DOC remove irrelevant parts in _validation.py
@@ -150,8 +150,7 @@ def cross_validate(estimator, X, y=None, *, groups=None, scoring=None, cv=None,
error_score : 'raise' or numeric, default=np.nan
Value to assign to the score if an error occurs in estimator fitting.
If set to 'raise', the error is raised.
- If a numeric value is given, FitFailedWarning is raised. This parameter
- does not affect the refit step, which will always raise the error.
+ If a numeric value is given, FitFailedWarning is raised.
.. versionadded:: 0.20
@@ -403,8 +402,7 @@ def cross_val_score(estimator, X, y=None, *, groups=None, scoring=None,
error_score : 'raise' or numeric, default=np.nan
Value to assign to the score if an error occurs in estimator fitting.
If set to 'raise', the error is raised.
- If a numeric value is given, FitFailedWarning is raised. This parameter
- does not affect the refit step, which will always raise the error.
+ If a numeric value is given, FitFailedWarning is raised.
.. versionadded:: 0.20
@@ -491,8 +489,7 @@ def _fit_and_score(estimator, X, y, scorer, train, test, verbose,
error_score : 'raise' or numeric, default=np.nan
Value to assign to the score if an error occurs in estimator fitting.
If set to 'raise', the error is raised.
- If a numeric value is given, FitFailedWarning is raised. This parameter
- does not affect the refit step, which will always raise the error.
+ If a numeric value is given, FitFailedWarning is raised.
parameters : dict or None
Parameters to be set on the estimator.
@@ -1282,8 +1279,7 @@ def learning_curve(estimator, X, y, *, groups=None,
error_score : 'raise' or numeric, default=np.nan
Value to assign to the score if an error occurs in estimator fitting.
If set to 'raise', the error is raised.
- If a numeric value is given, FitFailedWarning is raised. This parameter
- does not affect the refit step, which will always raise the error.
+ If a numeric value is given, FitFailedWarning is raised.
.. versionadded:: 0.20
@@ -1554,8 +1550,7 @@ def validation_curve(estimator, X, y, *, param_name, param_range, groups=None,
error_score : 'raise' or numeric, default=np.nan
Value to assign to the score if an error occurs in estimator fitting.
If set to 'raise', the error is raised.
- If a numeric value is given, FitFailedWarning is raised. This parameter
- does not affect the refit step, which will always raise the error.
+ If a numeric value is given, FitFailedWarning is raised.
.. versionadded:: 0.20
