Symbolic-Regression Boosting
June 24, 2022 ยท Declared Dead ยท ๐ Genetic Programming and Evolvable Machines
"No code URL or promise found in abstract"
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Authors
Moshe Sipper, Jason H Moore
arXiv ID
2206.12082
Category
cs.NE: Neural & Evolutionary
Cross-listed
cs.LG
Citations
6
Venue
Genetic Programming and Evolvable Machines
Last Checked
4 months ago
Abstract
Modifying standard gradient boosting by replacing the embedded weak learner in favor of a strong(er) one, we present SyRBo: Symbolic-Regression Boosting. Experiments over 98 regression datasets show that by adding a small number of boosting stages -- between 2--5 -- to a symbolic regressor, statistically significant improvements can often be attained. We note that coding SyRBo on top of any symbolic regressor is straightforward, and the added cost is simply a few more evolutionary rounds. SyRBo is essentially a simple add-on that can be readily added to an extant symbolic regressor, often with beneficial results.
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