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JOSS: https://github.com/SchlossLab/mikropml

machine-learning r-package rstats

Score: 13.697726522307391

Last synced: about 22 hours ago
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Repository metadata:

User-Friendly R Package for Supervised Machine Learning Pipelines

CodeMeta metadata:


Owner metadata:


GitHub Events

Total
Last Year

Committers metadata

Last synced: 3 days ago

Total Commits: 1,890
Total Committers: 22
Avg Commits per committer: 85.909
Development Distribution Score (DDS): 0.434

Commits in past year: 28
Committers in past year: 3
Avg Commits per committer in past year: 9.333
Development Distribution Score (DDS) in past year: 0.071

Name Email Commits
Kelly Sovacool k****l@g****m 1070
github-actions[bot] 4****] 405
Zena Lapp z****p@g****m 163
Begüm D. Topçuoğlu 3****u 100
BegumTop b****p@u****u 52
Begum Topcuoglu b****u@m****m 21
Nick Lesniak N****k@u****u 21
William L. Close c****l@g****m 13
Courtney Armour c****r@g****m 11
Pat Schloss p****s@u****u 9
Tuomas Borman t****m@u****i 5
Ariangela J. Kozik a****o@g****m 3
Lucas Bishop b****5@g****m 3
Begum Topcuoglu b****p@g****u 3
sklucas s****s 2
tomkoset t****t@u****u 2
Begum Topcuoglu b****p@g****u 2
Benjamin Valderrama 5****a 1
JMAStough j****h@g****m 1
Samara Rifkin s****7@y****m 1
Teun van den Brand t****d@g****m 1
agarretto96 a****6@g****m 1

Issue and Pull Request metadata

Last synced: 4 days ago

Total issues: 56
Total pull requests: 80
Average time to close issues: 4 months
Average time to close pull requests: 4 days
Total issue authors: 22
Total pull request authors: 9
Average comments per issue: 1.36
Average comments per pull request: 0.91
Merged pull request: 68
Bot issues: 0
Bot pull requests: 0

Past year issues: 3
Past year pull requests: 12
Past year average time to close issues: 1 day
Past year average time to close pull requests: about 13 hours
Past year issue authors: 2
Past year pull request authors: 2
Past year average comments per issue: 3.0
Past year average comments per pull request: 1.25
Past year merged pull request: 10
Past year bot issues: 0
Past year bot pull requests: 0

More stats: https://issues.ecosyste.ms/repositories/lookup?url=https://github.com/SchlossLab/mikropml

Top Issue Authors

  • kelly-sovacool (27)
  • pschloss (6)
  • zenalapp (3)
  • ecmaggioncalda (2)
  • sskoldas (1)
  • dansmith01 (1)
  • Benjamin-Valderrama (1)
  • SWi1 (1)
  • NLesniak (1)
  • joannacolovas (1)
  • Hesham999666 (1)
  • zhq90 (1)
  • marwa38 (1)
  • TuomasBorman (1)
  • alexmsalmeida (1)

Top Pull Request Authors

  • kelly-sovacool (66)
  • zenalapp (4)
  • courtneyarmour (3)
  • TuomasBorman (2)
  • BTopcuoglu (1)
  • megancoden (1)
  • Benjamin-Valderrama (1)
  • pschloss (1)
  • teunbrand (1)

Top Issue Labels

  • feature (19)
  • documentation (10)
  • bug (9)
  • good first issue (8)
  • JOSS-paper (6)
  • wontfix (2)
  • reprex (1)

Top Pull Request Labels

  • documentation (2)
  • JOSS-paper (2)
  • bug (1)

Package metadata

cran.r-project.org: mikropml

User-Friendly R Package for Supervised Machine Learning Pipelines

  • Homepage: https://www.schlosslab.org/mikropml/
  • Documentation: http://cran.r-project.org/web/packages/mikropml/mikropml.pdf
  • Licenses: MIT + file LICENSE
  • Latest release: 1.7.0 (published 10 months ago)
  • Last Synced: 2026-08-13T01:36:17.526Z (2 days ago)
  • Versions: 15
  • Dependent Packages: 0
  • Dependent Repositories: 1
  • Downloads: 410 Last month
  • Docker Downloads: 99
  • Rankings:
    • Forks count: 4.836%
    • Stargazers count: 6.831%
    • Docker downloads count: 17.16%
    • Average: 17.819%
    • Dependent repos count: 23.865%
    • Downloads: 25.564%
    • Dependent packages count: 28.657%
  • Maintainers (1)
conda-forge.org: r-mikropml

An interface to build machine learning models for classification and regression problems. 'mikropml' implements the ML pipeline described by Topçuoğlu et al. (2020) <doi:10.1128/mBio.00434-20> with reasonable default options for data preprocessing, hyperparameter tuning, cross-validation, testing, model evaluation, and interpretation steps. See the website <http://www.schlosslab.org/mikropml/> for more information, documentation, and examples.

  • Homepage: http://www.schlosslab.org/mikropml/
  • Licenses: MIT
  • Latest release: 1.4.0 (published almost 4 years ago)
  • Last Synced: 2026-08-07T20:04:33.267Z (7 days ago)
  • Versions: 10
  • Dependent Packages: 0
  • Dependent Repositories: 6
  • Rankings:
    • Dependent repos count: 13.923%
    • Average: 36.602%
    • Forks count: 40.167%
    • Stargazers count: 40.731%
    • Dependent packages count: 51.589%

Dependencies

DESCRIPTION cran
  • R >= 4.1.0 depends
  • MLmetrics * imports
  • caret * imports
  • dplyr * imports
  • e1071 * imports
  • glmnet * imports
  • kernlab * imports
  • randomForest * imports
  • rlang * imports
  • rpart * imports
  • stats * imports
  • utils * imports
  • xgboost * imports
  • doFuture * suggests
  • foreach * suggests
  • future * suggests
  • future.apply * suggests
  • ggplot2 * suggests
  • knitr * suggests
  • progress * suggests
  • progressr * suggests
  • purrr * suggests
  • rmarkdown * suggests
  • testthat * suggests
  • tidyr * suggests
.github/workflows/check.yml actions
  • actions/checkout v2 composite
  • actions/upload-artifact main composite
  • r-lib/actions/check-r-package v2 composite
  • r-lib/actions/setup-pandoc v2 composite
  • r-lib/actions/setup-r v2 composite
  • r-lib/actions/setup-r-dependencies v2 composite
.github/workflows/on-release.yml actions
  • actions/checkout v2 composite
  • ad-m/github-push-action master composite
.github/workflows/pr_build.yml actions
  • actions/checkout v2 composite
  • ad-m/github-push-action master composite
  • r-lib/actions/setup-pandoc v2 composite
  • r-lib/actions/setup-r v2 composite
.github/workflows/test-coverage.yml actions
  • actions/cache v1 composite
  • actions/checkout v2 composite
  • r-lib/actions/setup-pandoc v2 composite
  • r-lib/actions/setup-r v2 composite