Add Wilcoxon's signed rank test#237
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douwekiela
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Aug 9, 2022
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| ```python | ||
| wilcoxon = evaluate.load("wilcoxon") | ||
| results = wilcoxon.compute(predictions1=[-7, 123, 43, 4, 5], predictions2=[1337, -9, 1, 2, 3]) |
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Hrmm should probably make some of these floats to make clear that those are allowed too
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The documentation is not available anymore as the PR was closed or merged. |
lvwerra
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Aug 11, 2022
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Hi @douwekiela, thanks for the super clean PR. Left a comment regarding the feature types related to your own comment.
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| features=datasets.Features( | ||
| { | ||
| "predictions1": datasets.Value("int64"), | ||
| "predictions2": datasets.Value("int64"), | ||
| } | ||
| ), |
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If you want it to work for both int and float you can pass a list of dataset.Features and it then automatically detects which one works. You can have a look at BLEU. Alternatively, I think floats would probably work both cases anyway, no?
mathemakitten
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Aug 15, 2022
Add Wilcoxon's signed rank test for comparing model predictions, e.g. for testing whether the difference in BLEU score between two models is significant.
mathemakitten
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Sep 23, 2022
Add Wilcoxon's signed rank test for comparing model predictions, e.g. for testing whether the difference in BLEU score between two models is significant.
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Figured it'd be good to add a few more comparisons