Friends, I would like to use Random Forest in unsupervised mode to classify data that are from a mixture of categorical and continuous variables. The examples I find online use only continuous data, followed by an mds plot. Is it correct to use RF to obtain proximities for my mixed dataset and then perform some other form of clustering (i.e. pam, clara, etc.) using the proximities matrix? Or is there a way to perform unsupervised classification that will kick out cluster membership on this dataset in RF itself?
Thanks, Helen Poulos Yale School of Forestry ______________________________________________ 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.
