(Solved): Please write it clearly and precisely, thanks! 10 class o class 1 9 8 7 6 5 4 3 2 1 1 2 3 4 5 6 7 8 ...

10 class o class 1 9 8 7 6 5 4 3 2 1 1 2 3 4 5 6 7 8 9 10 Figure 1: Data for Neareset Neighbour classification Consider k-Nearest Neighbour (kNN) classification on the dataset given in Fig. 1 using Euclidean distance. Recall, in kNN, we assign the label to a test point based on the majority class of k nearest training points. Note: • The point can not be neighbour of itself. • Consider all the given data points for training. • In cases where two points have same distance, consider all the neighbours for majority voting even if the total number of neighbour exceed k. • The ties are resolved in favor of class 1. 2.1 What is the training error of 1-NN and 2-NN classifiers? Explain your calculations.