My collection of causal inference algorithms built on top of accessible, simple, out-of-the-box ML methods, aimed at being explainable and useful in the business context
Hello, first of all, thanks for making the code available!
I am having trouble reproducing your example. As you can see in this notebook https://github.com/millengustavo/causality/blob/master/examples/causal_diagrams.ipynb, I copied the definition code of the classes present in init.py from your repository and tried to apply it in the same dataset generated by fklearn. However, I obtained different results in the "observational" data. The performance was quite different.
Could you point me to the reason? I tested with different sample sizes without success.