For the data {(0,0), (1,0), (1,1), (0,5), (1,5), (5,5), (6,5), (6,4)} by taking k = 3. By taking the seed points to be the first three points, viz., (0,0), (1,0), and (1,1) employ k-means where pictorially you need to show the partition after each iteration. Please give your computations in the form of intermediate steps. perform clustering using both euclidean and Manhattan distance

Answer rating: 100% (QA)

The detailed answer for the above question is provided below KMeans Clustering Steps with Euclidean Distance Step 1 Initialization Given data points 00 10 11 05 15 55 65 64 Seed points 00 10 11 Step 2 ... View the full answer