[R] R-Package for Recursive Partitioning without Classification or Regression
bgunter.4567 at gmail.com
Fri Jul 28 16:55:39 CEST 2017
Recursive partitioning requires a response variable because splitting
criteria are based on node purity/homogeneity (by various criteria) of
So why did you not just search on "clustering" (e.g. at rseek.org)?
And in particular, have you looked at the CRAN task view on clustering
If nothing there satisfies your needs, you may need to clarify your query.
"The trouble with having an open mind is that people keep coming along
and sticking things into it."
-- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )
On Fri, Jul 28, 2017 at 5:56 AM, Tom D. Harray <tomdharray at gmail.com> wrote:
> 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,
> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
More information about the R-help