fairmodels (version 1.2.1)

plot.performance_and_fairness: Plot fairness and performance

Description

visualize fairness and model metric at the same time. Note that fairness metric parity scale is reversed so that the best models are in top right corner.

Usage

# S3 method for performance_and_fairness
plot(x, ...)

Value

ggplot object

Arguments

x

performance_and_fairness object

...

other plot parameters

Examples

data("german")

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

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


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

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

paf <- performance_and_fairness(fobject)
plot(paf)
# \donttest{

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

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

fobject <- fairness_check(explainer_rf, fobject)

# same explainers with different cutoffs for female
fobject <- fairness_check(explainer_lm, explainer_rf, fobject,
  protected = german$Sex,
  privileged = "male",
  cutoff = list(female = 0.4),
  label = c("lm_2", "rf_2")
)

paf <- performance_and_fairness(fobject)

plot(paf)
# }