10000 BaggingRegressor with **fit_params with CatBoostRegressor fit(..., eval_set= ()) · Issue #29591 · scikit-learn/scikit-learn · GitHub
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BaggingRegressor with **fit_params with CatBoostRegressor fit(..., eval_set= ()) #29591

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CoteDave opened this issue Jul 30, 2024 · 2 comments
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BaggingRegressor with **fit_params with CatBoostRegressor fit(..., eval_set= ()) #29591

CoteDave opened this issue Jul 30, 2024 · 2 comments
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@CoteDave
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Describe the issue linked to the documentation

How can we use the new **fit_params of the BaggingRegressor to add the eval_set of Catboost or LightGBM when calling the .fit() function ? The metadata routing documentation is incomplete about this !

Suggest a potential alternative/fix

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@CoteDave CoteDave added Documentation Needs Triage Issue requires triage labels Jul 30, 2024
@ogrisel
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ogrisel commented Aug 1, 2024

I don't think the metadata routing feature can be used to leverage extensions to the scikit-learn API in third party libraries.

However, I agree that we need a functional way to specify and route for early stopping validation sets in pipelines and other meta-estimators.

There are ongoing discussions and candidate implementation here:

@ogrisel ogrisel removed the Needs Triage Issue requires triage label Aug 1, 2024
@ogrisel
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ogrisel commented Aug 1, 2024

Let's close as duplicate.

@ogrisel ogrisel closed this as not planned Won't fix, can't repro, duplicate, stale Aug 1, 2024
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