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GECCO
2010
Springer

Robust symbolic regression with affine arithmetic

9 years 3 months ago
Robust symbolic regression with affine arithmetic
We use affine arithmetic to improve both the performance and the robustness of genetic programming for symbolic regression. During evolution, we use affine arithmetic to analyze expressions generated by the genetic operators, estimating their output range given the ranges of their inputs over the training data. These estimated output ranges allow us to discard trees that contain asymptotes as well as those whose output is too far from the desired output range determined by the training instances. We also perform linear scaling of outputs before fitness evaluation. Experiments are performed on 15 problems, comparing the proposed system with a baseline genetic programming system with protected operators, and with a similar system based on interval arithmetic. Results show that integrating affine arithmetic with an implementation of standard genetic programming reduces the number of fitness evaluations during training and improves generalization performance, minimizes overfitting, and co...
Cassio Pennachin, Moshe Looks, João A. de V
Added 02 Sep 2010
Updated 02 Sep 2010
Type Conference
Year 2010
Where GECCO
Authors Cassio Pennachin, Moshe Looks, João A. de Vasconcelos
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