[PNE-6511] Expose feature effects generation. #983
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At present, the backend will automatically generate feature effects upon successful training. However, that means old models lack them. Additionally, there may be circumstances where regenerating the values may be desired. The exposed endpoint will begin an asynchronous job which will generate new Shapley values, and replace the old ones.
anoto-moniz
commented
Jan 8, 2025
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| shapley = data.get("result") | ||
| if not shapley: | ||
| return data |
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There was a bug in the existing code which caused it to blow up if there was no result field, which would happen if either Shapley hadn't been run, or if the generation was in progress.
anoto-moniz
commented
Jan 8, 2025
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| self.session.put_resource(path, {}, version=self._api_version) | ||
| return self.get(uid, version=version) |
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The FeatureEffects object returned by the generate call will always be in progress and have no results yet. Additionally, as currently constructed, it doesn't provide an easy way to get the updated status: you'd have to retrieve the corresponding predictor, then call .feature_effects on it. So instead, this does the get automatically.
kroenlein
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Jan 8, 2025
anoto-moniz
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Jan 16, 2025
Revert "Merge pull request #983 from CitrineInformatics/feature/pne-6…
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At present, the backend will automatically generate feature effects upon successful training. However, that means old models lack them. Additionally, there may be circumstances where regenerating the values may be desired.
The exposed endpoint will begin an asynchronous job which will generate new Shapley values, and replace the old ones.
PR Type:
Adherence to team decisions