# it allows two different plots in the same frame par(mfrow = c(1,2)) # plot a ROC curve for a single prediction run # and color the curve according to cutoff. library(ROCR) data(ROCR.simple) pred <- prediction(ROCR.simple$predictions, ROCR.simple$labels) perf <- performance(pred,"tpr", "fpr") plot(perf,colorize = TRUE) # plot a ROC curve for a single prediction run # with CI by bootstrapping and fitted curve library(verification) roc.plot(ROCR.simple$labels,ROCR.simple$predictions, xlab = "False positive rate", ylab = "True positive rate", main = NULL, CI = T, n.boot = 100, plot = "both", binormal = TRUE)
giovedì 2 agosto 2007
Receiver Operating Characteristic (ROC) Curve in ROCR and verification packages
The following VERY basic code shows how to plot a simple ROC Curve both by means of ROCR package and by verification package.