R Observatory: Metrics for classyfire version 0.1-2

Balamuta, James Joseph

doi:10.5281/zenodo.21843040

This package was removed from CRAN on 2019-04-22. Its history is shown below.

Reason: check errors were not corrected despite reminders

Details below reflect version 0.1-2, its last release before removal.

classyfire

0.1-2Package record

Robust multivariate classification using highly optimised SVM ensembles

0packages depend

–downloads / year

–test coverage

–flavors OK

Overview

About

Maintained by Eleni ChatzimichaliCRAN page ↗

A collection of functions for the creation and application of highly optimised, robustly evaluated ensembles of support vector machines (SVMs). The package takes care of training individual SVM classifiers using a fast parallel heuristic algorithm, and combines individual classifiers into ensembles. Robust metrics of classification performance are offered by bootstrap resampling and permutation testing.

Install

R (source archive)

url <- "https://cran.r-project.org/src/contrib/Archive/classyfire/classyfire_0.1-2.tar.gz"
pkgFile <- "classyfire_0.1-2.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 (0.1-2) and builds it locally. Install its dependencies first, and note that building from source needs the usual compiler toolchain.

Health

CRAN checks

CRAN check results are not tracked yet.

Advisories

none known

How this is measured·How advisories are found

Documentation

In release 0.1-2

READMENoVignettesYes · 1 · staticNEWSYes · 33% structuredCitation fileNoWebsitenot declared in DESCRIPTION

Help pages: 14includes a package overview page
Examples that run: 0%13 never run
Exported functions with examples: 100%
Documented parameters: 100%
Return-value docs: 54%
Help pages citing references: 21%

How these are measured

Downloads

classyfire 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 (5)

R >= 3.0.0snowfall e1071 boot (>= 1.3-11)neldermead

Imports (2)

ggplot2 optimbase

LinkingTo (0)

none

Suggests (2)

RUnit knitr

Enhances (0)

none

Dependency license breakdown →

Reverse dependencies

0direct

–indirect (not tracked)

Nothing depends on this yet.

How these are counted

Code & Tests

People & History

People (2)

Eleni Chatzimichali

Contributor

Conrad Bessant

Contributor

Maintainer since 0.1-0 (2014)

Releases (3)

Pick two releases to compare their code metrics.

R
R 3.6.0 released · 2019-04-26
archivedRemoved from CRAN
2019-04-22
check errors were not corrected despite reminders
R
R 3.5.0 released · 2018-04-23
R
R 3.4.0 released · 2017-04-21
R
R 3.3.0 released · 2016-05-03
R
R 3.2.0 released · 2015-04-16
0.1-2
record
2015-01-11 · diff ↗ ·
added 1 export
ggFusedHist
0.1-1
record
2014-11-22 · diff ↗
0.1-0
record
2014-09-03
R
R 3.1.0 released · 2014-04-10

Package metadata

First published: 2014-09-03
Total releases: 3 / 12 yrs
License: GPL (>= 2) OSI
Minimum R: ≥ 3.0.0

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("classyfire")

Format

Chatzimichali, E., & Bessant, C. (n.d.). classyfire: Robust multivariate classification using highly optimised SVM ensembles (Version 0.1-2) [Computer software]. Retrieved October 26, 2026, from https://CRAN.R-project.org/package=classyfire

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 classyfire version 0.1-2 [Data set]. HJJB, LLC. Data release v2026-10-26. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-26, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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