Passing domain knowledge

[dg46]

I am planning to get rid of Java dependencies in cause2e by replacing py-causal with causal-learn for the discovery step.

However, my applications require passing domain knowledge in the form of required or forbidden edges in the causal graph. Py-causal and Tetrad have a great interface for domain knowledge. Will this be included in causal-learn, too? In the docs, I have only found possibilities for LiNGAM-type models, but not for GES or PC.

Thanks for finally translating Tetrad to Python!

[dg46]

Oops, found it for PC. Must have overlooked it, sorry. I will try this out, but it would still be helpful to have the functionality for other algorithm types.

[kunwuz]

Thanks for your feedback. Cause2e is a fantastic package! :)

In the future, we will include 'background_knowledge' for other methods. We will update you when these functions are available. Thanks for your interest in causal-learn!

[dg46]

Thanks a lot for the quick reply, sounds great!

[kunwuz]

Hi @dg46, just a quick update :) We've re-implemented FCI. Now it includes the background_knowledge. Also, the speed of FCI has been improved a lot.

[dg46]

Thank you for the update, I will give it a try!