I'm using the randomforest package to classify my dataset of continuous variables grouped into four categories (a, b, c, d). Using the varImp() and importance() functions I can get the class-specific and overall permutation variable importance. I would like to find out which of my variables provide the greatest separation between two and two groups - i.e. which variables have the highest variable importance for separating between group a and group c. I've come across the varImpGroup() function in RFgroove, but this seems to be directed at variable importance for a subset of variables instead of groups.

Is there a way to produce the variables importance for pairwise comparisons of groups, without having to run the classification separately for only two groups at a time?