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aorsf: Accelerated Oblique Random Survival Forests
Fit, interpret, and make predictions with oblique random survival forests. Oblique decision trees are notoriously slow compared to their axis based counterparts, but 'aorsf' runs as fast or faster than axis-based decision tree algorithms for right-censored time-to-event outcomes. Methods to accelerate and interpret the oblique random survival forest are described in Jaeger et al., (2023) <DOI:10.1080/10618600.2023.2231048>.
Getting started
Browse package contents
Package details |
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| Author | Byron Jaeger [aut, cre] (<https://orcid.org/0000-0001-7399-2299>), Nicholas Pajewski [ctb], Sawyer Welden [ctb], Christopher Jackson [rev], Marvin Wright [rev], Lukas Burk [rev] |
| Maintainer | Byron Jaeger <bjaeger@wakehealth.edu> |
| License | MIT + file LICENSE |
| Version | 0.1.1 |
| URL | https://github.com/ropensci/aorsf https://docs.ropensci.org/aorsf/ |
| Package repository | View on CRAN |
| Installation |
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