libuplift.datasets.Lalonde#

The Lalonde (jobs) datasets.

There are two versions of the dataset, including 1974 earnings (version B) and excluding 1974 earnings (vestion A).

Functions#

fetch_Lalonde([version, data_home, categ_as_strings, ...])

Load the Lalonde datasets (uplift regression).

Module Contents#

libuplift.datasets.Lalonde.fetch_Lalonde(version='A', data_home=None, categ_as_strings=False, download_if_missing=True, random_state=None, shuffle=False, return_X_y=False, as_frame=False)[source]#

Load the Lalonde datasets (uplift regression).

Download it if necessary.

There are two versions of the dataset, including 1974 earnings (version B) and excluding 1974 earnings (vestion A). Source: http://users.nber.org/~rdehejia/data/nswdata2.html

Parameters:
versionstring, optional

Specify which dataset to return. ‘A’ for larger files without 1974 earnings, ‘B’ for smaller files with 1974 earnings.

data_homestring, optional

Specify another download and cache folder for the datasets. By default all scikit-learn data is stored in ‘~/scikit_learn_data’ subfolders.

download_if_missingboolean, default=True

If False, raise a IOError if the data is not locally available instead of trying to download the data from the source site.

random_stateint, RandomState instance or None (default)

Determines random number generation for dataset shuffling. Pass an int for reproducible output across multiple function calls.

shufflebool, default=False

Whether to shuffle dataset.

return_X_yboolean, default=False.

If True, returns (data.data, data.target) instead of a Bunch object.

as_frameboolean, default=False

If True features are returned as pandas DataFrame. If False features are returned as object or float array. Float array is returned if all features are floats.

Returns:
datasetdict-like object with the following attributes:
dataset.datanumpy array of shape (581012, 54)

Each row corresponds to the 54 features in the dataset.

dataset.targetnumpy array of shape (581012,)

Each value corresponds to one of the 7 forest covertypes with values ranging between 1 to 7.

dataset.DESCRstring

Description of the forest covertype dataset.

(data, target)tuple if return_X_y is True