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mlr3learners vs mlr3mbo

A side-by-side editorial comparison of mlr3learners and mlr3mbo — release velocity, themes, recent moves, and the top alternatives to consider.

Shared themes:mlr3r-stats

mlr3learners vs mlr3mbo: at a glance

Featuremlr3learnersmlr3mbo
SectorAnalyticsAnalytics
Velocity score0.02.5
Sparks · 30d00
Top themesmlr3, machine-learning, r-stats, learnersbayesian-optimization, mlr3, hyperparameter-tuning, r-stats
Last editorial update1h ago1h ago
WebsiteVisit →Visit →

What is mlr3learners?

mlr3learners spends its releases absorbing upstream churn

mlr3learners wraps the standard model packages — ranger, xgboost, glmnet, kknn — for mlr3. Its recent history is dominated by upstream events rather than its own plans: kknn was pulled from CRAN and its learners removed in 0.11.0, then restored in 0.12.0 when the package returned. The newest release absorbs glmnet 5.0 while adding a predict_raw flag across all learners and probit support to logistic regression.

Read the full mlr3learners trajectory →

What is mlr3mbo?

mlr3mbo picked its defaults from a benchmark study, not from taste

mlr3mbo does model-based and Bayesian optimisation for mlr3. Its 1.0.0 release added a dictionary of pre-built acquisition-function optimisers and, more consequentially, replaced the default surrogate, acquisition function and optimiser settings with values derived from a large-scale benchmark study. The releases since are corrections to the acquisition-optimiser path exposed by that new default configuration.

Read the full mlr3mbo trajectory →

mlr3learners vs mlr3mbo: editorial side-by-side

M
mlr3learners
ANALYTICS
0.0

mlr3learners spends its releases absorbing upstream churn

◆ Current state

mlr3learners wraps the standard model packages — ranger, xgboost, glmnet, kknn — for mlr3. Its recent history is dominated by upstream events rather than its own plans: kknn was pulled from CRAN and its learners removed in 0.11.0, then restored in 0.12.0 when the package returned. The newest release absorbs glmnet 5.0 while adding a predict_raw flag across all learners and probit support to logistic regression.

◆ Where it's heading

The package's job is insulation, and the changelog shows what that costs — compatibility-only releases interleaved with small capability additions that expose more of each upstream model. The direction of travel is toward giving users access to the raw upstream objects rather than hiding them.

◆ Prediction

Expect the next release to track another upstream version bump, with incremental exposure of learner-specific fields continuing alongside.

M
mlr3mbo
ANALYTICS
2.5

mlr3mbo picked its defaults from a benchmark study, not from taste

◆ Current state

mlr3mbo does model-based and Bayesian optimisation for mlr3. Its 1.0.0 release added a dictionary of pre-built acquisition-function optimisers and, more consequentially, replaced the default surrogate, acquisition function and optimiser settings with values derived from a large-scale benchmark study. The releases since are corrections to the acquisition-optimiser path exposed by that new default configuration.

◆ Where it's heading

The package has moved from a toolkit that expected users to assemble a Bayesian optimisation loop into one with a defensible default loop, and the recent fixes — warm-start sizing on multi-objective archives, silently discarded terminators, stale x_domain values — are the consequences of more people running the default path.

◆ Prediction

Expect continued hardening of the acquisition-optimiser classes rather than new acquisition functions.

Alternatives to mlr3learners and mlr3mbo

Other Analytics products tracked by Sparkpulse, ranked by recent ship velocity. Each card links to a full editorial trajectory and lets you pivot into a head-to-head comparison with either mlr3learners or mlr3mbo.

See all mlr3learners alternatives → · See all mlr3mbo alternatives →

Recent activity from mlr3learners and mlr3mbo

Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.

  1. 23d agomlr3mboAcquisition optimiser fixes for warm starts and archives
  2. 2mo agomlr3learnerspredict_raw across all learners, plus probit and ranger internals
  3. 3mo agomlr3mboDictionary lookup and restart-limit fixes
  4. 4mo agomlr3mborush 1.0.0 compatibility and Surrogate$check()
  5. 5mo agomlr3mbomlr3mbo 1.0.0 ships benchmark-derived default settings
  6. 8mo agomlr3learnersxgboost 3.1.2.1 compatibility
  7. 9mo agomlr3learnersUncertainty estimation methods for ranger regression
  8. 10mo agomlr3mbomlr3learners 0.13.0 compatibility
  9. 10mo agomlr3learnersDevelopment snapshot: LDA test adjustment
  10. 11mo agomlr3mboMaintainer change and mlr3pipelines 0.9.0 upkeep
  11. 1y agomlr3learnerskknn learners restored after returning to CRAN
  12. 1y agomlr3learnerskknn learners removed after CRAN archival

Frequently asked questions

What is the difference between mlr3learners and mlr3mbo?

Both compete on the same themes — mlr3, r-stats — within Analytics. mlr3mbo is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.

Is mlr3learners better than mlr3mbo?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. mlr3mbo is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.

What are the best alternatives to mlr3learners?

Top mlr3learners alternatives in Analytics are ranked by recent ship velocity. Browse the "mlr3learners alternatives" section above for the current picks, or visit /alternatives/mlr3learners for the full list with editorial commentary on each.

What are the best alternatives to mlr3mbo?

Top mlr3mbo alternatives in Analytics are ranked by recent ship velocity. Browse the "mlr3mbo alternatives" section above for the current picks, or visit /alternatives/mlr3mbo for the full list with editorial commentary on each.