Do you mean supervised or unsupervised classification. If supervised, I have had great success using gradient boosted classification in package gbm. multinomial distribution will get you multiple classes and it will select relevant predictors by itself given the training data.
Not sure about the customized cost functions Jean-Olivier Irisson — Université Pierre et Marie Curie Laboratoire d'Océanographie de Villefranche 181 Chemin du Lazaret 06230 Villefranche-sur-Mer Tel: +33 04 93 76 38 04 Mob: +33 06 21 05 19 90 http://www.obs-vlfr.fr/~irisson/ Send me large files at: http://www.obs-vlfr.fr/~irisson/upload/ On Fri, Feb 28, 2014 at 5:53 PM, Sergio Fonda <sergio.fond...@gmail.com> wrote: > Focus on MASS, CCA and e1071 packages > Brgds, > Sergio > Il 28/feb/2014 17:47 "Luca Cerone" <luca.cer...@gmail.com> ha scritto: > >> Dear all, >> I would like some advices on R packages to solve classification problems. >> I have tried to search among the Task views, but couldn't find anything. >> >> Can somebody recommend me some packages? >> >> Some of the features I am looking for: >> - deal with multiple classes >> - use customized cost functions >> - perform features/predictors selection >> >> Any hint would be greatly appreciated, >> thanks a lot in advance for the help! >> Cheers, >> Luca >> >> ______________________________________________ >> 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. >> > > [[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. ______________________________________________ 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.
