causal-learn Python Package
Project description
causal-learn: Causal Discovery for Python
causal-learn is an open-source causal discovery library for Python, which is a Python translation and extension of Tetrad.
The package is on its very first version and we are actively developing it. Please, as a beta user, if you are willing, would you please kindly share any feedbacks (issues, suggestions, etc.) about it with us?
Package Overview
Our causal-learn implements methods for causal discovery:
- Constrained-based causal discovery methods.
- Score-based causal discovery methods.
- Causal discovery methods based on constrained functional causal models.
- Hidden causal representation learning.
- Granger causality.
- Multiple utilities for building your own method, such as independence tests, score functions, graph operations, and evaluations.
Install
causal-learn needs the following packages to be installed beforehand:
- python 3
- numpy
- networkx
- pandas
- scipy
- scikit-learn
- statsmodels
- pydot
(For visualization)
- matplotlib
- graphviz
To use causal-learn, we could install it using pip:
pip install causal-learn
Documentation
Please kindly refer to causal-learn Doc for detailed tutorials and usages.
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