> > +In terms of accuracy, LOO often results in poor estimation of the test error,

> I am not sure what it means to overfit the training data here. I would
> rather stay with the "has high variance as estimator of true error" and
> say that therefore k-fold is preferred. I'm sure @GaelVaroquaux has an
> opinion on this (and no time to voice it ^^).

I mostly agree with you on all points: I have an opinion, I agree on your
phrasing, and I have no time :).