• DocumentCode
    3644393
  • Title

    New feature selection method for multi-class data: Iteratively weighted AUC (IWA)

  • Author

    Petr Honzík;Pavel Kučera;Ondřej Hynčica;Daniel Haupt

  • Author_Institution
    Brno University of Technology, Faculty of Electrical Engineering and Communication, Department of Control and Instrumentation, Kolejní
  • Volume
    1
  • fYear
    2011
  • Firstpage
    336
  • Lastpage
    340
  • Abstract
    This paper deals with the new filter feature selection method Iteratively Weighted Area under Receiver Operating Characteristic (IWA). It is aimed for the multi-class problems with quantitative inputs. The experiments prove its superior quality in comparison to the equivalent methods.
  • Keywords
    "Correlation","Machine learning","Mathematical model","Computational modeling","Accuracy","Filtering algorithms","Indexes"
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Data Acquisition and Advanced Computing Systems (IDAACS), 2011 IEEE 6th International Conference on
  • Print_ISBN
    978-1-4577-1426-9
  • Type

    conf

  • DOI
    10.1109/IDAACS.2011.6072769
  • Filename
    6072769
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3644393