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roclab

0.1.4Package record

ROC-Optimizing Binary Classifiers

0packages depend
2.2Kdownloads / year
0.0%test coverage
13/13flavors OK

Overview

About

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: 8.7 min · r-oldrel-windows-x86_64
Status changes
  • OK13 OK2026-08-04
  • NOTE12 OK, 1 NOTE2026-08-01
  • OK13 OK2026-06-09
  • ERROR12 OK, 1 ERROR2026-06-08
  • OK13 OK2026-05-02
Show 2 earlier changesHide 2 earlier changes
  • ERROR11 OK, 1 ERROR2026-04-25
  • OK14 OK2026-03-10
Advisories

none known

Documentation

In release 0.1.4
READMEYes · 229 wordsVignettesYes · 1 · dynamicNEWSNoCitation fileNoWebsitenot declared in DESCRIPTION
Help pages
17 (1 internal)
Examples that run
100%15 run in a plain check
Exported functions with examples
83%
Documented parameters
100%
Return-value docs
100%
Help pages citing references
0%

Downloads

2.2K
CRAN downloads in the past year
Rank #18,584 · ~6/day · ~184/mo
Daily download trend is not available in this view yet.
31430 days
70190 days
2.2K1 year
Compare downloads with other packages →
Also on70 r2u4 autocran

Repository

3Stars
1Forks
0Open issues
0Open PRs
0Releases
25Commits
1Commit identities
25 commits · Last activity 2026-08-21 · 0% stars, 30d
Responsiveness
not measured

Stars over time

2025-10-29 · 22026-07-07 · 3
PracticesBeta

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

Checks run against github.com/gimunbae/roclab on 2026-10-18.

Continuous integration (2)
GitHub ActionsR CMD check workflow

The R CMD check workflow runs on Linux, macOS and Windows, and on R-devel

Lint, format, editor (1)
RStudio project
How this is detected·Detection ruleset v3 (2026-09-26)

Dependencies

Declared dependencies
12 external dependencies (excludes base and recommended)

Installing roclab adds 70 packages (37 with compiled code, 52 MB of source tarballs). Heaviest: stringi 11 MB, ggplot2 6.0 MB, data.table 5.7 MB.

Depends (0)
none
LinkingTo (0)
none
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

People & History

People (2)
Author, Maintainer since 0.1.3 (2025)
Releases (2)

Pick two releases to compare their code metrics.

  • R
    R 4.6.0 released · 2026-04-24
  • 0.1.4Latest
    record
    2025-11-04 · current release · diff ↗ ·
    added 1 export
    plot_roc
  • 0.1.3
    record
    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

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 package has no citation file, so citation() returns this entry built from DESCRIPTION.

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 v2026-10-22. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-22, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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