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UBayFS

1.0

A User-Guided Bayesian Framework for Ensemble Feature Selection

0packages depend
2Kdownloads / year
49.7%test coverage
13/13checks pass

Overview

About
Maintained by Anna JenulFirst published 2023-03-071 releasesCRAN page ↗GitHub ↗

The framework proposed in Jenul et al., (2022) doi:10.1007/s10994-022-06221-9, together with an interactive Shiny dashboard. 'UBayFS' is an ensemble feature selection technique embedded in a Bayesian statistical framework. The method combines data and user knowledge, where the first is extracted via data-driven ensemble feature selection. The user can control the feature selection by assigning prior weights to features and penalizing specific feature combinations. 'UBayFS' can be used for common feature selection as well as block feature selection.

Install

Health

CRAN checks
13OK
Slowest check: 4.7 min · r-oldrel-windows-x86_64
Code health
Yes
Tests · ratio 0.12
49.7%
Coverage · measured lines
100%
Documentation · exports
11
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
READMENoVignettesYes · dynamicpkgdown siteNoNEWSNoCode of conductNoContributing guideNo
Examples that run
100%
Documented parameters
100%
Return-value docs
100%
References docs
0%

Downloads

2K
CRAN downloads in the past year
Rank #17,263 · ~6/day · ~169/mo
Daily download trend is not available in this view yet.
16830 days
62390 days
2K1 year
Compare downloads with other packages →
Also on102 r2u

Repository

Repository
5Stars
1Forks
1Open issues
0Open PRs
1Releases
360Commits
4Contributors
feature-selectionrensemble-modelsuser-knowledgebayesian-statistics
License GPL-3.0 · 360 commits · Last activity 2023-07-13

Stars over time

2023-04-30 · 52026-07-07 · 5

Repository practices

Upstream repositoryBeta

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

Checks run against github.com/annajenul/ubayfs 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
23 external dependencies (excludes base and recommended)
Depends (1)
R >= 3.5.0
LinkingTo (0)
none
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

Code & Tests

People & History

People (5)
Maintainer (1)
Author, Maintainer
Authors (2)
Author, Maintainer
Contributors (2)
Contributor
Contributor
Reviewers (1)
Package Timeline

1 release. R releases are shown for context.

  • R
    R 4.6.0 released · 2026-04-24
  • 1.0Latest
    2026-03-10 · current release
  • R
    R 4.5.0 released · 2025-04-11

Package metadata

First published
2023-03-07
Total releases
1 / 3 yrs
License
GPL-3 OSI
Minimum R
≥ 3.5.0
Bundled data
70 KB / 1 file
Download size
1.2 MB
Installed size
not tracked yet
With dependencies
not tracked yet

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("UBayFS")
Jenul, A., Liland, K. H., Pilz, J., Schrunner, S., & Tomic, O. (2023). UBayFS: A User-Guided Bayesian Framework for Ensemble Feature Selection (Version 1.0) [Computer software]. https://doi.org/10.32614/CRAN.package.UBayFS

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 UBayFS version 1.0 [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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