fairlearn.datasets.fetch_adult#

fairlearn.datasets.fetch_adult(*, cache=True, data_home=None, as_frame=True, return_X_y=False)[source]#

Load the UCI Adult dataset (binary classification).

Read more in the User Guide.

Download it if necessary.

Samples total

48842

Dimensionality

14

Features

numeric, categorical

Classes

2

Source: UCI Repository [1] , Paper: R. Kohavi (1996) [2]

Prediction task is to determine whether a person makes over $50,000 a year.

Read more in the User Guide.

New in version 0.5.0.

Parameters

  • cache (bool, default=True) – Whether to cache downloaded datasets using joblib.

  • data_home (str, default=None) – Specify another download and cache folder for the datasets. By default, all fairlearn data is stored in ‘~/.fairlearn-data’ subfolders.

  • as_frame (bool, default=True) –

    If True, the data is a pandas DataFrame including columns with appropriate dtypes (numeric, string or categorical). The target is a pandas DataFrame or Series depending on the number of target_columns. The Bunch will contain a frame attribute with the target and the data. If return_X_y is True, then (data, target) will be pandas DataFrames or Series as describe above.

    Changed in version 0.9.0: Default value changed to True.

  • return_X_y (bool, default=False) – If True, returns (data.data, data.target) instead of a Bunch object.

Returns

  • dataset (Bunch) – Dictionary-like object, with the following attributes.

    datandarray, shape (48842, 14)

    Each row corresponding to the 14 feature values in order. If as_frame is True, data is a pandas object.

    targetnumpy array of shape (48842,)

    Each value represents whether the person earns more than $50,000 a year (>50K) or not (<=50K). If as_frame is True, target is a pandas object.

    feature_nameslist of length 14

    Array of ordered feature names used in the dataset.

    DESCRstring

    Description of the UCI Adult dataset.

    categoriesdict or None

    Maps each categorical feature name to a list of values, such that the value encoded as i is ith in the list. If as_frame is True, this is None.

    framepandas DataFrame

    Only present when as_frame is True. DataFrame with data and target.

  • (data, target) (tuple if return_X_y is True)

Notes

Our API largely follows the API of sklearn.datasets.fetch_openml().

References

1

R. Kohavi and B. Becker, UCI Machine Learning Repository: Adult Data Set, 01-May-1996. [Online]. Available: https://archive.ics.uci.edu/ml/datasets/adult.

2

R. Kohavi, “Scaling Up the Accuracy of Naive-Bayes Classifiers: a Decision-Tree Hybrid,” in Second International Conference on knowledge discovery and data mining: proceedings: August 2-4, 1996, Portland, Oregon, 1996, pp. 202–207.