Thierry Moudiki looks at an R port of a Python package:
Keep in mind that this package is for Machine Learning hyperparameter tuning: the global minimum won’t always be found, but this isn’t an issue, since it means you aren’t overfitting the training set.
It’s ported the same way as nnetsauce for R was: with
uvto create an isolated Python virtual environment containing the PythonGPoptpackage, andreticulateto call into it from R. Every function in this R package is a thin wrapper that returns the underlying Python object; the general rule is: object accesses with.’s in Python are replaced by$’s in R.
Click through for the instructions and examples of how it works. H/T R-Bloggers.