R help - Mar 2013 - CARET and NNET fail to train a model when the input is high dimensional

The following code fails to train a nnet model in a random dataset using
caret:

nR <- 700
nCol <- 2000
  myCtrl <- trainControl(method="cv", number=3,
preProcOptions=NULL,
classProbs = TRUE, summaryFunction = twoClassSummary)
  trX <- data.frame(replicate(nR, rnorm(nCol)))
  trY <- runif(1)*trX[,1]*trX[,2]^2+runif(1)*trX[,3]/trX[,4]
  trY <- as.factor(ifelse(sign(trY)>0,'X1','X0'))
  my.grid <- createGrid(method.name, grid.len, data=trX)
  my.model <-
train(trX,trY,method=method.name,trace=FALSE,trControl=myCtrl,tuneGrid=my.grid,
metric="ROC")
  print("Done")

The error I get is:
task 2 failed - "arguments imply differing number of rows: 1334, 666"

However, everything works if I reduce nR to, say 20.

Any thoughts on what may be causing this? Is there a place where I could
report this bug other than this mailing list?

Here is my session info:
> sessionInfo()
R version 2.15.2 (2012-10-26)
Platform: x86_64-unknown-linux-gnu (64-bit)

locale:
[1] C

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base

other attached packages:
[1] nnet_7.3-5      pROC_1.5.4      caret_5.15-052  foreach_1.4.0
[5] cluster_1.14.3  plyr_1.8        reshape2_1.2.2  lattice_0.20-13

loaded via a namespace (and not attached):
[1] codetools_0.2-8 compiler_2.15.2 grid_2.15.2     iterators_1.0.6
[5] stringr_0.6.2   tools_2.15.2

Thanks,

James

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James,

I did a fresh install from CRAN to get caret_5.15-61 and ran your code with
method.name = "nnet" and grid.len = 3.

I don't get an error, although there were issues:

   In nominalTrainWorkflow(dat = trainData, info = trainInfo,  ... :
     There were missing values in resampled performance measures.

The results had:

Resampling results across tuning parameters:

  size  decay  ROC    Sens   Spec   ROC SD   Sens SD  Spec SD
  1     0      0.521  0.52   0.521  0.0148   0.0312   0.00901
  1     1e-04  0.513  0.528  0.498  0.00616  0.00386  0.00552
  1     0.1    0.515  0.522  0.514  0.0169   0.0284   0.0426
  3     0      NaN    NaN    NaN    NA       NA       NA
  3     1e-04  NaN    NaN    NaN    NA       NA       NA
  3     0.1    NaN    NaN    NaN    NA       NA       NA
  5     0      NaN    NaN    NaN    NA       NA       NA
  5     1e-04  NaN    NaN    NaN    NA       NA       NA
  5     0.1    NaN    NaN    NaN    NA       NA       NA

To test more, I ran:

   > test <- nnet(trX, trY, size = 3, decay = 0)
   Error in nnet.default(trX, trY, size = 3, decay = 0) :
     too many (2107) weights

So, you need to pass in MaxNWts to nnet() with a value that let's you fit
the model. Off the top of my head, you could use something like:

   MaxNWts  = length(levels(trY))*(max(my.grid$.size) * (nCol + 1) +
max(my.grid$.size) + 1)

Also, this one of the methods for getting help (the other is to just email
me). I also try to keep up on stack exchange too.

Max



On Tue, Mar 5, 2013 at 9:47 PM, James Jong <ribonucleico@gmail.com> wrote:
> The following code fails to train a nnet model in a random dataset using
> caret:
>
> nR <- 700
> nCol <- 2000
>   myCtrl <- trainControl(method="cv", number=3,
preProcOptions=NULL,
> classProbs = TRUE, summaryFunction = twoClassSummary)
>   trX <- data.frame(replicate(nR, rnorm(nCol)))
>   trY <- runif(1)*trX[,1]*trX[,2]^2+runif(1)*trX[,3]/trX[,4]
>   trY <- as.factor(ifelse(sign(trY)>0,'X1','X0'))
>   my.grid <- createGrid(method.name, grid.len, data=trX)
>   my.model <- train(trX,trY,method=method.name
> ,trace=FALSE,trControl=myCtrl,tuneGrid=my.grid,
> metric="ROC")
>   print("Done")
>
> The error I get is:
> task 2 failed - "arguments imply differing number of rows: 1334,
666"
>
> However, everything works if I reduce nR to, say 20.
>
> Any thoughts on what may be causing this? Is there a place where I could
> report this bug other than this mailing list?
>
> Here is my session info:
> > sessionInfo()
> R version 2.15.2 (2012-10-26)
> Platform: x86_64-unknown-linux-gnu (64-bit)
>
> locale:
> [1] C
>
> attached base packages:
> [1] stats     graphics  grDevices utils     datasets  methods   base
>
> other attached packages:
> [1] nnet_7.3-5      pROC_1.5.4      caret_5.15-052  foreach_1.4.0
> [5] cluster_1.14.3  plyr_1.8        reshape2_1.2.2  lattice_0.20-13
>
> loaded via a namespace (and not attached):
> [1] codetools_0.2-8 compiler_2.15.2 grid_2.15.2     iterators_1.0.6
> [5] stringr_0.6.2   tools_2.15.2
>
> Thanks,
>
> James
>
>         [[alternative HTML version deleted]]
>
> ______________________________________________
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> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>


-- 

Max

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