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Fix default value of average in precision_recall_fscore_support #31270

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Fix default value of average in precision_recall_fscore_support #31270

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40502b3
Fix default value of verage in precision_recall_fscore_support
Foundsheep Apr 29, 2025
3ff208f
Fix default value of verage in precision_recall_fscore_support
Foundsheep Apr 29, 2025
d6908a6
Modify the documentation to follow the code
Foundsheep May 7, 2025
c271ae5
Merge branch 'fix_prfs_default_value' of https://github.com/Foundshee…
Foundsheep May 7, 2025
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4 changes: 2 additions & 2 deletions sklearn/metrics/_classification.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1793,7 +1793,7 @@ def precision_recall_fscore_support(
beta=1.0,
labels=None,
pos_label=1,
average=None,
average="binary",
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I think the documentation should follow the code, not the other way around. Changing this would change existing code behavior.

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Changed the documentation instead, and returned the code

warn_for=("precision", "recall", "f-score"),
sample_weight=None,
zero_division="warn",
Expand Down Expand Up @@ -1858,7 +1858,7 @@ def precision_recall_fscore_support(
`average != 'binary'` to report metrics for one label only.

average : {'micro', 'macro', 'samples', 'weighted', 'binary'} or None, \
default='binary'
default=None
This parameter is required for multiclass/multilabel targets.
If ``None``, the metrics for each class are returned. Otherwise, this
determines the type of averaging performed on the data:
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