fairlearn.metrics.demographic_parity_difference#

fairlearn.metrics.demographic_parity_difference(y_true, y_pred, *, sensitive_features, method='between_groups', sample_weight=None)[source]#

Calculate the demographic parity difference.

The demographic parity difference is defined as the difference between the largest and the smallest group-level selection rate, \(E[h(X) | A=a]\), across all values \(a\) of the sensitive feature(s). The demographic parity difference of 0 means that all groups have the same selection rate.

Read more in the User Guide.

Added in version 0.4.6.

Return type:

float

Parameters:
y_truearray_like

Ground truth (correct) labels.

y_predarray_like

Predicted labels \(h(X)\) returned by the classifier.

sensitive_featuresarray_like

The sensitive features over which demographic parity should be assessed

methodstr {‘between_groups’, ‘to_overall’}, default between_groups

How to compute the differences. See fairlearn.metrics.MetricFrame.difference() for details.

sample_weightarray_like

The sample weights

Returns:
float

The demographic parity difference