Estimating test error from the training data alone: validation set, k-fold CV and LOOCV (n = 100)
new data set
The wrong and the right way: choosing predictors before or inside cross-validation (pure noise)
run 10 data sets
reset
The bootstrap: resample the one sample you have
1 resample
200 resamples
reset