Compute surrogate explanation groves for predictive machine learning models and analyze complexity vs. explanatory power of an explanation according to Szepannek, G. and von Holt, B. (2023) <doi:10.1007/s41237-023-00205-2>.
Version: | 0.1-13 |
Imports: | gbm, dplyr, rpart, rpart.plot |
Suggests: | pdp, randomForest |
Published: | 2024-09-22 |
DOI: | 10.32614/CRAN.package.xgrove |
Author: | Gero Szepannek [aut, cre] |
Maintainer: | Gero Szepannek <gero.szepannek at web.de> |
License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
NeedsCompilation: | no |
Materials: | README NEWS |
CRAN checks: | xgrove results |
Reference manual: | xgrove.pdf |
Package source: | xgrove_0.1-13.tar.gz |
Windows binaries: | r-devel: xgrove_0.1-13.zip, r-release: xgrove_0.1-13.zip, r-oldrel: xgrove_0.1-13.zip |
macOS binaries: | r-release (arm64): xgrove_0.1-13.tgz, r-oldrel (arm64): xgrove_0.1-13.tgz, r-release (x86_64): xgrove_0.1-13.tgz, r-oldrel (x86_64): xgrove_0.1-13.tgz |
Old sources: | xgrove archive |
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