libuplift.datasets.tDCS#

tDCS dataset from Kaggle.

A randomized controlled trial dataset for tDCS (transcranial direct current stimulation) for allergic rhinitis treatment. Dataset from: https://www.kaggle.com/datasets/ziya07/randomized-controlled-trial-dataset

The dataset contains information about patients undergoing tDCS treatment for allergic rhinitis, including demographic information, treatment details, and outcomes.

Functions#

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

Load the tDCS dataset (uplift classification).

Module Contents#

libuplift.datasets.tDCS.fetch_tDCS(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 tDCS dataset (uplift classification).

Download it if necessary.

The treatment can be Sham (control) of tDCS. There is also a polarity attribute describing treatment polarity ‘-’ for controls.

The main target variable is whether a petient positively responded to treatment. Additional targets include measured biomarkers and symptom scores assessed at various time points after therapy.

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.targetnumpy array

Each value is 1 if treatment was successful, 0 otherwise.

dataset.treatmentnumpy array

Each value indicates the treatment group (0 or 1).

dataset.DESCRstring

Description of the tDCS dataset.

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