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ipred: Improved Predictors

Improved predictive models by indirect classification and bagging for classification, regression and survival problems as well as resampling based estimators of prediction error.

Version: 0.9-14
Depends: R (≥ 2.10)
Imports: rpart (≥ 3.1-8), MASS, survival, nnet, class, prodlim
Suggests: mvtnorm, mlbench, TH.data, randomForest, party
Published: 2023-03-09
Author: Andrea Peters [aut], Torsten Hothorn [aut, cre], Brian D. Ripley [ctb], Terry Therneau [ctb], Beth Atkinson [ctb]
Maintainer: Torsten Hothorn <Torsten.Hothorn at R-project.org>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
Copyright: see file COPYRIGHTS
NeedsCompilation: yes
Materials: NEWS
In views: Environmetrics, MachineLearning, Survival
CRAN checks: ipred results

Documentation:

Reference manual: ipred.pdf
Vignettes: Some more or less useful examples for illustration.

Downloads:

Package source: ipred_0.9-14.tar.gz
Windows binaries: r-devel: ipred_0.9-14.zip, r-release: ipred_0.9-14.zip, r-oldrel: ipred_0.9-14.zip
macOS binaries: r-release (arm64): ipred_0.9-14.tgz, r-oldrel (arm64): ipred_0.9-14.tgz, r-release (x86_64): ipred_0.9-14.tgz, r-oldrel (x86_64): ipred_0.9-14.tgz
Old sources: ipred archive

Reverse dependencies:

Reverse imports: ICcforest, LTRCforests, mlearning, nlcv, optBiomarker, permimp, pheble, pomodoro, recipes, RecordLinkage, RTextTools, survcomp
Reverse suggests: butcher, caret, caretEnsemble, censored, ensembleR, flowml, fscaret, MLInterfaces, party, pdp, subsemble, SuperLearner, superMICE

Linking:

Please use the canonical form https://CRAN.R-project.org/package=ipred 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.
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