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DOC Add scoring metric info in cross_val_score (#13445)
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sklearn/model_selection/_validation.py

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@@ -281,7 +281,13 @@ def cross_val_score(estimator, X, y=None, groups=None, scoring=None, cv='warn',
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scoring : string, callable or None, optional, default: None
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A string (see model evaluation documentation) or
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a scorer callable object / function with signature
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``scorer(estimator, X, y)``.
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``scorer(estimator, X, y)`` which should return only
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a single value.
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Similar to :func:`cross_validate`
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but only a single metric is permitted.
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If None, the estimator's default scorer (if available) is used.
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cv : int, cross-validation generator or an iterable, optional
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Determines the cross-validation splitting strategy.

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