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-4.5)customizedTraining_1.3.zip(r-4.4)customizedTraining_1.3.zip(r-4.3)
customizedTraining_1.3.tgz(r-4.4-any)customizedTraining_1.3.tgz(r-4.3-any)
customizedTraining_1.3.tar.gz(r-4.5-noble)customizedTraining_1.3.tar.gz(r-4.4-noble)
customizedTraining_1.3.tgz(r-4.4-emscripten)customizedTraining_1.3.tgz(r-4.3-emscripten)
customizedTraining.pdf |customizedTraining.html✨
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:

2.70 score 1 stars 10 scripts 307 downloads 3 exports 11 dependencies

Last updated 2 months agofrom:edb4170a20. Checks:7 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKJan 23 2025
R-4.5-winOKJan 23 2025
R-4.5-linuxOKJan 23 2025
R-4.4-winOKJan 23 2025
R-4.4-macOKJan 23 2025
R-4.3-winOKJan 23 2025
R-4.3-macOKJan 23 2025

Exports:customizedGlmnetcv.customizedGlmnetnonzero

Dependencies:codetoolsFNNforeachglmnetiteratorslatticeMatrixRcppRcppEigenshapesurvival