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DOC Long sentence was hard to parse and ambiguous in _classification.py (#15769)
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sklearn/metrics/_classification.py

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@@ -1842,10 +1842,10 @@ def classification_report(y_true, y_pred, labels=None, target_names=None,
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The reported averages include macro average (averaging the unweighted
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mean per label), weighted average (averaging the support-weighted mean
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per label), sample average (only for multilabel classification) and
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micro average (averaging the total true positives, false negatives and
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false positives) it is only shown for multi-label or multi-class
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with a subset of classes because it is accuracy otherwise.
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per label), and sample average (only for multilabel classification).
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Micro average (averaging the total true positives, false negatives and
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false positives) is only shown for multi-label or multi-class
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with a subset of classes, because it corresponds to accuracy otherwise.
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See also :func:`precision_recall_fscore_support` for more details
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on averages.
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