DOC Ensures that top_k_accuracy_score passes numpydoc validation#24259
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thomasjpfan merged 1 commit intoscikit-learn:mainfrom Aug 26, 2022
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Thank you for the PR! LGTM
Also, should I update the jaccard_score's accuracy_score description to match?
I would welcome this update in another PR. When merging, we squash PRs where the title becomes the commit message, so we prefer PRs to be as self contained as possible.
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Reference Issues/PRs
This pull request addresses #21350.
What does this implement/fix? Explain your changes.
sklearn.metrics._ranking.top_k_accuracy_scorestring fromFUNCTION_DOCSTRING_IGNORE_LISTat docstring's test file.Any other comments?
When I was looking for what exactly to add for the
accuracy_scoredescription I did agrep -r "accuracy_score : " sklearn/metricsand found this 3 instances whereaccuracy_scoreappears on "See Also" section (respectively forjaccard_score,zero_one_lossandhamming_loss):scikit-learn/sklearn/metrics/_classification.py
Lines 745 to 747 in feaf382
scikit-learn/sklearn/metrics/_classification.py
Lines 956 to 960 in feaf382
scikit-learn/sklearn/metrics/_classification.py
Lines 2431 to 2435 in feaf382
As the
zero_one_lossandhamming_lossdescription of theaccuracy_scorelooked more complete I decided to go with theirs for now. To be honest, I don't know what would be the best pattern you prefer. A loat of this "See Also" description are very straightforward, such as:scikit-learn/sklearn/metrics/_classification.py
Line 2436 in feaf382
Also, should I update the
jaccard_score'saccuracy_scoredescription to match? I'm just raising this because I think it would make sense if all the "See Also" descriptions were equal. But I don't know if you are concerned about this.Thanks in advance for the reviews! :D