Given the (dis)similarity matrix and the clustering results, how do I select the medoid in each cluster?
For example, one cluster contains totally 4 points: A, B, C, D. I know the similarity (or dissimilarity between each pair of them. How to pick one that is the most representative in this cluster?
My instinct is to choose the point with the minimum average distance to other points. I am not sure if this is correct.
I am using a linkage clustering method.
Things would be easier in k-means methods, but that is not what I need.
I would appreciate a lot if you can provide some links to codes along with the methods.