plot_ceteris_paribus_cutoff: Ceteris paribus cutoff plot

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

Ceteris paribus cutoff plot

Description

Ceteris paribus cutoff is way to check how will parity loss behave if we changed only cutoff in one subgroup. It plots object of class ceteris_paribus_cutoff. It might have two types - default and cumulated. Cumulated sums metrics and plots it all in one plot. When default one is used all chosen metrics will be plotted for each model.

Usage

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

Arguments

x	ceteris_paribus_cutoff object
...	other plot parameters

Value

ggplot2 object

Examples

data("compas")

# positive outcome - not being recidivist
two_yr_recidivism <- factor(compas$Two_yr_Recidivism, levels = c(1, 0))
y_numeric <- as.numeric(two_yr_recidivism) - 1
compas$Two_yr_Recidivism <- two_yr_recidivism


lm_model <- glm(Two_yr_Recidivism ~ .,
  data = compas,
  family = binomial(link = "logit")
)

explainer_lm <- DALEX::explain(lm_model, data = compas[, -1], y = y_numeric)

fobject <- fairness_check(explainer_lm,
  protected = compas$Ethnicity,
  privileged = "Caucasian"
)

cpc <- ceteris_paribus_cutoff(fobject, "African_American")
plot(cpc)

rf_model <- ranger::ranger(Two_yr_Recidivism ~ .,
  data = compas,
  probability = TRUE,
  num.trees = 200
)

explainer_rf <- DALEX::explain(rf_model, data = compas[, -1], y = y_numeric)

fobject <- fairness_check(explainer_lm, explainer_rf,
  protected = compas$Ethnicity,
  privileged = "Caucasian"
)

cpc <- ceteris_paribus_cutoff(fobject, "African_American")
plot(cpc)

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