can you please solve this assignement a step by step with hand written Suppose that the data mining task is to cluster points $($with $(x,y)$ representing location$)$ into three clusters, where

the points are:

$A_1(2,10),A_2(2,5),A_3(8,4),B1(5,8),B2(7,5),B_3(6,4),C_1(1,2),C_2(4,9).$

The distance function is Euclidean distance. Suppose initially we assign $A1,B1,$ and $C_1$ as the center of each

cluster, respectively. Use the $k-$means algorithm to show:

$($a$)$ The three cluster centers

$($b$)$ The final three clusters.

Let's consider a dataset containing five data points represented by their coordinates:

$($a$)$ Choose point $1$ and point $4$ as the initial medoids

$($b$)$ Calculate the dissimilarity between each data point and each medoid