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DOC Ensures that pair_confusion_matrix passes numpydoc validation #24094

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Aug 3, 2022
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DOC Ensures that pair_confusion_matrix passes numpydoc validation #24094

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9607f86
Fix doc validation errors for
Vincent-Maladiere Aug 3, 2022
0d85ad1
Merge branch 'main' into fix_doc_pair_confusion_matrix
glemaitre Aug 3, 2022
bb62eea
Update the reference DOI
Vincent-Maladiere Aug 3, 2022
72e4cf4
Apply suggestions from code review
Vincent-Maladiere Aug 3, 2022
221b98c
fix DOI index
Vincent-Maladiere Aug 3, 2022
98e662a
misplaced period
Vincent-Maladiere Aug 3, 2022
bd48000
Update sklearn/metrics/cluster/_supervised.py
Vincent-Maladiere Aug 3, 2022
f1d42d2
Update sklearn/metrics/cluster/_supervised.py
glemaitre Aug 3, 2022
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20 changes: 10 additions & 10 deletions sklearn/metrics/cluster/_supervised.py
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Original file line number Diff line number Diff line change
Expand Up @@ -159,7 +159,7 @@ def contingency_matrix(


def pair_confusion_matrix(labels_true, labels_pred):
"""Pair confusion matrix arising from two clusterings.
"""Pair confusion matrix arising from two clusterings [1]_.

The pair confusion matrix :math:`C` computes a 2 by 2 similarity matrix
between two clusterings by considering all pairs of samples and counting
Expand Down Expand Up @@ -188,9 +188,15 @@ def pair_confusion_matrix(labels_true, labels_pred):

See Also
--------
rand_score: Rand Score
adjusted_rand_score: Adjusted Rand Score
adjusted_mutual_info_score: Adjusted Mutual Information
rand_score: Rand Score.
adjusted_rand_score: Adjusted Rand Score.
adjusted_mutual_info_score: Adjusted Mutual Information.

References
----------
.. [1] :doi:`Hubert, L., Arabie, P. "Comparing partitions."
Journal of Classification 2, 193–218 (1985).
<10.1007/BF01908075>`

Examples
--------
Expand All @@ -211,12 +217,6 @@ def pair_confusion_matrix(labels_true, labels_pred):
[0, 2]]...

Note that the matrix is not symmetric.

References
----------
.. L. Hubert and P. Arabie, Comparing Partitions, Journal of
Classification 1985
https://link.springer.com/article/10.1007%2FBF01908075
"""
labels_true, labels_pred = check_clusterings(labels_true, labels_pred)
n_samples = np.int64(labels_true.shape[0])
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1 change: 0 additions & 1 deletion sklearn/tests/test_docstrings.py
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Expand Up @@ -39,7 +39,6 @@
"sklearn.metrics.cluster._supervised.adjusted_rand_score",
"sklearn.metrics.cluster._supervised.entropy",
"sklearn.metrics.cluster._supervised.fowlkes_mallows_score",
"sklearn.metrics.cluster._supervised.pair_confusion_matrix",
"sklearn.metrics.cluster._supervised.rand_score",
"sklearn.metrics.cluster._supervised.v_measure_score",
"sklearn.metrics.pairwise.pairwise_distances_chunked",
Expand Down