complete linkage Agglomerative hierarchical clustering, nnclust, spatclus or something else?

You asked earlier about nnclust:  it does single-linkage rather than complete-linkage clustering, that is, it defines clusters so that each point in the cluster has a nearest neighbour in the cluster closer than the threshold distance. This produces much less circular clusters than complete-linkage clustering.

The main distinctive feature of nnclust is that it is feasible even for quite large data sets, taking linear space and roughly nlogn time.

         -thomas

On Wed, Apr 21, 2010 at 03:14:46PM +0200, Roger Bivand wrote:

On Wed, 21 Apr 2010, Hans Ekbrand wrote:

[...]

Well, hclust was useful, once I understood how cutree works. What
would be the benefit of dnearneigh(), is it faster?

For larger data sets, hclust needs a triangular distance matrix,
dnearneigh does not. Finding graph components in the output "nb" object
also seems conceptually more direct.

OK, good to know if I run into trouble when using the code on larger
data-sets later on.

Thomas Lumley			Assoc. Professor, Biostatistics
tlumley at u.washington.edu	University of Washington, Seattle