Problem 1 (50 pts) Assume that following data points are given. Use Euclidean distance in your distance computations 9 4 ? ? i* 0 123 5618 a) Show two iterations of k-means clustering algorithm for these data points. Assume that k-3 and initial cluster means are (5,8) ; (4;3) ; (7,1). Give cluster means and cluster contents after each iteration. b) Show two iterations of k-medoid clustering algorithm for these data points. Assume that k-3 and initial cluster medoids are (5,8); (4;3); (7,1). Give cluster medoids and cluster contents after each iteration. c) Apply bottom-up hierarchical clustering algorithm for these data points using .Single linkage (nearest neighbor) Complete linkage Draw dendrogram graphs showing the sequence of how sub-clusters are merged together with the lifetime information (defined as the difference between the distances at two successive nodes). Problem 1 (50 pts) Assume that following data points are given. Use Euclidean distance in your distance computations 9 4 ? ? i* 0 123 5618 a) Show two iterations of k-means clustering algorithm for these data points. Assume that k-3 and initial cluster means are (5,8) ; (4;3) ; (7,1). Give cluster means and cluster contents after each iteration. b) Show two iterations of k-medoid clustering algorithm for these data points. Assume that k-3 and initial cluster medoids are (5,8); (4;3); (7,1). Give cluster medoids and cluster contents after each iteration. c) Apply bottom-up hierarchical clustering algorithm for these data points using .Single linkage (nearest neighbor) Complete linkage Draw dendrogram graphs showing the sequence of how sub-clusters are merged together with the lifetime information (defined as the difference between the distances at two successive nodes)