R Observatory: Metrics for MAKL version 1.0.1

Balamuta, James Joseph

doi:10.5281/zenodo.21843040

MAKL

1.0.1

Multiple Approximate Kernel Learning (MAKL)

0packages depend

2.1Kdownloads / year

–test coverage

13/13checks pass

Overview

About

Maintained by Ayyüce Begüm BektaşFirst published 2022-01-172 releasesCRAN page ↗

R package associated with the Multiple Approximate Kernel Learning (MAKL) algorithm proposed in doi:10.1093/bioinformatics/btac241. The algorithm fits multiple approximate kernel learning (MAKL) models that are fast, scalable and interpretable.

Install

R (CRAN)Ubuntu (r2u)Fedora (COPR)openSUSE (OBS)

install.packages("MAKL", repos = "https://cloud.r-project.org/")

Installs the current CRAN release. Prebuilt binaries on Windows and macOS.

Release

# enable cranapt (r2u) if it is not already set up, then install
grep -rqs r2u.stat.illinois.edu /etc/apt/sources.list /etc/apt/sources.list.d/ \
  || curl -fsSL https://raw.githubusercontent.com/eddelbuettel/r2u/master/inst/scripts/add_cranapt_noble.sh | sudo bash
sudo apt install -y r-cran-makl

Fast Ubuntu binaries via r2u (no compilation). The cranapt setup runs once and is skipped when it is already enabled.

bspm (used by r2u) also needs make: sudo apt install make

# enable the iucar/cran COPR if it is not already present, then install
ls /etc/yum.repos.d/*iucar*cran*.repo >/dev/null 2>&1 \
  || sudo dnf copr enable -y iucar/cran
sudo dnf install -y R-CRAN-MAKL

RPMs from the iucar/cran COPR, rebuilt from CRAN.

For install.packages() integration in R, also: sudo dnf install R-CoprManager

# add the autoCRAN OBS repo (Tumbleweed) if it is missing, then install
zypper -q lr | grep -qi autoCRAN \
  || sudo zypper addrepo https://download.opensuse.org/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Tumbleweed/devel:languages:R:autoCRAN.repo
sudo zypper install -y R-MAKL

RPMs auto-built from CRAN on openSUSE OBS (Tumbleweed).

Health

CRAN checks

13OK

Slowest check: 54 s · r-oldrel-windows-x86_64

Code health

None

Tests · ratio 0.00

not tracked

Coverage

100%

Documentation · exports

2

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
OK2026-03-10
14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE

Documentation

READMENoVignettesYes · dynamicpkgdown siteNoNEWSNoCode of conductNoContributing guideNo

Examples that run: not tracked
Documented parameters: 100%
Return-value docs: 100%
References docs: 0%

Downloads

2.1K

CRAN downloads in the past year

Rank #22,303 · ~6/day · ~174/mo

Releases R versions

Daily download trend is not available in this view yet.

11930 days

48890 days

2.1K1 year

Compare downloads with other packages →

Also on98 r2u8 autocran

Dependencies

Declared dependencies

4 external dependencies (excludes base and recommended)

Depends (0)

none

Imports (2)

AUC grplasso

LinkingTo (0)

none

Suggests (2)

rmarkdown knitr

Enhances (0)

none

Dependency license breakdown →

Reverse dependencies

0direct

0indirect

Nothing depends on this yet.

Code & Tests

People & History

People (2)

Maintainer (1)

Ayyüce Begüm Bektaş

Author, Maintainer

Authors (2)

Ayyüce Begüm Bektaş

Author, Maintainer

Mehmet Gönen

Author

Package Timeline

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

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
1.0.1Latest
2022-07-06 · current release · diff ↗
R
R 4.2.0 released · 2022-04-22
1.0.0
2022-01-17
R
R 4.1.0 released · 2021-05-18

Package metadata

First published: 2022-01-17
Total releases: 2 / 4 yrs
License: GPL (>= 3) OSI
Download size: 11 KB
Installed size: not tracked yet
With dependencies: not tracked yet

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("MAKL")

Format

Bektaş, A. B., & Gönen, M. (2022). MAKL: Multiple Approximate Kernel Learning (MAKL) (Version 1.0.1) [Computer software]. https://doi.org/10.32614/CRAN.package.MAKL

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 MAKL version 1.0.1 [Data set]. HJJB, LLC. Data release v2026-08-15. https://doi.org/10.5281/zenodo.21843040

From data release v2026-08-15, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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