mlr3proba: An R Package for Machine Learning in Survival Analysis

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 modeling and evaluation.

Submitted to Bioinformatics

References in corpus (4)

• Scikit-learn: Machine Learning in Python
• Random survival forests
• Time-to-Event Prediction with Neural Networks and Cox Regression
• Probabilistic supervised learning

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• Deep Learning for Survival Analysis: A Review
• survex: an R package for explaining machine learning survival models
• Interpretable machine learning for time-to-event prediction in medicine and healthcare
• Designing Machine Learning Toolboxes: Concepts, Principles and Patterns
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