Try the following: act <- c('good','good','bad','bad','good','good','bad','bad') pred <- c('good','bad','bad','bad','good','good','good','bad') table(pred,act) table(pred,act)/apply(table(pred,act),1,sum)
Cheers, Andreas On 1/3/07, Feng Qiu <[EMAIL PROTECTED]> wrote: > Hi everybody, I'm trying to do a statistic on the error rate of a prediction > algorithm. > > suppose this is the real category > [good, good, bad, bad, good, good, bad, bad] > this is the predicted category > [good, bad, bad, bad, good, good, good, bad] > > I'm trying to do a statistic on the error rate for each group("good","bad"): > what percentage of instances are predicted incorrectly for each group ? > Of course I can write a loop to do that, but is there a easy way to do that? > > Thank you! > > Best, > > Feng > > ______________________________________________ > 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. > ______________________________________________ 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.