Perform a hierarchical clustering of the one-dimensional set of points 1, 4, 9, 16, 25, 36, 49, 64, 81, assuming clusters are represented by their centroid (average), and at each step the clusters with the closest centroids are merged. (show each step) 1,4 -> 2.5 2.5, 9 -> 4.67 16, 25 -> 20.5 36, 49 -> 42.5 4.67, 20.5 -> 11 64, 81 -> 72.5 42.5, 72.5 -> 57.5 11, 57.5 -> 31.67 Jcluster 16 25 36 49 64 81 centroid distance 16 7. 25 36 49 13 64 81 17 11 15 cluster centroid distance 14 2.5 15 25 36 49 64 81 16 25 36 11 49 13 64 15 81 17 16 custer centroid distance 149 4.66666667 25 36 49 64 16 11.3333333 25 36 11 49 13 64 15 81 17 cluster centroid distance L49 15,25 20.5 15.8333333) 36 49 64 81 4.66666667 36 49 64 81 15.5 13 15 17 cluster 149 16,25 36,49 54 centroid 4.66656667 20.5 425 64 81 17 distance 15.8333333 22 21.5 custer LA9,16.25 36,49 64 centroid distance 11 425 315 64 215 17 cluster LA9,1625 3649 centroid 11 425 72.5 30 distance 31.5 149,16,25 36,48.64,81 cluster centraid distance 11 57.5 46.5 cluster LAS,16,25,,4864,81