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StratifiedRF

0.2.2Package record

Builds Trees by Sampling Variables in Groups

0packages depend
2.5Kdownloads / year
–test coverage
11/13flavors OK

Overview

About

Random Forest-like tree ensemble that works with groups of predictor variables. When building a tree, a number of variables is taken randomly from each group separately, thus ensuring that it considers variables from each group for the splits. Useful when rows contain information about different things (e.g. user information and product information) and it's not sensible to make a prediction with information from only one group of variables, or when there are far more variables from one group than the other and it's desired to have groups appear evenly on trees. Trees are grown using the C5.0 algorithm rather than the usual CART algorithm. Supports parallelization (multithreaded), missing values in predictors, and categorical variables (without doing One-Hot encoding in the processing). Can also be used to create a regular (non-stratified) Random Forest-like model, but made up of C5.0 trees and with some additional control options. As it's built with C5.0 trees, it works only for classification (not for regression).

Install

Health

CRAN checks
2NOTE11OK
Check messages
NOTECRAN incoming feasibilityr-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc
Maintainer: ‘David Cortes <david.cortes.rivera@gmail.com>’

No Authors@R field in DESCRIPTION.
Please add one, modifying
  Authors@R: person(given = "David",
                    family = "Cortes",
                    role = c("aut", "cre"),
                    email = "david.cortes.rivera@gmail.com")
as necessary.

CRAN check page ↗

Slowest check: 1.9 min · r-oldrel-windows-x86_64
Status changes
  • NOTE11 OK, 2 NOTENow
  • NOTE9 OK, 5 NOTE2026-03-10
Advisories

none known

Documentation

In release 0.2.2
READMENoVignettesNoNEWSNoCitation fileNoWebsitenot declared in DESCRIPTION
Help pages
5
Examples that run
100%5 run in a plain check
Exported functions with examples
100%
Documented parameters
100%
Return-value docs
50%
Help pages citing references
0%

Downloads

2.5K
CRAN downloads in the past year
Rank #18,995 · ~7/day · ~210/mo
Daily download trend is not available in this view yet.
25030 days
69590 days
2.5K1 year
Compare downloads with other packages →
Also on89 r2u135 c2d4u

Dependencies

Declared dependencies
2 external dependencies (excludes base and recommended)

Installing StratifiedRF adds 30 packages (20 with compiled code, 27 MB of source tarballs). Heaviest: stringi 11 MB, partykit 2.1 MB, Rcpp 1.8 MB.

Depends (0)
none
Imports (4)
C50dplyrparallelstats
LinkingTo (0)
none
Suggests (0)
none
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

People & History

People (from the free-text Author field) (1)

Maintainer since 0.1.1 (2017)

Releases (2)

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
  • R
    R 4.1.0 released · 2021-05-18
  • R
    R 4.0.0 released · 2020-04-24
  • R
    R 3.6.0 released · 2019-04-26
  • R
    R 3.5.0 released · 2018-04-23
  • 0.2.2Latest
    record
    2017-06-30 · current release · diff ↗
  • 0.1.1
    record
    2017-06-21
  • R
    R 3.4.0 released · 2017-04-21

Package metadata

First published
2017-06-21
Total releases
2 / 9 yrs
License
GPL-3 OSI
Download size
8.2 KB
Appears in task views

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("StratifiedRF")

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 StratifiedRF version 0.2.2 [Data set]. HJJB, LLC. Data release v2026-10-25. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-25, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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