Question 11: The k-nearest neighbor model can be used both for regression and classification. True/False?

Question 13: In the k-means clustering algorithm, depending on how the initial cluster centers are chosen, the algorithm might not converge to a solution. True/False? Question 14: Given a dataset }D={0,2,4,6,24,26}, initialize the k-means clustering algorithm with 2 cluster centers 1 = 3 and 2 = 4. What are the values of 1 and 2 after the first iteration of k-means? What are the values of 1 and 2 after the second iteration of k-means? (Question 15: The k-means algorithm will always find the global minima. True/False?

12. (5 points) The loss function of the k-means clustering algorithm is given by L=N1i=1Nk=1Kzi,kxik2, where K is the number of clusters being sought, zi,k{0,1} is a binary indicator variable indicating whether xi is assigned to cluster k(zi,k=1) or not (zi,k=0). Given the values of zi,k,i,k, how will you compute k ? Explain your algorithm for computing k in no more than 3-4 lines and also write the expression for k