Performing and testing principal component and hierarchical cluster analysis
Actually if we're wanting to select most extreme models to represent quadrants, that's different than selecting most dissimilar pairs. For that we'll want to take the mean and calculate center point then for each quadrant the model with greatest distance from it
That will work for standard RCF, if we're wanting to select indiv models for deep dives, will want to look into more robust methods