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Construction of Bayesian support vector regression in the feature space spanned by Bezier-Bernstein polynomial functions

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Abstract

Ill-posed inverse problems of recovering nonlinear dependencies in observational data are considered. An inductive method is developed for construction of a Bayesian model of support vector regression in Bernstein form. A new Bayesian evidence criterion is used to compare the adequacy of models.

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Authors and Affiliations

  1. Institute of Program Systems, National Academy of Sciences of Ukraine, Kiev, Ukraine

    O. Yu. Mytnik

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  1. O. Yu. Mytnik
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Translated from Kibernetika i Sistemnyi Analiz, No. 4, pp. 179–188, July–August 2007.

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Mytnik, O.Y. Construction of Bayesian support vector regression in the feature space spanned by Bezier-Bernstein polynomial functions. Cybern Syst Anal 43, 613–620 (2007). https://doi.org/10.1007/s10559-007-0087-x

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  • DOI: https://doi.org/10.1007/s10559-007-0087-x

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