• DocumentCode
    3109620
  • Title

    Discernibility Matrix Based Algorithm for Reduction of Attributes

  • Author

    Wang, Ruizhi ; Miao, Duoqian ; Hu, Guirong

  • Author_Institution
    Dept. of Comput. Sci. & Technol.,, Tongji Univ., Shanghai
  • fYear
    2006
  • fDate
    Dec. 2006
  • Firstpage
    477
  • Lastpage
    480
  • Abstract
    In rough set theory, it has been proved that finding the minimal reduct of information systems or decision tables is a NP-complete problem. Therefore, it is hard to obtain the set of the most concise rules by existing algorithms for reduction of knowledge. In this paper, the method of finding sub-optimal reduct based on discernibility matrix is proposed. In general, our method is better than existing methods with respect to the minimal reduct. However, we find that existing minimal reduct searching algorithms are incomplete for reduction of attributes in information systems or decision tables. Through analysis, we present a conjecture about the completeness of the minimal reduct algorithm
  • Keywords
    computational complexity; decision tables; information systems; rough set theory; NP-complete problem; decision tables; discernibility matrix; information systems; minimal reduct algorithm; rough set theory; Algorithm design and analysis; Computer science; Databases; Heuristic algorithms; Information systems; Intelligent agent; NP-complete problem; Set theory; Uncertainty;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Web Intelligence and Intelligent Agent Technology Workshops, 2006. WI-IAT 2006 Workshops. 2006 IEEE/WIC/ACM International Conference on
  • Conference_Location
    Hong Kong
  • Print_ISBN
    0-7695-2749-3
  • Type

    conf

  • DOI
    10.1109/WI-IATW.2006.58
  • Filename
    4053296