Use the k-means algorithm and Euclidean distance to cluster the following eight examples into three clusters:...

Use the k-means algorithm and Euclidean distance to cluster the following eight examples into three
clusters:
A1 = (26, 18), A2 = (20, 26), A3(14, 20), A4(24, 20), A5(14, 30), A6(22, 18), A7(8, 18), A8(12, 14)
a. Suppose that the initial seeds (centres of each cluster) are A2, A3, and A8. Run the k-means
algorithm for one epoch only. At the end of this epoch,
o show the new clusters (i.e., the examples belonging to each cluster);
o show the centres of the new clusters;
o draw a graph space with all eight points, and show the clusters after the first epoch and
the new centroids.
b. Complete the process for other iterations. How many more iterations are needed for the
algorithm to converge? Draw the final result of the remaining epochs.
Note: if an object is at the same minimum distance from two clusters, consider it as belonging to
both.

Expert Solution

orchestra answered 1 year ago

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