In the previous chapter, we compared the K-Means and K-Medoids algorithms. It was mentioned that, unlike K-Means, the K-Medoids algorithm has data points as medoids. Let's visualize the differences.

For example, for the training dataset with three clusters we can visualize the clusters and their centers for both K-Means and K-Medoids. The results are displayed below.

If you watch closely to the right chart and compare it with the central one, you will notice that marked points are data points, unlike the points on the left chart. I've marked these points with green arrows. Let's represent the difference using a more obvious example! The result of clustering using the K-Means algorithm, and cluster centers (labeled with 10) are displayed below.