DATA MINING
Desktop Survival Guide by Graham Williams |
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pdf("graphics/rplot-rocr-survey-tpfp.pdf") library(rpart) library(ROCR) load("survey.Rdata") survey.rp <- rpart(Salary.Group ~ ., data=survey) survey.pred <- predict(survey.rp, data=survey) pred <- prediction(survey.pred[,2], survey$Salary.Group) perf <- performance(pred, "tpr", "fpr") plot(perf) dev.off() |