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A comparison of heuristic methods for polynomial regression model induction

    Gints Jekabsons Affiliation
    ; Jurijs Lavendels Affiliation

Abstract

We compare four different heuristic methods for polynomial regression model induction. The methods are very different in their approaches. Our main concern in this study is in the differences of candidate model spaces the methods deal with (completely predefined versus non‐predefined), as well as search strategies used. We investigate the advantages and disadvantages of the approaches represented by the methods in terms of predictive error, complexity of the induced models and required computational resources. For empirical comparisons, we use twelve test problems.


First Published Online: 14 Oct 2010

Keyword : Polynomial regression, model selection, heuristic search, state space

How to Cite
Jekabsons, G., & Lavendels, J. (2008). A comparison of heuristic methods for polynomial regression model induction. Mathematical Modelling and Analysis, 13(1), 17-27. https://doi.org/10.3846/1392-6292.2008.13.17-27
Published in Issue
Mar 31, 2008
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