Thank you Max. I presume that in order to use caret with nnet and MaxNWts,
I would have to write my custom method for train that supports this new
argument.
>From what I read, when writing my custom method, I would need to define
functions "parameters", "model", "prediction", "prob" and "sort" and pass
them to trainControl.
However, If all I need is a new "parameters" function (in order to pass the
MaxNWTs argument to nnet), is there a way to reuse the other functions
("model", "prediction", "prob" and "sort") that are already defined for the
"nnet" method?
James
On Wed, Mar 6, 2013 at 9:59 AM, Max Kuhn <mxk...@gmail.com> wrote:
> 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 <ribonucle...@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]]
>>
>> ______________________________________________
>> R-help@r-project.org mailing list
>> https://stat.ethz.ch/mailman/listinfo/r-help
>> PLEASE do read the posting guide
>> http://www.R-project.org/posting-guide.html
>> and provide commented, minimal, self-contained, reproducible code.
>>
>
>
>
> --
>
> Max
>
[[alternative HTML version deleted]]
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