fairlearn.metrics.equal_opportunity_ratio#
- fairlearn.metrics.equal_opportunity_ratio(y_true, y_pred, *, sensitive_features, method='between_groups', sample_weight=None)[source]#
Calculate the equal opportunity ratio.
The equal opportunity ratio is defined as the ratio between the smallest and the largest group-level true positive rate,
, across all values of the sensitive feature(s). The equal opportunity ratio of 1 means that all groups have the same true positive rate.Read more in the User Guide.
- Return type:
- Parameters:
- y_truearray-like
Ground truth (correct) labels.
- y_predarray-like
Predicted labels
returned by the classifier.- sensitive_featuresarray-like
The sensitive features over which equal opportunity should be assessed
- methodstring {‘between_groups’, ‘to_overall’}, default
between_groups
How to compute the differences. See
fairlearn.metrics.MetricFrame.ratio()
for details.- sample_weightarray-like
The sample weights
- Returns:
- float
The equal opportunity ratio