aorsf: Accelerated Oblique Random Survival ForestsSource:
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., (2022) arXiv:2208.01129.
Maintainer: Byron Jaeger [email protected] (ORCID)
Nicholas Pajewski [contributor]
Sawyer Welden [email protected] [contributor]
Christopher Jackson [email protected] [reviewer]
Marvin Wright [reviewer]
Lukas Burk [reviewer]