Generate a fairness summary report

Usage

fairness_report(data, metrics = NULL)

Arguments

data: A fairness_data object.
metrics: A fairness_metrics object. If NULL, computed automatically.

Value

A fairness_report (list) with $summary, $flags, $recommendation.

Examples

set.seed(42)
fd <- fairness_data(
  predictions = c(runif(100, 0.2, 0.8), runif(100, 0.3, 0.9)),
  labels = c(rbinom(100, 1, 0.3), rbinom(100, 1, 0.5)),
  protected_attr = rep(c("A", "B"), each = 100)
)
fairness_report(fd)
#> 
#> ── Fairness Report 
#> Reference group: "B"
#> 
#> ! 3 disparity flag(s):
#> A / selection_rate: ratio = 0.797
#> A / fpr: ratio = 0.757
#> A / ppv: ratio = 0.567
#> 
#> 3 metric(s) violate the four-fifths rule (ratio outside [0.8, 1.25]). Consider
#> threshold adjustment or model recalibration.