• DocumentCode
    3027531
  • Title

    Stratified rough sets and granular computing

  • Author

    Yao, Y.Y.

  • Author_Institution
    Dept. of Comput. Sci., Regina Univ., Sask., Canada
  • fYear
    1999
  • fDate
    36342
  • Firstpage
    800
  • Lastpage
    804
  • Abstract
    This paper examines granulation structures for stratified rough set approximations. With respect to different level of granulations, various approximations are obtained. Two special types of granulation structures are investigated. A nested sequence of granulations by equivalence relations leads to a nested sequence of rough set approximations. A hierarchical granulation, characterized by a special class of equivalence relations, leads to a more general approximation structure
  • Keywords
    data mining; inference mechanisms; learning (artificial intelligence); rough set theory; equivalence relations; granular computing; granulation structures; nested sequence; stratified rough sets; Computer science; Rough sets; Set theory;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Information Processing Society, 1999. NAFIPS. 18th International Conference of the North American
  • Conference_Location
    New York, NY
  • Print_ISBN
    0-7803-5211-4
  • Type

    conf

  • DOI
    10.1109/NAFIPS.1999.781804
  • Filename
    781804
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3027531