Problem 2: (9 points) Nearest Neighbor Classification 0.4 0.6 1.4 2.7 3.2 4.1 4.6 4.8 Given the above data with one scalar feature r (whose values are given below each data point) and a class variable y e {-1, +1), with filled circles indicating y = +1 and squares y =-1 (the sign is also shown above each data point for redundancy), we use a k-nearest neighbor classifier to perform prediction; in the case of ties, we prefer class -1. Answer the following: (a) Compute the training crror rate of a 1-Nearest-Ncighbor classifier trained on these data. (b) Compute the leave-one-out cross-validation error rate of a 1-Ncarest-Neighbor classifier on these data. (c) Compute the training error for a 3-Nearest-Neighbor classifier on these data