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Multiple recursive projection twin support vector machine for multi-class classification

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Abstract

For multi-class classification problem, a novel multiple projection twin support vector machine (Multi-PTSVM) is proposed. Our Multi-PTSVM solves \(K\) quadratic programming problems (QPPs) to obtain \(K\) projection axes, which is similar to binary PTSVM, but the regularization terms and recursive procedure are introduced for each class, which improve the generalization ability greatly. Comparisons against the Multi-SVM, Multi-TWSVM, Multi-GEPSVM, and our Multi-PTSVM on both synthetic and benchmark datasets indicate that our Multi-PTSVM has its advantages.

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Acknowledgments

This work is supported by the National Natural Science Foundation of China (Nos. 11201426 and 11371365), the Zhejiang Provincial Natural Science Foundation of China (Nos. LQ12A01020, LQ13F030010 and LQ14G010004), the Ministry of Education, Humanities and Social Sciences Research Project of China (No. 13YJC910011), and the Scientific Research Fund of Zhejiang Provincial Education Department (No. Y201432746).

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Authors and Affiliations

  1. Zhijiang College, Zhejiang University of Technology, Hangzhou, 310024, People’s Republic of China

    Chun-Na Li, Yuan-Hai Shao & Zhi-Min Yang

  2. Hangzhou Navigation Instrument Company Limited and Institute of special equipment, Zhejiang University of Technology, Hangzhou, People’s Republic of China

    Yun-Feng Huang

  3. College of Science, Zhejiang University of Technology, Hangzhou, 310024, People’s Republic of China

    He-Ji Wu

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  1. Chun-Na Li
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  2. Yun-Feng Huang
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  4. Yuan-Hai Shao
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Correspondence to Yuan-Hai Shao.

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Li, CN., Huang, YF., Wu, HJ. et al. Multiple recursive projection twin support vector machine for multi-class classification. Int. J. Mach. Learn. & Cyber. 7, 729–740 (2016). https://doi.org/10.1007/s13042-014-0289-2

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  • DOI: https://doi.org/10.1007/s13042-014-0289-2

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