Mlr3proba: An R Package for Machine Learning in Survival Analysis

MCML Authors

Andreas Bender

Dr.

→ Group Bernd Bischl
 Statistical Learning and Data Science

Bernd Bischl

Prof. Dr.

Director

Statistical Learning and Data Science

Michel Lang

Dr.

* Former Member

→ Group Bernd Bischl
 Statistical Learning and Data Science

Abstract

As machine learning has become increasingly popular over the last few decades, so too has the number of machine-learning interfaces for implementing these models. Whilst many R libraries exist for machine learning, very few offer extended support for survival analysis. This is problematic considering its importance in fields like medicine, bioinformatics, economics, engineering and more. mlr3proba provides a comprehensive machine-learning interface for survival analysis and connects with mlr3’s general model tuning and benchmarking facilities to provide a systematic infrastructure for survival modelling and evaluation.

article SKB+21

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Bioinformatics

37.17. Sep. 2021.

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Authors

R. Sonabend • F. J. Király • A. Bender • B. Bischl • M. Lang

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Links

DOI

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Research Area

 A1 | Statistical Foundations & Explainability