Add recall_score function in Ivy with Test #27986
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This commit introduces the recall_score function, which calculates recall for binary or multilabel classification using Ivy's framework. The function supports micro, macro, and binary averaging, as well as the optional use of sample weights. Additionally, the code includes appropriate comments for better readability and understanding.
This commit includes a test for the recall_score function, leveraging the Hypothesis library. The test checks the integration of Ivy's recall_score with the specified backend and frontend configurations, covering various input scenarios. The test logic ensures appropriate handling of data types, values, and optional parameters such as 'average' and 'sample_weight'.
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Hi @zeus2x7 , Thank you in advance! |
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Hi @NiteshK84 , It's been a few days since I sent the pull request and I haven't received any feedback from you. I'm wondering if you have had a chance to review it. Please let me know if you have any questions or comments about the pull request. I'm happy to make any changes that you suggest. Thank you for your time and attention. |
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| @handle_frontend_test( | |||
| fn_tree="your.module.path.recall_score", # Update with the correct module path | |||
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Hi @muzakkirhussain011 could you name it correctly with the module path?
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Hi @zeus2x7 , |
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Hi @zeus2x7 , It's been almost a month since I sent the pull request. I have made the required changes. Please let me know if you have any questions or comments about the pull request. I'm happy to make any changes that you suggest. Thank you for your time and attention. |
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Hi @NiteshK84 , It's been almost a month since I sent the pull request. I have made the required changes. Please let me know if you have any questions or comments about the pull request. I'm happy to make any changes that you suggest. Thank you for your time and attention. |
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Hi @muzakkirhussain011, |
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Hi @NiteshK84 All backend tests are now passing with the updated code. Please find the attached screenshot for confirmation. |
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Hi @zeus2x7 , I have completed the backend tests, and all tests are passing successfully. I’ve attached a screenshot of the test results for your reference. Could you please prioritize the review of this pull request at your earliest convenience? Your timely feedback will be greatly appreciated. Thank you |
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Hi @zeus2x7 , I've addressed all the requested changes and the backend tests are passing. Could you please review the updates? Thank you! Best Regards |
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LGTM! |
Co-authored-by: ivy-branch <ivy.branch@lets-unify.ai>
PR Description
This PR introduces the recall_score function in Ivy, supporting binary or multilabel classification. It calculates recall with options for micro, macro, and binary averaging, along with support for sample weights. The code includes clear comments for readability.
A property-based test (test_recall_score) has been added using Hypothesis to ensure the correctness of the recall_score function across diverse input scenarios.
Changes:
Added recall_score function implementation.
Included property-based test (test_recall_score) for comprehensive validation.
Added comments for code clarity
Checklist