Recursive feature elimination (RFE) is a feature-selection strategy. It performs in two nested levels of cross-validation. First it tries to divide the training set into N folds. RFE puts one fold aside for testing the generalization and then trains itself with the remaining data.
In my case I only have two classes and would like to do RFE. The problem here is that, since there are only two classes, the algorithm can not put one aside and then train itself with the remaining folds (only one fold remains and training on single class is not sensible.)
I would be very much grateful if you could let me know what I could do here.