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# MultiLabelClassificationMetrics.ThresholdSelectionStrategy.precision(_:minimumRecall:)

A confidence threshold strategy for a specific precision that has at least a minimum recall value.

```
case precision(Float, minimumRecall: Float)
```

## Discussion

This strategy selects a threshold for each label by searching for the specified precision value on the label’s
precision-recall curve. At the precision, the recall must be greater than or equal to the minimum recall value,
otherwise a NaN threshold for the corresponding label is returned.

Use this strategy to reduce the rate of false-positive predictions while constraining the false-negative
predictions.

---

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