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stablelearner: Stability Assessment of Statistical Learning Methods

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 ORCID iD [aut, cre], Thomas Rusch [aut], Kurt Hornik ORCID iD [aut], Lennart Schneider ORCID iD [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

Documentation:

Reference manual: stablelearner.pdf
Vignettes: Variable Selection and Cutpoint Analysis of Random Forests

Downloads:

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 dependencies:

Reverse suggests: psychotree

Linking:

Please use the canonical form https://CRAN.R-project.org/package=stablelearner to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.