DOC Fix a typo in cross_validation.rst
@@ -245,13 +245,13 @@ Or as a dict mapping scorer name to a predefined or custom scoring function::
>>> from sklearn.metrics.scorer import make_scorer
>>> scoring = {'prec_macro': 'precision_macro',
- ... 'rec_micro': make_scorer(recall_score, average='macro')}
+ ... 'rec_macro': make_scorer(recall_score, average='macro')}
>>> scores = cross_validate(clf, iris.data, iris.target, scoring=scoring,
... cv=5, return_train_score=True)
>>> sorted(scores.keys()) # doctest: +NORMALIZE_WHITESPACE
- ['fit_time', 'score_time', 'test_prec_macro', 'test_rec_micro',
- 'train_prec_macro', 'train_rec_micro']
- >>> scores['train_rec_micro'] # doctest: +ELLIPSIS
+ ['fit_time', 'score_time', 'test_prec_macro', 'test_rec_macro',
+ 'train_prec_macro', 'train_rec_macro']
+ >>> scores['train_rec_macro'] # doctest: +ELLIPSIS
array([0.97..., 0.97..., 0.99..., 0.98..., 0.98...])
Here is an example of ``cross_validate`` using a single metric::
