I have been using the NNET package and have successfully run neural networks
on both continuous and binary targets. I managed to search the internet and
found out how to capture the error resulting from a binary model no
problems. My problem now is that I am trying to find how to calculate an
approriate error when modelling a continuous target. As a statistician I
immediately think of the RMSE, is it possible to calculate such a statistic
from the model? This would require kniowledge of the degrees of freedom in
the model (if there is an equivalent in a neural netwrok!?)  Ideally I would
like the proportion of the RMSE to total error. For example, one criteria of
model fit may be no worse than 10% error rate. It is this sort of statistic
that i am desperate to calc.Any help greatly appreciated.

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