R Observatory: Metrics for rerf version 2.0.4

Balamuta, James Joseph

doi:10.5281/zenodo.21843040

This package was removed from CRAN on 2020-10-28. Its history is shown below.

Reason: check issues were not corrected in time

Details below reflect version 2.0.4, its last release before removal.

rerf

2.0.4Package record

Randomer Forest

0packages depend

–downloads / year

–test coverage

–flavors OK

Overview

About

Maintained by Jesse PatsolicCRAN page ↗GitHub ↗

R-RerF (aka Randomer Forest (RerF) or Random Projection Forests) is an algorithm developed by Tomita (2016) arXiv:1506.03410v2 which is similar to Random Forest - Random Combination (Forest-RC) developed by Breiman (2001) doi:10.1023/A:1010933404324. Random Forests create axis-parallel, or orthogonal trees. That is, the feature space is recursively split along directions parallel to the axes of the feature space. Thus, in cases in which the classes seem inseparable along any single dimension, Random Forests may be suboptimal. To address this, Breiman also proposed and characterized Forest-RC, which uses linear combinations of coordinates rather than individual coordinates, to split along. This package, 'rerf', implements RerF which is similar to Forest-RC. The difference between the two algorithms is where the random linear combinations occur: Forest-RC combines features at the per tree level whereas RerF takes linear combinations of coordinates at every node in the tree.

Install

R (source archive)pak (dev)

url <- "https://cran.r-project.org/src/contrib/Archive/rerf/rerf_2.0.4.tar.gz"
pkgFile <- "rerf_2.0.4.tar.gz"
download.file(url, pkgFile)
install.packages(pkgFile, type = "source", repos = NULL)

This package is no longer on CRAN, so install.packages() cannot fetch it by name. This downloads the last archived source (2.0.4) and builds it locally. Install its dependencies first, and note that building from source needs the usual compiler toolchain.

if (!requireNamespace("pak", quietly = TRUE))
  install.packages("pak", repos = "https://cloud.r-project.org/")
pak::pak("neurodata/R-RerF")

Development version from neurodata/R-RerF. Installs pak first if it is not already available.

Health

CRAN checks

CRAN check results are not tracked yet.

Advisories

none known

How this is measured·How advisories are found

Documentation

In release 2.0.4

READMEYes · 1,008 wordsVignettesNoNEWSYes · 100% structured · does not mention 2.0.4Citation fileNoWebsitenot declared in DESCRIPTION

Help pages: 40 (1 internal)
Examples that run: 100%23 run in a plain check
Exported functions with examples: 100%
Documented parameters: 98%
Return-value docs: 100%
Help pages citing references: 3%

How these are measured

Downloads

rerf Releases R versions

Daily download trend is not available in this view yet.

Compare downloads with other packages →

How downloads are counted

Dependencies

Declared dependencies

8 external dependencies (excludes base and recommended)

Depends (2)

R >= 3.3.0Rcpp

Imports (6)

parallelRcppZigguratutilsstatsdummies mclust

LinkingTo (2)

Rcpp RcppArmadillo

Suggests (2)

roxygen2 testthat

Enhances (0)

none

Dependency license breakdown →

Reverse dependencies

0direct

–indirect (not tracked)

Nothing depends on this yet.

How these are counted

Code & Tests

Datasets

People & History

People (6)

Jesse Patsolic

Contributor, Maintainer since 2.0.2 (2018) · added in 2.0.2

James Browne

Author

Tyler Tomita

Author

Benjamin Falk

Contributor · added in 2.0.2

Jaewon Chung

Contributor · added in 2.0.2

Joshua Vogelstein

Thesis advisor · added in 1.1.1

Previously maintained by James Browne (1.0 to 1.1.3).

Releases (7)

Pick two releases to compare their code metrics.

R
R 4.1.0 released · 2021-05-18
archivedRemoved from CRAN
2020-10-28
check issues were not corrected in time
R
R 4.0.0 released · 2020-04-24
R
R 3.6.0 released · 2019-04-26
2.0.4
record
2019-03-15 · diff ↗
2.0.3
record
2019-02-06 · diff ↗ ·
added 1 export
PrintTree
2.0.2
record
2018-12-04 · diff ↗ ·
removed 3 exports
RandMat, RandMatCat, PackForest

added 11 exports
RandMatBinary, RandMatContinuous, RandMatCustom, RandMatFRC, RandMatFRCN, RandMatImageControl, RandMatImagePatch, RandMatPoisson, RandMatRF, RandMatTSpatch, Urerf
unarchivedReturned to CRAN
2018-07-29
1.1.3
record
2018-07-29 · diff ↗
archivedRemoved from CRAN
2018-07-25
C++ errors were not corrected despite reminder new/delete mismatches, alignment in new
1.1.2
record
2018-07-16 · diff ↗
1.1.1
record
2018-07-10 · diff ↗ ·
added 3 exports
FeatureImportance, PackForest, PackPredict
R
R 3.5.0 released · 2018-04-23
1.0
record
2017-10-08
R
R 3.4.0 released · 2017-04-21

Package metadata

First published: 2017-10-08
Total releases: 7 / 9 yrs
License: Apache License 2.0 | file LICENSE OSI · relicensed from GPL-2 in 2.0.2
Minimum R: ≥ 3.3.0
Bundled data: 3.1 MB / 2 files

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("rerf")

Format

Patsolic, J., Falk, B., Chung, J., Browne, J., Tomita, T., & Vogelstein, J. (n.d.). rerf: Randomer Forest (Version 2.0.4) [Computer software]. Retrieved October 26, 2026, from https://CRAN.R-project.org/package=rerf

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.

Format

APA

Balamuta, J. J. (2026). R Observatory: Metrics for rerf version 2.0.4 [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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