Exercise $1\mathrm{.}2$: Write the Matlab script for k$-$means clustering

$$ Import the dataset Mall$\_$Customers.csv$,$ using readtable function.

$$ Convert columns $4($Annual income$)$ and $5($Spending score$)$ of the table to X$,$ using table$2$array

function.

$$ Plot Spending score against Annual income.

$$ Set the number of clusters $($k$)$ from $1$ to $10,$ use $[$idx$,$C$,$ sumd$]=$ kmeans$($X$,$k$)($where sumd

returns the within$-$cluster sums of point$-$to$-$centroid distances or the WCSS $($within$-$cluster sum of

squares$)$ and the Elbow method to find the optimal number of clusters.

$$ Use the k chosen in the last step to perform the kmeans clustering and use gscatter function to

visualise the clusters. You can add the centroids of the clusters to the plot.

$$ Generate the silhouette plot to evaluate the clustering, using silhouette function.