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[Feature Request] Arbitrary base learners for GradientBoostingRegressor/Classifier
See original GitHub issueDescribe the workflow you want to enable / Describe your proposed solution
add an base_estimator argument to GradientBoostingRegressor/Classifier and HistGradientBoostingRegressor/Classifier, allowing them to do gradient boosting on any sklearn base estimator that supports weights, while also supporting GradientBoostingRegressor like early stopping, custom objective functions, and early stopping.
Describe alternatives you’ve considered, if relevant
sklearn.ensemble.AdaBoostClassifier supports specifying an arbitrary base_estimator It’d be pretty cool to have that for GradientBoostingRegressor/Classifier and HistGradientBoostingRegressor/Classifier
Additional context
Issue Analytics
- State:
- Created 3 years ago
- Comments:19 (15 by maintainers)
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Sorry I hadn’t seen your comment, Zach. If there are compelling use cases, I think it would be reasonable to support, except that we have made it difficult to name this meta estimator when we have already used GradientBoostingClassifier.
Via the
Baseparameter. See documentation here. .Note their implementation is quite slow.