Upload acute_inflammation.py

acute_inflammation.py

@@ -16,7 +16,8 @@ _BASE_FEATURE_NAMES = [
     "has_micturition_pains",
     "has_burnt_urethra",
     "has_inflammed_bladder",
-    "has_nephritis_of_renal_pelvis"
+    "has_nephritis_of_renal_pelvis",
+    "has_acute_inflammation"
 ]
 
 DESCRIPTION = "Acute_Inflammation dataset from the UCI ML repository."
@@ -44,7 +45,8 @@ features_types_per_config = {
         "has_micturition_pains": datasets.Value("bool"),
         "has_burnt_urethra": datasets.Value("bool"),
         "has_inflammed_bladder": datasets.Value("bool"),
-        "has_nephritis_of_renal_pelvis": datasets.Value("int8")
+        "has_nephritis_of_renal_pelvis": datasets.Value("bool"),
+        "has_acute_inflammation": datasets.ClassLabel(num_classes=2)
     }
 }
 features_per_config = {k: datasets.Features(features_types_per_config[k]) for k in features_types_per_config}
@@ -90,10 +92,12 @@ class Acute_Inflammation(datasets.GeneratorBasedBuilder):
     def preprocess(self, data: pandas.DataFrame, config: str = DEFAULT_CONFIG) -> pandas.DataFrame:
         data.columns = _BASE_FEATURE_NAMES
         boolean_features = ["has_nausea", "has_lumbar_pain", "has_urine_pushing",
-                            "has_micturition_pains", "has_burnt_urethra", "has_inflammed_bladder"]
+                            "has_micturition_pains", "has_burnt_urethra", "has_inflammed_bladder",
+                            "has_nephritis_of_renal_pelvis", "has_acute_inflammation"]
         for f in boolean_features:
             data.loc[:, f] = data[f].apply(lambda x: True if x == "yes" else False)
 
         data = data.astype({f: "bool" for f in boolean_features})
+        data = data.astype({"has_acute_inflammation": int})
         
         return data