Something I have noticed is that many users expect the result of .fit(X, y) to be converged for the default parameters, and are surprised that running it a second time results in a different equation. This is a reasonable assumption given that converged solutions are the typical behavior for other ML models or optimization routines!
So, I think the default behavior for PySR should be a bit more clear that "convergence" is not really well-defined for symbolic regression. Perhaps we could leave the same behavior, but basically show a warning to the user if niterations is not set explicitly, such as:
No stopping criteria given, so will exiting after 40 iterations. Increase `niterations` to search for longer.
This seems like a simple solution which would make it clear to users that they shouldn't expect the equations to be converged.
Something I have noticed is that many users expect the result of
.fit(X, y)to be converged for the default parameters, and are surprised that running it a second time results in a different equation. This is a reasonable assumption given that converged solutions are the typical behavior for other ML models or optimization routines!So, I think the default behavior for PySR should be a bit more clear that "convergence" is not really well-defined for symbolic regression. Perhaps we could leave the same behavior, but basically show a warning to the user if
niterationsis not set explicitly, such as:This seems like a simple solution which would make it clear to users that they shouldn't expect the equations to be converged.
We might also think about renaming
niterationstomax_iterationsto be more clear about this. We should make this in line with the other stopping criteria: https://astroautomata.com/PySR/api/#stopping-criteria