plot_stacked_metrics: Plot stacked Metrics

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

Plot stacked Metrics

Description

Stacked metrics is like plot for chosen_metric but with all unique metrics stacked on top of each other. Metrics containing NA's will be dropped to enable fair comparison.

Usage

## S3 method for class 'stacked_metrics'
plot(x, ...)

Arguments

x	stacked_metrics object
...	other plot parameters

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"
)

sm <- stack_metrics(fobject)
plot(sm)


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)

sm <- stack_metrics(fobject)
plot(sm)

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