[R] R-Package for Recursive Partitioning without Classification or Regression

David L Carlson dcarlson at tamu.edu
Fri Jul 28 17:09:26 CEST 2017

I think that diana() or mona() in package cluster are what you are looking for. The computational burdens of polythetic divisive clustering methods as they are called are substantial so the available methods use shortcuts that should provide good, but not necessarily optimal results.

David L Carlson
Department of Anthropology
Texas A&M University
College Station, TX 77840-4352

-----Original Message-----
From: R-help [mailto:r-help-bounces at r-project.org] On Behalf Of Tom D. Harray
Sent: Friday, July 28, 2017 7:56 AM
To: r-help at r-project.org
Subject: [R] R-Package for Recursive Partitioning without Classification or Regression


I have a question related to recursive partitioning, but I cannot find
an answer, likely because I don't know how to properly word my Google
search query.

All recursive partitioning examples, which I can find, are used for
either classification or regression trees like

   tree(Species ~ Sepal.Width + Petal.Width, data = iris)

which implies building a model. However, I would like to split data
like clustering similar to decision tree methods, because I have
nothing to predict.

My question is: Is there a package, which I can use to partition my
data without classification or regression so that it resembles
clustering methods?

Thanks and regards,


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