aif360.sklearn.metrics.ratio

aif360.sklearn.metrics.ratio(func, y_true, y_pred=None, prot_attr=None, priv_group=1, sample_weight=None, zero_division='warn', **kwargs)[source]

Compute the ratio between unprivileged and privileged subsets for an arbitrary metric.

Note: The optimal value of a ratio is 1. To make it a scorer, one must take the minimum of the ratio and its inverse.

Unprivileged group is taken to be the inverse of the privileged group.

Parameters:

  • func (function) – A metric function from sklearn.metrics or aif360.sklearn.metrics.

  • y_true (pandas.Series) – Outcome vector with protected attributes as index.

  • y_pred (array-like, optional) – Estimated outcomes.

  • prot_attr (array-like, keyword-only) – Protected attribute(s). If None, all protected attributes in y are used.

  • priv_group (scalar, optional) – The label of the privileged group.

  • sample_weight (array-like, optional) – Sample weights passed through to func.

  • zero_division ('warn', 0 or 1) – Sets the value to return when there is a zero division. If set to “warn”, this acts as 0, but warnings are also raised.

  • **kwargs – Additional keyword args to be passed through to func.

Returns:

scalar – Ratio of metric values for unprivileged and privileged groups.