My impression of what Eric means is that Bayesian model does not overfit, so you don’t need a testing set to evaluate overfitting problem. However, I think this is also under some context: you can surely have overfitting problem if your model is wrongly specified. It might be a bit more meaningful to think that under similar model complexity, a Bayesian model is more robust than a Frequensitic model.
(my two cents…)
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