• DocumentCode
    1941370
  • Title

    Enhancing Boosting by Feature Non-Replacement for Microarray Data Analysis

  • Author

    Guile, Geoffrey R. ; Wang, Wenjia

  • Author_Institution
    Univ. of East Anglia, Norwich
  • fYear
    2007
  • fDate
    12-17 Aug. 2007
  • Firstpage
    430
  • Lastpage
    435
  • Abstract
    We have investigated strategies for enhancing ensemble learning algorithms for DNA microarray data analysis. By using modified versions of AdaBoost, LogitBoost and BagBoosting we have shown that feature non-replacement provides an effective enhancement to the performance of all three algorithms, and overall, BagBoosting with feature non-replacement had the lowest error rates when used on six commonly-used cancer datasets.
  • Keywords
    DNA; biology computing; data analysis; learning (artificial intelligence); AdaBoost; BagBoosting; DNA microarray data analysis; LogitBoost; cancer datasets; ensemble learning algorithms; feature nonreplacement; Bagging; Boosting; Cancer; DNA; Data analysis; Diseases; Error analysis; Iterative algorithms; Neural networks; Voting;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 2007. IJCNN 2007. International Joint Conference on
  • Conference_Location
    Orlando, FL
  • ISSN
    1098-7576
  • Print_ISBN
    978-1-4244-1379-9
  • Electronic_ISBN
    1098-7576
  • Type

    conf

  • DOI
    10.1109/IJCNN.2007.4370995
  • Filename
    4370995
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1941370