Support vector machine with SOM-based quasi-linear kernel for nonlinear classification

Yuling Lin, Yong Fu, Jinglu Hu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper proposes a self-organizing maps (SOM) based kernel composition method for the quasi-linear support vector machine (SVM). The quasi-linear SVM is SVM model with quasi-linear kernel, in which the nonlinear separation hyperplane is approximated by multiple local linear models with interpolation. The basic idea underlying the proposed method is to use clustering and projection properties of SOM to partition the input space and construct a SOM based quasi-linear kernel. By effectively extracting the distribution information using SOM, the quasi-linear SVM with the SOM-based quasi-linear kernel is expected to have better performance in the cases of high-noise and high-dimension. Experiment results on synthetic datasets and real world datasets show the effectiveness of the proposed method.

Original languageEnglish
Title of host publicationProceedings of the International Joint Conference on Neural Networks
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3783-3789
Number of pages7
ISBN (Electronic)9781479914845
DOIs
Publication statusPublished - 2014 Sep 3
Event2014 International Joint Conference on Neural Networks, IJCNN 2014 - Beijing, China
Duration: 2014 Jul 62014 Jul 11

Publication series

NameProceedings of the International Joint Conference on Neural Networks

Conference

Conference2014 International Joint Conference on Neural Networks, IJCNN 2014
CountryChina
CityBeijing
Period14/7/614/7/11

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence

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  • Cite this

    Lin, Y., Fu, Y., & Hu, J. (2014). Support vector machine with SOM-based quasi-linear kernel for nonlinear classification. In Proceedings of the International Joint Conference on Neural Networks (pp. 3783-3789). [6889654] (Proceedings of the International Joint Conference on Neural Networks). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IJCNN.2014.6889654