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.
