unweighted_average_recall()

audmetric.unweighted_average_recall(truth, prediction, labels=None, *, zero_division=0)

Unweighted average recall.

$$\text{UAR} = \frac{1}{K} \sum^K_{k=1} \frac{\text{true positive}_k} {\text{true positive}_k + \text{false negative}_k}$$

Parameters

• truth (Sequence[Any]) – ground truth values/classes

• prediction (Sequence[Any]) – predicted values/classes

• labels (Optional[Sequence[Any]]) – included labels in preferred ordering. If no labels are supplied, they will be inferred from $\{\text{prediction}, \text{truth}\}$ and ordered alphabetically.

• zero_division (float) – set the value to return when there is a zero division

Return type

float

Returns

unweighted average recall

Examples

>>> unweighted_average_recall([0, 0], [0, 1])
0.25