A first approach to solve classification problems based on functional networks

  • Authors:

  • Rosa Eva Pruneda;Beatriz Lacruz;Cristina Solares

  • Affiliations:

  • University of Castilla-La Mancha Spain;University of Zaragoza Spain;University of Castilla-La Mancha Spain

  • Venue:
  • ICANN'05 Proceedings of the 15th international conference on Artificial neural networks: formal models and their applications - Volume Part II
  • Year:
  • 2005

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Abstract

In this paper the ability of the functional networks approach to solve classification problems is explored. Functional networks were introduced by Castillo et al. [1] as an alternative to neural networks. They have the same purpose, but unlike neural networks, neural functions are learned instead of weights, using families of linear independent functions. This is illustrated by applying several models of functional networks to a set of simulated data and to the well-known Iris data and Pima Indian data sets.