Update compas.py

compas.py

@@ -84,8 +84,8 @@ _BASE_FEATURE_NAMES = [
 ]
 _ENCODING_DICS = {
     "sex": {
-        "Male": 0,
-        "Female": 1
+        "Male": 1,
+        "Female": 0
     },
     "race": {
         "Caucasian": 0,
@@ -114,7 +114,7 @@ features_types_per_config = {
     },
 
     "two-years-recidividity": {
-        "sex": datasets.Value("int64"),
+        "is_male": datasets.Value("bool"),
         "age": datasets.Value("int64"),
         "race": datasets.Value("string"),
         "number_of_juvenile_fellonies": datasets.Value("int64"),
@@ -123,15 +123,15 @@ features_types_per_config = {
         "number_of_other_juvenile_offenses": datasets.Value("int64"),
         "number_of_prior_offenses": datasets.Value("int64"),
         "days_before_screening_arrest": datasets.Value("int64"),
-        "is_recidivous": datasets.Value("int64"),
+        "is_recidivous": datasets.Value("bool"),
         "days_in_custody": datasets.Value("int64"),
-        "is_violent_recidivous": datasets.Value("int64"),
+        "is_violent_recidivous": datasets.Value("bool"),
         "violence_decile_score": datasets.Value("int64"),
         "two_year_recidivous": datasets.ClassLabel(num_classes=2, names=("no", "yes")),
     },
     
     "two-years-recidividity-no-race": {
-        "sex": datasets.Value("int64"),
+        "is_male": datasets.Value("bool"),
         "age": datasets.Value("int64"),
         "number_of_juvenile_fellonies": datasets.Value("int64"),
         "decile_score": datasets.Value("int64"),
@@ -139,15 +139,15 @@ features_types_per_config = {
         "number_of_other_juvenile_offenses": datasets.Value("int64"),
         "number_of_prior_offenses": datasets.Value("int64"),
         "days_before_screening_arrest": datasets.Value("int64"),
-        "is_recidivous": datasets.Value("int64"),
+        "is_recidivous": datasets.Value("bool"),
         "days_in_custody": datasets.Value("int64"),
-        "is_violent_recidivous": datasets.Value("int64"),
+        "is_violent_recidivous": datasets.Value("bool"),
         "violence_decile_score": datasets.Value("int64"),
         "two_year_recidivous": datasets.ClassLabel(num_classes=2, names=("no", "yes")),
     },
     
     "priors-prediction": {
-        "sex": datasets.Value("int64"),
+        "is_male": datasets.Value("bool"),
         "age": datasets.Value("int64"),
         "race": datasets.Value("string"),
         "number_of_juvenile_fellonies": datasets.Value("int64"),
@@ -155,41 +155,41 @@ features_types_per_config = {
         "number_of_juvenile_misdemeanors": datasets.Value("int64"),
         "number_of_other_juvenile_offenses": datasets.Value("int64"),
         "days_before_screening_arrest": datasets.Value("int64"),
-        "is_recidivous": datasets.Value("int64"),
+        "is_recidivous": datasets.Value("bool"),
         "days_in_custody": datasets.Value("int64"),
-        "is_violent_recidivous": datasets.Value("int64"),
+        "is_violent_recidivous": datasets.Value("bool"),
         "violence_decile_score": datasets.Value("int64"),
         "two_year_recidivous": datasets.Value("int64"),
         "number_of_prior_offenses": datasets.Value("int64")
     },
     
     "priors-prediction-no-race": {
-        "sex": datasets.Value("int64"),
+        "is_male": datasets.Value("bool"),
         "age": datasets.Value("int64"),
         "number_of_juvenile_fellonies": datasets.Value("int64"),
         "decile_score": datasets.Value("int64"),
         "number_of_juvenile_misdemeanors": datasets.Value("int64"),
         "number_of_other_juvenile_offenses": datasets.Value("int64"),
         "days_before_screening_arrest": datasets.Value("int64"),
-        "is_recidivous": datasets.Value("int64"),
+        "is_recidivous": datasets.Value("bool"),
         "days_in_custody": datasets.Value("int64"),
-        "is_violent_recidivous": datasets.Value("int64"),
+        "is_violent_recidivous": datasets.Value("bool"),
         "violence_decile_score": datasets.Value("int64"),
         "two_year_recidivous": datasets.Value("int64"),
         "number_of_prior_offenses": datasets.Value("int64"),
     },
 
     "race": {
-        "sex": datasets.Value("int64"),
+        "is_male": datasets.Value("bool"),
         "age": datasets.Value("int64"),
         "number_of_juvenile_fellonies": datasets.Value("int64"),
         "decile_score": datasets.Value("int64"),
         "number_of_juvenile_misdemeanors": datasets.Value("int64"),
         "number_of_other_juvenile_offenses": datasets.Value("int64"),
         "days_before_screening_arrest": datasets.Value("int64"),
-        "is_recidivous": datasets.Value("int64"),
+        "is_recidivous": datasets.Value("bool"),
         "days_in_custody": datasets.Value("int64"),
-        "is_violent_recidivous": datasets.Value("int64"),
+        "is_violent_recidivous": datasets.Value("bool"),
         "violence_decile_score": datasets.Value("int64"),
         "two_year_recidivous": datasets.Value("int64"),
         "number_of_prior_offenses": datasets.Value("int64"),
@@ -210,8 +210,6 @@ class Compas(datasets.GeneratorBasedBuilder):
     # dataset versions
     DEFAULT_CONFIG = "two-years-recidividity"
     BUILDER_CONFIGS = [
-        CompasConfig(name="encoding",
-                    description="Encoding dictionaries for discrete labels."),
         CompasConfig(name="race",
                     description="Multiclass classification, predict `race` out of other features."),
         CompasConfig(name="two-years-recidividity",
@@ -222,13 +220,12 @@ class Compas(datasets.GeneratorBasedBuilder):
                      description="Compas regression task for estimating number of prior offenses of defendant."),
         CompasConfig(name="priors-prediction-no-race",
                      description="Compas regression task for estimating number of prior offenses of defendant. Race excluded from features."),
+        CompasConfig(name="encoding",
+                    description="Encoding dictionaries for discrete labels."),
     ]
 
 
-    def _info(self):
-        if self.config.name not in features_per_config:
-            raise ValueError(f"Unknown configuration: {self.config.name}")
-        
+    def _info(self):       
         info = datasets.DatasetInfo(description=DESCRIPTION, citation=_CITATION, homepage=_HOMEPAGE,
                                     features=features_per_config[self.config.name])
 
@@ -242,9 +239,6 @@ class Compas(datasets.GeneratorBasedBuilder):
         ]
     
     def _generate_examples(self, filepath: str):
-        if self.config.name not in features_types_per_config:
-            raise ValueError(f"Unknown config: {self.config.name}")
-
         if self.config.name == "encoding":
             data = self.encoding_dics()
         else:
@@ -334,6 +328,9 @@ class Compas(datasets.GeneratorBasedBuilder):
                     continue
             encoding_function = partial(self.encode, feature)
             data.loc[:, feature] = data[feature].apply(encoding_function)
+        data.loc[:, "is_recidivous"] = data["is_recidivous"].apply(bool)
+        data.loc[:, "is_violent_recidivous"] = data["is_violent_recidivous"].apply(bool)
+        data = data.astype({"is_recidivous": "bool", "is_violent_recidivous": "bool"})
                 
         return data[list(features_types_per_config[config].keys())]