Slight adjustment to the doc string of KMeans regarding the attribute… #12537
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looks good, thanks! Also looks like I had the last person that ask about this make a comment - but maybe adding it in the attribute description as well will make it more visible. |
amueller
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jnothman
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I've not checked if there are other pep8 issues.
… cluster_centers_
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Oops! I fixed the whitespace issues, re-analyzed it in Spyder, and squashed the commits. Should be okay as far as pep8 goes now. Hope the extra documentation can save you at least more trouble than I've already caused! |
jnothman
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Thanks @nicholastoddsmith |
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* upstream/master: joblib 0.13.0 (scikit-learn#12531) DOC tweak KMeans regarding cluster_centers_ convergence (scikit-learn#12537) DOC (0.21) Make sure plot_tree docs are generated and fix link in whatsnew (scikit-learn#12533) ALL Add HashingVectorizer to __all__ (scikit-learn#12534) BLD we should ensure continued support for joblib 0.11 (scikit-learn#12350) fix typo in whatsnew Fix dead link to numpydoc (scikit-learn#12532) [MRG] Fix segfault in AgglomerativeClustering with read-only mmaps (scikit-learn#12485) MNT (0.21) OPTiCS change the default `algorithm` to `auto` (scikit-learn#12529) FIX SkLearn `.score()` method generating error with Dask DataFrames (scikit-learn#12462) MNT KBinsDiscretizer.transform should not mutate _encoder (scikit-learn#12514)
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…ybutton * upstream/master: FIX YeoJohnson transform lambda bounds (scikit-learn#12522) [MRG] Additional Warnings in case OpenML auto-detected a problem with dataset (scikit-learn#12541) ENH Prefer threads for IsolationForest (scikit-learn#12543) joblib 0.13.0 (scikit-learn#12531) DOC tweak KMeans regarding cluster_centers_ convergence (scikit-learn#12537) DOC (0.21) Make sure plot_tree docs are generated and fix link in whatsnew (scikit-learn#12533) ALL Add HashingVectorizer to __all__ (scikit-learn#12534) BLD we should ensure continued support for joblib 0.11 (scikit-learn#12350) fix typo in whatsnew Fix dead link to numpydoc (scikit-learn#12532) [MRG] Fix segfault in AgglomerativeClustering with read-only mmaps (scikit-learn#12485) MNT (0.21) OPTiCS change the default `algorithm` to `auto` (scikit-learn#12529) FIX SkLearn `.score()` method generating error with Dask DataFrames (scikit-learn#12462) MNT KBinsDiscretizer.transform should not mutate _encoder (scikit-learn#12514)
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…it-learn#12537)" This reverts commit 35fa9ef.
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…it-learn#12537)" This reverts commit 35fa9ef.
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… cluster_centers_
Reference Issues/PRs
Fixes #12506
What does this implement/fix? Explain your changes.
This is a change to the KMeans doc string which highlights the fact that the attribute cluster_centers_ will not be consistent with labels_ if the algorithm stops before fully converging.
Any other comments?
There was a note in the documentation about this scenario, but it mentioned means_ and not cluster_centers_ (see the second modified block). I didn't see means_ defined anywhere so I updated it to cluster_centers_.