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 ______________________________________________ R-help@stat.math.ethz.ch 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.
