Causal-Learn: Causal Discovery in Python
Abstract
Causal discovery aims at revealing causal relations from observational data, which is a fundamental task in science and engineering. We describe causal-learn, an open-source Python library for causal discovery. This library focuses on bringing a comprehensive collection of causal discovery methods to both practitioners and researchers. It provides easy-to-use APIs for non-specialists, modular building blocks for developers, detailed documentation for learners, and comprehensive methods for all. Different from previous packages in R or Java, causal-learn is fully developed in Python, which could be more in tune with the recent preference shift in programming languages within related communities. The library is available at https://github.com/py-why/causal-learn.
Cite
Text
Zheng et al. "Causal-Learn: Causal Discovery in Python." Machine Learning Open Source Software, 2024.Markdown
[Zheng et al. "Causal-Learn: Causal Discovery in Python." Machine Learning Open Source Software, 2024.](https://mlanthology.org/mloss/2024/zheng2024jmlr-causallearn/)BibTeX
@article{zheng2024jmlr-causallearn,
title = {{Causal-Learn: Causal Discovery in Python}},
author = {Zheng, Yujia and Huang, Biwei and Chen, Wei and Ramsey, Joseph and Gong, Mingming and Cai, Ruichu and Shimizu, Shohei and Spirtes, Peter and Zhang, Kun},
journal = {Machine Learning Open Source Software},
year = {2024},
pages = {1-8},
volume = {25},
url = {https://mlanthology.org/mloss/2024/zheng2024jmlr-causallearn/}
}