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>.
Package details |
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Maintainer | |
License | MIT + file LICENSE |
Version | 0.1.5.9001 |
URL | https://github.com/ropensci/aorsf https://docs.ropensci.org/aorsf/ |
Package repository | View on GitHub |
Installation |
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