• DocumentCode
    2771245
  • Title

    Model Selection in an Ensemble Framework

  • Author

    Wichard, Jörg D.

  • Author_Institution
    Schering AG, Berlin and the Institute of Molecular Pharmacology Molecular Modelling Group, Robert Rössle Straβe 10, D-13125 Berlin-Buch, Germany. email: JoergWichard@web.de
  • fYear
    2006
  • fDate
    16-21 July 2006
  • Firstpage
    2187
  • Lastpage
    2192
  • Abstract
    We like to present a method to build ensemble models based on an extended cross-validation approach. The cross-validation puts several model classes in a tournament and selects the best performing model with respect to the validation set. This leads to a model selection strategy and an estimation of the expected modelling error.
  • Keywords
    Decision trees; Neural networks; Predictive models; Stability; Supervised learning; Testing; Training data;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 2006. IJCNN '06. International Joint Conference on
  • Print_ISBN
    0-7803-9490-9
  • Type

    conf

  • DOI
    10.1109/IJCNN.2006.247012
  • Filename
    1716382
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2771245