Dear all,
I want to measure the goodness of prediction of my linear model. That's why I was thinking about the area under roc curve. I'm trying the following, but I don't know how to avoid the error. Any help would be appreciated. library(ROCR) model.lm <- lm(log(outcome)~log(v1)+log(v2)+factor1) pred<-predict(model.lm) pred<-prediction(as.numeric(pred), as.numeric(log(outcome))) auc<-performance(pred,"auc") Error en prediction(as.numeric(pred), as.numeric(log(outcome))) : Number of classes is not equal to 2. ROCR currently supports only evaluation of binary classification tasks. u...@host.com -- View this message in context: http://r.789695.n4.nabble.com/area-under-roc-curve-tp3447420p3447420.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help@r-project.org 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.
