Diviyan Kalainathan
Diviyan Kalainathan
Hello @MAX00008888, There are two distinct things : - cdt.data that generates/provides data with the ground truth - cdt.causality methods, which goal is to find the ground truth graph that...
Yes, GES aims at producting the same graph as the one that generated your data (here `batch.next_observations.cpu().numpy()`) ; it tries to find causal relationships between the columns of your data....
Hi, Sadly, the causal methods try to find the true graph of the data (or the markov equivalence class - check out CPDAG), and more often than not, the assumptions...
Hello! You're welcome! I'll just keep this issue open to add the scores in the development roadmap
Hello ! Sorry about this issue, it is linked to #66 and I will definitely fix and update the SAM code (the paper had a few modifications recently) Best, Diviyan
Hi, the model has been updated/fixed, could you try again?
Hello ! Sorry for the delayed answer, did you try changing the independence test for one fit for discrete values ? Here is the doc on the available tests: https://fentechsolutions.github.io/CausalDiscoveryToolbox/html/causality.html#bnlearn-based-models...
Hello, Sorry, error in the implementation ! I just checked, I'll fix this ASAP Best, Diviyan
Hi, The fix is pushed to the github repo, but I need to migrate the CI to CircleCI to be able to push to PyPi/dockerhub Best, Diviyan
Yes the package isn't updated on pypi, I'll do it asap! Le ven. 10 juin 2022, 05:41, XMAHA ***@***.***> a écrit : > I use "m = GS(score='cor')", still got...