Finds K center objects from a distance matrix
[LAB,J,DM] = KCENTRES(D,K,N)
| 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.
hclust, prkmeans, emclust, modeseek,
|This file has been automatically generated. If badly readable, use the help-command in Matlab.|