i need it done manually not by code.

Question #6: K-Means Clustering [15 Points) Use the k-means algorithm and Euclidean distance to cluster the following 8 examples into 3 clusters: P1=(2,10), P2=(2,5), P3=(8,4), P4=(5,8), P5= (7,5), P6= (6,4), P7=(1,2), P8=(4,9). The distance matrix based to be used on the basis of Euclidean distance is given below: P1 P2 P3 P4 P5 P6 P7 P8 P1 P2 P3 P4 P5 P6 P7 P8 Suppose that the initial seeds (centers of each cluster) are P1, P3 and P8. Run the k-means algorithm for 1 epoch only. At the end of this epoch show: A. The new clusters (i.e. the examples belonging to each cluster) B. The centers of the new clusters C. Draw a 10 by 10 space with all the 8 points and show the clusters after the first epoch and the new centroids. D. How many more iterations are needed to converge? Draw the result for each epoch