Hello, does anyone have experience with the R pacakge, SDMtune? I'm trying to use it to optimize my models in selecting the best hyperparameter configuration. I think I understand the basics of how it works. You get a base model with the default settings and then can test model space with the optimizeModel function. In the example in the R documentation though it gives one of the testing data being just a random 20% subset of the data. I'm wondering, can you use this technique on a dataset that is crossvalidated instead? Thanks in advance for any help and guidance.

Makani