R Observatory: Metrics for exprso version 0.5.1

Balamuta, James Joseph

doi:10.5281/zenodo.21843040

This package was removed from CRAN on 2019-11-25. Its history is shown below.

Reason: check problems were not corrected in time

Details below reflect version 0.5.1, its last release before removal.

exprso

0.5.1

Rapid Deployment of Machine Learning Algorithms

0packages depend

–downloads / year

–test coverage

–checks pass

Overview

About

Maintained by Thomas Quinn9 releasesCRAN page ↗GitHub ↗

Supervised machine learning has an increasingly important role in data analysis. This package introduces a framework for rapidly building and deploying supervised machine learning in a high-throughput manner. This package provides a user-friendly interface that empowers investigators to execute state-of-the-art binary and multi-class classification, as well as regression, with minimal programming experience necessary.

Install

R (source archive)pak (dev)

url <- "https://cran.r-project.org/src/contrib/Archive/exprso/exprso_0.5.1.tar.gz"
pkgFile <- "exprso_0.5.1.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 (0.5.1) 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("tpq/exprso")

Development version from tpq/exprso. Installs pak first if it is not already available.

Health

CRAN checks

CRAN check results are not tracked yet.

Code health

Yes

Tests · ratio 0.22

not tracked

Coverage

100%

Documentation · exports

15

Dependencies · direct

Documentation

READMEYes · 441 wordsVignettesYes · dynamicpkgdown siteNoNEWSYes · 100% structuredCode of conductNoContributing guideNo

Examples that run: 0%
Documented parameters: 98%
Return-value docs: 94%
References docs: 0%

Downloads

exprso Releases R versions

Daily download trend is not available in this view yet.

Compare downloads with other packages →

Dependencies

Declared dependencies

22 external dependencies (excludes base and recommended)

Depends (2)

R >= 3.2.2kernlab

Imports (14)

clusterMASSe1071 glmnet frbslatticemethodsnnetplyr randomForest ROCRrpartsamplingstats

LinkingTo (0)

none

Suggests (14)

balance Biobase edgeR GEOquery h2o knitr limma magrittr mRMRe propr RankProd rmarkdown testthat vegan

Enhances (0)

none

Dependency license breakdown →

Reverse dependencies

0direct

–indirect (not tracked)

Nothing depends on this yet.

Code & Tests

People & History

People (3)

Maintainer (1)

Thomas Quinn

Author, Maintainer

Authors (1)

Thomas Quinn

Author, Maintainer

Contributors (2)

Daniel Tylee

Contributor

Samuel Lee

Contributor · added in 0.3.6

Package Timeline

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

R
R 4.0.0 released · 2020-04-24
archivedRemoved from CRAN
2019-11-25
check problems were not corrected in time
R
R 3.6.0 released · 2019-04-26
0.5.1
2019-03-23 · diff ↗
0.4.7
2018-12-12 · diff ↗
0.4.0
2018-07-25 · diff ↗
0.3.6
2018-05-09 · diff ↗
R
R 3.5.0 released · 2018-04-23
0.2.7
2017-12-14 · diff ↗
0.2.6
2017-11-30 · diff ↗
0.2.0
2017-11-18 · diff ↗
R
R 3.4.0 released · 2017-04-21
0.1.8
2016-12-23 · diff ↗
0.1.7
2016-09-27
R
R 3.3.0 released · 2016-05-03

Package metadata

Total releases: 9
License: GPL-2 OSI
Minimum R: ≥ 3.2.2
Bundled data: 3.8 KB / 2 files
Download size: not tracked yet
Installed size: not tracked yet
With dependencies: not tracked yet

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("exprso")

Format

Quinn, T., Tylee, D., & Lee, S. (n.d.). exprso: Rapid Deployment of Machine Learning Algorithms (Version 0.5.1) [Computer software]. Retrieved August 14, 2026, from https://CRAN.R-project.org/package=exprso

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.

Format

APA

Balamuta, J. J. (2026). R Observatory: Metrics for exprso version 0.5.1 [Data set]. HJJB, LLC. Data release v2026-08-13. https://doi.org/10.5281/zenodo.21843040

From data release v2026-08-13, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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