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Separation Surfaces through Genetic Programming

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Engineering of Intelligent Systems (IEA/AIE 2001)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2070))

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Abstract

The aim of this paper is to describe a study for the obtaining, symbolically, of the separation surfaces between clusters of a labelled database. A separation surface is an equation with the form ø; (x)=0, where ø is a function of R n → R. The calculation of function ø is begun by the development of the parametric regression by means of the use of the Genetic Programming. The symbolic regression consists in approximating an unknown function’s equation, through knowledge of certain points’ coordinates and the value that a function reaches with the same ones. This possibility was propose in [Koza92a] and its advantage in front of the classic statistical regressions is that it is not necessary previously to know the form the function. Once this surface is found, a classifier for the database could be obtained. The technique has been applied to different examples and the results have been very satisfactory.

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Authors and Affiliations

  1. Departamento de Lenguajes y Sistemas Informáticos, Av. Reina Mercedes s/n, 41012, Sevilla, Spain

    José C. Riquelme, Raúl Giráldez, Jesús S. Aguilar & Roberto Ruiz

Authors
  1. José C. Riquelme
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  2. Raúl Giráldez
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  3. Jesús S. Aguilar
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  4. Roberto Ruiz
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Editor information

Editors and Affiliations

  1. Hungarian Academy of Sciences, Intelligent Manufacturing and Business Processes Computer and Automation Research Institute, Kende utca 13-17, 1111, Budapest, Hungary

    László Monostori  & József Váncza  & 

  2. Department of Computer Science 601 University Drive, Southwest Texas State University, San Marcos, TX, 78666-4616, USA

    Moonis Ali

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© 2001 Springer-Verlag Berlin Heidelberg

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Riquelme, J.C., Giráldez, R., Aguilar, J.S., Ruiz, R. (2001). Separation Surfaces through Genetic Programming. In: Monostori, L., Váncza, J., Ali, M. (eds) Engineering of Intelligent Systems. IEA/AIE 2001. Lecture Notes in Computer Science(), vol 2070. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45517-5_47

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  • DOI: https://doi.org/10.1007/3-540-45517-5_47

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-42219-8

  • Online ISBN: 978-3-540-45517-2

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