An improved support vector machine with soft decision-making boundary

Boyang Li, Jinglu Hu, Kotaro Hirasawa

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

5 Citations (Scopus)

Abstract

This paper proposes an improved support vector machine (SVM) classifier by introducing a soft decision-making boundary for solving real-world classification problem. The soft decision-making boundary contains two parameters describing the offset and the shape, which are estimated automatically from the distribution of training samples around the boundary via a distribution of belief degree in the decision value domain. The SVMwith soft decisionmaking boundary increases classification accuracy by reducing the effects of data unbalance and noises in the realworld data. Simulation results show the effectiveness of the proposed approach.

Original languageEnglish
Title of host publicationProceedings of the IASTED International Conference on Artificial Intelligence and Applications, AIA 2008
Pages40-45
Number of pages6
Publication statusPublished - 2008 Dec 1
EventIASTED International Conference on Artificial Intelligence and Applications, AIA 2008 - Innsbruck, Austria
Duration: 2008 Feb 132008 Feb 15

Publication series

NameProceedings of the IASTED International Conference on Artificial Intelligence and Applications, AIA 2008

Conference

ConferenceIASTED International Conference on Artificial Intelligence and Applications, AIA 2008
CountryAustria
CityInnsbruck
Period08/2/1308/2/15

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Keywords

  • Real-world data classification
  • SVM
  • Soft decision-making boundary
  • Unbalanced data

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications

Cite this

Li, B., Hu, J., & Hirasawa, K. (2008). An improved support vector machine with soft decision-making boundary. In Proceedings of the IASTED International Conference on Artificial Intelligence and Applications, AIA 2008 (pp. 40-45). (Proceedings of the IASTED International Conference on Artificial Intelligence and Applications, AIA 2008).