Re: Interpolating data to find "new" training exemplars
Jeff Goslin wrote:
"Actually, the data is going to be used to train a neural net to
simulate the operation of a pancreas. As you know, the pancreas has no
knowledge, by itself, of when you are going to eat, exercise, and do
other things that affect blood sugar readings, or the release of insulin
into the bloodstream. The only thing that the pancreas has as any kind
of input is the current glucose level in the bloodstream as compared to
a short time ago, and it uses this input as a basis for how much insulin
to produce, or output."
In most situations I can imagine, this (interpolating historical data to
find "new" training exemplars) is not a good idea. The presumed "new"
exemplars are very synthetic and reflect the interpolation procedure as
much as they do the data. I would think that (unless you have a very
good reason for doing otherwise), your model (neural network or any
other empirical model) would better reflect reality by using only the
actual historical exemplars.
Will Dwinnell
[EMAIL PROTECTED]
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