Hi Abanero, first, I have to correct myself. Knn1 is a supervised learning algorithm, so my comment wasn't completely correct. In any case, if you want to do a clustering prior to a supervised classification, the function daisy() can handle any kind of variable. The resulting distance matrix can be used with a number of different methods.
And you're right, randomForest doesn't handle categorical variables either. So I haven't been of great help here... Cheers Joris On Thu, May 27, 2010 at 1:25 PM, abanero <gdevi...@xtel.it> wrote: > > Hi, > > thank you Joris and Ulrich for you answers. > > Joris Meys wrote: > > >see the library randomForest for example > > > I'm trying to find some example in randomForest with categorical variables > but I haven't found anything. Do you know any example with both categorical > and numerical variables? Anyway I don't have any class labels yet. How > could > I find clusters with randomForest? > > > Ulrich wrote: > > >Probably the simplest way is Affinity Propagation[...] All you need is a > way of measuring the similarity of >samples which is straightforward both > for numerical and categorical variables. > > I had a look at the documentation of the package apcluster. That's > interesting but do you have any example using it with both categorical and > numerical variables? I'd like to test it with a large dataset.. > > Thanks a lot! > Cheers > > Giuseppe > > -- > View this message in context: > http://r.789695.n4.nabble.com/cluster-analysis-and-supervised-classification-an-alternative-to-knn1-tp2231656p2232950.html > Sent from the R help mailing list archive at Nabble.com. > > ______________________________________________ > R-help@r-project.org mailing list > 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. > -- Joris Meys Statistical Consultant Ghent University Faculty of Bioscience Engineering Department of Applied mathematics, biometrics and process control Coupure Links 653 B-9000 Gent tel : +32 9 264 59 87 joris.m...@ugent.be ------------------------------- Disclaimer : http://helpdesk.ugent.be/e-maildisclaimer.php [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list 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.
