Support predicting Y on test set X
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Description
Currently the Orthogonal Random Forest module only supports giving the treatment effects of n treatment on the test set X_test. It would be helpful if there is a method to get the predicted Y of X_test for each treatment, including the control group. So an array of (n+1) columns is returned. Thanks!
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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 by locating the Orthogonal Random Forest module and its existing method for treatment effects on X_test. Trace how treatments and the control group are represented, then identify the tests covering predictions. Done means a method returns an (n+1)-column array of predicted Y values for X_test, including control, with corresponding test coverage.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 30/100