The data size isn't an issue. Can you send a reproducible example?
Max
On Jun 11, 2013, at 10:31 AM, Ferran Casarramona <ferran.casarram...@gmail.com>
wrote:
> 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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>
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