fairlearn.metrics.demographic_parity_ratio#

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

Calculate the demographic parity ratio.

The demographic parity ratio is defined as the ratio between the smallest and the largest group-level selection rate, \(E[h(X) | A=a]\), across all values \(a\) of the sensitive feature(s). The demographic parity ratio of 1 means that all groups have the same selection rate.

Read more in the User Guide.

Added in version 0.4.6.

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 (Literal['between_groups', 'to_overall']) – How to compute the differences. See fairlearn.metrics.MetricFrame.ratio() for details.

  • sample_weight (array_like) – The sample weights

Return type:

float

Returns:

The demographic parity ratio