Gene classification using an improved SVM classifier with soft decision boundary

Boyang Li*, Liangpeng Ma, Jinglu Hu, Kotaro Hirasawa

*この研究の対応する著者

研究成果: Conference contribution

3 被引用数 (Scopus)

抄録

One of the central problems of functional genomics is gene classification. Microarray data are currently a major source of information about the functionality of genes. Various mathematical techniques, such as neural networks (NNs), self-organizing map (SOM) and several statistical methods, have been applied to classify the data in attempts to extract the underlying knowledge. As for conventional classification, the problem mainly addressed so far has been how to classify the multi-label gene data and how to deal with the imbalance problem. In this paper, we proposed an improved support vector machine (SVM) classifier with soft decision boundary. This boundary is a classification boundary based on belief degrees of data. The boundary can reflect the distribution of data, especially in the mutual part between classes and the excursion caused by the data imbalance.

本文言語English
ホスト出版物のタイトルProceedings of SICE Annual Conference 2008 - International Conference on Instrumentation, Control and Information Technology
ページ2476-2480
ページ数5
DOI
出版ステータスPublished - 2008 12月 1
イベントSICE Annual Conference 2008 - International Conference on Instrumentation, Control and Information Technology - Tokyo, Japan
継続期間: 2008 8月 202008 8月 22

出版物シリーズ

名前Proceedings of the SICE Annual Conference

Conference

ConferenceSICE Annual Conference 2008 - International Conference on Instrumentation, Control and Information Technology
国/地域Japan
CityTokyo
Period08/8/2008/8/22

ASJC Scopus subject areas

  • 制御およびシステム工学
  • コンピュータ サイエンスの応用
  • 電子工学および電気工学

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