A comparison of heuristic methods for polynomial regression model induction
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
Keywords:
Polynomial regression, model selection, heuristic search, state spaceHow to Cite
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Copyright (c) 2008 The Author(s). Published by Vilnius Gediminas Technical University.
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Copyright (c) 2008 The Author(s). Published by Vilnius Gediminas Technical University.
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This work is licensed under a Creative Commons Attribution 4.0 International License.