• DocumentCode
    3229139
  • Title

    Rough Set Approach for Processing Information Table

  • Author

    Xu, E. ; Shaocheng, Tong ; Liangshan, Shao ; Baiqing, Ye

  • Author_Institution
    Liaoning Univ. of Technol., Jinzhou
  • Volume
    3
  • fYear
    2007
  • fDate
    July 30 2007-Aug. 1 2007
  • Firstpage
    239
  • Lastpage
    243
  • Abstract
    To deal with the problem of completing the information table, a new method was studied and proposed. First, define discernible vector and its addition rule by the indiscernible relation in rough set. Second, scan discernible vectors just only one time by the discernible vector addition rule in order to obtain the core attribute set and the important attributes. Then obtain a reduced attribute set by deleting redundant attributes. Finally, according to the dependence relation of condition and decision attributes, select the important breaking points,and complete the information table with the constraints of classification quality. The illustration and experiment results indicate that the method is effective and efficient.
  • Keywords
    computational complexity; rough set theory; discernible vector addition rule; information table processing; rough set approach; scan discernible vectors; Artificial intelligence; Bellows; Clustering algorithms; Computer networks; Concurrent computing; Distributed computing; Information systems; Machine learning algorithms; Rough sets; Software engineering;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing, 2007. SNPD 2007. Eighth ACIS International Conference on
  • Conference_Location
    Qingdao
  • Print_ISBN
    978-0-7695-2909-7
  • Type

    conf

  • DOI
    10.1109/SNPD.2007.309
  • Filename
    4287856