fairmodels (version 1.1.0)

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, ...)

Arguments

x

performance_and_fairness object

...

other plot parameters

Value

ggplot object

Examples

# NOT RUN {
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)

# }
# NOT RUN {
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)

# }