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I need help question solving euclidean distance of clustering of 3 cluster after 1 iteration. Figure 1 : Scatter plot of datasets and the initialized

I need help question solving euclidean distance of clustering of 3 cluster after 1 iteration.
Figure 1: Scatter plot of datasets and the initialized centers of 3 clusters
Given the input matrix x whose rows represent different data points, please perform a k-means
clustering on this dataset using the Euclidean distance as the distance function. Here k is chosen
as 3. The Euclidean distance d between input vector vec(p)inRn and vec(q)inRn is defined as
d=i=1n(pi-qi)22
All data in x were plotted in Figure 1. The center of 3 clusters were initialized as vec(c1)=(6.2,3.2)
(red), vec(c2)=(6.6,3.7)(green), vec(c3)=(6.5,3.0)(blue).
x=[5.93.24.62.96.22.84.73.25.54.25.03.04.93.16.73.15.13.86.03.0]
a.) What are 3 clusters and their centers after one iteration? Show the detailed steps, same as questions b.
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b. What are 3 clusters and their centers after two iterations?
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