Is it possible to use k-fold cross-validation with bootstrap forests model and standard least squares regression in JMP?
I have done the k-fold cross-validation with neural networks model, and I am looking for some methods which could use the same cross-validation, so that I can do model comparisons.
Would like to add we are experimenting with a new automated way to perform k-fold cv in the new XGBoost add-in for JMP Pro. If you have access to JMP Pro 15 and would like to try an early adopter version, please let me know. In addition, we are tentatively planning to have the add-in available in the JMP lab at Discovery Munich with JMP Pro 16 Early Adopter.
As I mentioned in your other discussion about the same topic, you might consider using AICc across all the candidate models. JMP Pro also provides a model comparison platform to assist you.