7. An extremal type of cross-validation is n-fold cross-validation on a training set of size n. If we want to estimate the error of k-NN, this amounts to classifying each training point by running k - NN on the remaining n1 points, and then looking at the fraction of mistakes made. It is commonly called leave-one-out cross-validation (LOOCV). Consider the following simple data set of just four points: What is the LOOCV error for 1-NN? For 3-NN