• DocumentCode
    3291075
  • Title

    Attribute Reduction in Information Systems via Oriented Association Coefficient

  • Author

    Wei, Li-Li

  • Author_Institution
    Sch. of Math. & Comput. Sci., Ningxia Univ., Yinchuan, China
  • fYear
    2009
  • fDate
    6-7 June 2009
  • Firstpage
    15
  • Lastpage
    18
  • Abstract
    Rough set data analysis has recently become a routine method in categorical data analysis. One of the important problems in rough set theory is attribute reduction. In this paper, the statistic named oriented association coefficient among attributes of information systems is introduced, which measures the non-linear relationships between qualitative variables. Based on this statistic, we present a new discriminant theorem of attribute reduction in information systems. Furthermore, experiments show that our approach is feasible and efficient.
  • Keywords
    data analysis; data mining; information systems; rough set theory; statistical analysis; attribute reduction; categorical data analysis; discriminant theorem; information system; oriented association coefficient; qualitative variable; rough set data analysis; statistical analysis; Bayesian methods; Computer science; Data analysis; Information analysis; Information systems; Mathematics; Probability; Set theory; Statistical analysis; Statistics; attribute reduction; categorical data; information systems; oriented association coefficient; rough set;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Web Mining and Web-based Application, 2009. WMWA '09. Second Pacific-Asia Conference on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-0-7695-3646-0
  • Type

    conf

  • DOI
    10.1109/WMWA.2009.56
  • Filename
    5232457