MLBazaar/BTB

Should we consider adding bayesmark to the benchmarking suite

kveerama opened this issue · 1 comments

The bayesmark package is another wrapper hyper parameter tuning library. We can add this to our benchmarking suite. Per their documentation, they wrap around:

The builtin optimizers are wrappers on the following projects:

    HyperOpt
    Nevergrad
    OpenTuner
    PySOT
    Scikit-optimize

https://github.com/uber/bayesmark/

And we already benchmark against HyperOpt. Note that OpenTuner is a previous package developed at MIT in 2014.

We have in the past tried Nevergrad. Alternatively, we can just add Nevergrad, Scitkit-optimize and PySOT individually.