An effective discretization based on Class-Attribute Coherence Maximization

doi:10.1016/j.patrec.2011.08.008

	An effective discretization based on Class-Attribute Coherence Maximization
	Li, Min 1,3,4; Deng, ShaoBo 2,3,4; Feng, Shengzhong 1; Fan, Jianping 1
	2011-11-01
发表期刊	PATTERN RECOGNITION LETTERS
ISSN	0167-8655
卷号	32 期号:15 页码:1962-1973
摘要	Discretization of continuous data is one of the important pre-processing tasks in data mining and knowledge discovery. Generally speaking, discretization can lead to improved predictive accuracy of induction algorithms, and the obtained rules are normally shorter and more understandable. In this paper, we present the Class-Attribute Coherence Maximization (CACM) algorithm and the Efficient-CACM algorithm. We have compared the performance of our algorithms with the most relevant discretization algorithm, Fast Class-Attribute Interdependence Maximization (Fast-CAIM) discertization algorithm (Kurgan and Cios, 2003). Empirical evaluation of our algorithms and Fast-CAIM on 12 well-known datasets shows that ours generate the superior discretization scheme, which can significantly improve the classification performance of C4.5 and RBF-SVM classifier. As to the execution time of discretization, ours also prove faster than Fast-CAIM algorithm, with the Efficient-CACM algorithm having the shortest execution time. (C) 2011 Elsevier B.V. All rights reserved.
关键词	Discretization CAIM CACM Classification Class-Attribute Independence Redundancy (CAIR)
DOI	10.1016/j.patrec.2011.08.008
收录类别	SCI
语种	英语
资助项目	National High Technology Research and Development Program of China (863 Programs)[2007AA120502] ; National High Technology Research and Development Program of China (863 Programs)[2006AA01A114] ; Jiangxi Education Department, China[GJJ11632]
WOS研究方向	Computer Science
WOS类目	Computer Science, Artificial Intelligence
WOS记录号	WOS:000297885900004
出版者	ELSEVIER SCIENCE BV
引用统计	被引频次：11[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/13048
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Li, Min
作者单位	1.Chinese Acad Sci, Shenzhen Inst Adv Technol, Shenzhen 518055, Guangdong, Peoples R China 2.Chinese Acad Sci, Inst Comp Technol, Key Lab Intelligent Informat Proc, Beijing 100080, Peoples R China 3.Chinese Acad Sci, Grad Sch, Beijing 100080, Peoples R China 4.Nanchang Inst Technol, Nanchang 330099, Jiangxi, Peoples R China
推荐引用方式 GB/T 7714	Li, Min,Deng, ShaoBo,Feng, Shengzhong,et al. An effective discretization based on Class-Attribute Coherence Maximization[J]. PATTERN RECOGNITION LETTERS,2011,32(15):1962-1973.
APA	Li, Min,Deng, ShaoBo,Feng, Shengzhong,&Fan, Jianping.(2011).An effective discretization based on Class-Attribute Coherence Maximization.PATTERN RECOGNITION LETTERS,32(15),1962-1973.
MLA	Li, Min,et al."An effective discretization based on Class-Attribute Coherence Maximization".PATTERN RECOGNITION LETTERS 32.15(2011):1962-1973.