---
title: "hasMinimumRecall(_:forPrecision:)"
framework: vision
role: symbol
role_heading: Instance Method
path: "vision/classificationobservation/hasminimumrecall(_:forprecision:)"
---

# hasMinimumRecall(_:forPrecision:)

Determines whether the observation has a minimum recall value for a specific precision.

## Declaration

```swift
func hasMinimumRecall(_ minimumRecall: Float, forPrecision precision: Float) -> Bool
```

## Parameters

- `minimumRecall`: The minimum desired percentage of all positive classifications that the algorithm correctly classifies.
- `precision`: The percentage of correct positive classifications.

## Return Value

Return Value A Boolean value that indicates whether the classification observation achieves a minimum recall value for a specific precision.

## Discussion

Discussion The following example uses the hasMinimumRecall(_:forPrecision) method to perform a high-precision filter on the results of a ClassifyImageRequest. let results = try await request.perform(on: image)     .filter { $0.hasMinimumRecall(0.01, forPrecision: 0.9) } A high-precision filter retains a smaller number of observations, with less chance to contain false positives. Testing can help determine the balance point between the minimumRecall and precision values to return the best results for a specific use case.

## See Also

### Determining precision and recall

- [hasMinimumPrecision(_:forRecall:)](vision/classificationobservation/hasminimumprecision(_:forrecall:).md)