• DocumentCode
    382923
  • Title

    Adaptive features of machine learning methods

  • Author

    Berka, Petr

  • Author_Institution
    Lab. for Intelligent Syst., Univ. of Econ., Prague, Czech Republic
  • Volume
    2
  • fYear
    2002
  • fDate
    2002
  • Firstpage
    40
  • Abstract
    This paper gives a survey of (symbolic) machine learning methods, that exhibit significant features of adaptivity. The paper discusses incremental learning, learning in dynamically changing domains, knowledge integration, theory revision, case based reasoning and inductive logic programming.
  • Keywords
    adaptive systems; belief maintenance; case-based reasoning; inductive logic programming; learning (artificial intelligence); adaptive features; case based reasoning; dynamically changing domains; incremental learning; inductive logic programming; knowledge integration; smart adaptive system; survey; symbolic machine learning methods; theory revision; Adaptive systems; Artificial intelligence; Data mining; Decision trees; Inference algorithms; Iterative algorithms; Learning systems; Logic programming; Machine learning; Stress;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Systems, 2002. Proceedings. 2002 First International IEEE Symposium
  • Print_ISBN
    0-7803-7134-8
  • Type

    conf

  • DOI
    10.1109/IS.2002.1042571
  • Filename
    1042571
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=382923