Create a MATLAB function:

%% The k-Means Algorithm function [means , clusters] kMeansClustering (data, k, distFunc , tol, max!ter) = Initialization: Pick k random data points from the data set or use the option k-means++ initial- ization (see below). Assign these to ew Repeat old 2. Cluster the data based on these old means, i.e. assign each data point a number 1-k corre- sponding to which mean it is closest to based on the distFunc 3. Take the average of value of each of these clusters and assign them as the new mean values or new Stop when either the max iterations is reached or maxk Ik1new-lold lla