clustering with feature order preferences

	clustering with feature order preferences
	Sun Jun ; Zhao Wenbo ; Xue Jiangwei ; Shen Zhiyong ; Shen Yidong
刊名	INTELLIGENT DATA ANALYSIS
	2010
卷号	14 期号:4 页码:479-495
关键词	Clustering domain knowledge Bregman divergence feature order preferences entropy regularization prototype-based clustering convex optimization quadratic programming
ISSN号	1088-467X
学科主题	Computer Science ; Artificial Intelligence
收录类别	SCI
公开日期	2011-05-23
附注	We propose a clustering algorithm that effectively utilizes feature order preferences, which have the form that feature s is more important than feature t. Our clustering formulation aims to incorporate feature order preferences into prototype-based clustering. The derived algorithm automatically learns distortion measures parameterized by feature weights which will respect the feature order preferences as much as possible. Our method allows the use of a broad range of distortion measures such as Bregman divergences. Moreover, even when generalized entropy is used in the regularization term, the subproblem of learning the feature weights is still a convex programming problem. Empirical results on some datasets demonstrate the effectiveness and potential of our method.
内容类型	期刊论文
源URL	[http://124.16.136.157/handle/311060/9684]
专题	软件研究所_计算机科学国家重点实验室 _期刊论文
推荐引用方式 GB/T 7714	Sun Jun,Zhao Wenbo,Xue Jiangwei,et al. clustering with feature order preferences[J]. INTELLIGENT DATA ANALYSIS,2010,14(4):479-495.
APA	Sun Jun,Zhao Wenbo,Xue Jiangwei,Shen Zhiyong,&Shen Yidong.(2010).clustering with feature order preferences.INTELLIGENT DATA ANALYSIS,14(4),479-495.
MLA	Sun Jun,et al."clustering with feature order preferences".INTELLIGENT DATA ANALYSIS 14.4(2010):479-495.