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-l
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 distanc
On Wed, 21 Apr 2010, Hans Ekbrand wrote:
On Wed, Apr 21, 2010 at 01:42:05PM +0200, Roger Bivand wrote:
So you do not want hclust at all, really. Look at dnearneigh() in spdep,
setting a 100m bound. Then use n.comp.nb() to see which points belong to
which graph component, using perhaps plot.nb w
On Wed, Apr 21, 2010 at 01:42:05PM +0200, Roger Bivand wrote:
> So you do not want hclust at all, really. Look at dnearneigh() in spdep,
> setting a 100m bound. Then use n.comp.nb() to see which points belong to
> which graph component, using perhaps plot.nb with colours to distinguish
> the
On Wed, 21 Apr 2010, Hans Ekbrand wrote:
On Tue, Apr 20, 2010 at 11:13:22PM +0200, Hans Ekbrand wrote:
Roger Bivand wrote:
On Tue, 20 Apr 2010, Hans Ekbrand wrote:
I have just read about clustering on wikipedia, and learnt that what I
want is:
Agglomerative hierarchical clustering, with com
On Tue, Apr 20, 2010 at 11:13:22PM +0200, Hans Ekbrand wrote:
> Roger Bivand wrote:
> > On Tue, 20 Apr 2010, Hans Ekbrand wrote:
> >
> >> I have just read about clustering on wikipedia, and learnt that what I
> >> want is:
> >>
> >> Agglomerative hierarchical clustering, with complete linkage
> >
>
Roger Bivand wrote:
> On Tue, 20 Apr 2010, Hans Ekbrand wrote:
>
>> I have just read about clustering on wikipedia, and learnt that what I
>> want is:
>>
>> Agglomerative hierarchical clustering, with complete linkage
>
> library(cluster)
> ?hclust
>
> is for clustering with moderate numbers of poi
On Tue, 20 Apr 2010, Hans Ekbrand wrote:
I have just read about clustering on wikipedia, and learnt that what I
want is:
Agglomerative hierarchical clustering, with complete linkage
library(cluster)
?hclust
is for clustering with moderate numbers of points.
Below: in UTM, the units are metr
I have just read about clustering on wikipedia, and learnt that what I
want is:
Agglomerative hierarchical clustering, with complete linkage
I searched for suitable r-packages for this and found nnclust, and
spatclus. Are those the packages that you could recommend for
clustering events data (the
