This is almost unreadable (is your space bar broken?) but you seem to be
missing the non-linearity of the hidden units.
The definition is in the book nnet (sic) supports, in a layout I cannot
reproduce in plain text.
On Mon, 16 Jul 2007, dos Reis, Marlon wrote:
> Hello,
> I've been working with "nnet" and now I'd like to use
the weigths, from
> the fitted model, to iterpret some of variables impornatce.
> I used the following command:
> mts <- nnet(y=Y,x=X,size =4, rang = 0.1,
> decay = 5e-4, maxit = 5000,linout=TRUE)
> X is (m x n) Y is (m x 1)
> And then I get the coeficients by:
> Wts<-coef(mts)
>
> b->h1 i1->h1 i2->h1 i3->h1
i4->h1
> i5->h1 i6->h1 i7->h1 ...
> b->o h1->o h2->o h3->o h4->o
...
>
> I understood that I should get the predicted Y (hat(Y)) by:
>
> hat(Y)>
(b->o)+((b->h1)sum(X[,1:m]*Wts[i1:m-h1]+X[,1:m]*Wts[i1:m-h2]+...+X[,1:m]
> *Wts[i1:m-h4]))*(h1->o)+
> ((b->h2)sum(X[,1:m]*Wts[i1:m-h2]+X[,1:m]*Wts[i1:m-h2]+...+X[,1:m]*Wts[i1
> :m-h4]))*(h2->o)+...)
> Am I missed some point on this definition of NNET.
> Thanks in advance,
> Best Regards,
> Marlon !!!
>
>
> ======================================================================>
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--
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)
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