• DocumentCode
    511251
  • Title

    Research on Least Squares Support Vector Machine Combinatorial Optimization Algorithm

  • Author

    Taian, Liu ; Yunjia, Wang ; Wentong, Liu

  • Author_Institution
    Coll. of Environ. & Spatial Inf., China Univ. of Min. & Technol. (CUMT), Xuzhou, China
  • Volume
    1
  • fYear
    2009
  • fDate
    25-27 Dec. 2009
  • Firstpage
    452
  • Lastpage
    454
  • Abstract
    LS-SVM(least squares support vector machine) has been widely used in engineering practice. However, the solving of LS-SVM still remains difficult under the condition of large sample. Based on algorithm of combinatorial optimization, this paper put forward the combinatorial optimization least squares support vector machine algorithm. On several different data aggregation of dimensions, the numerical value experiment and comparison are carried out on traditional LS-SVM algorithm, COLS-SVM algorithm and its improvement algorithm. The numerical value test has shown that COLS-SVM algorithm and its improvement algorithm are effective and have certain advantages on time and regression accuracy, compared with traditional LS-SVM algorithm.
  • Keywords
    combinatorial mathematics; least squares approximations; optimisation; support vector machines; SVM; combinatorial optimization algorithm; data aggregation; least squares support vector machine; Application software; Computer applications; Educational institutions; Equations; Informatics; Least squares methods; Optimization methods; Sparse matrices; Support vector machines; Testing; Combinatorial optimization algorithm; Least squares support vector machine; Linear equations least squares support vector machine; Sparse method;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Science-Technology and Applications, 2009. IFCSTA '09. International Forum on
  • Conference_Location
    Chongqing
  • Print_ISBN
    978-0-7695-3930-0
  • Electronic_ISBN
    978-1-4244-5423-5
  • Type

    conf

  • DOI
    10.1109/IFCSTA.2009.116
  • Filename
    5385037