can any moses gurus comment on using the diversity scoring options? for some bioinformatics work we are more interested in evolving a minimal ensemble of models to maximally represent the patterns distinguishing two sample sets rather than just maximizing out of sample prediction accuracy. in other words, we want to maximize the number of unique features in a model ensemble of a given size and accuracy. more generally, are there procedures for choosing optimal ensemble models beyond combining the top n models from different cross-validation runs?
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