• DocumentCode
    547401
  • Title

    An incremental algorithm of support vector machine based on distance ratio and k nearest neighbor

  • Author

    Bing-xiang, Liu ; Xiang, Cheng

  • Author_Institution
    Sch. of Inf. Eng., JDZ Ceramic Inst., Jingdezhen, China
  • Volume
    1
  • fYear
    2011
  • fDate
    10-12 June 2011
  • Firstpage
    18
  • Lastpage
    20
  • Abstract
    For large data sets and data updated situation, incremental training algorithm is an effective solution of support vector machine training. To improve speed of incremental support vector machine training algorithm, this paper combines the distance ratio method and the nearest neighbor method to extract boundary samples, and an incremental support vector machine algorithm based on distance ratio and k nearest neighbor was proposed, this algorithm can eliminate useless samples as far as possible, thus reduces the training time at remaining essentially the same training accuracy.
  • Keywords
    learning (artificial intelligence); support vector machines; very large databases; data updated situation; distance ratio; incremental algorithm; incremental training algorithm; k nearest neighbor algorithm; large data sets; support vector machine training; Accuracy; Classification algorithms; Statistical learning; Support vector machine classification; Training; distance ratio; incremental; k nearest neighbor; support vector machine;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Science and Automation Engineering (CSAE), 2011 IEEE International Conference on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-1-4244-8727-1
  • Type

    conf

  • DOI
    10.1109/CSAE.2011.5953162
  • Filename
    5953162