Ulrich wrote: >Affinity propagation produces quite a number of clusters.
I tried with q=0 and produces 17 clusters. Anyway that's a good idea, thanks. I'm looking to test it with my dataset. So I'll probably use daisy() to compute an appropriate dissimilarity then apcluster() or another method to determine clusters. What do you suggest in order to assign a new observation to a determined cluster? It seems that RandomForest doesn't work with both numerical and categorical predictors (thanks to Joris). Christian wrote: >and the implement >nearest neighbours classification myself if I needed it. >It should be pretty straightforward to implement. Do you intend modify the code of the knn1() function by yourself? thanks to everyone! -- View this message in context: http://r.789695.n4.nabble.com/cluster-analysis-and-supervised-classification-an-alternative-to-knn1-tp2231656p2233210.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.