• DocumentCode
    253490
  • Title

    General regression in cloud computing

  • Author

    Bobak, Martin ; Hluchy, Ladislav ; Tran, Van-Long

  • Author_Institution
    Inst. of Inf., Bratislava, Slovakia
  • fYear
    2014
  • fDate
    3-5 July 2014
  • Firstpage
    79
  • Lastpage
    82
  • Abstract
    Regression is one of the approach/technology of machine learning. This technology is used in a situation where we want to estimate from input parameters the scalar quantity. In practice we often face with situation where due to deficient computing resources, we are not able to train required function (in sense the minimum error). This phenomenon can cause a various factors (e.g. large number of training data, high degree of training function ...). An interesting question is: how helpful is cloud computing in this situation.
  • Keywords
    cloud computing; learning (artificial intelligence); parameter estimation; regression analysis; cloud computing; deficient computing resources; general regression; input parameter estimation; machine learning; scalar quantity; Cloud computing; Complexity theory; Linear regression; Mathematical model; Operating systems; Training; Virtualization; cloud computing; machine learning; regression;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Engineering Systems (INES), 2014 18th International Conference on
  • Conference_Location
    Tihany
  • Type

    conf

  • DOI
    10.1109/INES.2014.6909380
  • Filename
    6909380