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arXiv · 2002.11631

CausalML: Python Package for Causal Machine Learning

Huigang Chen·Totte Harinen·Jeong-Yoon Lee·Mike Yung·Zhenyu Zhao
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Abstract

CausalML is a Python implementation of algorithms related to causal inference and machine learning. Algorithms combining causal inference and machine learning have been a trending topic in recent years. This package tries to bridge the gap between theoretical work on methodology and practical applications by making a collection of methods in this field available in Python. This paper introduces the key concepts, scope, and use cases of this package.

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Huigang Chen, Totte Harinen, Jeong-Yoon Lee, Mike Yung, Zhenyu Zhao. 2020-02-25. CausalML: Python Package for Causal Machine Learning. https://arxiv.org/abs/2002.11631

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