uber/causalml

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Uplift modeling and causal inference with machine learning algorithms

Stars: 6k
Forks: 877
Open beginner issues: 0
Indexed issues: 11

Dominant language: Python
License: No license data
Last GitHub push: Aug 20, 2026
Latest indexed: Sep 19, 2026
Contributing guide: Contributing guide
Code of conduct: Code of conduct
Beginner labels: No beginner labels indexed
PR merge metrics: No merged PRs in 30d

Beginner friendly Everything

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11 open issues indexed

Error to import causal forest regressor Open

bug

Difficulty 3/5 1-2 days Newbie friendliness 45/100

uber/causalml#1048 · 1 comment · Opened Sep 10, 2026
mape silently returns NaN when all targets are near-zero (empty filtered slice) Open

Difficulty 3/5 1-2 days Newbie friendliness 68/100

uber/causalml#1047 · Opened Sep 10, 2026
GradientBoostedPropensityModel early-stopping split ignores random_state and is not stratified Open

Difficulty 2/5 1-3 hours Newbie friendliness 88/100

uber/causalml#1045 · Opened Sep 4, 2026
cate_scoring default learner is oversized for its own per-fold, per-arm call pattern Open

enhancement

Difficulty 4/5 3-5 days Newbie friendliness 48/100

uber/causalml#1037 · 1 comment · 1 reaction · Opened Aug 20, 2026
S-, T- and X-learner bootstrap confidence intervals are not reproducible Open

bug

Difficulty 4/5 3-5 days Newbie friendliness 52/100

uber/causalml#1036 · 1 comment · Opened Aug 20, 2026
Normalize meta-learner random_state handling through check_random_state Open

refactoring

Difficulty 3/5 1-2 days Newbie friendliness 68/100

uber/causalml#1035 · 1 comment · Opened Aug 20, 2026
rlearner_score still requires outcome_learner while its siblings default to LightGBM Open

enhancement

Difficulty 2/5 1-3 hours Newbie friendliness 78/100

uber/causalml#1034 · 1 comment · 1 reaction · Opened Aug 20, 2026
sklearn metadata routing: let `treatment` reach a learner inside a Pipeline Open

enhancement

Difficulty 4/5 3-5 days Newbie friendliness 55/100

uber/causalml#986 · 7 comments · Opened Jul 31, 2026
Flip every signature to `(X, y, treatment, ...)` and delete the deprecation shim Open

enhancement refactoring

Difficulty 5/5 Over a week Newbie friendliness 25/100

uber/causalml#985 · 1 comment · Opened Jul 31, 2026
Adopt the scikit-learn `fit(X, y, treatment, ...)` argument order (v1.0 M1) Open

enhancement refactoring

Difficulty 5/5 Over a week Newbie friendliness 45/100

uber/causalml#980 · Opened Jul 31, 2026
CausalML is not compatible with Scikit-Learn Pipeline Open

enhancement

Difficulty 4/5 3-5 days Newbie friendliness 48/100

uber/causalml#854 · 2 comments · 1 reaction · Opened Oct 24, 2025

uber/causalml

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