Discriminative Least Squares Regression for Multiclass Classification and Feature Selection
Xiang, Shiming1; Nie, Feiping2; Meng, Gaofeng1; Pan, Chunhong1; Zhang, Changshui3
2012-11-01
发表期刊IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
卷号23期号:11页码:1738-1754
文章类型Article
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.
关键词Feature Selection Least Squares Regression Multiclass Classification Sparse Learning
WOS标题词Science & Technology ; Technology
关键词[WOS]MUTUAL INFORMATION ; PREDICTION
收录类别SCI
语种英语
WOS研究方向Computer Science ; Engineering
WOS类目Computer Science, Artificial Intelligence ; Computer Science, Hardware & Architecture ; Computer Science, Theory & Methods ; Engineering, Electrical & Electronic
WOS记录号WOS:000310370300006
引用统计
被引频次:104[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/7999
专题模式识别国家重点实验室_先进数据分析与学习
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
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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.
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