• DocumentCode
    1659931
  • Title

    Extension of rough set under incomplete information systems

  • Author

    Wang, Guoyin

  • Author_Institution
    Inst. of Comput. Sci. & Technol., Chongqing Univ. of Posts & Telecommun., China
  • Volume
    2
  • fYear
    2002
  • fDate
    6/24/1905 12:00:00 AM
  • Firstpage
    1098
  • Lastpage
    1103
  • Abstract
    The classical rough set theory is based on complete information systems. It classifies objects using upper-approximation and lower-approximation defined on an indiscernibility relation that is a kind of equivalent relation. In order to process incomplete information systems, the classical rough set theory needs to be extended, especially, the indiscernibility relation needs to be extended to some inequivalent relation. There are several extensions for the indiscernibility relation at present, such as tolerance relation, non-symmetric similarity relation, and valued tolerance relation. Unfortunately, these extensions have their own limitation. We develop a new extension of rough set theory that is based on a limited tolerance relation
  • Keywords
    information systems; knowledge acquisition; probability; rough set theory; incomplete information systems; indiscernibility relation; limited tolerance relation; rough set theory; Computer science; Educational programs; Information systems; Knowledge acquisition; Probability; Set theory; Statistical analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems, 2002. FUZZ-IEEE'02. Proceedings of the 2002 IEEE International Conference on
  • Conference_Location
    Honolulu, HI
  • Print_ISBN
    0-7803-7280-8
  • Type

    conf

  • DOI
    10.1109/FUZZ.2002.1006657
  • Filename
    1006657