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cvwrapr
View on CRAN: Click
here
Download and install cvwrapr package within the R console
Install from CRAN:
install.packages("cvwrapr")
Install from Github:
library("remotes")
install_github("cran/cvwrapr") Install by package version:
library("remotes")
install_version("cvwrapr", "1.0") Attach the package and use:
library("cvwrapr")
Maintained by
Kenneth Tay
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[Scholar Profile | Author Map]
All associated links for this package
First Published: 2021-06-11
Latest Update:
Description:
Tools for performing cross-validation (CV). The main function is a
general purpose wrapper that performs k-fold CV for any tuning parameter in
any supervised learning method. The package also has a function that
computes the loss incurred by a set of predictions for a variety of loss
functions and model families.
How to cite:
Kenneth Tay (2021). cvwrapr: Tools for Cross Validation. R package version 1.0, https://cran.r-project.org/web/packages/cvwrapr. Accessed 08 Oct. 2026.
Previous versions and publish date:
(2026-07-09 07:29), 1.0 (2021-06-11 12:10)
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Other R packages that cvwrapr depends,
imports, suggests or enhances
Complete documentation for cvwrapr
Functions, R codes and Examples using
the cvwrapr R package
Some associated functions: availableTypeMeasures . buildPredMat . checkValidTypeMeasure . computeError . computeRawError . computeStats . coxnet.deviance . fid . getCindex . getOptLambda . getTypeMeasureName . kfoldcv . plot.cvobj . print.cvobj .
Some associated R codes: availableTypeMeasures.R . buildPredMat.R . checkValidTypeMeasure.R . computeError.R . computeRawError.R . computeStats.R . coxnet.deviance.R . getAUC.R . getCindex.R . getOptLambda.R . getSoftmax.R . getTypeMeasureName.R . kfoldcv.R . plot.cvobj.R . print.cvobj.R . Full cvwrapr package functions and examples
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