Why is the default n_trees=1000 in ForestDRLearner?
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Description
That seems rather large, especially as in CausalForestDML the default is n_estimators=100, and the ForestDRLearner with n_trees=1000 can take quite a while to fit. Also for example in XGBoost, also a tree method, the default number of trees is 100.
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Research direction
Start by locating the ForestDRLearner and CausalForestDML definitions and comparing their tree-count defaults. Check how ForestDRLearner's n_trees affects fitting time and whether documentation or tests encode the current value. Done means reaching a maintainer-supported default decision and updating the relevant behavior and references.
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Assessment
- Tech stack
- python
- Domain
- machine-learning, performance
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100