fairmodels (version 1.2.1)

plot_fairmodels: Plot fairmodels

Description

Easier access to all plots in fairmodels. Provide plot type (that matches to function name), pass additional parameters and plot.

Usage

plot_fairmodels(x, type, ...)
# S3 method for explainer
plot_fairmodels(x, type = "fairness_check", ..., protected, privileged)
# S3 method for fairness_object
plot_fairmodels(x, type = "fairness_check", ...)
# S3 method for default
plot_fairmodels(x, type = "fairness_check", ...)

Value

ggplot2 object

Arguments

x

object created with fairness_check or with explain

type

character, type of plot. Should match function name in fairmodels. Default is fairness_check.

...

other parameters passed to fairmodels functions.

protected

factor, vector containing sensitive attributes such as gender, race, etc...

privileged

character/factor, level in factor denoting privileged subgroup

Details

types (function names) available:

• fairness_check

• stack_metrics

• fairness_heatmap

• fairness_pca

• fairness_radar

• group_metric

• choose_metric

• metric_scores

• performance_and_fairness

• all_cutoffs

• ceteris_paribus_cutoff

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)

# works with explainer when protected and privileged are passed
plot_fairmodels(explainer_lm,
  type = "fairness_radar",
  protected = german$Sex,
  privileged = "male"
)

# or with fairness_object
fobject <- fairness_check(explainer_lm,
  protected = german$Sex,
  privileged = "male"
)

plot_fairmodels(fobject, type = "fairness_radar")