pam {fastkmedoids} | R Documentation |
PAM (Partitioning Around Medoids)
Description
The original Partitioning Around Medoids (PAM) algorithm or k-medoids clustering, as proposed by Kaufman and Rousseeuw; a largely equivalent method was also proposed by Whitaker in the operations research domain, and is well known by the name "fast interchange" there. (Schubert and Rousseeuw, 2019)
Usage
pam(rdist, n, k, maxiter = 0L)
Arguments
rdist |
The distance matrix (lower triangular matrix, column wise storage) |
n |
The number of observations |
k |
The number of clusters to produce |
maxiter |
The maximum number of iterations (default: 0) |
Value
KMedoids S4 class
References
L. Kaufman, P. J. Rousseeuw "Clustering by means of Medoids" Information Systems and Operational Research 21(2)
[Package fastkmedoids version 1.2 Index]