Datasets:
Upload adult.py
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adult.py
CHANGED
@@ -130,8 +130,15 @@ class Adult(datasets.GeneratorBasedBuilder):
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AdultConfig(name="income-no race",
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description="Adult for income threshold binary classification, race excluded from features."),
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AdultConfig(name="race",
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-
description="Adult for race multiclass classification."),
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]
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def _info(self):
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if self.config.name not in features_per_config:
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@@ -191,6 +198,7 @@ class Adult(datasets.GeneratorBasedBuilder):
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features = list(features_types_per_config["race"].keys())
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features[features.index("over_threshold")] = "threshold"
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data.loc[:, "over_threshold"] = data.sex.apply(str)
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data = data[features]
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data.columns = ["age", "capital_gain", "capital_loss", "education", "final_weight",
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"hours_per_week", "marital_status", "native_country", "occupation", "relationship", "sex", "workclass", "over_threshold", "race"]
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AdultConfig(name="income-no race",
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description="Adult for income threshold binary classification, race excluded from features."),
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AdultConfig(name="race",
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description="Adult for race (multiclass) classification."),
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]
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race_encoder = {
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"White": 0,
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"Black": 1,
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"Asian-Pac-Islander": 2,
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"Amer-Indian-Eskimo": 3,
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"Other": 4,
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}
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def _info(self):
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if self.config.name not in features_per_config:
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features = list(features_types_per_config["race"].keys())
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features[features.index("over_threshold")] = "threshold"
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data.loc[:, "over_threshold"] = data.sex.apply(str)
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data.loc[:, "race"] = data.sex.apply(lambda x: race_encoder[x])
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data = data[features]
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data.columns = ["age", "capital_gain", "capital_loss", "education", "final_weight",
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"hours_per_week", "marital_status", "native_country", "occupation", "relationship", "sex", "workclass", "over_threshold", "race"]
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