meta cost


Hello everyone.
I need to automatically obtain the fundamentals that underlie the making of a decision. The clearest way I have found is a decision tree but I have needed to improve its performance so I have inserted it into a metacost. As it is an assembled classifier I can not find a way to do it. That is, I can not find a way to show that part of the final model is impacting me in the prediction.
Any ideas?
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