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mlquantify

0.2.0Package record

Algorithms for Class Distribution Estimation

0packages depend
2.3Kdownloads / year
–test coverage
7/13flavors OK

Overview

About

Quantification is a prominent machine learning task that has received an increasing amount of attention in the last years. The objective is to predict the class distribution of a data sample. This package is a collection of machine learning algorithms for class distribution estimation. This package include algorithms from different paradigms of quantification. These methods are described in the paper: A. Maletzke, W. Hassan, D. dos Reis, and G. Batista. The importance of the test set size in quantification assessment. In Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, IJCAI20, pages 2640–2646, 2020. doi:10.24963/ijcai.2020/366.

Install

Health

CRAN checks
6NOTE7OK
Check messages
NOTERd cross-referencesr-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc, r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-patched-linux-x86_64, r-release-linux-x86_64
Unknown package ‘CORElearn’ in Rd xrefs
NOTEdependencies in R coder-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc
Namespaces in Imports field not imported from:
  ‘caret’ ‘randomForest’
All declared Imports should be used.

CRAN check page ↗

Slowest check: 1.2 min · r-oldrel-windows-x86_64
Status changes
  • NOTE7 OK, 6 NOTENow
  • NOTE11 OK, 2 NOTE2026-06-09
  • ERROR10 OK, 2 NOTE, 1 ERROR2026-06-08
  • NOTE11 OK, 2 NOTE2026-05-02
  • ERROR9 OK, 2 NOTE, 1 ERROR2026-04-25
  • NOTE12 OK, 2 NOTE2026-03-10
Advisories

none known

Documentation

In release 0.2.0
READMEYes · 1,047 wordsVignettesNoNEWSNoCitation fileNoWebsitenot declared in DESCRIPTION
Help pages
19
Examples that run
100%18 run in a plain check
Exported functions with examples
100%
Documented parameters
100%
Return-value docs
100%
Help pages citing references
89%

Downloads

2.3K
CRAN downloads in the past year
Rank #20,997 · ~6/day · ~188/mo
Daily download trend is not available in this view yet.
25330 days
63190 days
2.3K1 year
Compare downloads with other packages →
Also on68 r2u2 autocran

Repository

7Stars
1Forks
0Open issues
0Open PRs
0Releases
16Commits
1Commit identities
16 commits · Last activity 2022-01-20
Responsiveness
not measured

Stars over time

2025-01-25 · 72026-07-07 · 7
PracticesBeta

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

Checks run against github.com/andregustavom/mlquantify on 2026-10-18.

CRAN release process (1)
cran-comments.md
Lint, format, editor (1)
RStudio project
How this is detected·Detection ruleset v3 (2026-09-26)

Dependencies

Declared dependencies
4 external dependencies (excludes base and recommended)

Installing mlquantify adds 65 packages (36 with compiled code, 48 MB of source tarballs). Heaviest: stringi 11 MB, ggplot2 6.0 MB, data.table 5.7 MB.

Depends (0)
none
Imports (4)
LinkingTo (0)
none
Suggests (1)
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

Datasets

People & History

People (4)
Author, Maintainer since 0.1.4 (2020)
Contributor
Contributor
Thesis advisor
Releases (3)

Pick two releases to compare their code metrics.

  • R
    R 4.6.0 released · 2026-04-24
  • 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
  • R
    R 4.2.0 released · 2022-04-22
  • 0.2.0Latest
    record
    2022-01-20 · current release · diff ↗ ·
    added 1 export
    PWK
  • R
    R 4.1.0 released · 2021-05-18
  • unarchivedReturned to CRAN
    2021-04-13
  • 0.1.5
    record
    2021-04-13 · diff ↗ ·
    removed 2 exports
    TernarySearch, getHist
  • archivedRemoved from CRAN
    2021-04-06
    check problems were not corrected in time
  • 0.1.4
    record
    2020-09-23
  • R
    R 4.0.0 released · 2020-04-24

Package metadata

First published
2020-09-23
Total releases
3 / 6 yrs
License
GPL (>= 2.0)
Bundled data
83 KB / 1 file
Download size
105 KB

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("mlquantify")
Maletzke, A., Batista, G., Cherman, E., & dos Reis, D. (2022). mlquantify: Algorithms for Class Distribution Estimation (Version 0.2.0) [Computer software]. https://doi.org/10.32614/CRAN.package.mlquantify

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 mlquantify version 0.2.0 [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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