• DocumentCode
    2388939
  • Title

    Extending the learnability of decision trees

  • Author

    Elomaa, Tapio

  • Author_Institution
    Dept. of Comput. Sci., Helsinki Univ., Finland
  • fYear
    1991
  • fDate
    10-13 Nov 1991
  • Firstpage
    504
  • Lastpage
    505
  • Abstract
    The author concentrates on B. Natarajan´s (1991) framework for learning classes of total functions of discrete domains. A. Ehrenfeucht and D. Haussler (1989) have shown that a subclass of decision trees is learnable in the sense defined by L. Valiant (1984). The author generalizes their definitions to m-ary domains and shows that the learnability of restricted decision tree classifiers carries over to the extended model
  • Keywords
    decision theory; learning systems; trees (mathematics); decision trees; discrete domains; learnability; m-ary domains; restricted decision tree classifiers; Classification tree analysis; Computer science; Decision trees; Machine learning; Polynomials;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Tools for Artificial Intelligence, 1991. TAI '91., Third International Conference on
  • Conference_Location
    San Jose, CA
  • Print_ISBN
    0-8186-2300-4
  • Type

    conf

  • DOI
    10.1109/TAI.1991.167034
  • Filename
    167034
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2388939