A Novel Genetic Programming Based Approach for Classification Problems

  • L. P. Cordella
  • C. De Stefano
  • F. Fontanella
  • A. Marcelli
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3617)

Abstract

A new genetic programming based approach to classification problems is proposed. Differently from other approaches, the number of prototypes in the classifier is not a priori fixed, but automatically found by the system. In fact, in many problems a single class may contain a variable number of subclasses. Hence, a single prototype, may be inadequate to represent all the members of the class. The devised approach has been tested on several problems and the results compared with those obtained by a different genetic programming based approach recently proposed in the literature.

Keywords

Genetic Programming Recognition Rate Production Rule Logical Expression Derivation Tree 
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 2005

Authors and Affiliations

  • L. P. Cordella
    • 1
  • C. De Stefano
    • 2
  • F. Fontanella
    • 1
  • A. Marcelli
    • 3
  1. 1.Dipartimento di Informatica e SistemisticaUniversità di Napoli Federico IINapoliItaly
  2. 2.Dipartimento di Automazione, Elettromagnetismo, Ingegneria dell’Informazione e Matematica IndustrialeUniversità di CassinoCassinoItaly
  3. 3.Dipartimento di Ingegneria dell’Informazione e Ingegneria ElettricaUniversità di SalernoFiscianoItaly

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