• DocumentCode
    867688
  • Title

    Avoiding Pitfalls in Neural Network Research

  • Author

    Zhang, G. Peter

  • Author_Institution
    J. Mack Robinson Coll. of Bus., Georgia State Univ., Atlanta, GA
  • Volume
    37
  • Issue
    1
  • fYear
    2007
  • Firstpage
    3
  • Lastpage
    16
  • Abstract
    Artificial neural networks (ANNs) have gained extensive popularity in recent years. Research activities are considerable, and the literature is growing. Yet, there is a large amount of concern on the appropriate use of neural networks in published research. The purposes of this paper are to: 1) point out common pitfalls and misuses in the neural network research; 2) draw attention to relevant literature on important issues; and 3) suggest possible remedies and guidelines for practical applications. The main message we aim to deliver is that great care must be taken in using ANNs for research and data analysis
  • Keywords
    data analysis; neural nets; pattern classification; artificial neural network research; data analysis; pitfalls avoidance; Application software; Data analysis; Databases; Guidelines; Humans; Neural networks; Pattern recognition; Predictive models; Software packages; Statistics; Data; model building; model evaluation; neural networks; pitfalls; publication bias; software;
  • fLanguage
    English
  • Journal_Title
    Systems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1094-6977
  • Type

    jour

  • DOI
    10.1109/TSMCC.2006.876059
  • Filename
    4033002