0.12.0 (Jan 2022)

CausalML surpassed 637K downloads on PyPI and 2,500 stars on Github!
We have 4 new community contributors, Luis (@lgmoneda ), Ravi (@raviksharma), Louis (@LouisHernandez17) and JackRab (@Jackrab). Thanks for the contribution!
We refactored and speeded up UpliftTreeClassifier/UpliftRandomForestClassifier by 5x with Cython (#422 #440 by @jeongyoonlee)
We revamped our API documentation, it now includes the latest methodology, references, installation, notebook examples, and graphs! (#413 by @huigangchen @t-tte @zhenyuz0500 @jeongyoonlee @paullo0106)
Our team gave talks at 2021 Conference on Digital Experimentation @ MIT (CODE@MIT), Causal Data Science Meeting 2021, and KDD 2021 Tutorials on CausalML introduction and applications. Please take a look if you missed them! Full list of publications and talks can be found here.

Updates

Update documentation on Instrument Variable methods @huigangchen (#447)
Add benchmark simulation studies example notebook by @t-tte (#443)
Add sample_weight support for R-learner by @paullo0106 (#425)
Fix incorrect binning of numeric features in UpliftTreeClassifier by @jeongyoonlee (#420)
Update papers, talks, and publication info to README and refs.bib by @zhenyuz0500 (#410 #414 #433)
Add instruction for contributing.md doc by @jeongyoonlee (#408)
Fix incorrect feature importance calculation logic by @paullo0106 (#406)
Add parallel jobs support for NearestNeighbors search with n_jobs parameter by @paullo0106 (#389)
Fix bug in simulate_randomized_trial by @jroessler (#385)
Add GA pytest workflow by @ppstacy (#380)