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ODRF

0.0.5

Oblique Decision Random Forest for Classification and Regression

0packages depend
3Kdownloads / year
33.3%test coverage
13/13checks pass

Overview

About
Maintained by Yu LiuFirst published 2023-02-284 releasesCRAN page ↗GitHub ↗

The oblique decision tree (ODT) uses linear combinations of predictors as partitioning variables in a decision tree. Oblique Decision Random Forest (ODRF) is an ensemble of multiple ODTs generated by feature bagging. Oblique Decision Boosting Tree (ODBT) applies feature bagging during the training process of ODT-based boosting trees to ensemble multiple boosting trees. All three methods can be used for classification and regression, and ODT and ODRF serve as supplements to the classical CART of Breiman (1984) DOI:10.1201/9781315139470 and Random Forest of Breiman (2001) DOI:10.1023/A:1010933404324 respectively.

Install

Health

CRAN checks
13OK
Slowest check: 6.2 min · r-devel-windows-x86_64
Code health
Yes
Tests · ratio 0.06
33.3%
Coverage · measured lines
94%
Documentation · exports
17
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
  • OK2026-05-02
    13 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • NOTE2026-04-22
    12 OK · 2 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • ERROR2026-04-18
    11 OK · 2 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
Show 1 earlier snapshots
  • NOTE2026-03-10
    12 OK · 2 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE

Documentation

Documentation
READMEYes · 586 wordsVignettesYes · dynamicpkgdown siteNoNEWSYes · 100% structuredCode of conductNoContributing guideNo
Examples that run
100%
Documented parameters
84%
Return-value docs
100%
References docs
39%

Downloads

3K
CRAN downloads in the past year
Rank #14,364 · ~8/day · ~246/mo
Daily download trend is not available in this view yet.
19030 days
73790 days
3K1 year
Compare downloads with other packages →
Also on379 r2u20 autocran

Repository

Repository
7Stars
2Forks
8Open issues
0Open PRs
0Releases
154Commits
1Contributors
License GPL-3.0 · 154 commits · Last activity 2025-04-28

Stars over time

2023-12-28 · 82026-07-07 · 7

Repository practices

Upstream repositoryBeta

13 development-tooling and community-health practices detected across 7 families in the upstream repository

Checks run against github.com/liuyu-star/odrf on 2026-08-23.

Continuous integration (5)
GitHub ActionsGitLab CITravis CIAppVeyorCircleCI
Reproducibility and dev environment (1)
data-raw/
CRAN release process (2)
cran-comments.mdCRAN-SUBMISSION
Docs source (1)
README.Rmd
Show all practices
Lint, format, editor (1)
RStudio project
Coverage (1)
Codecov
Governance and community (2)
Issue templatesSupport guide
How this is detected·Detection ruleset v1 (2026-07-18)

Dependencies

Declared dependencies
17 external dependencies (excludes base and recommended)
Depends (2)
R >= 3.5.0partykit
Imports (16)
doParallelforeachgluegraphicsgridlifecyclemagrittrnnetparallelPursuitRcpprlangstatsrpartmethodsglmnet
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

Code & Tests

Datasets

People & History

People (2)
Maintainer (1)
Author, Maintainer, Copyright holder
Authors (2)
Author, Maintainer, Copyright holder
Copyright holders (1)
Author, Maintainer, Copyright holder
Package Timeline

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

  • R
    R 4.6.0 released · 2026-04-24
  • 0.0.5Latest
    2025-04-26 · current release · diff ↗
  • R
    R 4.5.0 released · 2025-04-11
  • R
    R 4.4.0 released · 2024-04-24
  • 0.0.4
    2023-05-28 · diff ↗
  • R
    R 4.3.0 released · 2023-04-21
  • 0.0.3
    2023-03-16 · diff ↗
  • 0.0.2
    2023-02-28
  • R
    R 4.2.0 released · 2022-04-22

Package metadata

First published
2023-02-28
Total releases
4 / 3 yrs
License
GPL (>= 3) OSI
Minimum R
≥ 3.5.0
Bundled data
74 KB / 3 files
Download size
247 KB
Installed size
not tracked yet
With dependencies
not tracked yet

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("ODRF")
Liu, Y., & Xia, Y. (2025). ODRF: Oblique Decision Random Forest for Classification and Regression (Version 0.0.5) [Computer software]. https://doi.org/10.32614/CRAN.package.ODRF

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 ODRF version 0.0.5 [Data set]. HJJB, LLC. Data release v2026-08-24. https://doi.org/10.5281/zenodo.21843040

From data release v2026-08-24, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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