Anthony Blaom, PhD

The problem is we are missing `logger` in the cloning of the resampling machine happening here: https://github.com/pebeto/MLJTuning.jl/blob/6f295b7439a9884fa35c16841ded33db2d272227/src/tuned_models.jl#L590

I think `CPUProcesses` should be fine, but we should add a test for this at MLJFlow.jl (and for `CPUThreads`).

Thanks for the addition. Sadly, this is still not working for me. I'm getting three experiments, with different id's and same name, "horse" on the server. (I'm only expecting one)....

Interestingly, I'm getting the same kind of error for `acceleration=Distributed`: ```julia using Distributed addprocs(2) nprocs() # 3 using MLJ using MLFlowClient logger = MLFlowLogger("http://127.0.0.1:5000", experiment_name="rock") X, y = make_moons() model...

Okay, see here for a MWE: https://github.com/JuliaAI/MLFlowClient.jl/issues/40

Revisiting this issue after a few months. It looks like the multithreading issue is not likely to be addressed soon. Perhaps we can proceed with this PR, after strictly ruling...

Thanks for the suggestion, but integration tests only test default values.

Thanks for this. This might potentially help, but, as mentioned earlier, I think we have sufficient models for testing MLJ integration. If you want, you could add the integration tests...

The [compat] bounds for SymbolicRegression now appear so out of date that a very old version is being loaded in integration tests, and the metadata of that old version is...

We may need to do something like that. Another possibility is to require each packages to run their own integration tests. The original idea was that a user could load...