libuplift.datasets.Tamoxifen#

The Tamoxifen dataset from Melania Pintilie’s book “Competing Risks, A Practical Perspective”.

Functions#

fetch_Tamoxifen([data_home, download_if_missing, ...])

Load the Tamoxifen randomized trial dataset from Melania

Module Contents#

libuplift.datasets.Tamoxifen.fetch_Tamoxifen(data_home=None, download_if_missing=True, random_state=None, shuffle=False, categ_as_strings=False, return_X_y=False, as_frame=False)[source]#

Load the Tamoxifen randomized trial dataset from Melania Pintilie’s book “Competing Risks, A Practical Perspective.

The description of the original study can be found in [1].

Uses a local copy of the data.

Targets

  • target_surv_time: survival time

  • target_surv_status: 1=death

  • target_loctime:

  • target_lcens: 1=local relapse

  • target_axltime: time to axillary relapse

  • target_acens: 1=axillary relapse

  • target_distime: time to distance relapse

  • target_dcens: 1=distance relapse

  • target_maltime: time to second malignancy

  • target_mcens: 1=second malignancy

Parameters:
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.

categ_as_stringsbool, default=False

Whether to return categorical variables as strings.

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

Each row corresponds to the features in the dataset.

dataset.DESCRstring

Description of the dataset.

(data, target_time, target_status)tuple if

return_X_y is True

References

[1]

A.W. Fyles, et al., “Tamoxifen with or without breast irradiation in women 50 years of age or older with early breast cancer”. New England Journal of Medicine, 351(10), 963–970, 2004 (https://www.nejm.org/doi/10.1056/NEJMoa040595).