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Should we consider adding bayesmark to the benchmarking suite
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.