Overfitting: A frequentist illusion?
	• If you do not have much data, you should use a simple model, because a complex one will overfit. – This is true. But only if you assume that fitting a model means choosing a single best setting of the parameters. – If you use the full posterior over parameter settings, overfitting disappears! – With little data, you get very vague predictions because many different parameters settings have significant posterior probability