• DocumentCode
    475940
  • Title

    Approach for absolute attribute reductions in rough sets

  • Author

    Pei, Xiao-Bing

  • Author_Institution
    Coll. of Software, HuaZhong Univ. of Sci. & Technol., Wuhan
  • Volume
    1
  • fYear
    2008
  • fDate
    12-15 July 2008
  • Firstpage
    391
  • Lastpage
    394
  • Abstract
    Attribute reductions is one of the basic contents in rough sets and one of the most problem in knowledge acquisition. At present, the methods used are often Pawlakpsilas data analysis and Skowronpsilas discernible matrix methods. In this paper an approach for the set of all absolute attribute reductions is proposed based on the discernible attribute set. Finally, we also show the experimental results by examples.
  • Keywords
    knowledge acquisition; rough set theory; absolute attribute reductions; data analysis; discernible matrix methods; knowledge acquisition; rough sets; Cybernetics; Data analysis; Educational institutions; Information systems; Knowledge acquisition; Machine learning; NP-hard problem; Rough sets; Set theory; Absolute attribute reduction; Rough set;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics, 2008 International Conference on
  • Conference_Location
    Kunming
  • Print_ISBN
    978-1-4244-2095-7
  • Electronic_ISBN
    978-1-4244-2096-4
  • Type

    conf

  • DOI
    10.1109/ICMLC.2008.4620437
  • Filename
    4620437