Use the k-means algorithm and Euclidean  distance to cluster the following 10 examples into 3 clusters:

Assume  that the initial clusters are A, E and H. 

Pt	X1	X2
A	1	2
B	8	5
C	4	9
D	2	4
E	9	7
F	5	9
G	3	5
H	6	9
I	4	4
J	7	9

a Develop a 10x10  distance metric for the above dataset.

b. Perform K-Means clustering and show all  the calculations performed at each iteration.

c. Draw a 10 by 10 space with all the 10 points  and show the clusters and the new centroids after each iteration.