auc: Area under the ROC curve (AUC)

In BruceZhaoR/pjutils: Pingjia data calculation tools

Description

auc computes the area under the receiver-operator characteristic curve (AUC).

Usage

auc(actual, predicted)

Arguments

actual	The actual value.
predicted	A numeric vector of predicted values, where the smallest values correspond to the observations most believed to be in the negative class and the largest values indicate the observations most believed to be in the positive class. Each element represents the prediction for the corresponding element in actual.

Details

auc uses the fact that the area under the ROC curve is equal to the probability that a randomly chosen positive observation has a higher predicted value than a randomly chosen negative value. In order to compute this probability, we can calculate the Mann-Whitney U statistic. This method is very fast, since we do not need to compute the ROC curve first.

Author(s)

@mfrasco

Examples

actual <- c(1, 1, 1, 0, 0, 0)
predicted <- c(0.9, 0.8, 0.4, 0.5, 0.3, 0.2)
auc(actual, predicted)

BruceZhaoR/pjutils documentation built on May 20, 2019, 11:38 a.m.