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customizedTraining

1.3

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

0packages depend
2.4Kdownloads / year
test coverage
13/13checks pass

Overview

About
Maintained by Scott PowersFirst published 2016-02-124 releasesCRAN page ↗

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.

Install

Health

CRAN checks
13OK
Slowest check: 1.2 min · r-oldrel-windows-x86_64
Code health
None
Tests · ratio 0.00
not tracked
Coverage
100%
Documentation · exports
2
Dependencies · direct
Check history
  • OK2026-08-05
    13 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • NOTE2026-08-01
    12 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • OK2026-03-10
    14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE

Documentation

Documentation
READMEYes · 26 wordsVignettesNopkgdown siteNoNEWSNoCode of conductNoContributing guideNo
Examples that run
100%
Documented parameters
100%
Return-value docs
100%
References docs
8%

Downloads

2.4K
CRAN downloads in the past year
Rank #16,389 · ~6/day · ~197/mo
Daily download trend is not available in this view yet.
16330 days
65590 days
2.4K1 year
Compare downloads with other packages →
Also on112 r2u11 autocran

Dependencies

Declared dependencies
2 external dependencies (excludes base and recommended)
Depends (0)
none
Imports (2)
LinkingTo (0)
none
Suggests (0)
none
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

Code & Tests

Datasets

People & History

People (3)
Maintainer (1)
Author, Maintainer
Authors (3)
Author, Maintainer
Package Timeline

4 releases. Pick two to compare their code metrics. R releases are shown for context.

  • R
    R 4.6.0 released · 2026-04-24
  • R
    R 4.5.0 released · 2025-04-11
  • 1.3Latest
    2025-01-08 · current release · diff ↗
  • R
    R 4.4.0 released · 2024-04-24
  • R
    R 4.3.0 released · 2023-04-21
  • R
    R 4.2.0 released · 2022-04-22
  • R
    R 4.1.0 released · 2021-05-18
  • R
    R 4.0.0 released · 2020-04-24
  • R
    R 3.6.0 released · 2019-04-26
  • 1.2
    2019-01-29 · diff ↗
  • R
    R 3.5.0 released · 2018-04-23
  • R
    R 3.4.0 released · 2017-04-21
  • 1.1
    2016-09-14 · diff ↗
  • R
    R 3.3.0 released · 2016-05-03
  • 1.0
    2016-02-12
  • R
    R 3.2.0 released · 2015-04-16

Package metadata

First published
2016-02-12
Total releases
4 / 10 yrs
License
GPL-2 OSI
Bundled data
25 KB / 1 file
Download size
40 KB
Installed size
not tracked yet
With dependencies
not tracked yet

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("customizedTraining")
Powers, S., Hastie, T., & Tibshirani, R. (2025). customizedTraining: Customized Training for Lasso and Elastic-Net Regularized Generalized Linear Models (Version 1.3) [Computer software]. https://doi.org/10.32614/CRAN.package.customizedTraining

This is what citation() produces when a package has no citation file of its own. If it prints something else, use that.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

APA

Balamuta, J. J. (2026). R Observatory: Metrics for customizedTraining version 1.3 [Data set]. HJJB, LLC. Data release v2026-08-15. https://doi.org/10.5281/zenodo.21843040

From data release v2026-08-15, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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