Is there a way to perform stratified cross validation when using the train function to fit a model to a large imbalanced data set? I know straight forward k fold cross validation is possible but my categories are highly unbalanced. I've seen discussion about this topic but no real definitive answer.
Thanks in advance.
There is a parameter called 'index' which can let user specified the index to do cross validation.