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Neural Networks, Clustering Techniques, and Function Approximation Problems

  • Jesús González
  • Ignacio Rojas
  • Héctor Pomares
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2415)

Abstract

To date, clustering techniques have always been oriented to solve classification and pattern recognition problems. However, some authors have applied them unchanged to construct initial models for function approximators. Nevertheless, classification and function approximation problems present quite different objectives. Therefore it is necessary to design new clustering algorithms specialized in the problem of function approximation.

Keywords

Cluster Algorithm Output Response Cluster Technique Target Function Output Variability 
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

  • Jesús González
    • 1
  • Ignacio Rojas
    • 1
  • Héctor Pomares
    • 1
  1. 1.Department of Computer Architecture and Computer Technology E.T.S. Ingeniería InformáticaUniversity of GranadaGranadaSpain

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