• DocumentCode
    3630285
  • Title

    Accuracy boosting induction of fuzzy rules with Artificial Immune Systems

  • Author

    Adam Kalina;Edward Mezyk;Olgierd Unold

  • Author_Institution
    Value Based Advisors Sp. z o.o., ul. Po?abian 35, 52-339 Wroc?aw, Poland
  • fYear
    2008
  • Firstpage
    155
  • Lastpage
    159
  • Abstract
    The paper introduces accuracy boosting extension to a novel induction of fuzzy rules from raw data using artificial immune system methods. Accuracy boosting relies on fuzzy partition learning. The modified algorithm was experimentally proved to be more accurate for all learning sets containing non-crisp attributes.
  • Keywords
    "Boosting","Fuzzy systems","Artificial immune systems","Fuzzy sets","Data mining","Partitioning algorithms","Genetic algorithms","Computer science","Information technology","Control engineering computing"
  • Publisher
    ieee
  • Conference_Titel
    Computer Science and Information Technology, 2008. IMCSIT 2008. International Multiconference on
  • Print_ISBN
    978-83-60810-14-9
  • Type

    conf

  • DOI
    10.1109/IMCSIT.2008.4747233
  • Filename
    4747233
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3630285