plot_performance_and_fairness: Plot fairness and performance

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

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 class 'performance_and_fairness'
plot(x, ...)

Arguments

x	performance_and_fairness object
...	other plot parameters

Value

ggplot object

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)


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)

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