Use registry pattern to make classification metric set

rexmex/metricset.py

@@ -1,18 +1,6 @@
 from typing import Collection, List, Tuple
 
-from rexmex.metrics.classification import (
-    accuracy_score,
-    average_precision_score,
-    balanced_accuracy_score,
-    f1_score,
-    fowlkes_mallows_index,
-    matthews_correlation_coefficient,
-    pr_auc_score,
-    precision_score,
-    recall_score,
-    roc_auc_score,
-    specificity,
-)
+from rexmex.metrics.classification import classifications
 from rexmex.metrics.rating import (
     mean_absolute_error,
     mean_absolute_percentage_error,
@@ -104,17 +92,14 @@ class ClassificationMetricSet(MetricSet):
     """
 
     def __init__(self):
-        self["roc_auc"] = roc_auc_score
-        self["pr_auc"] = pr_auc_score
-        self["average_precision"] = average_precision_score
-        self["f1_score"] = binarize(f1_score)
-        self["matthews_correlation_coefficent"] = binarize(matthews_correlation_coefficient)
-        self["fowlkes_mallows_index"] = binarize(fowlkes_mallows_index)
-        self["precision"] = binarize(precision_score)
-        self["recall"] = binarize(recall_score)
-        self["specificity"] = binarize(specificity)
-        self["accuracy"] = binarize(accuracy_score)
-        self["balanced_accuracy"] = binarize(balanced_accuracy_score)
+        super().__init__()
+        for func in classifications:
+            name = func.__name__
+            if name.endswith("_score"):
+                name = name[: -len("_score")]
+            if func.binarize:
+                func = binarize(func)
+            self[name] = func
 
     def __repr__(self):
         """