take the training set and split it again into a training subset and a testing subset. Then we can build models on this training subset and pick the best model based on this testing subset. Let’s call the former the sub-training set and the latter the validation set for clarity. The validation set is separate from the final test set, on which we are never going to make any modeling decisions. This procedure is often called nested holdout testing.
Holdout testing
