Bugfix rscorer discrete outcome treatment #977
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Signed-off-by: maartenvanhooft <mjgvanhooft@gmail.com>
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Pull Request Overview
This PR fixes a bug where the discrete_outcome flag was not forwarded to RScorer in CausalForestDML.tune and adds a minimal test to ensure tuning and fitting succeed when both outcome and treatment are discrete.
- Pass
discrete_outcomeintoRScorerduring tuning. - Add a test that runs
tuneandfitwithdiscrete_outcome=Trueanddiscrete_treatment=True.
Reviewed Changes
Copilot reviewed 2 out of 2 changed files in this pull request and generated no comments.
| File | Description |
|---|---|
| econml/dml/causal_forest.py | Included discrete_outcome=est.discrete_outcome in RScorer instantiation within tune. |
| econml/tests/test_dml.py | Added test_causal_forest_tune_with_discrete_outcome_and_treatment to verify no errors when both flags are true. |
Comments suppressed due to low confidence (1)
econml/tests/test_dml.py:1304
- [nitpick] The new test does not include any assertions to verify the estimator's behavior. Consider adding checks—for example, assert that the internally inferred outcome dimension (
est._d_y) matches the expected number of classes or that callingest.effect(X)returns an array of the correct shape—to ensure discrete flags are honored.
def test_causal_forest_tune_with_discrete_outcome_and_treatment(self):
kbattocchi
approved these changes
Jun 6, 2025
carl-offerfit
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Jul 7, 2025
Signed-off-by: maartenvanhooft <mjgvanhooft@gmail.com> Signed-off-by: Carl Gold <carl.goldd@braze.com>
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Issue #875
Changes:
discrete_outcomeflag to RScorer. As a result, it gets initiated by it's default valueFalse, which is unintended behaviour if we wantdiscrete_outcome=TrueFirst contribution here, please review critically for any mistakes or inconsistencies!
I see that the CI pipeline awaits approval. I think I did everything that is expected from me, so I'll mark it as ready for review. But perhaps the pipeline flags something.