First of all, I would like to thank you for setting up this website for reader like myself.
For "normal" validation, the aim is to estimate out of sample error for
a given hypothesis, which depends on D-train.
For cross validation, the aim seems to have changed to estimate out of sample error for
averaged hypothesis each trained with N-1 data points. Essentially, the estimates is about the expectation of out of sample error over all N-1 training set.
My question is how to resolve the inconsistency? Thank you.
Zhenlan,