DOC use the arxiv directive in the docstrings

[SultanOrazbayev]

Reference Issues/PRs

References #21088

• update :arxiv:

What does this implement/fix? Explain your changes.

Update docstrings to use consistent naming of :arxiv: links.

Any other comments?

Together with @aufarkari we updated the :arxiv: links only (so :doi: still need to be updated in a separate PR).

[ogrisel]

Did you address all the remaining arxiv links in one single PR?

If not please put the names of the code / doc modules in the title of the PR so that others can see more specifically what this PR is about.

[cmarmo]

Thanks @SultanOrazbayev the lint check is failing with the following error

sklearn/linear_model/_sag.py:233:1: W293 blank line contains whitespace

Do you mind fixing the check? Thanks!
You can find more details about the lint check on this page.

[SultanOrazbayev]

Thanks @SultanOrazbayev the lint check is failing with the following error

sklearn/linear_model/_sag.py:233:1: W293 blank line contains whitespace

Do you mind fixing the check? Thanks! You can find more details about the lint check on this page.

Sorry about this, I was using the web editor, so this slipped through.

[cmarmo]

Hi @aufarkari , thanks for your follow-up. You need to fix conflicts before adding new modifications. You might want to have a look to the github documentation for this.

[aufarkari]

Noted. I will edit accordingly.

…

On Sun, Dec 19, 2021 at 9:37 PM Chiara Marmo ***@***.***> wrote: ***@***.**** commented on this pull request. Hi @aufarkari <https://github.com/aufarkari> , thanks for your follow-up. You need to fix conflicts before adding new modifications. You might want to have a look to the github documentation <https://docs.github.com/en/pull-requests/collaborating-with-pull-requests/addressing-merge-conflicts/resolving-a-merge-conflict-using-the-command-line> for this. ------------------------------ In sklearn/cluster/_hierarchical_fast.pyx <#21418 (comment)> : > @@ -451,7 +451,7 @@ def single_linkage_label(L): return _single_linkage_label(L) -# Implements MST-LINKAGE-CORE from https://arxiv.org/abs/1109.2378 +# Implements MST-LINKAGE-CORE from :arxiv:`<1109.2378>` This link is commented out, then not rendered in the documentation (see my previous comment <#21418 (comment)> ). I believe it is better to revert this change, otherwise the link is not copy-pastable. ------------------------------ In sklearn/ensemble/_hist_gradient_boosting/splitting.pyx <#21418 (comment)> : > @@ -500,7 +500,7 @@ cdef class Splitter: # case yields the best gain: either missing values go to # the right (left to right scan) or to the left (right to # left case). See algo 3 from the XGBoost paper - # https://arxiv.org/abs/1603.02754 + # :arxiv:`<1603.02754>` Same comment as before. — Reply to this email directly, view it on GitHub <#21418 (review)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/AF5XLH2MX7S3TYX45DNQ3ZTUR2JFZANCNFSM5GSMA3GQ> . Triage notifications on the go with GitHub Mobile for iOS <https://apps.apple.com/app/apple-store/id1477376905?ct=notification-email&mt=8&pt=524675> or Android <https://play.google.com/store/apps/details?id=com.github.android&referrer=utm_campaign%3Dnotification-email%26utm_medium%3Demail%26utm_source%3Dgithub>. You are receiving this because you were mentioned.Message ID: ***@***.***>

[cmarmo]

You still have some lint errors:

sklearn/neural_network/_multilayer_perceptron.py:1024:70: W291 trailing whitespace
sklearn/neural_network/_multilayer_perceptron.py:1492:89: E501 line too long (92 > 88 characters)
sklearn/neural_network/_multilayer_perceptron.py:1495:70: W291 trailing whitespace
sklearn/neural_network/_stochastic_optimizers.py:240:89: E501 line too long (108 > 88 characters)

They prevent the build of the documentation making more difficult the review.

[cmarmo]

Hi @aufarkari , thanks for following up. Some conflicts arose, a synchronization with upstream main is needed to allow all the checks to run.

[jjerphan]

LGTM given that the CI passes.

[glemaitre]

Thanks @SultanOrazbayev All is good with the CIs. Let's merge.

[SultanOrazbayev]

Thank you very much! This was a joint effort with @aufarkari. Great to make a small contribution to scikit-learn!

[glemaitre]

Nice work to both you then :)