• DocumentCode
    3661108
  • Title

    Multiple SVM-RFE for multi-class gene selection on DNA Microarray data

  • Author

    Li Zhang; Xiaojuan Huang

  • Author_Institution
    School of Computer Science and Technology &
  • fYear
    2015
  • fDate
    7/1/2015 12:00:00 AM
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    This paper presents a new multi-class gene selection and classification method based on multiple support vector machine recursive feature elimination (SVM-RFE). For a multi-class DNA microarray problem, we solve it as multiple binary classification problems. First, the one-versus-all method is used to decompose the multi-class task into multiple binary problems. Second, an SVM-RFE is adopted to select genes for each binary problem. Then, an SVM classifier is used to train the selected gene data for a binary problem. Finally, we combine the outputs of multiple SVM classifiers. Experimental results on three DNA Microarray datasets show that the proposed method achieves higher classification accuracy.
  • Keywords
    "DNA","Lungs","Bioinformatics"
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks (IJCNN), 2015 International Joint Conference on
  • Electronic_ISBN
    2161-4407
  • Type

    conf

  • DOI
    10.1109/IJCNN.2015.7280417
  • Filename
    7280417