Using ForestDMLCateEstimator for binary outcome
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Description
Hi all,
Am I able to use ForestDMLCateEstimator with a model that has a binary treatment and a binary outcome?
I read through the other conversation in https://github.com/microsoft/EconML/issues/204, but it appears to be more focused on the LinearDMLCateEstimator, and its unclear to me:
1: Whether the concern about the residuals also applies to the regression forest final stage.
2: Whether I also need to wrap the Y model in RegWrapper()
Thank you in advance!
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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 with the ForestDMLCateEstimator and RegWrapper entry points, then review the residual discussion in issue #204. Determine whether binary treatment and outcome are supported, whether the regression-forest final stage changes the residual concern, and whether RegWrapper is required; done means documenting clear answers for all three questions.
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Assessment
- Tech stack
- machine-learning, python
- Domain
- machine-learning
- Issue type
- Documentation
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100