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[Feature]: Add priori of equation form #494
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Hi @prozhuyi, The current method for doing this is exemplified here: https://astroautomata.com/PySR/examples/#9-custom-objectives. An easier way to do this is being discussed here: MilesCranmer/SymbolicRegression.jl#193. (Help is always appreciated!) Cheers, |
@MilesCranmer Can SymbolicRegression.jl/issues/193 be used in pysr ? Is there this module in PySRRegressor ? |
@zhuyi-bjut this is something in development at the moment. It likely won’t be ready for at the very least a few months. In the meantime I would try the custom objectives and post on the discussions page with any issues you are running into. |
Hi Miles @MilesCranmer , When I implement constraints such as F = f ( x1, x2, x3 ) / g ( x4, x5 ), the regularization term is constructed to constrain the child nodes. However, when I deal with symbolic nodes, I construct constraints according to PySR/examples/#9-custom-objectives : it actually forces prediction to be equal to f1 / g1, but does not pass ' / ' to loss. Therefore, in subsequent processing, it may be necessary to manually replace other symbols with ' / '. I wonder whether it is possible to constrain the symbol node to be equal to a certain symbol, such as tree.l = = ' / ', just like using the regularization term to constrain the child node. Can similar functions be implemented in the loss item ? |
Assuming that |
Feature Request
Hi!When I want to find some expressions from my data, I want his form to be specific. For example, I hope that the equation form obtained by pysr is C1 * x1 + ( C2 * x2 / F ), where F is the term to be found, C1 and C2 are constants to be found. This is equivalent to the form of a constrained expression tree, that is, adding a priori. Is it possible for today 's pysr to implement this function ?
Thanks!
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