Luc Rocher

Hi @kmundnic, thanks for the detailed reproducible example, highly appreciate! I don't think we stated that the method works with _missing_ data, but with incomplete samples (that is, a subsample...

Sorry for the late reply. At the moment, the MI matrix is computed here: https://github.com/cynddl/Discreet.jl/blob/904793f59e0dde96539dc986c597191a6be098fe/src/mutual_information.jl#L38 A simple trick would be, when iterating over couples of columns ``(x, y)``, to drop...

Thank you for reporting this issue. I'm happy to announce that it should soon work. I have a working update in https://github.com/computationalprivacy/CorrectMatch.jl/tree/upgrading-deps that now passes all the tests on Julia...

Hi @abesolberg, would you be able to test with the new release? This should be fixed now.

Could this be the normal output to expect for your datasets? The tests pass as usual for `individual_uniqueness`, so I'm hoping the code works well.

We're getting there, I just pushed a new version on the master branch. :) Seems like it now works on some architectures and not others: https://github.com/computationalprivacy/CorrectMatch.jl/actions/runs/2805373612

Thanks for the report @abesolberg! I'll try to have a look soon.

Hi @NikolaiKorti, thanks for your message. Could you please share a small reproducible code example for me to check and understand what you were expected from individual_uniqueness(·)?

You will get the result you expect using: ``` G = fit_mle(GaussianCopula, A; exact_marginal=true) ``` Without setting _exact_marginal_, the code tries to fit whatever distribution works best for each marginal,...

Spoke too soon! That won't work when the data doesn't match the domain, or if the order changes over time. And might not match the way the model calculates the...