Weighted AUC from Outlier Scores — wauc_from

Computes the weighted AUC with the weighting scheme described in Kamulete, V. M. (2021). This assumes that the training set is the reference distribution and specifies a particular functional form to derive weights from threshold scores.

wauc_from_os(os_train, os_test, weight = NULL)

Arguments

os_train: Outlier scores in training (reference) set.
os_test: Outlier scores in test set.
weight: Numeric vector of weights of length length(os_train) + length(os_test). The first length(os_train) weights belongs to the training set, the rest is for the test set. If NULL, the default, all weights are set to 1.

Value

The weighted AUC (scalar value) given the weighting scheme.

References

Kamulete, V. M. (2022). Test for non-negligible adverse shifts. In The 38th Conference on Uncertainty in Artificial Intelligence. PMLR.

Examples

# \donttest{
library(dsos)
set.seed(12345)
os_train <- rnorm(n = 100)
os_test <- rnorm(n = 100)
test_stat <- wauc_from_os(os_train, os_test)
# }