Update multiclass_sensitivity_macro.py

multiclass_sensitivity_macro.py

@@ -90,45 +90,7 @@ class multiclass_sensitivity_macro(evaluate.Metric):
         """Returns the scores"""
         # TODO: Compute the different scores of the module
 
-        from collections import defaultdict
-        """
-        Calculate multiclass sensitivity (recall) for each class,
-        as well as weighted and macro averages.
-
-        Args:
-            references (list): List of true class labels.
-            predictions (list): List of predicted class labels.
-
-        Returns:
-            tuple: Class-wise sensitivity, weighted average sensitivity, macro average sensitivity.
-        """
-        # 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
-
-        macro_avg_sensitivity = sum(class_sensitivities.values()) / len(class_sensitivities) if class_sensitivities else 0
+        from imblearn.metrics import sensitivity_score
         return {
-            "macro_sensitivity": macro_avg_sensitivity,
+            "macro_sensitivity": sensitivity_score(references, predictions, average = "macro"),
         }