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Binary Tree Construction of Multiclass Pinball SVM Via Farthest Centroid Selection

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Advances in Intelligent Systems and Interactive Applications (IISA 2017)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 686))

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Abstract

The paper generalizes PinSVM to multiclass version by using binary tree structure. At each internal node, all inherited classes are first divided into two groups via farthest centroid selection. Then, PinSVM is constructed between two groups. When each group contains only one class, the leaf node can be identified. The experimental results show that binary-tree multiclass PinSVM is very competitive with one-versus-one PinSVM and one-versus-one SVM. Especially in terms of computational time, it has clear superiority than them.

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Acknowledgements

This work was supported in part by the National Natural Science Foundation of China under grant 61602056, the Doctoral Scientific Research Foundation of Liaoning Province under grant 201601348, and the Scientific Research Project of Liaoning Provincial Committee of Education under grant LZ2016005.

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Authors and Affiliations

  1. College of Information Science and Technology, Bohai University, Jinzhou, 121000, China

    Qiangkui Leng

  2. Research and Teaching Institute of College Basics, Bohai University, Jinzhou, 121000, China

    Fude Liu

  3. College of Engineering, Bohai University, Jinzhou, 121000, China

    Yuping Qin

Authors
  1. Qiangkui Leng
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  2. Fude Liu
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  3. Yuping Qin
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Corresponding author

Correspondence to Qiangkui Leng .

Editor information

Editors and Affiliations

  1. Technical University of Catalonia, Barcelona, Spain

    Fatos Xhafa

  2. Department of Computer Science and Engineering, Faculty of Engineering and Technology, SOA University, Bhubaneswar, Odisha, India

    Srikanta Patnaik

  3. School of Information Technologies, University of Sydney, Sydney, New South Wales, Australia

    Albert Y. Zomaya

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Leng, Q., Liu, F., Qin, Y. (2018). Binary Tree Construction of Multiclass Pinball SVM Via Farthest Centroid Selection. In: Xhafa, F., Patnaik, S., Zomaya, A. (eds) Advances in Intelligent Systems and Interactive Applications. IISA 2017. Advances in Intelligent Systems and Computing, vol 686. Springer, Cham. https://doi.org/10.1007/978-3-319-69096-4_45

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  • DOI: https://doi.org/10.1007/978-3-319-69096-4_45

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-69095-7

  • Online ISBN: 978-3-319-69096-4

  • eBook Packages: EngineeringEngineering (R0)

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