• DocumentCode
    2754225
  • Title

    Decision Rule Generation Based on Similarity Relation*

  • Author

    An, Liping ; Tong, Lingyun

  • Author_Institution
    Bus. Sch., Nankai Univ., Tianjin
  • Volume
    2
  • fYear
    0
  • fDate
    0-0 0
  • Firstpage
    5915
  • Lastpage
    5918
  • Abstract
    The indiscernibility relation is the mathematical basis for the classical rough set theory. It is natural to extend the indiscernibility relation originally used for the definition of the rough approximation when the data describing objects is imprecise or when small differences are meaningless in the context of the study. This situation can be modeled using a binary relation that represents a certain form of similarity. Based on the concepts of lower and upper approximations using the similarity relation, the nonsimilarity matrix and the nonsimilarity function are presented to induce the minimal decision rules. An example is illustrated to demonstrate the application of this new approach
  • Keywords
    decision theory; function approximation; matrix algebra; rough set theory; binary relation; decision rule generation; indiscernibility relation; minimal decision rules; nonsimilarity function; nonsimilarity matrix; rough approximation; rough set theory; similarity relation; Fuzzy sets; Rough sets; Set theory; Technology management; Decision rules; Rough sets; Rule generation; Similarity relation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on
  • Conference_Location
    Dalian
  • Print_ISBN
    1-4244-0332-4
  • Type

    conf

  • DOI
    10.1109/WCICA.2006.1714213
  • Filename
    1714213