$2(16$ points$).$ Assume K$-$Means is used to cluster the dataset consisting of the points shown below. Moreover, Euclidean distance is used as the distance function: d$[($x$1,$x$2),($xl$\text{'},$x$2)=(($xl$-$xl$)2+($x$2-$x$2)27\mathrm{.}5$ to compute distances between centroids and objects in the dataset. Moreover, K$-$Means initial clusters C$1,$ C$2,$ and C$3$ are as follows: C$1$: $\{(2\mathrm{.}2),(8,8)$ C$2$: $\{(4,6),(8,0)\}$ C$3$: $\{(4,8),(6,10)\}$ Now K$-$means is run for a single iteration; what are the new clusters and what are their centroids?