I have to perform predictive model over the dataset $D$ (with 1000 obs). From $D$, I extract 700 obs for training $(T)$ and 300 obs for validation $( V )$.
I need to perform bootstrap or 10-fold cross validation sampling.
The question is which of these sets should I use?
Divide $D$ in 10 subsets and alternate training and validation between them ?
Divide $T$ (the training subset) in 10 subsets and perform training/validation on those subsets? $V$ is used only for final validation.