Ok, I am sorry, My trainingset consists of a 60 x 204 matrix (independent_training – 204 features). I have 60 continuous labels (dependent_training, ranging from 2.25 to 135).
this is all the code I use: library(kernlab) rvm(as.matrix(independent_training), dependent_training, type="regression", kernel = "vanilladot") On 13.02.2012, at 16:40, David Winsemius wrote: > > On Feb 13, 2012, at 10:23 AM, Martin Batholdy wrote: > >> Hi, >> >> For another trainingset I get this error message, which again is rather >> cryptic to me: >> > Just imagine how it seems to us! > >> Setting default kernel parameters >> >> Error in array(0, c(n, p)) : 'dim' specifies too large an array >> RMate stopped at line 0 of selection >> Calls: rvm ... .local -> backsolve -> as.matrix -> chol -> diag -> array > > You are on you way to the prize for the greatest number of cryptic (your > word) postings in a short interval. (And this one doesn't even have the > context of your posting of 8 minutes ago.) > >> thanks for any suggestions! > > More details about data and code. > > -- > David Winsemius, MD > West Hartford, CT > ______________________________________________ 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.
