Thanks Miguel, I've set up my flow in the same way you've got above (except I partition my data before the start group node) and ran the score node. As expected, I get the rules used for every tree. What I'd like are the rules for the final bagged model. IE the rules selected for the final model by majority vote. When you run the score node, EM scores your validation and training datasets (if you use a partition node before the start groups node. not sure what it does without one), including adding a node ID. if this is the node ID from the final bagged model, than one could search for the features found in in the full dataset, note which levels are missing within each node ID, and reverse engineer the bagged rules. Am I thinking about this correctlly? Basically I'm looking to get the rules picked via majority vote. Thanks, Jon
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