• DocumentCode
    2723982
  • Title

    JackKnife method for validating neural network models

  • Author

    Allred, L.G.

  • Author_Institution
    Ogden Air Logistics Center, Hill Air Force Base, UT
  • fYear
    1991
  • fDate
    8-14 Jul 1991
  • Abstract
    Summary form only given. Most methods for validating neural networks rely on the exclusion of a portion of the data throughout a portion or all of the network training process. This approach can be somewhat wasteful, particularly when the cost of samples can exceed a million dollars each. It is suggested that a more appropriate (and efficient) validation method is the JackKnife method. Although the JackKnife method was developed to validate statistical estimation procedures, it is equally applicable to the process of validating the performance of a neural network
  • Keywords
    neural nets; JackKnife method; network training process; neural network models validation; performance; Costs; Logistics; Neural networks;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 1991., IJCNN-91-Seattle International Joint Conference on
  • Conference_Location
    Seattle, WA
  • Print_ISBN
    0-7803-0164-1
  • Type

    conf

  • DOI
    10.1109/IJCNN.1991.155456
  • Filename
    155456