Symbolic-Regression Boosting

June 24, 2022 ยท Declared Dead ยท ๐Ÿ› Genetic Programming and Evolvable Machines

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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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