Graphical and computational methods that can be used to assess the stability of results from supervised statistical learning.
Version: | 0.1-5 |
Depends: | R (≥ 3.0.0) |
Imports: | graphics, methods, MASS, e1071, partykit, party, randomForest, ranger |
Suggests: | utils, Formula, nnet, rpart, evtree, rchallenge, knitr, rmarkdown |
Published: | 2023-04-13 |
DOI: | 10.32614/CRAN.package.stablelearner |
Author: | Michel Philipp [aut], Carolin Strobl [aut], Achim Zeileis [aut, cre], Thomas Rusch [aut], Kurt Hornik [aut], Lennart Schneider [aut] |
Maintainer: | Achim Zeileis <Achim.Zeileis at R-project.org> |
License: | GPL-2 | GPL-3 |
NeedsCompilation: | no |
Citation: | stablelearner citation info |
Materials: | NEWS |
CRAN checks: | stablelearner results |
Reference manual: | stablelearner.pdf |
Vignettes: |
Variable Selection and Cutpoint Analysis of Random Forests |
Package source: | stablelearner_0.1-5.tar.gz |
Windows binaries: | r-devel: stablelearner_0.1-5.zip, r-release: stablelearner_0.1-5.zip, r-oldrel: stablelearner_0.1-5.zip |
macOS binaries: | r-release (arm64): stablelearner_0.1-5.tgz, r-oldrel (arm64): stablelearner_0.1-5.tgz, r-release (x86_64): stablelearner_0.1-5.tgz, r-oldrel (x86_64): stablelearner_0.1-5.tgz |
Old sources: | stablelearner archive |
Reverse suggests: | psychotree |
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