# hasMinimumPrecision(_:forRecall:) Determines whether the observation has a minimum precision value for a specific recall. ``` func hasMinimumPrecision(_ minimumPrecision: Float, forRecall recall: Float) -> Bool ``` ## Parameters `minimumPrecision` The minimum desired percentage of correct positive classifications. `recall` The percentage of all positive classifications that the algorithm correctly classified. ## Return Value A Boolean value that indicates whether the classification observation provides a minimum percentage of correct results that meet the desired recall. ## Discussion The following example uses the `hasMinimumPrecision(_:forRecall)` method to perform a high-recall filter on the results of a `ClassifyImageRequest`: ```swift let results = try await request.perform(on: image) .filter { $0.hasMinimumPrecision(0.1, forRecall: 0.8) } ``` A high-recall filter retains a much broader range of observations, but can result in more false positive results. Testing can help determine the balance point between the `minimumPrecision` and `recall` 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)