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DOC Ensure completeness_score passes numpydoc validation #23016

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Apr 1, 2022
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DOC Ensure completeness_score passes numpydoc validation #23016

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c3afd9a
remove completeness_score from test ignore list
aj-white Apr 1, 2022
284996d
correct section order of completeness_score
aj-white Apr 1, 2022
786d420
Capitalise and full stop on parameters and returns
aj-white Apr 1, 2022
f90b444
Add description to See Also section
aj-white Apr 1, 2022
fba57ab
Fix summary starts with infinitive verb
aj-white Apr 1, 2022
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18 changes: 9 additions & 9 deletions sklearn/metrics/cluster/_supervised.py
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Expand Up @@ -554,7 +554,7 @@ def homogeneity_score(labels_true, labels_pred):


def completeness_score(labels_true, labels_pred):
"""Completeness metric of a cluster labeling given a ground truth.
"""Compute completeness metric of a cluster labeling given a ground truth.

A clustering result satisfies completeness if all the data points
that are members of a given class are elements of the same cluster.
Expand All @@ -572,15 +572,20 @@ def completeness_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
-------
completeness : float
score between 0.0 and 1.0. 1.0 stands for perfectly complete labeling
Score between 0.0 and 1.0. 1.0 stands for perfectly complete labeling.

See Also
--------
homogeneity_score : Homogeneity metric of cluster labeling.
v_measure_score : V-Measure (NMI with arithmetic mean option).

References
----------
Expand All @@ -589,11 +594,6 @@ def completeness_score(labels_true, labels_pred):
conditional entropy-based external cluster evaluation measure
<https://aclweb.org/anthology/D/D07/D07-1043.pdf>`_

See Also
--------
homogeneity_score
v_measure_score

Examples
--------

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1 change: 0 additions & 1 deletion sklearn/tests/test_docstrings.py
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Expand Up @@ -59,7 +59,6 @@
"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.completeness_score",
"sklearn.metrics.cluster._supervised.entropy",
"sklearn.metrics.cluster._supervised.fowlkes_mallows_score",
"sklearn.metrics.cluster._supervised.homogeneity_completeness_v_measure",
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