| Literature DB >> 33523131 |
Raphael Sonabend1, Franz J Király1, Andreas Bender2, Bernd Bischl2, Michel Lang2.
Abstract
MOTIVATION: 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. AVAILABILITY: mlr3proba is available under an LGPL-3 license on CRAN and at https://github.com/mlr-org/mlr3proba, with further documentation at https://mlr3book.mlr-org.com/survival.html.Entities:
Year: 2021 PMID: 33523131 DOI: 10.1093/bioinformatics/btab039
Source DB: PubMed Journal: Bioinformatics ISSN: 1367-4803 Impact factor: 6.937