I like the h2o.ai tool for ml. It is java but it is familiar and does a decent job.
Here is info about stratified splitting in general:
I have a variable that is strongly imbalanced, so I need R-gui based stratified splitting of my data on that variable, in h2o.ai. Is there a way to do it?
An R command for splitting data in the h2o.ai tool is this:
splits = h2o.splitFrame(mydata, ratios=myratio, destination_frames=...)
There is no option for stratification in the splitframe variable. The I know in the Flow (web interface to running java) tool they allow balanced classes in the cross-validated approach, so somewhere in there it is doing stratified splitting.
I hate to do this in base R because the memory handling in R is not as effective as in h2o.ai and my data sizes are large.