DOC Ensures that SpectralBiclustering passes numpydoc validation #21393
Conversation
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
|
I merged too quickly with realizing there was a linting error. Let me fix it. |
|
@ogrisel Thank you so much for reviewing the PR! So sorry for the trailing whitespace. |
glemaitre
pushed a commit
to glemaitre/scikit-learn
that referenced
this pull request
Oct 23, 2021
glemaitre
pushed a commit
that referenced
this pull request
Oct 25, 2021
samronsin
pushed a commit
to samronsin/scikit-learn
that referenced
this pull request
Nov 30, 2021
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
Reference Issues/PRs
Addresses #20308
What does this implement/fix? Explain your changes.
This PR ensures
SpectralBiclusteringis compatible with numpydoc.SpectralBiclusteringfrom:scikit-learn/maint_tools/test_docstrings.py
Line 20 in e34b64c
SpectralCoclustering.Any other comments?
Thanks #DataUmbrella! Thanks so much @glemaitre for so patiently reviewing my PRs! Please let me know if there is anything I can do to improve my future PRs and help scikit-learn.