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.
- Parameters:
y_true (array-like) – Ground truth (correct) labels.
y_pred (array-like) – Predicted labels \(h(X)\) returned by the classifier.
sensitive_features (array-like) – The sensitive features over which demographic parity should be assessed
method (str) – How to compute the differences. See
fairlearn.metrics.MetricFrame.difference()for details.sample_weight (array-like) – The sample weights
- Returns:
The demographic parity difference
- Return type: