Discriminative Least Squares Regression for Multiclass Classification and Feature Selection

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	Discriminative Least Squares Regression for Multiclass Classification and Feature Selection
	Xiang, Shiming1 ; Nie, Feiping 2; Meng, Gaofeng1 ; Pan, Chunhong1 ; Zhang, Changshui 3
刊名	IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
	2012-11-01
卷号	23 期号:11 页码:1738-1754
关键词	Feature selection least squares regression multiclass classification sparse learning
英文摘要	This paper presents a framework of discriminative least squares regression (LSR) for multiclass classification and feature selection. The core idea is to enlarge the distance between different classes under the conceptual framework of LSR. First, a technique called epsilon-dragging is introduced to force the regression targets of different classes moving along opposite directions such that the distances between classes can be enlarged. Then, the epsilon-draggings are integrated into the LSR model for multiclass classification. Our learning framework, referred to as discriminative LSR, has a compact model form, where there is no need to train two-class machines that are independent of each other. With its compact form, this model can be naturally extended for feature selection. This goal is achieved in terms of L-2,L-1 norm of matrix, generating a sparse learning model for feature selection. The model for multiclass classification and its extension for feature selection are finally solved elegantly and efficiently. Experimental evaluation over a range of benchmark datasets indicates the validity of our method.
WOS标题词	Science & Technology ; Technology
类目[WOS]	Computer Science, Artificial Intelligence ; Computer Science, Hardware & Architecture ; Computer Science, Theory & Methods ; Engineering, Electrical & Electronic
研究领域[WOS]	Computer Science ; Engineering
关键词[WOS]	MUTUAL INFORMATION ; PREDICTION
收录类别	SCI
语种	英语
WOS记录号	WOS:000310370300006
公开日期	2015-09-22
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/7999]
专题	自动化研究所_模式识别国家重点实验室_遥感图像处理团队
作者单位	1.Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China 2.Univ Texas Arlington, Dept Comp Sci & Engn, Arlington, TX 76019 USA 3.Tsinghua Univ, State Key Lab Intelligent Technol & Syst, Tsinghua Natl Lab Informat Sci & Technol, Dept Automat, Beijing 100084, Peoples R China
推荐引用方式 GB/T 7714	Xiang, Shiming,Nie, Feiping,Meng, Gaofeng,et al. Discriminative Least Squares Regression for Multiclass Classification and Feature Selection[J]. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS,2012,23(11):1738-1754.
APA	Xiang, Shiming,Nie, Feiping,Meng, Gaofeng,Pan, Chunhong,&Zhang, Changshui.(2012).Discriminative Least Squares Regression for Multiclass Classification and Feature Selection.IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS,23(11),1738-1754.
MLA	Xiang, Shiming,et al."Discriminative Least Squares Regression for Multiclass Classification and Feature Selection".IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 23.11(2012):1738-1754.