• DocumentCode
    495179
  • Title

    Gene Selection Using l1-Norm Least Square Regression

  • Author

    Hang, Xiyi

  • Author_Institution
    Dept. of Electr. & Comput. Eng., California State Univ., Northridge, CA, USA
  • Volume
    5
  • fYear
    2009
  • fDate
    March 31 2009-April 2 2009
  • Firstpage
    38
  • Lastpage
    41
  • Abstract
    A new gene selection method is proposed based on l1-norm least square regression. The numerical experiment shows that the new approach is, at last comparable to two popular methods: ANOVA and BSS/WSS.
  • Keywords
    biology computing; genetics; learning (artificial intelligence); least squares approximations; pattern classification; regression analysis; dataset training; gene profile classification system; gene selection method; l1-norm least square regression; Analysis of variance; Cancer; Computer science; Filters; Genetic algorithms; Input variables; Least squares methods; Minimization methods; Support vector machine classification; Support vector machines; Gene selection; classification; l1-norm; least square regression;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Science and Information Engineering, 2009 WRI World Congress on
  • Conference_Location
    Los Angeles, CA
  • Print_ISBN
    978-0-7695-3507-4
  • Type

    conf

  • DOI
    10.1109/CSIE.2009.984
  • Filename
    5170492
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=495179