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Comparison · Analytics
desirability2 vs mlr3mbo
A side-by-side editorial comparison of desirability2 and mlr3mbo — release velocity, themes, recent moves, and the top alternatives to consider.
desirability2 vs mlr3mbo: at a glance
What is desirability2?
desirability2 is making multi-metric model selection a first-class tidymodels step.
desirability2 implements desirability functions, which map several metrics onto a common 0-1 scale so they can be combined into a single objective. The package is young: three releases, the first of which only added a NEWS file. Its substance arrived in 0.1.0 with hooks into tidymodels' tune package.
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.
desirability2 vs mlr3mbo: editorial side-by-side
desirability2
0.0ANALYTICS
desirability2 is making multi-metric model selection a first-class tidymodels step.
◆ Current state
desirability2 implements desirability functions, which map several metrics onto a common 0-1 scale so they can be combined into a single objective. The package is young: three releases, the first of which only added a NEWS file. Its substance arrived in 0.1.0 with hooks into tidymodels' tune package.
◆ Where it's heading
The direction is integration rather than standalone use. Version 0.1.0 added select_best_desirability() and show_best_desirability() to resolve a tuning run against several metrics at once; 0.2.0 exported make_desirability_cols() so other packages can build on it and made data-driven limits the default, removing the need to state ranges by hand. Both releases move work from the user into the package.
◆ Prediction
The exported helper and the developer-facing desirability() API point to adoption by other tidymodels packages as the next step rather than new functionality here.
mlr3mbo
2.5ANALYTICS
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 desirability2 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 desirability2 or mlr3mbo.
textrecipes
Text features finally stay sparse all the way to the model.
probably
The package that made calibration a step instead of an afterthought.
workflowsets
workflowsets keeps widening what counts as a model worth comparing.
workflows
The tidymodels pipeline grew a third stage, and it happens after the model runs.
vetiver
Posit's MLOps package went quiet for two years, then came back to keep up with recipes.
See all desirability2 alternatives → · See all mlr3mbo alternatives →
Recent activity from desirability2 and mlr3mbo
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 23d agomlr3mboAcquisition optimiser fixes for warm starts and archives
- 3mo agomlr3mboDictionary lookup and restart-limit fixes
- 4mo agomlr3mborush 1.0.0 compatibility and Surrogate$check()
- 5mo agomlr3mbomlr3mbo 1.0.0 ships benchmark-derived default settings ⚡
- 10mo agomlr3mbomlr3learners 0.13.0 compatibility
- 11mo agodesirability2make_desirability_cols() exported; data-driven limits on by default
- 11mo agomlr3mboMaintainer change and mlr3pipelines 0.9.0 upkeep
- 1y agodesirability2Desirability-based model selection added for tune ⚡
- 3y agodesirability2NEWS.md added to track package changes
Frequently asked questions
What is the difference between desirability2 and mlr3mbo?
They serve adjacent needs but don't currently overlap on shipped themes. 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 desirability2 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 desirability2?
Top desirability2 alternatives in Analytics are ranked by recent ship velocity. Browse the "desirability2 alternatives" section above for the current picks, or visit /alternatives/desirability2 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.