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aorsf: Accelerated Oblique Random Forests
Fit, interpret, and compute predictions with oblique random forests. Includes support for partial dependence, variable importance, passing customized functions for variable importance and identification of linear combinations of features. Methods for 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 | 0.1.5 |
| URL | https://github.com/ropensci/aorsf https://docs.ropensci.org/aorsf/ |
| Package repository | View on CRAN |
| Installation |
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