compute_loss: Compute the FARO Loss Between Feature Allocations

In fangs: Feature Allocation Neighborhood Greedy Search Algorithm

Compute the FARO Loss Between Feature Allocations

Description

The FARO loss is computed between two feature allocations, each represented in binary matrix form.

Usage

compute_loss(Z1, Z2, a = 1, augmented = FALSE)

Arguments

Z1	A feature allocation in binary matrix form, with items in the rows and features in the columns.
Z2	A feature allocation in binary matrix form, with items in the rows and features in the columns.
a	A numeric scalar for the cost parameter of generalized Hamming distance used in FARO loss. The other cost parameter, b, is equal to 2 - a.
augmented	If TRUE, the column permutation (used by FARO loss to compare the feature allocations) is returned for each matrix.

Value

The FARO loss as a scalar value if augmented = FALSE, otherwise, a list of 3 elements including the loss and the two column permutations.

References

D. B. Dahl, D. J. Johnson, R. J. Andros (2023), Comparison and Bayesian Estimation of Feature Allocations, Journal of Computational and Graphical Statistics, \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1080/10618600.2023.2204136")}.

Examples

Z1 <- matrix(c(0,1,1,0,1,1,0,1,1,1,1,1), byrow=TRUE, nrow=6)
Z2 <- matrix(c(0,0,1,0,0,0,0,0,0,0,0,0,1,1,1,0,1,0), byrow=TRUE, nrow=6)
compute_loss(Z1,Z2)
x <- compute_loss(Z1,Z2,a=1,TRUE)
sum(cbind(Z1,0) != Z2)
sum(cbind(Z1,0)[,x$permutation1] != Z2)
sum(cbind(Z1,0) != Z2[,x$permutation2])

fangs documentation built on April 11, 2025, 5:51 p.m.