The hardware and bandwidth for this mirror is donated by METANET, the Webhosting and Full Service-Cloud Provider.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]metanet.ch.

CARRoT: Predicting Categorical and Continuous Outcomes Using One in Ten Rule

Predicts categorical or continuous outcomes while concentrating on a number of key points. These are Cross-validation, Accuracy, Regression and Rule of Ten or "one in ten rule" (CARRoT), and, in addition to it R-squared statistics, prior knowledge on the dataset etc. It performs the cross-validation specified number of times by partitioning the input into training and test set and fitting linear/multinomial/binary regression models to the training set. All regression models satisfying chosen constraints are fitted and the ones with the best predictive power are given as an output. Best predictive power is understood as highest accuracy in case of binary/multinomial outcomes, smallest absolute and relative errors in case of continuous outcomes. For binary case there is also an option of finding a regression model which gives the highest AUROC (Area Under Receiver Operating Curve) value. The option of parallel toolbox is also available. Methods are described in Peduzzi et al. (1996) <doi:10.1016/S0895-4356(96)00236-3> , Rhemtulla et al. (2012) <doi:10.1037/a0029315>, Riley et al. (2018) <doi:10.1002/sim.7993>, Riley et al. (2019) <doi:10.1002/sim.7992>.

Version: 3.0.2
Depends: R (≥ 3.4.0)
Imports: stats, utils, nnet, doParallel, Rdpack, parallel, foreach
Published: 2023-10-13
DOI: 10.32614/CRAN.package.CARRoT
Author: Alina Bazarova [aut, cre], Marko Raseta [aut]
Maintainer: Alina Bazarova <al.bazarova at fz-juelich.de>
License: GPL-2
NeedsCompilation: yes
Citation: CARRoT citation info
CRAN checks: CARRoT results

Documentation:

Reference manual: CARRoT.pdf

Downloads:

Package source: CARRoT_3.0.2.tar.gz
Windows binaries: r-devel: CARRoT_3.0.2.zip, r-release: CARRoT_3.0.2.zip, r-oldrel: CARRoT_3.0.2.zip
macOS binaries: r-release (arm64): CARRoT_3.0.2.tgz, r-oldrel (arm64): CARRoT_3.0.2.tgz, r-release (x86_64): CARRoT_3.0.2.tgz, r-oldrel (x86_64): CARRoT_3.0.2.tgz
Old sources: CARRoT archive

Linking:

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