• DocumentCode
    2302016
  • Title

    Explicit versus implicit set-covering for supervised learning

  • Author

    Kowalski, Stephen V. ; Moldovan, Dan

  • Author_Institution
    Dept. of Electr. Eng. Syst., Univ. of Southern California, Los Angeles, CA, USA
  • fYear
    1994
  • fDate
    6-9 Nov 1994
  • Firstpage
    688
  • Lastpage
    691
  • Abstract
    It has been shown that implicit covering algorithms are effective for learning concepts from preclassified training examples. In this paper, we show that by making these covering algorithms explicit, concepts with lower error rates can be learned. Experimental results are reported for three real domains
  • Keywords
    errors; learning (artificial intelligence); set theory; concept learning; error rates; explicit set covering; implicit set covering; learning concepts; preclassified training examples; supervised learning; Artificial intelligence; Computer science; Error analysis; Humans; Supervised learning; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Tools with Artificial Intelligence, 1994. Proceedings., Sixth International Conference on
  • Conference_Location
    New Orleans, LA
  • Print_ISBN
    0-8186-6785-0
  • Type

    conf

  • DOI
    10.1109/TAI.1994.346425
  • Filename
    346425
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2302016