If I understand correctly, the pam algorithm is a greedy search for a set of medoids such that no other set offers a lower cost (i.e.: the sum of distances of points to their nearest medoid).
However, when does the pam algorithm fail? Are there general cases for which it is known to reach the global optimum? (say, for some ratio of k and n?)
Are there nice counter examples demonstrating when some set of medoid is stable (i.e.: would lead pam to converge), but sub optimal?
idx
vectors it is not a bunch of2
followed by a bunch of1
's. Some mischaracterization took place but for all intended purposes that clustering is great. $\endgroup$