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""" |
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Collection of common benchmark datasets from fairness research. |
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Each dataset object contains a `pandas.DataFrame` as `df` attribute |
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that holds the actual data. |
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The dataset object will take care of loading, preprocessing |
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and validating the data. |
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The preprocessing is done by standard practices that are associated with |
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this data set: from its manual (e.g., README) |
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or as other did in the literature. |
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See :class:`ethically.dataset.Dataset` |
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for additional attribute and complete documentation. |
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Currently these are the available datasets: |
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- ProPublica recidivism/COMPAS dataset, |
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see: :class:`~ethically.dataset.COMPASDataset` |
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- Adult dataset, see: :class:`~ethically.dataset.AdultDataset` |
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- German credit dataset, see: :class:`~ethically.dataset.GermanDataset` |
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Usage |
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----- |
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.. code:: python |
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>>> from ethically.dataset import COMPASDataset |
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>>> compas_ds = COMPASDataset() |
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>>> print(compas_ds) |
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<ProPublica Recidivism/COMPAS Dataset. 6172 rows, 56 columns in |
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which {race, sex} are sensitive attributes> |
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>>> type(compas_ds.df) |
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<class 'pandas.core.frame.DataFrame'> |
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>>> compas_ds.df['race'].value_counts() |
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African-American 3175 |
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Caucasian 2103 |
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Hispanic 509 |
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Other 343 |
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Asian 31 |
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Native American 11 |
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Name: race, dtype: int64 |
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""" |
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from ethically.dataset.adult import AdultDataset |
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from ethically.dataset.compas import COMPASDataset |
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from ethically.dataset.core import Dataset |
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from ethically.dataset.fico import build_FICO_dataset |
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from ethically.dataset.german import GermanDataset |
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ResponsiblyAI /
responsibly
