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sklearn/metrics/ranking.py

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@@ -993,7 +993,7 @@ def label_ranking_loss(y_true, y_score, sample_weight=None):
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unique_inverse[y_true.indices[start:stop]],
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minlength=len(unique_scores))
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all_at_reversed_rank = np.bincount(unique_inverse,
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minlength=len(unique_scores))
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minlength=len(unique_scores))
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false_at_reversed_rank = all_at_reversed_rank - true_at_reversed_rank
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# if the scores are ordered, it's possible to count the number of

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