Upload adult.py

adult.py

@@ -43,9 +43,9 @@ _BASE_FEATURE_NAMES = [
     "over_threshold",
 ]
 _ENCODING_DICS = {
-    "sex": {
-            "Male": 0,
-            "Female": 1
+    "is_male": {
+            "Male": True,
+            "Female": False
         }
 }
 _RACE_ENCODING = {
@@ -119,7 +119,7 @@ features_types_per_config = {
         "occupation": datasets.Value("string"),
         "race": datasets.Value("string"),
         "relationship": datasets.Value("string"),
-        "sex": datasets.Value("int8"),
+        "is_male": datasets.Value("bool"),
         "workclass": datasets.Value("string"),
         "over_threshold": datasets.ClassLabel(num_classes=2, names=("no", "yes"))
     },
@@ -134,7 +134,7 @@ features_types_per_config = {
         "native_country": datasets.Value("string"),
         "occupation": datasets.Value("string"),
         "relationship": datasets.Value("string"),
-        "sex": datasets.Value("int8"),
+        "is_male": datasets.Value("bool"),
         "workclass": datasets.Value("string"),
         "over_threshold": datasets.ClassLabel(num_classes=2, names=("no", "yes"))
     },
@@ -149,7 +149,7 @@ features_types_per_config = {
         "native_country": datasets.Value("string"),
         "occupation": datasets.Value("string"),
         "relationship": datasets.Value("string"),
-        "sex": datasets.Value("int8"),
+        "is_male": datasets.Value("bool"),
         "workclass": datasets.Value("string"),
         "over_threshold": datasets.Value("int8"),
         "race": datasets.ClassLabel(num_classes=5, names=["White", "Black", "Asian-Pac-Islander", "Amer-Indian-Eskimo", "Other"])
@@ -169,7 +169,7 @@ class Adult(datasets.GeneratorBasedBuilder):
     DEFAULT_CONFIG = "income"
     BUILDER_CONFIGS = [
         AdultConfig(name="encoding",
-                    description="Encoding dictionaries."),
+                    description="Encoding dictionaries for discrete features."),
         AdultConfig(name="income",
                     description="Adult for income threshold binary classification."),
         AdultConfig(name="income-no race",
@@ -234,7 +234,7 @@ class Adult(datasets.GeneratorBasedBuilder):
         return data
 
 
-    def preprocess(self, data: pandas.DataFrame, config: str = "income") -> pandas.DataFrame:
+    def preprocess(self, data: pandas.DataFrame, config: str = DEFAULT_CONFIG) -> pandas.DataFrame:
         data.drop("education", axis="columns", inplace=True)
         data = data.rename(columns={"threshold": "over_threshold"})