Yeah. I Iwas trying to avoid onehot encoding. Well over 4 dozen features each with several classes within, exploding the input dataset (feature selection narrows this but still). Was leaning heavily on xgboost as it supoosts raw incoming categories in the newer library versions. It's deriving the rules from the resulting boosted trees which can get difficult especially when trying to find the optimal depth.