I try to seed a k-means clustering with canopy clustering. Problem: Depending
on the choice for t1 and t2, canopy clustering gives me too many canopies or
just 1.
I thought I could solve this with the clusterFilter parameter, but no luck.
Although I can restrict the number of _canopy clusters_ with the clusterFilter
parameter leading to what would be a good value for k, this parameter has no
effect on the _canopy centroids_ that are created, and these are the seed for
k-means.
Is there a way to get a seed for k-means that reflects the value given for the
clusterFilter parameter in canopy clustering?
