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DOC Ensures that LabelPropagation passes numpydoc validation #21347

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DOC Ensures that LabelPropagation passes numpydoc validation #21347

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g4brielvs
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Reference Issues/PRs

Addresses #20308

What does this implement/fix? Explain your changes.

This PR ensures LabelPropagation is compatible with numpydoc.

Any other comments?

Thanks #DataUmbrella!

@jmloyola
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Hi @g4brielvs, thanks for the PR. There are a couple of failing tests, but I don't think they are related to your modifications.
Nevertheless, there was another person working on the same estimator (PR) that is waiting for review. Maybe you didn't see the message in the issue because there are too many comments there. Try to load all the issue messages to find out if the estimator is already taken or not. Note that you have to click on Load more... a couple of times to load all the messages.

ogrisel
ogrisel approved these changes Oct 16, 2021
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LGTM with the following suggestions for improvement in the description of the input data:

sklearn/semi_supervised/_label_propagation.py
Parameters
----------
X : array-like of shape (n_samples, n_features)
A matrix of shape (n_samples, n_samples) will be created from this.
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Suggested change
A matrix of shape (n_samples, n_samples) will be created from this.
Input data that will be used to create a kernel matrix of shape
`(n_samples, n_samples)`.

sklearn/semi_supervised/_label_propagation.py
Comment on lines +464 to +466
y : array-like of shape (n_samples,)
`n_labeled_samples` (unlabeled points are marked as -1)
All unlabeled samples will be transductively assigned labels.
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y : array-like of shape (n_samples,)
`n_labeled_samples` (unlabeled points are marked as -1)
All unlabeled samples will be transductively assigned labels.
y : array-like of shape (n_samples,)
Target class values with unlabeled points marked as -1.
All unlabeled samples will be transductively assigned labels
internally.

@genvalen
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genvalen commented Oct 16, 2021 •
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Hi all! I apologize for taking so long to complete the estimator task and for causing this confusion. My PR is now updated and hopefully ready to be merged, if that is still okay @ogrisel

@jmloyola @g4brielvs I wanted to mention that another great way to see if an estimator is being worked on is to check the Pull Requests tab and filter for "DOC Ensures", or something similar. This shows all the open pull requests with this phrase in the title. :)

@glemaitre
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I merged the PR of @genvalen that was already partly reviewed and ready to merge. Thanks @g4brielvs

@glemaitre glemaitre closed this Oct 21, 2021
@g4brielvs g4brielvs deleted the doc-labelpropagation branch October 21, 2021 17:33
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@g4brielvs @jmloyola @genvalen @glemaitre @ogrisel