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Automatic Recurrent and Feed-Forward ANN Rule and Expression Extraction with Genetic Programming

  • Julian Dorado
  • Juan R. Rabuñal
  • Antonino Santos
  • Alejandro Pazos
  • Daniel Rivero
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2439)

Abstract

Various rule-extraction techniques using ANN have been used so far, most of them being applied on multi-layer ANN, since they are more easily handled. In many cases, extraction methods focusing on different types of networks and training have been implemented. However, there are virtually no methods that view the extraction of rules from ANN as systems which are independent from their architecture, training and internal distribution of weights, connections and activation functions. This paper proposes a ruleextraction system of ANN regardless of their architecture (multi-layer or recurrent), using Genetic Programming as a rule-exploration technique.

Keywords

Artificial Neural Network Genetic Programming Fuzzy Rule Rule Extraction Symbolic Regression 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Julian Dorado
    • 1
  • Juan R. Rabuñal
    • 1
  • Antonino Santos
    • 1
  • Alejandro Pazos
    • 1
  • Daniel Rivero
    • 1
  1. 1.Facultad InformáticaUniv. da CoruñaA CoruñaSpain

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