# Two-stage clustering in R

• Is it possible to do 2-stage cluster analysis in R?
• Can anybody provide me resource on it?
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You mean like clustering on a sample to quickly get good starting centroids for the 'full' pass? Or more like two different methods altogether? –  Marcin Apr 28 '11 at 0:06
Are you referring to the clustering algorithm which SPSS calls two-step? spss.ch/upload/… –  Jeromy Anglim Apr 28 '11 at 2:13
Yeah! I'm taking about spss kind of 2-step clustering.But I want to do it using R. –  Ari Apr 28 '11 at 4:08
The closest package that I can think of is birch, but it is not available on CRAN anymore so you have to get the source and install it yourself (R CMD install birch_1.1-3.tar.gz works fine for me, OS X 10.6 with R version 2.13.0 (2011-04-13)). It implements the original algorithm described in
which relies on cluster feature tree, as does SPSS TwoStep (I cannot check, though). There's a possibility of using the k-means algorithm to perform clustering on birch object (kmeans.birch()), that is partition the subclusters into k groups such that the sum of squares of all the points in each subcluster to the assigned cluster centers is minimized.