to create and modify clusterings themselves. In addition to this general setting and overview, the second focus is used on discussions of the essential ingredients of the demographic cluster algorithm of IBM's Intelligent Miner, based Condorcet's criterion.
引用
收藏
页码：303 / 360
页数：57
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