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Solving Imbalanced Regression Tasks

0packages depend
3Kdownloads / year
28.1%test coverage
13/13flavors OK

Overview

About

Imbalanced domain learning has almost exclusively focused on solving classification tasks, where the objective is to predict cases labelled with a rare class accurately. Such a well-defined approach for regression tasks lacked due to two main factors. First, standard regression tasks assume that each value is equally important to the user. Second, standard evaluation metrics focus on assessing the performance of the model on the most common cases. This package contains methods to tackle imbalanced domain learning problems in regression tasks, where the objective is to predict extreme (rare) values. The methods contained in this package are: 1) an automatic and non-parametric method to obtain such relevance functions; 2) visualisation tools; 3) suite of evaluation measures for optimisation/validation processes; 4) the squared-error relevance area measure, an evaluation metric tailored for imbalanced regression tasks. More information can be found in Ribeiro and Moniz (2020) doi:10.1007/s10994-020-05900-9.

Install

Health

CRAN checks
13OK
Slowest check: 2.9 min · r-devel-windows-x86_64
Status changes
  • OK13 OK2026-08-05
  • NOTE12 OK, 1 NOTE2026-08-01
  • OK13 OK2026-06-09
  • ERROR12 OK, 1 ERROR2026-06-08
  • OK14 OK2026-03-10
Advisories

none known

Documentation

In release 0.1.5
READMENoVignettesNoNEWSNoCitation fileNoWebsitenot declared in DESCRIPTION
Help pages
16 (8 internal)
Examples that run
100%8 run in a plain check
Exported functions with examples
100%
Documented parameters
100%
Return-value docs
100%
Help pages citing references
6%

Downloads

3K
CRAN downloads in the past year
Rank #15,524 · ~8/day · ~254/mo
Daily download trend is not available in this view yet.
29330 days
78590 days
3K1 year
Compare downloads with other packages →
Also on516 r2u5 autocran

Repository

19Stars
4Forks
0Open issues
1Open PRs
0Releases
9Commits
3Commit identities
machine-learningimbalanced-learningregressionimbalance-dataevaluation-metrics
9 commits · Last activity 2023-04-03 · The default branch showed an older version (0.1.4) than CRAN on 2026-10-18
Responsiveness
How these are sampled
PRs merged (all time)
not measured
Median days to close, 50 most recently updated closed issues
0
Median days to close, 50 most recently updated closed PRs
not measured

Stars over time

2024-10-24 · 192026-07-07 · 19
PracticesBeta

Checks run against github.com/nunompmoniz/iron on 2026-10-18.

No development-tooling practices detected in the upstream repository.

How this is detected·Detection ruleset v3 (2026-09-26)

Dependencies

Declared dependencies
12 external dependencies (excludes base and recommended)

Installing IRon adds 70 packages (34 with compiled code, 66 MB of source tarballs). Heaviest: stringi 11 MB, ggplot2 6.0 MB, doBy 4.3 MB.

Depends (1)
R >= 2.10
LinkingTo (1)
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

Datasets

People & History

People (3)
Maintainer since 0.1.5 (2025), Author
Contributor

Previously maintained by Nuno Moniz (0.1.0 to 0.1.4).

Releases (5)

Pick two releases to compare their code metrics.

  • R
    R 4.6.0 released · 2026-04-24
  • 0.1.5Latest
    record
    2025-10-31 · current release · diff ↗
  • R
    R 4.5.0 released · 2025-04-11
  • R
    R 4.4.0 released · 2024-04-24
  • R
    R 4.3.0 released · 2023-04-21
  • 0.1.4
    record
    2023-01-20 · diff ↗
  • 0.1.3
    record
    2022-10-29 · diff ↗
  • unarchivedReturned to CRAN
    2022-06-14
  • 0.1.2
    record
    2022-06-14 · diff ↗
  • archivedRemoved from CRAN
    2022-06-12
    check issues were not corrected in time
  • 0.1.0
    record
    2022-05-27
  • R
    R 4.2.0 released · 2022-04-22

Package metadata

First published
2022-05-27
Total releases
5 / 4 yrs
License
CC0
Minimum R
≥ 2.10
Bundled data
544 KB / 2 files
Download size
566 KB

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("IRon")
P. Ribeiro, R., Margarido, M., & Moniz, N. (2025). IRon: Solving Imbalanced Regression Tasks (Version 0.1.5) [Computer software]. https://doi.org/10.32614/CRAN.package.IRon

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 IRon version 0.1.5 [Data set]. HJJB, LLC. Data release v2026-10-21. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-21, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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