• DocumentCode
    2769868
  • Title

    Classification with Tree-Based Ensembles Applied to the WCCI 2006 Performance Prediction Challenge Datasets

  • Author

    Dahinden, Corinne

  • Author_Institution
    ETH Zurich, Zurich
  • fYear
    0
  • fDate
    0-0 0
  • Firstpage
    1669
  • Lastpage
    1672
  • Abstract
    Our contribution to the WCCI 2006 performance prediction challenge is built on a modified random forests scheme, with cross-validation as a means for tuning parameters and estimating error-rates. This simple and computationally very efficient approach was found to yield better predictive performance than many algorithms of much higher complexity.
  • Keywords
    error statistics; pattern classification; trees (mathematics); WCCI 2006 Performance Prediction Challenge datasets; error-rate estimation; modified random forests scheme; tree-based ensembles; Classification algorithms; Classification tree analysis; Error analysis; High performance computing; Humans; Input variables; Machine learning algorithms; Parameter estimation; Regression tree analysis; Seminars;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 2006. IJCNN '06. International Joint Conference on
  • Conference_Location
    Vancouver, BC
  • Print_ISBN
    0-7803-9490-9
  • Type

    conf

  • DOI
    10.1109/IJCNN.2006.246635
  • Filename
    1716308
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2769868