• Title of article

    Online independent reduced least squares support vector regression

  • Author/Authors

    Yongping Zhao، نويسنده , , Jianguo Sun، نويسنده , , Zhong-Hua Du، نويسنده , , Zhi-An Zhang، نويسنده , , Yebo Li، نويسنده ,

  • Issue Information
    روزنامه با شماره پیاپی سال 2012
  • Pages
    16
  • From page
    37
  • To page
    52
  • Abstract
    In this paper, an online algorithm, viz. online independent reduced least squares support vector regression (OIRLSSVR), is proposed based on the linear independence and the reduced technique. As opposed to some offline algorithms, OIRLSSVR takes the realtime advantage, which is confirmed using benchmark data sets. In comparison with online algorithm, the realtime of OIRLSSVR is also favorable. As for this point, it is tested with experiments on the benchmark data sets and a more realistic scenario namely a diesel engine example. All in all, OIRLSSVR can enhance the modeling realtime, especially for the case where the samples enter in a flow mode.
  • Keywords
    Support vector regression , Machine Learning , Online algorithm , Offline algorithm , Linear independence
  • Journal title
    Information Sciences
  • Serial Year
    2012
  • Journal title
    Information Sciences
  • Record number

    1215136