[R] How to use AUC metric in caret

[Neha gupta]

Hello everyone

I am using nested resampling in caret (5-fold outer and bootstrap inner
resampling) and by default, it shows the "Accuracy" metric. How can I use
it for the ROC/AUC metric?

My code is:

d=readARFF("apns.arff")
index <- createDataPartition(d$isKilled , p = .70,list = FALSE)
tr <- d[index, ]
ts <- d[-index, ]

boot <- trainControl(method = "boot", number=100, search="random",
classProbs = TRUE, summaryFunction = twoClassSummary)

outer_folds <- createFolds(d$isKilled, k = 5)
boot <- trainControl(method = "boot", number=10)

CV1 <- lapply(outer_folds, function(index){
  tr <- d[-index, ]
  ts <- d[index,]

  cart1 <-train(isKilled ~ ., data = tr,
                method = "rpart",

                    tuneLength = 20,
                 metric = "Accuracy",
                 preProc = c("center", "scale", "nzv"),
                 trControl = boot)

  postResample(predict(cart1, ts), ts$isKilled)
})
sapply(CV1, function(x) x[3]) -> CV_MAE1
CV_MAE1

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