An improved support vector machine with soft decision-making boundary

Boyang Li*, Jinglu Hu, Kotaro Hirasawa

*この研究の対応する著者

研究成果: Conference contribution

5 被引用数 (Scopus)

抄録

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.

本文言語English
ホスト出版物のタイトルProceedings of the IASTED International Conference on Artificial Intelligence and Applications, AIA 2008
ページ40-45
ページ数6
出版ステータスPublished - 2008 12月 1
イベントIASTED International Conference on Artificial Intelligence and Applications, AIA 2008 - Innsbruck, Austria
継続期間: 2008 2月 132008 2月 15

出版物シリーズ

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

Conference

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

ASJC Scopus subject areas

  • 人工知能
  • コンピュータ サイエンスの応用

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