• DocumentCode
    1817131
  • Title

    Pattern classifying neural network based on Fisher´s linear discriminant function

  • Author

    Lee, Jong Chan ; Kim, Yung Hwan ; Lee, Won Don ; Lee, Suk Hoon

  • Author_Institution
    Coll. of Natural Sci., ChungNam Nat. Univ., Daejun, South Korea
  • Volume
    1
  • fYear
    1992
  • fDate
    7-11 Jun 1992
  • Firstpage
    743
  • Abstract
    The network model for two-class pattern classification originally proposed by C. Koutsougeras and C.A. Papachristou (1988) is extended to n-class pattern classification. The proposed model has the advantage of expanding the network by adding the units during the partitioning of the input space while other models have the network topology specified. The result is compared with that of ID3, which is known as a knowledge acquisition tool in machine learning. The comparison shows that the proposed model leads to a better correct rate. This improvement might result from the additional consideration of the optimal projection direction, which ID3 does not consider
  • Keywords
    knowledge acquisition; learning (artificial intelligence); neural nets; pattern recognition; Fisher´s linear discriminant function; ID3; knowledge acquisition tool; machine learning; n-class pattern classification; network topology; partitioning; pattern classifying neural nets; Computer science; Hypercubes; Intelligent networks; Knowledge acquisition; Linear discriminant analysis; Machine learning; Neural networks; Neurons; Pattern classification; Statistics;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 1992. IJCNN., International Joint Conference on
  • Conference_Location
    Baltimore, MD
  • Print_ISBN
    0-7803-0559-0
  • Type

    conf

  • DOI
    10.1109/IJCNN.1992.287098
  • Filename
    287098