Hello, I'm trying to use the party package function varimp() to get conditional variable importance measures, as I'm aware that some of my variables are correlated. However I keep getting error messages (such as the example below). I get similar errors with three separate datasets that I'm using. At a guess it might be something to do with the very large number of variables (e.g. 23 variables, 250 or so data points) but I was wondering if anyone had any other ideas. It works fine for regular variable importance calculation.
Code: biomass.cf<-cforest(Total.biomass ~ ., data=biomass, control=cforest_unbiased(ntree=2500, mtry=8)) biomass.cf.vi<-varimp(biomass.cf, conditional=TRUE) Error: Error in if (node[[5]][[1]] == variableID) cp <- node[[5]][[3]] : argument is of length zero In addition: Warning messages: 1: In matrix(as.logical(cl), nrow = nlevels(x)) : data length [2] is not a sub-multiple or multiple of the number of rows [17] 2: In matrix(as.logical(cl), nrow = nlevels(x)) : data length [2] is not a sub-multiple or multiple of the number of rows [17] 3: In matrix(as.logical(cl), nrow = nlevels(x)) : data length [2] is not a sub-multiple or multiple of the number of rows [17] 4: In matrix(as.logical(cl), nrow = nlevels(x)) : data length [2] is not a sub-multiple or multiple of the number of rows [17] Many thanks, Meghann Mears, PhD student University of Sheffield Department of Animal & Plant Sciences ______________________________________________ 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.
