• DocumentCode
    2329222
  • Title

    Decision rule extraction method based on rough set theory and fuzzy set theory

  • Author

    Wang, Mingi-Chun ; Wang, Zenc-Ou ; ZHang, Ming ; Yan, Peng

  • Author_Institution
    Dept. of Syst. Eng., Tianjin Univ., China
  • Volume
    4
  • fYear
    2005
  • fDate
    18-21 Aug. 2005
  • Firstpage
    2212
  • Abstract
    A quantitative decision table can be transformed into a qualitative decision one by using the fuzzy set theory. This paper develops the definition of membership function mentioned in the literature, and proposes transforming rules from the quantitative decision table to the qualitative decision table with the properties of membership function. The rules can change an n-dimension quantitative decision table into an n-dimension qualitative decision table instead of a 3n-dimension one. So it greatly decreases afterward computing complexity of rule extraction using rough set theory, while increases the quality of extracted rules.
  • Keywords
    data mining; decision tables; fuzzy set theory; rough set theory; decision rule extraction method; fuzzy set theory; membership function; qualitative decision table; quantitative decision table; rough set theory; Computer science education; Cybernetics; Fuzzy set theory; Hip; Machine learning; Medical diagnosis; Set theory; Tellurium; Decision Table; Fuzzy Set; Rough Set; Rule Extraction;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics, 2005. Proceedings of 2005 International Conference on
  • Conference_Location
    Guangzhou, China
  • Print_ISBN
    0-7803-9091-1
  • Type

    conf

  • DOI
    10.1109/ICMLC.2005.1527312
  • Filename
    1527312