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-boun...@r-project.org] On Behalf Of Tom D. Harray Sent: Friday, July 28, 2017 7:56 AM To: r-help@r-project.org Subject: [R] R-Package for Recursive Partitioning without Classification or Regression 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 ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
