scikit-learn / scikit-learn/scikit-learn
XGBRegressor is not working with wrapping `MultiOutputRegressor(StackingRegressor())` and `MultiOutputRegressor(VotingRegressor())`
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- Dominant language
- Python
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Description
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Describe the workflow you want to enable
XGBRegressor is working well with StackingRegressor() and VotingRegressor() but when I try MultiOutputRegressor(StackingRegressor()) and MultiOutputRegressor(VotingRegressor()) it return error: ValueError: The estimator XGBRegressor should be a regressor.
Could we upgrade the MultiOutputRegressor() for this case? Thanks!
Describe your proposed solution
upgrade the MultiOutputRegressor()
Describe alternatives you've considered, if relevant
No response
Additional context
No response
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by reproducing the reported workflow using MultiOutputRegressor with StackingRegressor and VotingRegressor around XGBRegressor, then inspect the estimator validation involved in the ValueError. Done should mean both wrapped workflows are accepted without the error and have regression tests covering them.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, scikit-learn
- Domain
- machine-learning
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Quiet
- Clarity
- Needs clarification
- Newbie friendliness
- 35/100