• DocumentCode
    3249559
  • Title

    What should a classifier system learn?

  • Author

    Kovacs, Tim

  • Author_Institution
    Sch. of Comput. Sci., Birmingham Univ., UK
  • Volume
    2
  • fYear
    2001
  • fDate
    2001
  • Firstpage
    775
  • Abstract
    We consider the issue of how a classifier system should learn to represent a Boolean function. We identify four properties which may be desirable of a representation; that it be complete, accurate, minimal and nonoverlapping, and distinguish variations on two of these properties for the XCS system. We question whether the bias against overlapping rules evident in some systems is appropriate, and find that XCS´s bias against overlapping rules is very strong
  • Keywords
    Boolean functions; learning systems; pattern classification; Boolean function; Learning Classifier Systems; XCS system; classifier system; overlapping rules; Boolean functions; Computer science; Machine learning; Monitoring; Statistics; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation, 2001. Proceedings of the 2001 Congress on
  • Conference_Location
    Seoul
  • Print_ISBN
    0-7803-6657-3
  • Type

    conf

  • DOI
    10.1109/CEC.2001.934268
  • Filename
    934268
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3249559