prkmeans
PRKMEANS
PRTools k-means clustering
[LABELS,B] = PRKMEANS(A,K,MAXIT,INIT)
Input | A | Matrix or dataset | K | Number of clusters to be found (optional; default: 2) | MAXIT | maximum number of iterations (optional; default: 50) | INIT | Labels for initialisation, or 'rand' : take at random K objects as initial means, or 'kcentres' : use KCENTRES for initialisation (default) |
Output | LABELS | Cluster assignments, 1..K | B | Dataset with original data and labels LABELS: | B | = PRDATASET(A,LABELS) |
Description K-means clustering of data vectors in A. Iterations may be stopped before stability is reached due to the setting of PRTIME.
Faster and more advanced tools for cluster analysis may be found in the ClusterTools toolbox. See also
datasets, hclust, kcentres, modeseek, emclust, prtime, This file has been automatically generated. If badly readable, use the help-command in Matlab. |
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