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Genetic Programming Theory and Practice X pp 139–154Cite as

Symbolic Regression Model Comparison Approach Using Transmitted Variation

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Part of the book series: Genetic and Evolutionary Computation ((GEVO))

Abstract

Model evaluation in symbolic regression generated by GP is of critical importance for successful industrial applications. Typically this model evaluation is achieved by a tradeoff between model complexity and R 2. The chapter introduces a model comparison approach based on the transmission of variation from the inputs to the output. The approach is illustrated with three different data sets from real industrial applications.

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Author information

Authors and Affiliations

  1. The Dow Chemical Company, Freeport, TX, USA

    Flor A. Castillo, Carlos M. Villa & Arthur K. Kordon

Authors
  1. Flor A. Castillo
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  2. Carlos M. Villa
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  3. Arthur K. Kordon
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Corresponding author

Correspondence to Flor A. Castillo .

Editor information

Editors and Affiliations

  1. Center for the Study of Complex Systems, University of Michigan, West Hall 323, Ann Arbor, 48109, Michigan, USA

    Rick Riolo

  2. Evolved Analytics Europe BVBA, Vossenlaan, Beerse, 2340, Belgium

    Ekaterina Vladislavleva

  3. , Department of Biochemistry and Molecular, The Pennsylvania State University, Wartik Laboratory, University Park, 16802, Pennsylvania, USA

    Marylyn D Ritchie

  4. , Institute for Quantitative, Dartmouth Medical School, Medical Center Drive, Lebanon, 03756, New Hampshire, USA

    Jason H. Moore

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Castillo, F.A., Villa, C.M., Kordon, A.K. (2013). Symbolic Regression Model Comparison Approach Using Transmitted Variation. In: Riolo, R., Vladislavleva, E., Ritchie, M., Moore, J. (eds) Genetic Programming Theory and Practice X. Genetic and Evolutionary Computation. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-6846-2_10

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  • DOI: https://doi.org/10.1007/978-1-4614-6846-2_10

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  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4614-6845-5

  • Online ISBN: 978-1-4614-6846-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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