Dear all: I¡¯m trying to get unbiased feature importance of my data via package ¡°party¡±, which contains 1-5 integer value, and a few numeric values attributes. The class label is 1-5 integer value as well. In total I have 20 features with 1100 observations. I checked the type my data in R using class(my_data_cell), no factor has been observed. I received a commond error like others did from the past. > lu = read.csv(file=file.choose()) > lu.cf <- cforest(Target ~ ., data = lu, control = cforest_unbiased(mtry = 2, > ntree = 50)) > lu.cf <- cforest(Target ~ ., data = lu, control = cforest_unbiased(mtry = 2, > ntree = 100)) > cvi_lu = varimp(lu.cf,threshold = 0.2,conditional= TRUE,OOB=TRUE) Error in model.matrix.default(as.formula(f), data = blocks) : allocMatrix: too many elements specified
Anybody please given suggestion? Thanks a lot! [[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.