plot.fairness_object {fairmodels} | R Documentation |
Plot fairness object
Description
Plot fairness check enables to look how big differences are between base subgroup (privileged) and unprivileged ones.
If bar plot reaches red zone it means that for this subgroup fairness goal is not satisfied. Multiple subgroups and models can be plotted.
Red and green zone boundary can be moved through epsilon parameter, that needs to be passed through fairness_check
.
Usage
## S3 method for class 'fairness_object'
plot(x, ..., fairness_metrics = c("ACC", "TPR", "PPV", "FPR", "STP"))
Arguments
x |
|
... |
other plot parameters |
fairness_metrics |
character, vector of metrics. Subset of fairness metrics to be used. The full set is defined as c("ACC", "TPR", "PPV", "FPR", "STP"). |
Value
ggplot2
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"
)
plot(fobject)
rf_model <- ranger::ranger(Risk ~ .,
data = german,
probability = TRUE,
max.depth = 3,
num.trees = 100,
seed = 1
)
explainer_rf <- DALEX::explain(rf_model,
data = german[, -1],
y = y_numeric
)
fobject <- fairness_check(explainer_rf, fobject)
plot(fobject)
# custom print
plot(fobject, fairness_metrics = c("ACC", "TPR"))
[Package fairmodels version 1.2.1 Index]