tidytext
Finished, widely taught, and shipping roxygen fixes.
Comparison · Analytics
bonsai vs mlr3mbo
A side-by-side editorial comparison of bonsai and mlr3mbo — release velocity, themes, recent moves, and the top alternatives to consider.
bonsai vs mlr3mbo: at a glance
What is bonsai?
bonsai keeps widening tidymodels' boosted-tree engine bench, catboost most recently
bonsai exists to attach non-core tree engines to parsnip's boost_tree() and rand_forest(), and the release history reads as a steady accumulation of them: partykit, aorsf, lightgbm, and now catboost. The 0.4.x line is spent making catboost behave like a full tidymodels citizen rather than adding anything new.
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.
bonsai vs mlr3mbo: editorial side-by-side
bonsai
0.0ANALYTICS
bonsai keeps widening tidymodels' boosted-tree engine bench, catboost most recently
◆ Current state
bonsai exists to attach non-core tree engines to parsnip's boost_tree() and rand_forest(), and the release history reads as a steady accumulation of them: partykit, aorsf, lightgbm, and now catboost. The 0.4.x line is spent making catboost behave like a full tidymodels citizen rather than adding anything new.
◆ Where it's heading
Each engine follows the same arc — land it, then close the gaps that keep it from tuning cleanly (parameter naming, multi_predict, threading, case weights). Recent work is squarely in that second phase for catboost, with dials supplying the matching parameter objects on its own release schedule. Bug-fix density is high relative to new surface.
◆ Prediction
Expect the catboost integration to keep filling in tuning and GPU-related arguments before any further engine is added; the entries give no signal about which engine would come next.
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 bonsai 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 bonsai 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 bonsai alternatives → · See all mlr3mbo alternatives →
Recent activity from bonsai and mlr3mbo
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 23d agomlr3mboAcquisition optimiser fixes for warm starts and archives
- 2mo agobonsaicatboost gains multi_predict() and corrected tuning parameters
- 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 agomlr3mboMaintainer change and mlr3pipelines 0.9.0 upkeep
- 1y agobonsaicatboost engine added to boost_tree()
- 1y agobonsailightgbm accepts sparse matrices for fit and predict
- 2y agobonsaiaorsf fit failure in multisession workers fixed
- 2y agobonsaiaorsf engine added; lightgbm gains dataset params and case weights
- 3y agobonsailightgbm num_leaves becomes tunable; alias arguments disallowed
Frequently asked questions
What is the difference between bonsai 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 bonsai 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 bonsai?
Top bonsai alternatives in Analytics are ranked by recent ship velocity. Browse the "bonsai alternatives" section above for the current picks, or visit /alternatives/bonsai-r 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.