[R] CVnn2 + nnet question
Manoj - Hachibushu Capital
Wanzare at HCJP.com
Mon Jun 14 13:52:24 CEST 2004
Thanks for the prompt reply. I don't think I am using any non default
arguments but still...here is the exact syntax for two different case
(skip = T and default) and the corresponding error message that I
receive.
Default Case ("skip = F")
Syntax : nn.test <-
CVnn2(Y~X1+X2+X3+X4+X5+X6+X7+X8+X9+X10+X11,all.data.norm[1:train.set,],m
axit=500,nreps=10)
Error message:
Fold 1
Size = 0 decay = 0
Inner fold 1Error in nnet.default(x,y,w.....) : No
weights to fit.
Case where Skip = T:
Syntax: nn.test <-
CVnn2(Y~X1+X2+X3+X4+X5+X6+X7+X8+X9+X10+X11,all.data.norm[1:train.set,],m
axit=500,nreps=10,skip=T)
Error message:
Fold 1
Size=0 decay = 0
Inner fold 1Error in switch(type,raw=z,class= { : inappropriate
fit for class
Manoj
-----Original Message-----
From: Prof Brian Ripley [mailto:ripley at stats.ox.ac.uk]
Sent: Monday, June 14, 2004 8:26 PM
To: Manoj - Hachibushu Capital
Cc: r-help at stat.math.ethz.ch
Subject: Re: [R] CVnn2 + nnet question
You are trying to fit a neural network with no connections. That makes
no
sense unless skip=T (as on the page you are quoting).
On Mon, 14 Jun 2004, Manoj - Hachibushu Capital wrote:
> Hi,
> I am trying to determine the number of units in the hidden layer
> and the decay rate using the CVnn2 script found in MASS directory
> (reference: pg 348,MASS-4).
>
> The model that I am using is in the form of Y ~ X1 + X2 + X3...
> + X11 and the underlying data is time-series in nature.
>
> I found the MASS and nnet package extremely useful (many thanks
> to the contributors).
`contributors'? Do see the DESCRIPTION file: it is hardly anonymous
work.
> However I am getting an error while using the CVnn2
> function...it says
You have not shown us the call you used, but the default arguments are
size = rep(6, 2), lambda = c(0.001, 0.01) so you have used non-default
args without telling us what.
> Fold 1
> Size = 0, decay = 0, inner fold 1 Error in nnet.default(x,y,w,....):
No
> weights to fit.
>
> Obliviously I am doing something wrong but am not able to figure
> it out.
Please do re-read the basic description of neural nets and nnet().
> Do I have pass any weights? I am bit confused since the
> documentation of nnet suggests says "Wts: initial parameter vector. If
> missing chosen at Random". Has anybody faced the same error? I am
using
> the latest R version on Linux box.
--
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 272866 (PA)
Oxford OX1 3TG, UK Fax: +44 1865 272595
More information about the R-help
mailing list