• DocumentCode
    2415009
  • Title

    Speed up SVM-RFE Procedure Using Margin Distribution

  • Author

    Yuan, Yingqin ; Hrebien, Leonid ; Kam, Moshe

  • Author_Institution
    Res. & Eng. Center, Whirlpool Corp., Benton Harbor, MI
  • fYear
    2005
  • fDate
    28-28 Sept. 2005
  • Firstpage
    297
  • Lastpage
    302
  • Abstract
    In this paper, a new method is introduced to speed up the recursive feature ranking procedure by using the margin distribution of a trained SVM. The method, M-RFE, continuously eliminates features without retraining the SVM as long as the margin distribution of the SVM does not change significantly. Synthetic datasets and two benchmark microarray datasets were tested on M-RFE. Comparison with original SVM-RFE shows that our method speeds up the feature ranking procedure considerably with little or no performance degradation. Comparison of M-RFE to a similar speed up technique, E-RFE, provides similar classification performance, but with reduced complexity
  • Keywords
    feature extraction; pattern classification; support vector machines; SVM-recursive feature elimination; margin distribution; microarray dataset; pattern classification; recursive feature ranking; support vector machines; Acceleration; Accuracy; Benchmark testing; Cancer; Data engineering; Degradation; Entropy; Laboratories; Support vector machine classification; Support vector machines;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning for Signal Processing, 2005 IEEE Workshop on
  • Conference_Location
    Mystic, CT
  • Print_ISBN
    0-7803-9517-4
  • Type

    conf

  • DOI
    10.1109/MLSP.2005.1532917
  • Filename
    1532917