  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.
