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Ah, I've built a foot gun here - the predict method in fastprop automatically applies the feature scaling to its inputs, which is needed for inference when loading from a checkpoint but breaks the workflow in your case.
I've been hacking on the code and trying to modify model.train_and_test to return the predictions. I thought I could just put
in place of
However, the correlations I calculate from the values returned in pred are much lower than those returned in test_results. What am I missing?
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