• DocumentCode
    1556480
  • Title

    Neural network ensembles

  • Author

    Hansen, Lars Kai ; Salamon, Peter

  • Author_Institution
    Dept. of Math. Sci., San Diego State Univ., CA, USA
  • Volume
    12
  • Issue
    10
  • fYear
    1990
  • fDate
    10/1/1990 12:00:00 AM
  • Firstpage
    993
  • Lastpage
    1001
  • Abstract
    Several means for improving the performance and training of neural networks for classification are proposed. Crossvalidation is used as a tool for optimizing network parameters and architecture. It is shown that the remaining residual generalization error can be reduced by invoking ensembles of similar networks
  • Keywords
    learning systems; neural nets; pattern recognition; classification; crossvalidation; neural networks; pattern recognition; performance; residual generalization error; training; Computer architecture; Data mining; Databases; Fault tolerance; Feedforward systems; Neural networks; Neurons; Pattern recognition; Performance analysis; Supervised learning;
  • fLanguage
    English
  • Journal_Title
    Pattern Analysis and Machine Intelligence, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0162-8828
  • Type

    jour

  • DOI
    10.1109/34.58871
  • Filename
    58871
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1556480