• DocumentCode
    1809991
  • Title

    A comparison of Eclectic learning and Stagger

  • Author

    Batsaihan, Jargalsaihan ; Barker, Cory

  • Author_Institution
    Dept. of Comput. Sci., Brigham Young Univ., Provo, UT, USA
  • Volume
    2
  • fYear
    1999
  • fDate
    36342
  • Firstpage
    1271
  • Abstract
    This project compares two machine-learning methods, Stagger and Eclectic, on their classification correctness. Both systems were tested with real-world data sets previously used and tested in other machine learning and statistical literature. The Eclectic system performed better than Stagger on every data set
  • Keywords
    Boolean functions; generalisation (artificial intelligence); learning (artificial intelligence); learning systems; neural nets; pattern classification; Boolean function; Eclectic system; Stagger system; generalisation; machine-learning; neural nets; pattern classification; Computer networks; Computer science; Counting circuits; Impedance matching; Iris; Learning systems; Machine learning; Machine learning algorithms; Pattern matching; System testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 1999. IJCNN '99. International Joint Conference on
  • Conference_Location
    Washington, DC
  • ISSN
    1098-7576
  • Print_ISBN
    0-7803-5529-6
  • Type

    conf

  • DOI
    10.1109/IJCNN.1999.831144
  • Filename
    831144
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1809991