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Version: 0.0.1 | ||
Date: 2022-08-22 18:00:32 UTC | ||
SHA: ebf0254a9ce00f29f47458d176b0d7cc5bc9a1d6 | ||
Date: 2022-08-23 12:19:47 UTC | ||
SHA: 35dd46f06b82ff711b23781dc7374723737096df |
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email = "[email protected]", | ||
role = "rev") | ||
) | ||
Description: 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>. | ||
Description: 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>. | ||
License: MIT + file LICENSE | ||
Encoding: UTF-8 | ||
LazyData: true | ||
|
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YEAR: 2021 | ||
COPYRIGHT HOLDER: orsf2 authors | ||
YEAR: 2022 | ||
COPYRIGHT HOLDER: aorsf authors (Byron C. Jaeger, Sawyer Welden, and Nicholas M. Pajewski) |
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