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roclab

0.1.4

ROC-Optimizing Binary Classifiers

0packages depend
1.6Kdownloads / year
0.0%test coverage
13/13checks pass

Overview

About
Maintained by Gimun BaeFirst published 2025-10-282 releasesCRAN page ↗GitHub ↗

Implements ROC (Receiver Operating Characteristic)–Optimizing Binary Classifiers, supporting both linear and kernel models. Both model types provide a variety of surrogate loss functions. In addition, linear models offer multiple regularization penalties, whereas kernel models support a range of kernel functions. Scalability for large datasets is achieved through approximation-based options, which accelerate training and make fitting feasible on large data. Utilities are provided for model training, prediction, and cross-validation. The implementation builds on the ROC-Optimizing Support Vector Machines. For more information, see Hernàndez-Orallo, José, et al. (2004) doi:10.1145/1046456.1046489, presented in the ROC Analysis in AI Workshop (ROCAI-2004).

Install

Health

CRAN checks
13OK
Slowest check: 8.9 min · r-oldrel-windows-x86_64
Code health
Yes
Tests · ratio 0.09
0.0%
Coverage · measured lines
100%
Documentation · exports
11
Dependencies · direct
Check history
  • OK2026-08-04
    13 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • NOTE2026-08-01
    12 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • OK2026-06-09
    13 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • ERROR2026-06-08
    12 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
  • OK2026-05-02
    13 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Show 2 earlier snapshots
  • ERROR2026-04-25
    11 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
  • OK2026-03-10
    14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE

Documentation

Documentation
READMEYes · 229 wordsVignettesYes · dynamicpkgdown siteNoNEWSNoCode of conductNoContributing guideNo
Examples that run
100%
Documented parameters
100%
Return-value docs
100%
References docs
0%

Downloads

1.6K
CRAN downloads in the past year
Rank #22,120 · ~4/day · ~135/mo
Daily download trend is not available in this view yet.
13430 days
49090 days
1.6K1 year
Compare downloads with other packages →
Also on65 r2u22 autocran

Repository

Repository
3Stars
1Forks
0Open issues
0Open PRs
0Releases
24Commits
1Contributors
24 commits · Last activity 2025-11-04 · 0% stars, 30d

Stars over time

2025-10-29 · 22026-07-07 · 3

Repository practices

Upstream repositoryBeta

2 development-tooling and community-health practices detected across 2 families in the upstream repository

Checks run against github.com/gimunbae/roclab on 2026-08-16.

Continuous integration (1)
GitHub Actions
Lint, format, editor (1)
RStudio project
How this is detected·Detection ruleset v1 (2026-07-18)

Dependencies

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

Nothing depends on this yet.

Code & Tests

People & History

People (2)
Maintainer (1)
Author, Maintainer
Authors (2)
Author, Maintainer
Package Timeline

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

  • R
    R 4.6.0 released · 2026-04-24
  • 0.1.4Latest
    2025-11-04 · current release · diff ↗
  • 0.1.3
    2025-10-28
  • R
    R 4.5.0 released · 2025-04-11

Package metadata

First published
2025-10-28
Total releases
2 / 1 yrs
License
MIT + file LICENSE OSI
Download size
101 KB
Installed size
not tracked yet
With dependencies
not tracked yet

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("roclab")
Bae, G., & Shin, S. J. (2025). roclab: ROC-Optimizing Binary Classifiers (Version 0.1.4) [Computer software]. https://doi.org/10.32614/CRAN.package.roclab

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 roclab version 0.1.4 [Data set]. HJJB, LLC. Data release v2026-08-16. https://doi.org/10.5281/zenodo.21843040

From data release v2026-08-16, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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