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DOC Ensure that label_ranking_average_precision_score passes numpydoc validation #23504

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Jun 1, 2022
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DOC Ensure that label_ranking_average_precision_score passes numpydoc validation #23504

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2 changes: 1 addition & 1 deletion sklearn/metrics/_ranking.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1058,6 +1058,7 @@ def label_ranking_average_precision_score(y_true, y_score, *, sample_weight=None
Returns
-------
score : float
Ranking-based average precision score.

Examples
--------
Expand All @@ -1067,7 +1068,6 @@ def label_ranking_average_precision_score(y_true, y_score, *, sample_weight=None
>>> y_score = np.array([[0.75, 0.5, 1], [1, 0.2, 0.1]])
>>> label_ranking_average_precision_score(y_true, y_score)
0.416...

"""
check_consistent_length(y_true, y_score, sample_weight)
y_true = check_array(y_true, ensure_2d=False)
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1 change: 0 additions & 1 deletion sklearn/tests/test_docstrings.py
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Expand Up @@ -40,7 +40,6 @@
"sklearn.metrics._plot.precision_recall_curve.plot_precision_recall_curve",
"sklearn.metrics._ranking.coverage_error",
"sklearn.metrics._ranking.dcg_score",
"sklearn.metrics._ranking.label_ranking_average_precision_score",
"sklearn.metrics._ranking.roc_auc_score",
"sklearn.metrics._ranking.roc_curve",
"sklearn.metrics._ranking.top_k_accuracy_score",
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