[SciPy-user] Academic Question?
conor.robinson at gmail.com
Thu Aug 31 11:41:32 CDT 2006
One 1ofC is a way of encoding categories for a neural network or other model
You can run into problems, however if you have an attribute with lets
say 400 different categories, aka the curse of dimensionality. On one
had you would like your net to consider all categories (given there
are ample examples of each in your training set). RBF functions are
especially bad at this (look into the biological premise of the RBF),
but fast to train. Feed forward nets are better, but slower to train.
In a typical sample you may not have examples of all 400 categories
and you would like to compress your input so the net is looking at
statically relevant information. Im looking into a GA process for
compressing 1ofC, and in general papers or a plethora of information
on encoding and represention. In my opinion the represention problem
is the cornerstone of any model in most cases.
On 8/30/06, Bill Baxter <wbaxter at gmail.com> wrote:
> What is 1ofC? Googling for it didn't turn up anything useful.
> On 8/30/06, Conor Robinson <conor.robinson at gmail.com> wrote:
> > Thanks Aarre,
> > I have both of those resources, they are good, but I'm really looking
> > for a study comparing encoding schema. I've been combing the
> > University California libraries, however most studies use a "hand
> > wave" gesture or don't mention how they encode whatsoever. I've
> > developed a basic technique for compressing 1ofC, but I would like to
> > see what others have done. In bishop around p. 230 he notes you can
> > use cross entropy with sigmoid for probabilities.
> > Conor
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