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

Yuling Lin, Yong Fu, Takayuki Furuzuki

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 (Print)9781479914845
DOIs
Publication statusPublished - 2014 Sep 3
Event2014 International Joint Conference on Neural Networks, IJCNN 2014 - Beijing
Duration: 2014 Jul 62014 Jul 11

Other

Other2014 International Joint Conference on Neural Networks, IJCNN 2014
CityBeijing
Period14/7/614/7/11

Fingerprint

Self organizing maps
Support vector machines
Interpolation
Chemical analysis
Experiments

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence

Cite this

Lin, Y., Fu, Y., & Furuzuki, T. (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] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IJCNN.2014.6889654

Support vector machine with SOM-based quasi-linear kernel for nonlinear classification. / Lin, Yuling; Fu, Yong; Furuzuki, Takayuki.

Proceedings of the International Joint Conference on Neural Networks. Institute of Electrical and Electronics Engineers Inc., 2014. p. 3783-3789 6889654.

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

Lin, Y, Fu, Y & Furuzuki, T 2014, Support vector machine with SOM-based quasi-linear kernel for nonlinear classification. in Proceedings of the International Joint Conference on Neural Networks., 6889654, Institute of Electrical and Electronics Engineers Inc., pp. 3783-3789, 2014 International Joint Conference on Neural Networks, IJCNN 2014, Beijing, 14/7/6. https://doi.org/10.1109/IJCNN.2014.6889654
Lin Y, Fu Y, Furuzuki T. Support vector machine with SOM-based quasi-linear kernel for nonlinear classification. In Proceedings of the International Joint Conference on Neural Networks. Institute of Electrical and Electronics Engineers Inc. 2014. p. 3783-3789. 6889654 https://doi.org/10.1109/IJCNN.2014.6889654
Lin, Yuling ; Fu, Yong ; Furuzuki, Takayuki. / Support vector machine with SOM-based quasi-linear kernel for nonlinear classification. Proceedings of the International Joint Conference on Neural Networks. Institute of Electrical and Electronics Engineers Inc., 2014. pp. 3783-3789
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