[R] nnet classification accuracy vs. other models

[Albedo]

The only thing that I could have done wrong with nnet
(that I 
can think of) is not enough nuerons in hidden layer,
but then
again this is actually limited by my computer memory.

However, I did estimate the error a little bit
different - I have
enough data for test set, which I used for classification
accuracy estimation only.

 Edgar Acuna <edgar at cs.uprm.edu>:

> I think that you are using nnet incorrectly. I have
compared several
> classifiers (including that ones that you mention in
your e-mail) on the
> same dataset and I have never found more of a 20% of
difference in the
> missclassification error. Of course, I estimated the
misclassification
> error by cross validation.
>
> Regards
> Edgar Acuna
> UPR-MATH
>
> On Sat, 13 Mar 2004, Albedo wrote:
>
> > I was wandering if anybody ever tried to compare
the classification
> > accuracy of nnet to other (rpart, tree, bagging)
models. From what I
> > know, there is no reason to expect a significant
difference in
> > classification accuracy between these models, yet
in my particular case
> > I get about 10% error rate for tree, rpart and
bagging model and 80%
> > error rate for nnet, applied to the same data.
> >
> > Thanks.
> >
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