MeasureFairnessComposite {mlr3fairness}R Documentation

Composite Fairness Measure

Description

Computes a composite measure from multiple fairness metrics and aggregates them using aggfun (defaulting to mean()).

Protected Attributes

The protected attribute is specified as a col_role in the corresponding Task():
⁠<Task>$col_roles$pta = "name_of_attribute"⁠
This also allows specifying more than one protected attribute, in which case fairness will be considered on the level of intersecting groups defined by all columns selected as a predicted attribute.

Super class

mlr3::Measure -> MeasureFairnessComposite

Methods

Public methods

Inherited methods

Method new()

Creates a new instance of this R6 class.

Usage
MeasureFairnessComposite$new(
  id = NULL,
  measures,
  aggfun = function(x) mean(x),
  operation = groupdiff_absdiff,
  minimize = TRUE,
  range = c(-Inf, Inf)
)
Arguments
id

(character(1))
Id of the measure. Defaults to the concatenation of ids in measure.

measures

(list of MeasureFairness)
List of fairness measures to aggregate.

aggfun

(⁠function()⁠)
Aggregation function used to aggregate results from respective measures. Defaults to sum.

operation

(⁠function()⁠)
The operation used to compute the difference. A function that returns a single value given input: computed metric for each subgroup. Defaults to groupdiff_absdiff. See MeasureFairness for more information.

minimize

(logical(1))
Should the measure be minimized? Defaults to TRUE.

range

(numeric(2))
Range of the resulting measure. Defaults to c(-Inf, Inf).

Method clone()

The objects of this class are cloneable with this method.

Usage
MeasureFairnessComposite$clone(deep = FALSE)
Arguments
deep

Whether to make a deep clone.

Examples

library("mlr3")
# Equalized Odds Metric
MeasureFairnessComposite$new(measures = msrs(c("fairness.fpr", "fairness.tpr")))

# Other metrics e.g. based on negative rates
MeasureFairnessComposite$new(measures = msrs(c("fairness.fnr", "fairness.tnr")))
[Package mlr3fairness version 0.3.2 Index]