[R] nnet learning
Samuel Kemp
sam.kemp2 at ntlworld.com
Mon Oct 18 14:31:57 CEST 2004
Hi,
I am trying to make a neural network learning a "noisy sine wave".
Suppose I generate my data like so..
x <- seq(-2*pi, 2*pi, length=500)
y <- sin(x) + rnorm(500, sd=sqrt(0.075))
I then train the neural net on the first 400 points using
c <- nnet(as.matrix(x[1:400]),as.matrix(y[1:400]), size=3, maxit=10000,
abstol=0.075, decay=0.007)
Inspecting the fit of the training set against the actual values using:
pmat<- plot(y[1:400])
lines(c$fitted.values, col="blue", lwd=2)
It seems as though neural net is not learning the negative values. I
have tried running nnet several times, but each time I get the same
problem. I have also tried upsampling, but no joy.
I suspect that I am not using nnet correctly. Can anyone provide any
hints/solutions?
Any help appreciated.
Kind Regards,
Samuel Kemp.
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