Hi all,
Thanks for the replies - they have helped shaped my thinking and are
starting to push me in a better direction. Maybe I should explain a
little more about what I'm trying to achieve.
I am analysing satellite data across the global ocean, and am
interested in trying to classify areas of
Hi,
Thanks for the replies - they have helped shaped my thinking and are
starting to push me in a better direction. Maybe I should explain a
little more about what I'm trying to achieve.
I am analysing satellite data across the global ocean, and am
interested in trying to classify areas of the
Dear R-Help,
I have a clustering problem with hclust that I hope someone can help
me with. Consider the classic hclust example:
hc - hclust(dist(USArrests), ave)
plot(hc)
I would like to cut the tree up in such a way so as to avoid small
clusters, so that we get a minimum number of
Can't put my finger on it but something about your idea rubs me the
wrong way. Maybe it's that the tree depends on the hierarchical
clustering algorithm and the choice on how to trim it should be based
on something more defensible than avoid singletons. In this example
Hawaii is really different
On Thu, May 24, 2012 at 9:31 AM, r-help.20.tre...@spamgourmet.com wrote:
Dear R-Help,
I have a clustering problem with hclust that I hope someone can help
me with. Consider the classic hclust example:
hc - hclust(dist(USArrests), ave)
plot(hc)
I would like to cut the tree up in
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