Considering the K-means algorithm, after current iteration, we have 4 centroids: Centroid of cluster 1 (0, 1) Centroid of cluster 2 (2, 2) Centroid of cluster 3 (-3, 4) Centroid of cluster 4 (3, -1) Using Manhattan Distance defined as: Manhattan Distance between P(x, ) and P2(x2, y2)xx2lly1-y2l Assign the point P1 (-2, -3) to its corresponding cluster