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customizedTraining
View on CRAN: Click
here
Download and install customizedTraining package within the R console
Install from CRAN:
install.packages("customizedTraining")
Install from Github:
library("remotes")
install_github("cran/customizedTraining") Install by package version:
library("remotes")
install_version("customizedTraining", "1.3") Attach the package and use:
library("customizedTraining")
Maintained by
Scott Powers
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2016-02-12
Latest Update: 2025-01-08
Description:
Customized training is a simple technique for transductive
learning, when the test covariates are known at the time of training. The
method identifies a subset of the training set to serve as the training set
for each of a few identified subsets in the training set. This package
implements customized training for the glmnet() and cv.glmnet() functions.
How to cite:
Scott Powers (2016). customizedTraining: Customized Training for Lasso and Elastic-Net Regularized Generalized Linear Models. R package version 1.3, https://cran.r-project.org/web/packages/customizedTraining. Accessed 02 Nov. 2026.
Previous versions and publish date:
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View customizedTraining citation profile
Other R packages that customizedTraining depends,
imports, suggests or enhances
Complete documentation for customizedTraining
Functions, R codes and Examples using
the customizedTraining R package
Some associated functions: Vowel . customizedGlmnet . cv.customizedGlmnet . nonzero.customizedGlmnet . nonzero . nonzero.singleton . plot.customizedGlmnet . plot.cv.customizedGlmnet . predict.customizedGlmnet . predict.cv.customizedGlmnet . predict.singleton . print.customizedGlmnet . print.cv.customizedGlmnet .
Some associated R codes: customizedGlmnet.R . cv.customizedGlmnet.R . nonzero.R . nonzero.customizedGlmnet.R . nonzero.singleton.R . plot.customizedGlmnet.R . plot.cv.customizedGlmnet.R . predict.customizedGlmnet.R . predict.cv.customizedGlmnet.R . predict.singleton.R . print.customizedGlmnet.R . print.cv.customizedGlmnet.R . Full customizedTraining package functions and examples
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