• DocumentCode
    2481715
  • Title

    Study on condition attributes and decision attribute based on rough sets theory

  • Author

    Kong, Zhi ; Luan, Haoli ; Gao, Liqun ; Wang, Lifu ; Lu, Zhiguang

  • Author_Institution
    Inf. Sci. & Eng., Northeastern Univ., Shenyang
  • fYear
    2008
  • fDate
    25-27 June 2008
  • Firstpage
    2044
  • Lastpage
    2047
  • Abstract
    The attributes of rough set play an important roles in rough theory. We discussed attribute subdivision in this paper. In the attribute subdivision we mainly research the relationship between attribute subdivision and the upper approximation, lower approximation, quality of approximation classification, accuracy of approximation classification, number of decision rules and relative reduction. Meanwhile, the qualities of non-redundant and redundant attributes are analyzed. In the decision subdivision, the attribute subdivision and decision subdivision are studied in the same decision table. Finally, an example is shown to understand the above properties. The research is helpful for the attribute reduction, formation of decision rules and enhancing confidences of decision rules.
  • Keywords
    rough set theory; approximation classification accuracy; approximation classification quality; attribute subdivision; condition attributes; decision attribute; decision rules; decision subdivision; decision table; lower approximation; nonredundant attributes; redundant attributes; relative reduction; rough sets theory; upper approximation; Artificial intelligence; Automation; Data mining; Engineering management; Heat engines; Intelligent control; Knowledge acquisition; Pattern recognition; Rough sets; Set theory; Approximation accuracy; Approximation quality; Attribute subdivision; Decision subdivision; Rough set;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Control and Automation, 2008. WCICA 2008. 7th World Congress on
  • Conference_Location
    Chongqing
  • Print_ISBN
    978-1-4244-2113-8
  • Electronic_ISBN
    978-1-4244-2114-5
  • Type

    conf

  • DOI
    10.1109/WCICA.2008.4593239
  • Filename
    4593239