Update multiclass_sensitivity_weighted.py

multiclass_sensitivity_weighted.py

@@ -87,36 +87,7 @@ class multiclass_sensitivity_weighted(evaluate.Metric):
         pass
 
     def _compute(self, predictions, references):
-        from collections import defaultdict
-        """Returns the scores"""
-        # TODO: Compute the different scores of the module
-        # Count true positives, false negatives, and true instance counts for each class
-        tp_counts = defaultdict(int)
-        fn_counts = defaultdict(int)
-        true_counts = defaultdict(int)
-
-        for true_label, pred_label in zip(references, predictions):
-            true_counts[true_label] += 1
-            if true_label == pred_label:
-                tp_counts[true_label] += 1
-            else:
-                fn_counts[true_label] += 1
-
-        # Calculate class-wise sensitivity
-        class_sensitivities = {}
-        total_weight = sum(true_counts.values())
-        weighted_sum = 0.0
-
-        for class_label in set(references):
-            tp = tp_counts[class_label]
-            fn = fn_counts[class_label]
-            true_instances = true_counts[class_label]
-
-            sensitivity = tp / (tp + fn) if (tp + fn) > 0 else 0
-            class_sensitivities[class_label] = sensitivity
-            weighted_sum += sensitivity * true_instances
-
-        weighted_avg_sensitivity = weighted_sum / total_weight if total_weight > 0 else 0
+        from imblearn.metrics import sensitivity_score
         return {
-            "weighted_sensitivity": weighted_avg_sensitivity,
+            "weighted_sensitivity": sensitivity_score(references, predictions, average = "weighted")
         }