# WeightedAUC: WeightedAUC In WeightedROC: Fast, Weighted ROC Curves

## Description

Calculate the exact area under the ROC curve.

## Usage

 `1` ```WeightedAUC(tpr.fpr) ```

## Arguments

 `tpr.fpr` Output of `WeightedROC`: data.frame with the true positive rate (TPR) and false positive rate (FPR).

Numeric scalar.

## Author(s)

Toby Dylan Hocking

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40``` ```library(WeightedROC) ## Compute the AUC for this weighted data set. y <- c(0, 0, 1, 1, 1) w <- c(1, 1, 1, 4, 5) y.hat <- c(1, 2, 3, 1, 1) tp.fp <- WeightedROC(y.hat, y, w) (wauc <- WeightedAUC(tp.fp)) ## For the un-weighted ROCR example data set, verify that our AUC is ## the same as that of ROCR/pROC. if(require(microbenchmark) && require(ROCR) && require(pROC)){ data(ROCR.simple, envir=environment()) microbenchmark(WeightedROC={ tp.fp <- with(ROCR.simple, WeightedROC(predictions, labels)) wroc <- WeightedAUC(tp.fp) }, ROCR={ pred <- with(ROCR.simple, prediction(predictions, labels)) rocr <- performance(pred, "auc")@y.values[[1]] }, pROC={ proc <- pROC::auc(labels ~ predictions, ROCR.simple, algorithm=2) }, times=10) rbind(WeightedROC=wroc, ROCR=rocr, pROC=proc) #same } ## For the un-weighted pROC example data set, verify that our AUC is ## the same as that of ROCR/pROC. data(aSAH, envir=environment()) table(aSAH\$s100b) if(require(microbenchmark)){ microbenchmark(WeightedROC={ tp.fp <- with(aSAH, WeightedROC(s100b, outcome)) wroc <- WeightedAUC(tp.fp) }, ROCR={ pred <- with(aSAH, prediction(s100b, outcome)) rocr <- performance(pred, "auc")@y.values[[1]] }, pROC={ proc <- pROC::auc(outcome ~ s100b, aSAH, algorithm=2) }, times=10) rbind(WeightedROC=wroc, ROCR=rocr, pROC=proc) } ```

WeightedROC documentation built on Feb. 1, 2020, 9:07 a.m.