Not a direct answer, but from your description it looks like you are better of with supervised classification algorithms instead of unsupervised clustering. see the library randomForest for example. Alternatively, you can try a logistic regression or a multinomial regression approach, but these are parametric methods and put requirements on the data. randomForest is completely non-parametric.
Cheers Joris On Wed, May 26, 2010 at 3:45 PM, abanero <gdevi...@xtel.it> wrote: > > Hi, > I have a 1.000 observations with 10 attributes (of different types: > numeric, > dicotomic, categorical ecc..) and a measure M. > > I need to cluster these observations in order to assign a new observation > (with the same 10 attributes but not the measure) to a cluster. > > I want to calculate for the new observation a measure as the average of the > meausures M of the observations in the cluster assigned. > > I would use cluster analysis ( Clara algorithm?) and then knn1 (in > package class) to assign the new observation to a cluster. > > The problem is: Im not able to use knn1 because some of attributes are > categorical. > > Do you know something like knn1 that works with categorical variables > too? Do you have any suggestion? > > -- > View this message in context: > http://r.789695.n4.nabble.com/cluster-analysis-and-supervised-classification-an-alternative-to-knn1-tp2231656p2231656.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.
