• DocumentCode
    468140
  • Title

    An Efficient Method for Attribute Reduction in Incomplete Information Systems

  • Author

    Li, Renpu ; Zhao, Yongsheng ; Zhang, Fuzeng ; Song, Lihua

  • Author_Institution
    Ludong Univ., Yantai
  • Volume
    1
  • fYear
    2007
  • fDate
    24-27 Aug. 2007
  • Firstpage
    352
  • Lastpage
    356
  • Abstract
    Attribute reduction is an important issue of data mining. In this paper a novel method based on rough sets is provided for attribute reduction in incomplete information systems. Through a transformation technique, an incomplete system is firstly converted into a new and simpler system and then reducts are obtained from the transformed system. It is proved by theorem that the transformed system has the same reducts as the previous one. Experiments show that the proposed method is more efficient on reduct computation of incomplete information systems.
  • Keywords
    data mining; rough set theory; attribute reduction; data mining; incomplete information systems; rough sets; transformed system; Computer science; Data mining; Information systems; Machine learning; Rough sets; Set theory;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems and Knowledge Discovery, 2007. FSKD 2007. Fourth International Conference on
  • Conference_Location
    Haikou
  • Print_ISBN
    978-0-7695-2874-8
  • Type

    conf

  • DOI
    10.1109/FSKD.2007.152
  • Filename
    4405946