plot.performance_and_fairness {fairmodels} | R Documentation |
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 |
|
... |
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)
[Package fairmodels version 1.2.1 Index]