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SVM-RFE with Relevancy and Redundancy Criteria for Gene Selection

  • Piyushkumar A. Mundra
  • Jagath C. Rajapakse
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4774)

Abstract

This paper introduces a novel gene selection method incorporating mutual information in the support vector machine recursive feature elimination (SVM-RFE). We incorporate an additional term of mutual information based minimum redundancy maximum relevancy criteria along with feature weight calculated by SVM algorithm. We tested proposed method on colon cancer and leukemia cancer gene expression dataset. The results show that the proposed method performs better than the original SVM-RFE method. The selected gene subset has better classification accuracy and better generalization capability.

Keywords

Gene selection mutual information minimum redundancy maximum relevancy SVM-RFE cancer classification 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Piyushkumar A. Mundra
    • 1
  • Jagath C. Rajapakse
    • 1
    • 2
  1. 1.Bioinformatics Research Center, School of Computer Engineering, Nanyang Technological University, 50 Nanyang Avenue, 639798Singapore
  2. 2.Singapore-MIT Alliance, N2-B2C-15, 50 Nanyang AvenueSingapore

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