fairmodels (version 1.2.1)

print.stacked_metrics: 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 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)