update class info

fixed_recall.py

@@ -39,9 +39,9 @@ class FixedRecall(evaluate.Metric):
 
     def _info(self):
         return evaluate.MetricInfo(
-            description="Custom built Recall metric for true *multilabel* classification - the 'multilabel' config_name var in the evaluate.EvaluationModules class appears to better address multi-class classification, where features can fall under a multitude of labels. Granted, the subtlety is minimal and easily confused. This class is implemented with the intention of enabling the evaluation of multiple multilabel classification metrics at the same time using the evaluate.CombinedEvaluations.combine method.",
-            citation="",
-            inputs_description="'average': This parameter is required for multiclass/multilabel targets. If None, the scores for each class are returned. Otherwise, this determines the type of averaging performed on the data. Options include: {‘micro’, ‘macro’, ‘samples’, ‘weighted’, ‘binary’} or None.",
+            description=_DESCRIPTION,
+            citation=_CITATION,
+            inputs_description=_INPUTS,
             features=datasets.Features(
                 {
                     "predictions": datasets.Sequence(datasets.Value("int32")),