Fix issues with sklearn 1.4 #1045
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DON'T MERGE YET. Some skorch tests fail with sklearn v1.4. This commit fixes them: 1. Inheritance structure of scorers seems to have changed. 2. classes_ attribute should always be numpy array 3. CalibratedClassifierCV only works with predict_proba being float64 To fix the latter, I'm now casting the output of predict_proba to float64. However, I'm not sure if this is a good idea, as it might break existing code. I'm just adding it in for now to check if the tests pass.
thomasjpfan
reviewed
Feb 8, 2024
For Python 3.8, an older sklearn version (1.3.2) is installed, which does not result in the test failing. Therefore, instead of requiring a strict xfail, make xfail optional.
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Hey @BenjaminBossan, I've just run into issues 2 and 3 from here. Is there likely to be a new skorch release including these soon, or would I be best to install from master to get the fixes for now? |
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@foster999 Good point, thanks. I also just tested scikit-learn 1.5.0 and this time around, there don't seem to be any regressions. Release will come very soon. |
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Excellent, thanks for the quick response! Shall keep my eyes peeled for a release 🚀 |
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@foster999 Release is out (v1.0.0 no less) |
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Thanks for the heads up @BenjaminBossan ❤️ |
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Some skorch tests fail with sklearn v1.4. This commit fixes them:
classes_attribute should always be numpy arrayCalibratedClassifierCVonly works with the output ofpredict_probabeing float64To fix the latter, I'm now casting the output of
predict_probato float64. However, I'm not sure if this is a good idea, as it might break existing code. I'm just adding it in for now to check if the tests pass.Update: So the tests pass. Regarding the issue with
CalibratedClassifierCVand float32, here are some suggestions:NeuralNetto optionally casty_probato float64.Personally, I'm in favor of 2.