• DocumentCode
    556430
  • Title

    Based on support vector machine approach to missing data

  • Author

    Li-hua, Yang ; Qing-hua, Nie

  • Author_Institution
    Sch. of Inf. Eng., JingDeZhen Ceramic Inst., Jingdezhen, China
  • Volume
    1
  • fYear
    2011
  • fDate
    22-23 Oct. 2011
  • Firstpage
    252
  • Lastpage
    254
  • Abstract
    This paper systematically analyzes the causes and the mechanism of missing data, and research the processing method of missing data based on the support vector machine. And the results show that the prediction based on support vector machine method is more desirable than neural network, wavelet network model. And this method can promote and apply in the prediction of missing data to a certain extend.
  • Keywords
    data analysis; support vector machines; missing data; neural network; support vector machine; wavelet network model; Buildings; Fitting; Support vector machines; SVM; completing; missing values;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    System Science, Engineering Design and Manufacturing Informatization (ICSEM), 2011 International Conference on
  • Conference_Location
    Guiyang
  • Print_ISBN
    978-1-4577-0247-1
  • Type

    conf

  • DOI
    10.1109/ICSSEM.2011.6081198
  • Filename
    6081198
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=556430