• DocumentCode
    2021031
  • Title

    Interval-based neural networks for soft decisions

  • Author

    Nava, Patricia A.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Texas Univ., El Paso, TX, USA
  • Volume
    5
  • fYear
    2001
  • fDate
    2001
  • Firstpage
    3264
  • Abstract
    The performance of neural networks, when the training data is limited, can be improved by incorporation of interval techniques. These techniques improve performance by introducing the ability to classify imprecise data. Performance can be further improved by incorporating the ability to make soft decisions. Soft decisions differ from hard decisions by allowing the decision-making system the option of deferring to a human. This decision-rejection option has the effect of reducing the error rate of the decision-making system. The paper discusses three distinct techniques for making soft decisions and the performance of the interval-based neural network that utilizes these techniques
  • Keywords
    decision support systems; feedforward neural nets; fuzzy neural nets; fuzzy set theory; pattern classification; uncertainty handling; ANNs; artificial neural networks; decision-making system; decision-rejection option; error rate reduction; fuzzy systems; hard decisions; imprecise data classification; interval computation; interval techniques; interval-based neural networks; soft decisions; training data; Artificial neural networks; Character recognition; Computer networks; Decision making; Error analysis; Fuzzy systems; Humans; Neural networks; Testing; Training data;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, Man, and Cybernetics, 2001 IEEE International Conference on
  • Conference_Location
    Tucson, AZ
  • ISSN
    1062-922X
  • Print_ISBN
    0-7803-7087-2
  • Type

    conf

  • DOI
    10.1109/ICSMC.2001.972022
  • Filename
    972022