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Distance matrix

A common strategy in clustering the units of the SOM is to calculate a distance matrix between the reference vectors and use a high value of the matrix as an indication of a cluster border [46, 26, 45]. In 3D visualization of such a matrix, the clusters will appear as ``valleys''. The problem then is how to determine which map units belong to a given cluster. For this agglomerative and devisive algorithms are typically used, e.g. in [32, 49]. Agglomerative algorithms usually have the following steps:

  1. assign each map unit to its own cluster
  2. calculate the distances between all clusters
  3. join the two closest clusters
  4. if only a user-defined number of clusters exists, end, otherwise iterate from step 2
In addition to distance some other joining criteria can be used. In contiguity-constrained clustering the clusters in step 3 are required to be adjacent [32].

Juha Vesanto
Tue May 27 12:40:37 EET DST 1997