Given the matrix X whose rows represent different data points, you are asked to perform a k-means clustering on this dataset using the Euclidean distance as the distance function. Here k is chosen as 3 and distance function is the Euclidean function. All data in X are given below. The centers of 3 clusters were initialized as c1 = (6.2, 3.2), c2 = (6.6, 3.7) and c3 = (6.5, 3.0).

What are the final clusters after k-means converges?

Problem 4. Given the matrix X whose rows represent different data points, you are asked to perform a kmeans clustering on this dataset using the Euclidean distance as the distance function. Here Is is chosen as 3 and distance function is the Euclidean function. All data in X are given below. The centers of 3 clusters were initialized as cl = (62,32), (:2 = (6.6,3.7) and 03 = (65,30). 5.9 3.2 4.6 2.9 6.2 2.8 4.7 3.2 X = 5.5 4.2 5.0 3.0 4.9 3.1 6.7 3.1 5.1 3.8 6.0 3.0 What are the nal clusters after kIneans converges