Question $3$

The table below provides a data set containing $7$ observations with $2$ features:

We wish to identify two clusters of this data set using $K-$means clustering with $K=2.$ We use the

Euclidean distance measure. Suppose that we initially assign the observations #$1,$#$2,$#$3$ as cluster $1$ and

the observations #$4,$#$5,$#$6,$#$7$ as cluster $2.$

What are the cluster centroids and cluster assignments after the first iteration of $K-$means clustering?

What are the cluster centroids and cluster assignments after the second iteration of $K-$means clustering?

Do we need to proceed to the third iteration? If yes, continue the $K-$means clustering algorithm until

it converges. If no$,$ explain why.K clustering