Pick the one with the lowest error rate on your training data? Hadley On 5/7/07, Wensui Liu <[EMAIL PROTECTED]> wrote: > well, how to do you know which ones are the best out of several hundreds? > I will average all results out of several hundreds. > > On 5/7/07, hadley wickham <[EMAIL PROTECTED]> wrote: > > On 5/6/07, nathaniel Grey <[EMAIL PROTECTED]> wrote: > > > Hello R-Users, > > > > > > I have been using (nnet) by Ripley to train a neural net on a test > > > dataset, I have obtained predictions for a validtion dataset using: > > > > > > PP<-predict(nnetobject,validationdata) > > > > > > Using PP I can find the -2 log likelihood for the validation datset. > > > > > > However what I really want to know is how well my nueral net is doing at > > > classifying my binary output variable. I am new to R and I can't figure > > > out how you can assess the success rates of predictions. > > > > > > > table(PP, binaryvariable) > > should get you started. > > > > Also if you're using nnet with random starts, I strongly suggest > > taking the best out of several hundred (or maybe thousand) trials - it > > makes a big difference! > > > > Hadley > > > > ______________________________________________ > > [email protected] mailing list > > https://stat.ethz.ch/mailman/listinfo/r-help > > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > > and provide commented, minimal, self-contained, reproducible code. > > > > > -- > WenSui Liu > A lousy statistician who happens to know a little programming > (http://spaces.msn.com/statcompute/blog) >
______________________________________________ [email protected] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
