Data Science, Machine Learning, Statistics, Open Source, Crossvalidation.
estimation of how our model will perform. So this basic train/test approach is better than the first approach. Still, it has an issue: it’s sensible to the selection of the test set. We could get lucky and select an easy test set causing an overly optimistic generalization error (or unlucky and