Designing multilayer perceptrons from nearest-neighbor systems

  • Authors:
  • S. G. Smyth

  • Affiliations:
  • BT Lab., Martlesham Heath

  • Venue:
  • IEEE Transactions on Neural Networks
  • Year:
  • 1992

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Abstract

Although multilayer perceptrons have been shown to be adept at providing good solutions to many problems, they have a major drawback in the very large amount of time needed for training (for example, on the order of CPU days for some of the author's experiments). The paper describes a method of producing a reasonable starting point by using a nearest-neighbor classifier. The method is further expanded to provide a method of `programming' the upper layer of any network assuming the lower layers already exist