• DocumentCode
    394124
  • Title

    GA-parameter optimisation of evolving connectionist systems for classification and a case study from bioinformatics

  • Author

    Kasabov, Nikola ; Song, Qun

  • Author_Institution
    Knowledge Eng. & Discovery Res. Inst., Auckland Univ. of Technol., New Zealand
  • Volume
    2
  • fYear
    2002
  • fDate
    18-22 Nov. 2002
  • Firstpage
    602
  • Abstract
    The paper describes an algorithm for parameter optimisation of evolving connectionist systems (ECOS) in an offline processing mode. The algorithm is illustrated on a case study of a classification system that uses gene expression data to predict an outcome of a treatment of cancer disease.
  • Keywords
    genetic algorithms; genetics; medical computing; neural nets; pattern classification; ECOS; GA-parameter optimisation; bioinformatics; cancer disease; case study; classification system; evolving connectionist systems; gene expression data; offline processing mode; parameter optimisation; Bioinformatics; Cancer; Computer aided software engineering; Diseases; Gene expression; Knowledge engineering; Neural networks; Neurons; Paper technology; Predictive models;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Information Processing, 2002. ICONIP '02. Proceedings of the 9th International Conference on
  • Print_ISBN
    981-04-7524-1
  • Type

    conf

  • DOI
    10.1109/ICONIP.2002.1198128
  • Filename
    1198128
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=394124