Hi,
I'm very new to R. I am most interested in the variable importance measures
that result from randomForest, but many of my predictors are highly
correlated. My first question is:
1. do highly correlated variables render variable importance measures in
randomForest invalid?
and 2. I know that cforest is robust to highly correlated variables,
however, I do not have enough space on my machine to run cforest. I used the
keep.forest = false option when using randomForest and that solved my space
issue. Is there a similar option for cforest (besides savesplitstats FALSE,
which isn't helping)
below is my code and error message
Thanks in advance!
> fit <- cforest(formula = y ~ x1 + x2+ x3+ x4+ x5+
+ x6+ x7+ x8+ x9+ x10, data=data, control= cforest_unbiased(savesplitstats
FALSE, ntree = 50, mtry = 5)
1: In mf$data <- data :
Reached total allocation of 3955Mb: see help(memory.size)
2: In mf$data <- data :
Reached total allocation of 3955Mb: see help(memory.size)
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