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Solving Classification Problems Using Infix Form Genetic Programming

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Book cover Advances in Intelligent Data Analysis V (IDA 2003)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2810))

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Abstract

A new evolutionary technique, called Infix Form Genetic Programming (IFGP) is proposed in this paper. The IFGP individuals are strings encoding complex mathematical expressions. The IFGP technique is used for solving several classification problems. All test problems are taken from PROBEN1 and contain real world data. IFGP is compared to Linear Genetic Programming (LGP) and Artificial Neural Networks (ANNs). Numerical experiments show that IFGP is able to solve the considered test problems with the same (and sometimes even better) classification error than that obtained by LGP and ANNs.

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Author information

Authors and Affiliations

  1. Department of Computer Science, Faculty of Mathematics and Computer Science, Babeş-Bolyai University, Kogălniceanu 1, Cluj-Napoca, 3400, Romania

    Mihai Oltean & Crina Groşan

Authors
  1. Mihai Oltean
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  2. Crina Groşan
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Editor information

Editors and Affiliations

  1. Berkeley Initiative in Soft Computing (BISC), University of California at Berkeley, USA

    Michael R. Berthold

  2. Freie Universität Berlin, Garystr. 21, 14195, Berlin, Germany

    Hans-Joachim Lenz

  3. Department of Computer Science, University of Colorado, Boulder, Colorado, USA

    Elizabeth Bradley

  4. Otto-von-Guericke-University of Magdeburg, Germany

    Rudolf Kruse

  5. Department of Knowledge Processing and Language Engineering, University of Magdeburg, Universitätsplatz 2, 39106, Magdeburg, Germany

    Christian Borgelt

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© 2003 Springer-Verlag Berlin Heidelberg

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Oltean, M., Groşan, C. (2003). Solving Classification Problems Using Infix Form Genetic Programming. In: R. Berthold, M., Lenz, HJ., Bradley, E., Kruse, R., Borgelt, C. (eds) Advances in Intelligent Data Analysis V. IDA 2003. Lecture Notes in Computer Science, vol 2810. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45231-7_23

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  • DOI: https://doi.org/10.1007/978-3-540-45231-7_23

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-40813-0

  • Online ISBN: 978-3-540-45231-7

  • eBook Packages: Springer Book Archive

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