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ALICE

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2021年5月

As computing systems are more frequently and more actively intervening in societally critical domains such as healthcare, education and governance, it is critical to correctly predict and understand the causal effects of these interventions. Without an A/B test, conventional machine…

Github for DoWhy: A library for causal inference

2019年7月

EconML is a Python package for estimating heterogeneous treatment effects from observational data via machine learning. This package was designed and built as part of the ALICE project at Microsoft Research with the goal to combine state-of-the-art machine learning techniques…

Github for EconML: A Python Package for ML-Based Heterogeneous Treatment Effects Estimation