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DOC Ensures that adjusted_rand_score passes numpydoc validation #24345

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Sep 3, 2022
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DOC Ensures that adjusted_rand_score passes numpydoc validation #24345

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41 changes: 20 additions & 21 deletions sklearn/metrics/cluster/_supervised.py
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Original file line number Diff line number Diff line change
Expand Up @@ -335,17 +335,35 @@ def adjusted_rand_score(labels_true, labels_pred):
Parameters
----------
labels_true : int array, shape = [n_samples]
Ground truth class labels to be used as a reference
Ground truth class labels to be used as a reference.

labels_pred : array-like of shape (n_samples,)
Cluster labels to evaluate
Cluster labels to evaluate.

Returns
-------
ARI : float
Similarity score between -0.5 and 1.0. Random labelings have an ARI
close to 0.0. 1.0 stands for perfect match.

See Also
--------
adjusted_mutual_info_score : Adjusted Mutual Information.

References
----------
.. [Hubert1985] L. Hubert and P. Arabie, Comparing Partitions,
Journal of Classification 1985
https://link.springer.com/article/10.1007%2FBF01908075

.. [Steinley2004] D. Steinley, Properties of the Hubert-Arabie
adjusted Rand index, Psychological Methods 2004

.. [wk] https://en.wikipedia.org/wiki/Rand_index#Adjusted_Rand_index

.. [Chacon] :doi:`Minimum adjusted Rand index for two clusterings of a given size,
2022, J. E. Chacón and A. I. Rastrojo <10.1007/s11634-022-00491-w>`

Examples
--------
Perfectly matching labelings have a score of 1 even
Expand Down Expand Up @@ -379,25 +397,6 @@ def adjusted_rand_score(labels_true, labels_pred):

>>> adjusted_rand_score([0, 0, 1, 1], [0, 1, 0, 1])
-0.5

References
----------
.. [Hubert1985] L. Hubert and P. Arabie, Comparing Partitions,
Journal of Classification 1985
https://link.springer.com/article/10.1007%2FBF01908075

.. [Steinley2004] D. Steinley, Properties of the Hubert-Arabie
adjusted Rand index, Psychological Methods 2004

.. [wk] https://en.wikipedia.org/wiki/Rand_index#Adjusted_Rand_index

.. [Chacon] :doi:`Minimum adjusted Rand index for two clusterings of a given size,
2022, J. E. Chacón and A. I. Rastrojo <10.1007/s11634-022-00491-w>`


See Also
--------
adjusted_mutual_info_score : Adjusted Mutual Information.
"""
(tn, fp), (fn, tp) = pair_confusion_matrix(labels_true, labels_pred)
# convert to Python integer types, to avoid overflow or underflow
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1 change: 0 additions & 1 deletion sklearn/tests/test_docstrings.py
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Expand Up @@ -21,7 +21,6 @@
"sklearn.metrics._ranking.roc_curve",
"sklearn.metrics.cluster._bicluster.consensus_score",
"sklearn.metrics.cluster._supervised.adjusted_mutual_info_score",
"sklearn.metrics.cluster._supervised.adjusted_rand_score",
"sklearn.metrics.cluster._supervised.entropy",
"sklearn.metrics.cluster._supervised.fowlkes_mallows_score",
"sklearn.metrics.pairwise.pairwise_distances_chunked",
Expand Down