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

Michal Kubista michal.kubista at nielsen.com
Tue Aug 1 11:37:09 CEST 2017


Hello Tom,
what you describe seems like using hierarchical clustering and
plotting a dendrogram to me, even though only in the "visual" way, not
in the math behind the algorithms.

Are you looking for something like this?
https://rpubs.com/gaston/dendrograms

Just please note, that this is very far from rpart in term of how the
algorithms work (already mentioned by Bert Gunter)

Best,
Michal

2017-07-28 14:56 GMT+02:00 Tom D. Harray <tomdharray at gmail.com>:
> Hello,
>
> 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
>
>    library(tree)
>    data(iris)
>    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,
>
> Dirk
>
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