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 <[EMAIL PROTECTED]>: > 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. > > > > ______________________________________________ > > [EMAIL PROTECTED] mailing list > > https://www.stat.math.ethz.ch/mailman/listinfo/r-help > > PLEASE do read the posting guide! > http://www.R-project.org/posting-guide.html > > > > ______________________________________________ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html