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mlrMBO

1.1.6

Bayesian Optimization and Model-Based Optimization of Expensive Black-Box Functions

10packages depend
85.2Kdownloads / year
79.2%test coverage
13/13checks pass

Overview

About
Maintained by Martin BinderFirst published 2017-03-129 releasesCRAN page ↗GitHub ↗

Flexible and comprehensive R toolbox for model-based optimization ('MBO'), also known as Bayesian optimization. It implements the Efficient Global Optimization Algorithm and is designed for both single- and multi- objective optimization with mixed continuous, categorical and conditional parameters. The machine learning toolbox 'mlr' provide dozens of regression learners to model the performance of the target algorithm with respect to the parameter settings. It provides many different infill criteria to guide the search process. Additional features include multi-point batch proposal, parallel execution as well as visualization and sophisticated logging mechanisms, which is especially useful for teaching and understanding of algorithm behavior. 'mlrMBO' is implemented in a modular fashion, such that single components can be easily replaced or adapted by the user for specific use cases.

Install

Health

CRAN checks
13OK
Slowest check: 8.9 min · r-oldrel-macos-x86_64
Code health
Yes
Tests · ratio 0.33
79.2%
Coverage · measured lines
100%
Documentation · exports
9
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

Documentation
READMEYes · 327 wordsVignettesYes · dynamicpkgdown siteNoNEWSYes · 100% structuredCode of conductNoContributing guideNo
Examples that run
100%
Documented parameters
97%
Return-value docs
85%
References docs
5%

Downloads

85.2K
CRAN downloads in the past year
Rank #1,528 · ~233/day · ~7.1K/mo
Daily download trend is not available in this view yet.
5.5K30 days
17.7K90 days
85.2K1 year
Compare downloads with other packages →
Also on600 r2u20 autocran5.6K conda_forge95 c2d4u

Repository

Repository
186Stars
47Forks
82Open issues
14Open PRs
2Releases
1,656Commits
23Contributors
model-based-optimizationrr-packageoptimizationmlrhyperparameter-optimizationblack-box-optimizationbayesian-optimization
1,656 commits · Last activity 2026-03-01

Stars over time

2025-04-12 · 1862026-07-07 · 186

Repository practices

Upstream repositoryBeta

5 development-tooling and community-health practices detected across 4 families in the upstream repository

Checks run against github.com/mlr-org/mlrmbo on 2026-08-16.

Continuous integration (1)
tic
Docs source (1)
README.Rmd
Lint, format, editor (2)
EditorConfigRStudio project
Coverage (1)
Codecov
How this is detected·Detection ruleset v1 (2026-07-18)

Dependencies

Declared dependencies
29 external dependencies (excludes base and recommended)
LinkingTo (0)
none
Enhances (0)
none

Code & Tests

People & History

People (7)
Maintainer (1)
Maintainer · added in 1.1.6
Authors (6)
Package Timeline

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

  • R
    R 4.6.0 released · 2026-04-24
  • 1.1.6Latest
    2026-03-01 · current release · diff ↗
  • 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
  • 1.1.5.1
    2022-07-04 · diff ↗
  • R
    R 4.2.0 released · 2022-04-22
  • R
    R 4.1.0 released · 2021-05-18
  • 1.1.5
    2020-10-23 · diff ↗
  • R
    R 4.0.0 released · 2020-04-24
  • 1.1.4
    2020-02-28 · diff ↗
  • 1.1.3
    2019-12-02 · diff ↗
  • R
    R 3.6.0 released · 2019-04-26
  • 1.1.2
    2018-06-21 · diff ↗
  • R
    R 3.5.0 released · 2018-04-23
  • 1.1.1
    2018-01-03 · diff ↗
Show 4 earlier events
  • 1.1.0
    2017-05-13 · diff ↗
  • R
    R 3.4.0 released · 2017-04-21
  • 1.0.0
    2017-03-12
  • R
    R 3.3.0 released · 2016-05-03

Package metadata

First published
2017-03-12
Total releases
9 / 9 yrs
License
BSD_2_clause + file LICENSE OSI
Download size
676 KB
Installed size
not tracked yet
With dependencies
not tracked yet

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("mlrMBO")
Binder, M., Bischl, B., Bossek, J., Horn, D., Lang, M., Richter, J., & Thomas, J. (2026). mlrMBO: Bayesian Optimization and Model-Based Optimization of Expensive Black-Box Functions (Version 1.1.6) [Computer software]. https://doi.org/10.32614/CRAN.package.mlrMBO

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.

APA

Balamuta, J. J. (2026). R Observatory: Metrics for mlrMBO version 1.1.6 [Data set]. HJJB, LLC. Data release v2026-08-17. https://doi.org/10.5281/zenodo.21843040

From data release v2026-08-17, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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