print_stacked_metrics: Print stacked metrics

In ModelOriented/FairModels: Flexible Tool for Bias Detection, Visualization, and Mitigation

Print stacked metrics

Description

Stack metrics sums parity loss metrics for all models. Higher value of stacked metrics means the model is less fair (has higher bias) for subgroups from protected vector.

Usage

## S3 method for class 'stacked_metrics'
print(x, ...)

Arguments

x	stacked_metrics object
...	other print parameters

Examples

data("german")

y_numeric <- as.numeric(german$Risk) - 1

lm_model <- glm(Risk ~ .,
  data = german,
  family = binomial(link = "logit")
)

rf_model <- ranger::ranger(Risk ~ .,
  data = german,
  probability = TRUE,
  num.trees = 200,
  num.threads = 1
)

explainer_lm <- DALEX::explain(lm_model, data = german[, -1], y = y_numeric)
explainer_rf <- DALEX::explain(rf_model, data = german[, -1], y = y_numeric)

fobject <- fairness_check(explainer_lm, explainer_rf,
  protected = german$Sex,
  privileged = "male"
)

sm <- stack_metrics(fobject)
print(sm)

ModelOriented/FairModels documentation built on Aug. 30, 2022, 5:48 p.m.