I am using an x-learner (and doubly robust learner as well) for uplift modeling. I have a control group and 10 treatments. To start, I have just be creating one x-learner and passing it all the treatments. But now I'm thinking -- would it be better to have 10 separate x-learners, each modeling a different treatment against the control? What are advantages/disadvantages to one metalearner with all the treatments thrown in vs. 10 metalearners with one per treatment?

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