Problem 1 (10 points). The k-means algorithm, which we discussed in the class, is being run on a small two-dimensional dataset. After a certain number of iterations, you have two clusters as shown below: ID X y Cluster a 3 4 Cluster 1 b 3 7 Cluster 1 5 6 Cluster 1 d 6 4 Cluster 2 e 7 6 Cluster 2 f 8 5 Cluster 2 g 9 7 Cluster 2 Run one more iteration of the k-Means clustering algorithm and show the two clusters at the end of the iteration. Use Manhattan distance when calculating the distance between objects.