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PRTools User Guide



Finds K center objects from a distance matrix


 D Distance matrix between, e.g. M objects (may be a dataset)
 K Number of center objects to be found (optional; default: 1)
 N Number of trials starting from a random initialisation  (optional; default: 1)

 LAB Integer labels: each object is assigned to its nearest center
 J Indices of the center objects
 DM A list of distances corresponding to J: for each center in J the maximum distance of the objects assigned to this center.


Finds K center objects from a symmetric distance matrix D. The center  objects are chosen from all M objects such that the maximum of the  distances over all objects to the nearest center is minimised. For K > 1,  the results depend on a random initialisation. The procedure is repeated  N times and the best result is returned.

If N = 0, initialisation is not random, but done by a systematic  selection based on a greedy approach.

Faster and more advanced tools for cluster analysis may be found in the  ClusterTools toolbox.

See also

hclust, prkmeans, emclust, modeseek,

PRTools Contents

PRTools User Guide

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