Update ISCO-08 Hierarchical Accuracy Measure implementation

isco_hierarchical_accuracy.py

@@ -38,6 +38,9 @@ _CITATION = """
 
 _DESCRIPTION = """
 The ISCO-08 Hierarchical Accuracy Measure is an implementation of the measure described in [Functional Annotation of Genes Using Hierarchical Text Categorization](https://www.researchgate.net/publication/44046343_Functional_Annotation_of_Genes_Using_Hierarchical_Text_Categorization) (Kiritchenko, Svetlana and Famili, Fazel. 2005) and adapted for the ISCO-08 classification scheme by the International Labour Organization.
+
+The measure rewards more precise classifications that correctly identify an occupation's placement down to the specific Unit group level and applies penalties for misclassifications based on the hierarchical distance between the correct and assigned categories.
+
 """
 
 _KWARGS_DESCRIPTION = """
@@ -56,13 +59,13 @@ Examples:
     Example 1
 
     >>> ham = evaluate.load("danieldux/isco_hierarchical_accuracy")
-    >>> results = ham.compute(reference=["1111", "1112", "1113", "1114"], predictions=["1111", "1113", "1120", "1211"])
+    >>> results = ham.compute(reference=["1111", "1112", "1113", "1114", "1120"], predictions=["1111", "1113", "1120", "1211", "2111"])
     >>> print(results)
     {
-        'accuracy': 0.25,
-        'hierarchical_precision': 0.7142857142857143,
-        'hierarchical_recall': 0.5,
-        'hierarchical_fmeasure': 0.588235294117647
+        "accuracy": 0.2,
+        "hierarchical_precision": 0.5,
+        "hierarchical_recall": 0.7777777777777778,
+        "hierarchical_fmeasure": 0.6086956521739131,
     }
 """
 
@@ -87,13 +90,6 @@ class ISCO_Hierarchical_Accuracy(evaluate.Metric):
             description=_DESCRIPTION,
             citation=_CITATION,
             inputs_description=_KWARGS_DESCRIPTION,
-            # This defines the format of each prediction and reference
-            # features=datasets.Features(
-            #     {
-            #         "predictions": datasets.Value("string"),
-            #         "references": datasets.Value("string"),
-            #     }
-            # ),
             features=datasets.Features(
                 {
                     "references": datasets.Sequence(datasets.Value("string")),