QQ客服 官方微博 反馈留言

	Improving associative classification by incorporating novel interestingness measures
	Lan, Y ; Janssens, D ; Chen, GQ ; Wets, G
	2010-05-11 ; 2010-05-11
关键词	associative classification intensity of implication dilated chi-square credit scoring Computer Science, Artificial Intelligence Engineering, Electrical & Electronic Operations Research & Management Science
中文摘要	Associative classification has aroused significant attention in recent years and proved to generate good results in previous research efforts. This paper aims to contribute to this line of research by the development of more effective associative classifiers. Our goal is to achieve this by the incorporation of two novel interesting measures, i.e. intensity of implication and dilated chi-square, into an existing associative classification algorithm, respectively. The former interesting measure was merely proposed with the purpose of mining meaningful association rules, while the latter was designed to reveal the interdependence between condition and class variables. Each of these two measures is applied as the primary sorting criterion within the context of the well-known CBA algorithm in an attempt to organize the composition of the rule sets in a more reasonable sequence. Benchmarking experiments on 16 popular UCI datasets revealed that our algorithms could empirically generate accurate and significantly more compact decision lists. In addition to this, the algorithm was validated on a separate credit scoring dataset, which contained 7190 credit scoring samples. (c) 2005 Elsevier Ltd. All rights reserved.
语种	英语 ; 英语
出版者	PERGAMON-ELSEVIER SCIENCE LTD ; OXFORD ; THE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND
内容类型	期刊论文
源URL	[http://hdl.handle.net/123456789/26112]
专题	清华大学
推荐引用方式 GB/T 7714	Lan, Y,Janssens, D,Chen, GQ,et al. Improving associative classification by incorporating novel interestingness measures[J],2010, 2010.
APA	Lan, Y,Janssens, D,Chen, GQ,&Wets, G.(2010).Improving associative classification by incorporating novel interestingness measures..
MLA	Lan, Y,et al."Improving associative classification by incorporating novel interestingness measures".(2010).

个性服务

查看访问统计

相关权益政策

暂无数据

收藏/分享

除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。