ENH Adds roc weighted scorers to SCORERS (#14417)

thomasjpfan · amueller · commit 96bfae69ce49 · 2019-09-04T15:41:29.000-04:00
diff --git a/doc/modules/model_evaluation.rst b/doc/modules/model_evaluation.rst
@@ -72,6 +72,10 @@ Scoring                           Function
 'recall' etc.                     :func:`metrics.recall_score`                      suffixes apply as with 'f1'
 'jaccard' etc.                    :func:`metrics.jaccard_score`                     suffixes apply as with 'f1'
 'roc_auc'                         :func:`metrics.roc_auc_score`
+'roc_auc_ovr'                     :func:`metrics.roc_auc_score`
+'roc_auc_ovo'                     :func:`metrics.roc_auc_score`
+'roc_auc_ovr_weighted'            :func:`metrics.roc_auc_score`
+'roc_auc_ovo_weighted'            :func:`metrics.roc_auc_score`
 
 **Clustering**
 'adjusted_mutual_info_score'      :func:`metrics.adjusted_mutual_info_score`
diff --git a/sklearn/metrics/scorer.py b/sklearn/metrics/scorer.py
@@ -558,6 +558,8 @@ def make_scorer(score_func, greater_is_better=True, needs_proba=False,
                accuracy=accuracy_scorer, roc_auc=roc_auc_scorer,
                roc_auc_ovr=roc_auc_ovr_scorer,
                roc_auc_ovo=roc_auc_ovo_scorer,
+               roc_auc_ovr_weighted=roc_auc_ovr_weighted_scorer,
+               roc_auc_ovo_weighted=roc_auc_ovo_weighted_scorer,
                balanced_accuracy=balanced_accuracy_scorer,
                average_precision=average_precision_scorer,
                neg_log_loss=neg_log_loss_scorer,
diff --git a/sklearn/metrics/tests/test_score_objects.py b/sklearn/metrics/tests/test_score_objects.py
@@ -55,7 +55,8 @@
                'recall', 'recall_weighted', 'recall_macro', 'recall_micro',
                'neg_log_loss', 'log_loss', 'brier_score_loss',
                'jaccard', 'jaccard_weighted', 'jaccard_macro',
-               'jaccard_micro', 'roc_auc_ovr', 'roc_auc_ovo']
+               'jaccard_micro', 'roc_auc_ovr', 'roc_auc_ovo',
+               'roc_auc_ovr_weighted', 'roc_auc_ovo_weighted']
 
 # All supervised cluster scorers (They behave like classification metric)
 CLUSTER_SCORERS = ["adjusted_rand_score",
