[R] Predict.nnet ?

[Yves Gauvreau]

Is there something I could do while waiting so that I could go on with my
work?

Thanks in advance

Yves Gauvreau


PS data.x range of values is in [0..1] if it matters



----- Original Message -----
From: "Yves Gauvreau" <cyg at sympatico.ca>
To: "Prof Brian D Ripley" <ripley at stats.ox.ac.uk>
Cc: <r-help at stat.math.ethz.ch>
Sent: Wednesday, October 25, 2000 5:54 AM
Subject: Re: [R] Predict.nnet ?


> Here is what I have
>
> > library(nnet)
> > package.description("nnet")$Version
> [1] "6.2-1"
>
> data.x <- data.frame(p1=p1, p2=p2, p3=p3, p4=p4, p5=p5)
>
> dim(data.x) => 4583  100
>
> dim(data.y) => 4583 3 {matrix}
>
> samp <- sample(1:nrow(data.y), 1500)
>
> data.nn <- nnet.default(x=data.x[samp,], y=data.y[samp,], size=20,
rang=0.1,
> skip=T, MaxNWts=2500, linout=T, decay=2.5e-4, maxit=100)
>
> **** a call to nnet(...) only complains about missing argument
>
> I hit the return key and nnet start doing it's job to the end without
> complaining.
>
> data.predict <- predict(data.nn, data.x[-samp,])
>
> Run for a little while (a few seconds) and I get a message box:
>
> Rgui.exe Application error
>
> The instruction at 0x10001181 reference memory at 0x05fb1000
> The memory could not be read.
>
> Click OK to terminate.
> Click on CANCEL to debug
>
> *********
>
> I was using R 1010 so I though the problem could be because I don't have
the
> latest version. So I downloaded and installed the latest release of both R
> and VR yesterday before posting the help request.
>
> I'm surprise as you may be (Ripley) that I can train the network with no
> obvious problem and that when I try to test the results using predict it
> doesn't work. I understand that the forward pass needed by the nnet code
to
> compute the error, gradient and hessian (if asked for) should be the same.
> It seems though, there could be a different approach for each?
>
> I even tried this
>
> data.predict <- predict(data.nn, data.x[100:120,])
>
> with the same result.
>
> Anyway, I though I may be using the library the wrong way? I don't know
and
> I'm still puzzle!
>
> Any suggestion on how to figure out what's wrong?
>
> Yves Gauvreau
>
>
>
>
>
> ----- Original Message -----
> From: "Prof Brian D Ripley" <ripley at stats.ox.ac.uk>
> To: "Yves Gauvreau" <cyg at sympatico.ca>
> Cc: <r-help at stat.math.ethz.ch>
> Sent: Wednesday, October 25, 2000 2:17 AM
> Subject: Re: [R] Predict.nnet ?
>
>
> > On Tue, 24 Oct 2000, Yves Gauvreau wrote:
> >
> > > Hi,
> > >
> > > I have a problem with predict.nnet when I try to use it. It crashes R
> with a
> > > memory access violation.
> >
> > It should tell you in which DLL, which would help.
> >
> > > platform Windows
> > > arch     x86
> > > os       Win32
> > > system   x86, Win32
> > > status
> > > major    1
> > > minor    1.1
> > > year     2000
> > > month    August
> > > day      15
> > > language R
> > >
> > > I admit the data set is quite large ~ [3000, 101] and its a 3 class
> problem.
> > > I know that it works fine when there is a single target. I wonder if
> what
> > > I'm doing is wrong or if could be a bug of some kind?
> >
> > Not really much there to go on, I'm afraid.  You do have the latest
> version
> > of the VR bundle?  (9.2-1: package.description("nnet")$Version will tell
> > you).  There was an R-related memory-management problem on a few
platforms
> > (not Solaris, yes on Linux PPC, seen once on Linux i386, in nnet not
> > predict.nnet) in the immediately previous release (6.1-9, perhaps also
> > 6.1-8).
> >
> > Certainly you should be able to do this, and the scripts in the bundle
> > do an example with three output and predicting to a large set.
> > As a workaround, does predicting to a smaller set of observations help?
> > You can then build up the big prediction in pieces.
> >
> > --
> > Brian D. Ripley,                  ripley at stats.ox.ac.uk
> > Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
> > University of Oxford,             Tel:  +44 1865 272861 (self)
> > 1 South Parks Road,                     +44 1865 272860 (secr)
> > Oxford OX1 3TG, UK                Fax:  +44 1865 272595
> >
>
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