• DocumentCode
    2101496
  • Title

    Learning from historical precedent

  • Author

    Pazzani, Michael J.

  • Author_Institution
    Dept. of Inf. & Comput. Sci., California Univ., Irvine, CA, USA
  • fYear
    1989
  • fDate
    27-31 Mar 1989
  • Firstpage
    150
  • Lastpage
    156
  • Abstract
    Explanation-based learning, a method of abstracting general principles from a small number of prior cases, is discussed. The author demonstrates the feasibility of applying this method to economic sanction incidents. This approach is contrasted with regression analysis, a traditional quantitative method. A method for integrating these two approaches is proposed
  • Keywords
    economics; expert systems; explanation; government data processing; learning systems; economic sanction incidents; explanation based learning; historical precedent; regression analysis; Africa; Australia; Computer science; Decision making; Economic forecasting; Failure analysis; History; Learning systems; Regression analysis; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    AI Systems in Government Conference, 1989.,Proceedings of the Annual
  • Conference_Location
    Washington, DC
  • Print_ISBN
    0-8186-1934-1
  • Type

    conf

  • DOI
    10.1109/AISIG.1989.47318
  • Filename
    47318
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2101496