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@pnucci pnucci commented Feb 6, 2023

Clearer and more illustrative description about the beta parameter. The original text mentions "weight of recall", without being clear that it's a ratio. Two intuitive examples are added, instead of discussing the asymptotic behaviour of beta.

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What does this implement/fix? Explain your changes.

Simple improvement in the documentation for f_beta_score, to make it more accurate and pragmatic.

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Clearer and more illustrative description about the `beta` parameter
@pnucci pnucci closed this Feb 6, 2023
@pnucci pnucci reopened this Feb 6, 2023
@pnucci pnucci changed the title [MRG] Better documentation for f_beta_score DOC Clearer and more illustrative description for f_beta_score Feb 6, 2023
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Thank you for the PR @pnucci !

Co-authored-by: Thomas J. Fan <thomasjpfan@gmail.com>
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@thomasjpfan just one thing: with that suggestion, we lost the word "importance". Now we are saying "ratio of recall to precision". I still believe we should say something like
"ratio of recall importance to precision importance"
or
"importance ratio of recall to precision"
after all, beta is not a ratio of the metrics, just a ratio of their importance/weights
what are your thoughts?

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thomasjpfan commented Feb 8, 2023

I was trying to think of a way not to say importance twice. In any case, I am okay with your original suggestion:

ratio of recall importance to precision importance

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pnucci commented Apr 17, 2023

Hi @thomasjpfan, are you ok with the last proposal? are we good to approve it?
Cheers

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Thank you for the update! LGTM

@thomasjpfan thomasjpfan added Quick Review For PRs that are quick to review Waiting for Second Reviewer First reviewer is done, need a second one! labels May 16, 2023
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LGTM as it is. Thanks @pnucci!

@thomasjpfan thomasjpfan merged commit 6d356dd into scikit-learn:main May 22, 2023
REDVM pushed a commit to REDVM/scikit-learn that referenced this pull request Nov 16, 2023
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3 participants