auc_matrix: Compute AUC from matrix labels

In xplus: Positive and Unlabeled Learning from Unbalanced Cases and Sparse Structures

Compute AUC from matrix labels

Description

Compute AUC from matrix labels

Usage

auc_matrix(y, prob, weights = NULL)

Arguments

y	Two-column finite nonnegative class masses (negative, positive); soft labels, counts, and zero-mass rows are supported.
prob	Finite numeric scores, one per row; values outside ⁠[0, 1]⁠ are allowed.
weights	Optional finite nonnegative numeric row weights without recycling; NULL means unit weights.

Value

Weighted rank AUC with half credit for ties; NA with a warning if either effective class mass is zero.

References

Zhou et al. (2022). doi:10.1371/journal.pcbi.1009956

See Also

auc(), assess()

Examples

y <- cbind(c(1, 1, 0, 0), c(0, 0, 1, 1))
p <- c(0.2, 0.3, 0.7, 0.8)
auc_matrix(y, p)

xplus documentation built on Sept. 26, 2026, 5:07 p.m.