• DocumentCode
    2466111
  • Title

    Selection of classifiers based on the MDL principle using the VC dimension

  • Author

    Kudo, Mineichi ; Shimbo, Masm

  • Author_Institution
    Dept. of Inf. Eng., Hokkaido Univ., Sapporo, Japan
  • Volume
    2
  • fYear
    1996
  • fDate
    25-29 Aug 1996
  • Firstpage
    886
  • Abstract
    The MDL (minimum description length) criterion is used to select the best classifier among several types of classifiers on a given pattern recognition problem. Unlike previous studies, our technique can compare a wide variety of classifiers if we know a combinational property, viz., the Vapnick-Chervonenkis (VC) dimension. Three classifiers are compared using this criterion. Experimental results show the effectiveness of the method
  • Keywords
    pattern classification; MDL principle; VC dimension; Vapnick-Chervonenkis dimension; classifier selection; combinational property; minimum description length criterion; pattern recognition problem; Communication channels; Costs; Decision trees; Decoding; Length measurement; Pattern recognition; Silicon carbide; Tin; Virtual colonoscopy;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition, 1996., Proceedings of the 13th International Conference on
  • Conference_Location
    Vienna
  • ISSN
    1051-4651
  • Print_ISBN
    0-8186-7282-X
  • Type

    conf

  • DOI
    10.1109/ICPR.1996.547203
  • Filename
    547203
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2466111