package prbnmcn-clustering

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K-medoids functor.

type init =

| Forgy
(*
Forgy selects k elements at random (without replacement) as initial centroids.
*)
| KmedoidsPP
(*
KmedoidsPP selects initial medoids iteratively with probabilities proportional to their distance to the previously selected centroids. This intuitively allows to spread them well.
*)

Initial choice of medoids. This implementation provides several initialization algorithms, the standard one being Kmedoids++, identical to Kmeans++

type algorithm =

| PAM
(*
PAM stands for Partition Around Medoids - the classical greedy algorithm. Costly.
*)
| VoronoiIteration
(*
Another heuristic, proceeding similarly to Lloyd's algorithm for Kmeans. Less costly (but still more than Kmeans) but perhaps less precise.
*)

Algorithm used to perform partitioning.

type termination =

See K_means.

and constraints = {

}

exception KmedoidsError of string

Exception thrown by k_medoids in case something goes awry.

module Make (E : Intf.Metric) : sig ... end