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Time-to-event (T2E) analysis is a branch of statistics that models theduration of time it takes for an event to occur. Such events can includeoutcomes like death, unemployment, or product failure. Most modern machinelearning (ML) algorithms, like decision trees and kernel methods, are supportedfor T2E modelling with data science software (python and R). To complementthese developments, SurvSet is the first open-source T2E dataset repositorydesigned for a rapid benchmarking of ML algorithms and statistical methods. Thedata in SurvSet have been consistently formatted so that a single preprocessingmethod will work for all datasets. SurvSet currently has 76 datasets which varyin dimensionality, time dependency, and background (the majority of which comefrom biomedicine). SurvSet is available on PyPI and can be installed with pipinstall SurvSet. R users can download the data directly from the correspondinggit repository.

SurvSet: An open-source time-to-event dataset repository