I am trying to compare several models of classification tree using the ROCR package
however, the x-axis
in this package correspond to the rate of positive prediction
whereas in every blog/forum where I searched it corresponds to the population%
.
Therefore I don't have any idea how to interpret the curves I have.
You can find below the code I wrote for each model and the plots :
for (i in 1:nfold) {
tree.result[[i]]$roc$prediction <- prediction(tree.result[[i]]$data$predProb, tree.result[[i]]$data$real)
tree.result[[i]]$roc$lift <- performance(tree.result[[i]]$roc$prediction, "lift", "rpp")
}
# nfold = number of split in the data/number of models
plot(tree.result$model.1$roc$lift, col="blue")
plot(tree.result$model.2$roc$lift, add=TRUE,col="red")
plot(tree.result$model.3$roc$lift, add=TRUE,col="green")
Result :
Do you know how to interpret this curve ? Is it exactly the same principle than with population%
in abscissa?