clustering based on assignment - centroid update iterations
The clustering is based on an Index object that assigns training
points to the centroids. Therefore, at each iteration the centroids
are added to the index.
On output, the centroids table is set to the latest version
of the centroids and they are also added to the index. If the
centroids table it is not empty on input, it is also used for
initialization.
To do several clusterings, just call train() several times on
different training sets, clearing the centroid table in between.
clustering based on assignment - centroid update iterations
The clustering is based on an Index object that assigns training points to the centroids. Therefore, at each iteration the centroids are added to the index.
On output, the centroids table is set to the latest version of the centroids and they are also added to the index. If the centroids table it is not empty on input, it is also used for initialization.
To do several clusterings, just call train() several times on different training sets, clearing the centroid table in between.