Sorry, Patrick and other victims. My bad~~
The data file can be accessed at
http://zhanglab.ccmb.med.umich.edu/TM-fold/featureSelection_rec.vectors
The code is attached below. Error happens at "data.cforest.varimp <-
varimp(data.cforest, conditional = TRUE)": "Error in
model.matrix.default(as.formula(f),data = blocks): term 1 would
require 4e+17 columns".
Reducing dimension of each vector to 300 still gives same error feedback.
library(randomForest)
library(party)
set.seed(71)
rawinput <- read.table("featureSelection_rec.vectors")
rawinput$V1 <- as.factor(as.numeric(rawinput$V1))
data.controls <- cforest_unbiased(ntree=500, mtry=3)
data.cforest <- cforest(V1~.,data=rawinput,controls=data.controls)
data.cforest.varimp <- varimp(data.cforest, conditional = TRUE)
Thanks!
jinrui,
Quoting Patrick Connolly <[email protected]>:
On Thu, 16-Jun-2011 at 09:19AM -0400, Jinrui Xu wrote:
Thanks for your feedback.
I think the problem is not because of many levels. There is only 1
column with two levels as class labels in my input data.
Below is my code. The commandline "data.cforest.varimp <-
varimp(data.cforest, conditional = TRUE)" reports "Error in
model.matrix.default(as.formula(f),data = blocks): term 1 would require
4e+17 columns"
I also attached my input file. Hope you can run it for me to check what
the problem is. Thanks a lot!
PS: It takes 10 mins to finish the code below by 1 cpu and upto 2.5 GB
memory. You can reduce the columns in the rawinput, which reduces
computing intense and feeds back same error.
It also uses 10% of my monthly mobile data allowance to download a
10Mb data file. Please don't send that much with email. Give a URL
to where those interested can download it.
--
~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.
___ Patrick Connolly
{~._.~} Great minds discuss ideas
_( Y )_ Average minds discuss events
(:_~*~_:) Small minds discuss people
(_)-(_) ..... Eleanor Roosevelt
~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.
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