Partial derivative loss about pysr HOT 5 CLOSED

What specific part of their paper are you referring to? [for reference, their paper is my favorite all-time :) ]

from pysr.

yeah, in Figure.2 of the paper, they select the best equations by comparing predicted partial derivatives with numerical partial derivatives. In pysr, this is compare predicted value with train data value. So, I wonder if this method can be added to pysr.

from pysr.

Good idea. I was thinking about adding this but haven't yet. Would be really interesting to try. The fact that the backend of PySR is written in Julia makes this really easy since it already has autodiff setup!

from pysr.

Hi,Miles
I find some codes in LossFunction.jl, which is "(prediction, completion) = differentiableEvalTreeArray(tree, dataset.X, options)". what is I am interesting in whether it used to the Partial derivative loss. If it is, I am want to know how to used it. Thanks!

from pysr.

This should be doable now, with custom objective functions implemented: https://astroautomata.com/PySR/examples/#9-custom-objectives. (eval_diff_tree_array is the differential operator - see https://astroautomata.com/SymbolicRegression.jl/stable/api/#Derivatives).

Cheers,
Miles

from pysr.