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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: | 0.1-7 |
| Imports: | gbm, dplyr, rpart, rpart.plot |
| Suggests: | pdp, randomForest |
| Published: | 2023-09-13 |
| Author: | Gero Szepannek [aut, cre] |
| Maintainer: | Gero Szepannek <gero.szepannek at web.de> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: | no |
| Citation: | xgrove citation info |
| Materials: | README NEWS |
| CRAN checks: | xgrove results |
| Reference manual: | xgrove.pdf |
| Package source: | xgrove_0.1-7.tar.gz |
| Windows binaries: | r-devel: xgrove_0.1-7.zip, r-release: xgrove_0.1-7.zip, r-oldrel: xgrove_0.1-7.zip |
| macOS binaries: | r-release (arm64): xgrove_0.1-7.tgz, r-oldrel (arm64): xgrove_0.1-7.tgz, r-release (x86_64): xgrove_0.1-7.tgz, r-oldrel (x86_64): xgrove_0.1-7.tgz |
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