[MRG] Fix #13134: Ensure sorted bin edges for KBinsDiscretizer strategy kmeans#13135
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qinhanmin2014 merged 1 commit intoscikit-learn:masterfrom Feb 12, 2019
SandroCasagrande:fix_kbinsdiscretizer_kmeans
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[MRG] Fix #13134: Ensure sorted bin edges for KBinsDiscretizer strategy kmeans#13135qinhanmin2014 merged 1 commit intoscikit-learn:masterfrom SandroCasagrande:fix_kbinsdiscretizer_kmeans
qinhanmin2014 merged 1 commit intoscikit-learn:masterfrom
SandroCasagrande:fix_kbinsdiscretizer_kmeans
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jnothman
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I've not confirmed the test fails at master, but this lgtm
Please add an entry to the change log at doc/whats_new/v0.20.rst under 0.20.3. Like the other entries there, please reference this pull request with :issue: and credit yourself (and other contributors if applicable) with :user:
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It fails at master |
qinhanmin2014
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LGTM, thanks @SandroCasagrande
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…retizer (scikit-learn#13135)" This reverts commit 7762f1f.
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…retizer (scikit-learn#13135)" This reverts commit 7762f1f.
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Reference Issues/PRs
Fixes #13134
What does this implement/fix? Explain your changes.
Since centers returned by 1d kmeans can be unsorted, I simply added a sort before constructing the bin edges. I also added a test which reproduces the issue when not sorting centers.
Any other comments?
Performance of sorting centers should not be an issue compared to kmeans itself. In most circumstances the list of centers is already sorted, but afaik in this situation checking if the numpy array is sorted is not better than invoking sort() directly (https://stackoverflow.com/questions/47004506/check-if-a-numpy-array-is-sorted), so I skipped the check.