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MSDLSR: Margin Scalable Discriminative Least Squares Regression for Multi-category Classification
Wang, Lingfeng; Zhang, Xuyao; Pan, Chunhong
Source PublicationIEEE Transactions on Neural Networks and Learning Systems
2015-10
Pages1-7
AbstractIn this brief, we propose a new margin scalable discriminative least squares regression (MSDLSR) model for multicategory classification. The main motivation behind the MSDLSR is to explicitly control the margin of DLSR model. We first prove that the DLSR is a relaxation of the traditional L₂-support vector machine. Based on this fact, we further provide a theorem on the margin of DLSR. With this theorem, we add an explicit constraint on DLSR to restrict the number of zeros of dragging values, so as to control the margin of DLSR. The new model is called MSDLSR. Theoretically, we analyze the determination of the margin and support vectors of MSDLSR. Extensive experiments illustrate that our method outperforms the current state-of-the-art approaches on various machine leaning and real-world data sets.
KeywordDiscriminative Least Squares Regression (Dlsr) Least Squares Regression (Lsr) Multicategory Classification.
Indexed BySCI
Language英语
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/10723
Collection模式识别国家重点实验室_先进数据分析与学习
Affiliation中国科学院自动化研究所
Recommended Citation
GB/T 7714
Wang, Lingfeng,Zhang, Xuyao,Pan, Chunhong. MSDLSR: Margin Scalable Discriminative Least Squares Regression for Multi-category Classification[J]. IEEE Transactions on Neural Networks and Learning Systems,2015:1-7.
APA Wang, Lingfeng,Zhang, Xuyao,&Pan, Chunhong.(2015).MSDLSR: Margin Scalable Discriminative Least Squares Regression for Multi-category Classification.IEEE Transactions on Neural Networks and Learning Systems,1-7.
MLA Wang, Lingfeng,et al."MSDLSR: Margin Scalable Discriminative Least Squares Regression for Multi-category Classification".IEEE Transactions on Neural Networks and Learning Systems (2015):1-7.
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