Package: customizedTraining 1.3

customizedTraining: Customized Training for Lasso and Elastic-Net Regularized Generalized Linear Models

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.

Authors:Scott Powers [aut, cre], Trevor Hastie [aut], Robert Tibshirani [aut]

customizedTraining_1.3.tar.gz
customizedTraining_1.3.zip(r-4.7)customizedTraining_1.3.zip(r-4.6)customizedTraining_1.3.zip(r-4.5)
customizedTraining_1.3.tgz(r-4.6-any)customizedTraining_1.3.tgz(r-4.5-any)
customizedTraining_1.3.tar.gz(r-4.7-any)customizedTraining_1.3.tar.gz(r-4.6-any)
customizedTraining_1.3.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
customizedTraining/json (API)

# Install 'customizedTraining' in R:
install.packages('customizedTraining', repos = c('https://saberpowers.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/saberpowers/customizedtraining/issues

Datasets:
  • Vowel - Vowel Recognition

On CRAN:

Conda:

2.70 score 1 stars 10 scripts 216 downloads 3 exports 11 dependencies

Last updated from:edb4170a20. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK112
source / vignettesOK147
linux-release-x86_64OK103
macos-release-arm64OK166
macos-oldrel-arm64OK195
windows-develOK94
windows-releaseOK65
windows-oldrelOK74
wasm-releaseOK113

Exports:customizedGlmnetcv.customizedGlmnetnonzero

Dependencies:codetoolsFNNforeachglmnetiteratorslatticeMatrixRcppRcppEigenshapesurvival