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@@ -39,10 +39,26 @@ To use causal-learn, we could install it using [pip](https://pypi.org/project/sq
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pip install causal-learn
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```
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# Documentation
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Please kindly refer to [causal-learn Doc](https://causal-learn.readthedocs.io/en/latest/) for detailed tutorials and usages.
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# Running examples
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For search methods in causal discovery, there are various running examples in the **‘tests’** directory, such as TestPC.py and TestGES.py.
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For the implemented modules, such as (conditional) independent test methods, we provide unit tests for the convenience of developing your own methods.
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# Benchmarks
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For the convenience of our community, [CMU-CLeaR](https://www.cmu.edu/dietrich/causality) group maintains a list of benchmark datasets including real-world scenarios and various learning tasks. Please refer to the following links:
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*[https://github.com/cmu-phil/example-causal-datasets](https://github.com/cmu-phil/example-causal-datasets) (maintained by Joseph Ramsey)
Please feel free to let us know if you have any recommendation regarding causal datasets with high-quality. We are grateful for any effort that benefits the development of causality community.
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