[ENH] Add online regressor support and River adapter#1068
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patelchaitany wants to merge 2 commits into
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[ENH] Add online regressor support and River adapter#1068patelchaitany wants to merge 2 commits into
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Add River adapter package (utils, clone, RiverRegressor) and a coerce_to_skpro_regressor helper. Introduce BaseOnlineRegressor and capability:pred_int tag; update BaseProbaRegressor to check pred_int for probabilistic methods.
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Nice! Though I think there is somet duplication going on.
- I think the new base class,
BaseOnlineRegressor, can be merged intoBaseProbaRegressor, there is no substantial added functionality. - The new jackknife-plus regressor can be merged into the existing one (the non-MAPIE regressor), simply add the
updatelogic.
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Reference Issues/PRs
#1066
What does this implement/fix? Explain your changes.
This PR adds the foundation for online regression in skpro, including a new regressor_online scitype and BaseOnlineRegressor with capability:update and capability:pred_int. It introduces the capability:pred_int tag and gates probabilistic prediction methods on regressors that do not support them. It also adds RiverRegressor as a point-prediction adapter for River models, with deepcopy-based cloning and coerce_to_skpro_regressor() for wrapping raw River estimators.
Does your contribution introduce a new dependency? If yes, which one?
No
What should a reviewer concentrate their feedback on?
Did you add any tests for the change?
Any other comments?
PR checklist
For all contributions
How to: add yourself to the all-contributors file in the
skproroot directory (not theCONTRIBUTORS.md). Common badges:code- fixing a bug, or adding code logic.doc- writing or improving documentation or docstrings.bug- reporting or diagnosing a bug (get this pluscodeif you also fixed the bug in the PR).maintenance- CI, test framework, release.See here for full badge reference
For new estimators
docs/source/api_reference/taskname.rst, follow the pattern.Examplessection.python_dependenciestag and ensureddependency isolation, see the estimator dependencies guide.