Authors: Erwin Stinstra Gijs Rennen Geert Teeuwen
Publish Date: 2007/05/03
Volume: 35, Issue: 4, Pages: 315-326
Abstract
The subject of this paper is a new approach to symbolic regression Other publications on symbolic regression use genetic programming This paper describes an alternative method based on Pareto simulated annealing Our method is based on linear regression for the estimation of constants Interval arithmetic is applied to ensure the consistency of a model To prevent overfitting we merit a model not only on predictions in the data points but also on the complexity of a model For the complexity we introduce a new measure We compare our new method with the Kriging metamodel and against a symbolic regression metamodel based on genetic programming We conclude that Paretosimulatedannealingbased symbolic regression is very competitive compared to the other metamodel approachesThis article is published under an open access license Please check the Copyright Information section for details of this license and what reuse is permitted If your intended use exceeds what is permitted by the license or if you are unable to locate the licence and reuse information please contact the Rights and Permissions team
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