• DocumentCode
    2548010
  • Title

    Evaluation Method and Application Based on Rough Set-Support Vector Regression Model

  • Author

    Wang, Xiu-mei ; Zhang, Xing ; Gao, Chong

  • Author_Institution
    Sch. of Bus. & Adm., North China Electr. power Univ., Baoding
  • Volume
    2
  • fYear
    2009
  • fDate
    22-24 Jan. 2009
  • Firstpage
    331
  • Lastpage
    335
  • Abstract
    Support Vector Machine has the convenient superiority in the classification. Recently it has been extended to the domain of regression problems. However, due to the increasing index, excess input data and complicated system structure, it is difficult to achieve good accuracy in results. This paper adopts combination method of rough set and support vector machine so as to establish rough set attribute reducing support vector regression model to carry out the comprehensive evaluation of the innovative talents training in engineering universities. The experimental results show that this method has strong objectivity and impartiality, and can increase the computing speed.
  • Keywords
    regression analysis; rough set theory; support vector machines; evaluation method; innovative talents training; rough set attribute; rough set support vector regression model; support vector machine; Application software; Databases; Information systems; Power engineering and energy; Power engineering computing; Redundancy; Set theory; Stochastic systems; Support vector machine classification; Support vector machines; Evaluation; rough set; support vector machine;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Engineering and Technology, 2009. ICCET '09. International Conference on
  • Conference_Location
    Singapore
  • Print_ISBN
    978-1-4244-3334-6
  • Type

    conf

  • DOI
    10.1109/ICCET.2009.56
  • Filename
    4769616