• DocumentCode
    2769838
  • Title

    LogitBoost with Trees Applied to the WCCI 2006 Performance Prediction Challenge Datasets

  • Author

    Lutz, Roman Werner

  • Author_Institution
    ETH Zurich, Zurich
  • fYear
    0
  • fDate
    0-0 0
  • Firstpage
    1657
  • Lastpage
    1660
  • Abstract
    We apply LogitBoost with a tree-based learner to the five WCCI 2006 performance prediction challenge datasets. The number of iterations and the tree size is estimated by 10-fold cross-validation. We add a simple shrinkage strategy to make the algorithm more stable. The results are very promising since we won the challenge.
  • Keywords
    pattern classification; statistical analysis; trees (mathematics); LogitBoost; high-dimensional classification problems; prediction challenge datasets; shrinkage strategy; tree-based learner; Bit error rate; Error analysis; Logistics; Predictive models; Protection; Regression tree analysis; Seminars; Statistics; Terminology; Testing;
  • 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.2006.246633
  • Filename
    1716306
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2769838