• DocumentCode
    3292035
  • Title

    Function S-Rough Sets Method in Feature Selection

  • Author

    Hu, Haiqing ; Wang, Pitao ; Shi, Kaiquan

  • Author_Institution
    Sch. of Control Sci. & Eng., Univ. of Jinan, Jinan
  • Volume
    5
  • fYear
    2008
  • fDate
    18-20 Oct. 2008
  • Firstpage
    261
  • Lastpage
    265
  • Abstract
    Function S-rough sets is defined by function equivalence class, function is a kind of feature. By using of function S-rough sets, this paper gives a new feature selection method, gives concepts of lower approximation features and upper approximation features, furthermore, it presents the structure of F-feature pair, gives its characteristic discussion. F-feature selection method given in this paper has gotten applied in image processing, object recognition and etc, it is becoming a new research direction in recognition theory.
  • Keywords
    approximation theory; feature extraction; rough set theory; F-lower approximation features; F-upper approximation features; R-function equivalence class; feature selection; feature selection method; function S-rough sets method; image processing; object recognition; Control systems; Delay; Fuzzy systems; Image processing; Image recognition; Knowledge engineering; Mathematics; Object recognition; Rough sets; Set theory; eigenvector; feature; feature selection; function S-rough sets; precision;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems and Knowledge Discovery, 2008. FSKD '08. Fifth International Conference on
  • Conference_Location
    Jinan Shandong
  • Print_ISBN
    978-0-7695-3305-6
  • Type

    conf

  • DOI
    10.1109/FSKD.2008.204
  • Filename
    4666534