Symbolic-Regression Boosting
This work offers a simple add-on method to enhance symbolic regressors, which is incremental but beneficial for practitioners in regression tasks.
The authors tackled the problem of improving symbolic regression performance by integrating boosting stages, achieving statistically significant improvements on 98 regression datasets with just 2-5 boosting stages.
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.