# hasMinimumRecall(_:forPrecision:) Determines whether the observation has a minimum recall value for a specific precision. ``` 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 A Boolean value that indicates whether the classification observation achieves a minimum recall value for a specific precision. ## Discussion The following example uses the `hasMinimumRecall(_:forPrecision)` method to perform a high-precision filter on the results of a `ClassifyImageRequest`. ```swift 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. --- Copyright © 2026 Apple Inc. All rights reserved. | [Terms of Use](https://www.apple.com/legal/internet-services/terms/site.html) | [Privacy Policy](https://www.apple.com/privacy/privacy-policy)