bootstrappedROC: bootstrappedROC

In Peder2911/evallib: Simple binary classifier evaluation

Description

Helper function that makes ROC graph data from predictions and outcomes with confidence intervals and standard deviation.

Usage

bootstrappedROC(pred, actual, res, draws = 100, parallel = FALSE)

Arguments

pred	Probability predictions
actual	Outcomes
res	Resolution of ROC thresholds. A float between 0 and 1.
draws	Number of times to randomly sample the data for bootstrapping. Larger numbers yield better results, but also increase runtime.

Details

Note that the function requires specification of the resolution, since it must be possible to collapse the results into an array.

Value

A list containing ROC data and AUC with confidence intervals.

Examples

pred <- sample(seq(0,1,0.001), size = 150, replace = TRUE)
actual <- sample(c(0,1), size = 150, replace = TRUE)
bootstrappedROC(pred,actual,roc)

Peder2911/evallib documentation built on Dec. 18, 2019, 2:41 a.m.