Hello,
I'm training a set of data with Caret package using an elastic net (glmnet).
Most of the time train works ok, but when the data set grows in size I get
the following error:
Error en { :
task 1 failed - "arguments imply differing number of rows: 9, 10"
and several warnings like this one:
1: In eval(expr, envir, enclos) :
model fit failed for Resample01
My call to train function is like this:
fit <- train(TrainingPreCols, TrainingFrame[,PCol], method="glmnet",
preProcess = c("center","scale"))
When TrainingPreCols is 17420 obs. of 27 variables, the function works ok.
But with a size of 47000 obs of 27 variables I get the former error.
¿Could be the amount of data the cause of this error?
Any help is appreciated,
Ferran
P.D.:
This is my sessionInfo()
R version 2.15.0 (2012-03-30)
Platform: x86_64-pc-mingw32/x64 (64-bit)
locale:
[1] LC_COLLATE=Spanish_Spain.1252 LC_CTYPE=Spanish_Spain.1252
LC_MONETARY=Spanish_Spain.1252
[4] LC_NUMERIC=C LC_TIME=Spanish_Spain.1252
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] glmnet_1.9-3 Matrix_1.0-12 doSNOW_1.0.7 iterators_1.0.6
snowfall_1.84-4
[6] snow_0.3-12 caret_5.16-04 reshape2_1.2.2 plyr_1.8
lattice_0.20-6
[11] cluster_1.14.4 foreach_1.4.1
loaded via a namespace (and not attached):
[1] codetools_0.2-8 grid_2.15.0 stringr_0.6.2 tools_2.15.0
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