Questions regarding DRPolicyForest results
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Description
Hi, thanks for the great ci library.
I'm using DRPolicyForest and facing some issue.
model = DRPolicyForest(...)
Question 1: model's predict_value() and predict_proba() are returning different rankings between treatments.
- for example, predict_value() for T2 is higher for some records, but predict_proba() for T1 is higher.
I thought they return the same rankings (order of magnitude), but they aren't.
How should I interpret this?
Question 2: model's predict() method returns zero values for Treatment=0 (control). However, if I draw a plot, model.plot(), there is a None Treatment(T=0) leaf with numerous samples.
Why do they return different results?
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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 DRPolicyForest predict_value(), predict_proba(), predict(), and plot() entry points, then reproduce both reported discrepancies. Done means explaining the differing treatment rankings and the Treatment=0/None leaf behavior, or identifying a confirmed defect with a focused fix and regression test.
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Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100