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mlr3tuning vs tidyposterior

A side-by-side editorial comparison of mlr3tuning and tidyposterior — release velocity, themes, recent moves, and the top alternatives to consider.

Shared themes:r-package

mlr3tuning vs tidyposterior: at a glance

Featuremlr3tuningtidyposterior
SectorAnalyticsAnalytics
Velocity score2.50.0
Sparks · 30d00
Top themesmlr3, hyperparameter-tuning, async-optimization, callbackstidymodels, bayesian-analysis, model-comparison, maintenance-mode
Last editorial update1h ago1h ago
WebsiteVisit →Visit →

What is mlr3tuning?

mlr3tuning is rebuilding its async machinery under a stable public surface

mlr3tuning provides hyperparameter optimization for the mlr3 ecosystem, and its recent history is dominated by the asynchronous tuning path: archive freezing, callback stages around queue evaluation, and version-locked compatibility with the rush backend. Releases pair a small feature with several fixes and an explicit compatibility line naming the mlr3 or rush version they track. The most recent release drops all workarounds for older rush versions, which suggests that dependency has stabilized enough to require rather than accommodate.

Read the full mlr3tuning trajectory →

What is tidyposterior?

A finished Bayesian model-comparison package in pure maintenance mode

tidyposterior compares model performance using Bayesian resampling analysis, and it reached its intended shape years ago. Every release since 1.0.0 has been maintenance: a broken test under R-devel, a maintainer email change, and most recently compatibility with an upcoming ggplot2 release plus the base-pipe transition. The substantive API decisions — autoplot() over ggplot() methods, tibble returns from contrast_models() — were settled in the 0.x series.

Read the full tidyposterior trajectory →

mlr3tuning vs tidyposterior: editorial side-by-side

M
mlr3tuning
ANALYTICS
2.5

mlr3tuning is rebuilding its async machinery under a stable public surface

◆ Current state

mlr3tuning provides hyperparameter optimization for the mlr3 ecosystem, and its recent history is dominated by the asynchronous tuning path: archive freezing, callback stages around queue evaluation, and version-locked compatibility with the rush backend. Releases pair a small feature with several fixes and an explicit compatibility line naming the mlr3 or rush version they track. The most recent release drops all workarounds for older rush versions, which suggests that dependency has stabilized enough to require rather than accommodate.

◆ Where it's heading

Two things are being tidied at once. The async archive is converging on a consistent data.table representation across batch and async variants, so results are shaped the same regardless of how tuning ran. Separately, the package is becoming a better ecosystem citizen — unioning tuner properties on load instead of overwriting them, removing its callbacks on unload, and raising informative errors from AutoTuner accessors on an untrained model. Both are the marks of a package used as a dependency more than as a destination.

◆ Prediction

With rush pinned to 1.2.0 and the compatibility shims gone, the next release is likely to expose more of the async path through callbacks rather than change the tuning interface.

T
tidyposterior
ANALYTICS
0.0

A finished Bayesian model-comparison package in pure maintenance mode

◆ Current state

tidyposterior compares model performance using Bayesian resampling analysis, and it reached its intended shape years ago. Every release since 1.0.0 has been maintenance: a broken test under R-devel, a maintainer email change, and most recently compatibility with an upcoming ggplot2 release plus the base-pipe transition. The substantive API decisions — autoplot() over ggplot() methods, tibble returns from contrast_models() — were settled in the 0.x series.

◆ Where it's heading

The package tracks its dependencies rather than developing on its own line, and the dependencies do the moving: rstanarm API changes, dplyr 1.0.0, testthat 3e, ggplot2. Its integration surface widened once, when perf_mod() gained methods for tuning parameter objects from tune, finetune, and workflowsets, and has been stable since. This is what a completed package in an active ecosystem looks like.

◆ Prediction

Expect the next release to be triggered by an upstream change rather than by anything tidyposterior wants to do differently.

Alternatives to mlr3tuning and tidyposterior

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 mlr3tuning or tidyposterior.

See all mlr3tuning alternatives → · See all tidyposterior alternatives →

Recent activity from mlr3tuning and tidyposterior

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

  1. 18d agomlr3tuningmlr3tuning 1.6.1 stops clobbering other packages' tuner properties
  2. 4mo agomlr3tuningmlr3tuning 1.6.0 aligns archive column order across tuning classes
  3. 8mo agomlr3tuningmlr3tuning 1.5.1 tracks xgboost 3.1.2.1
  4. 8mo agomlr3tuningmlr3tuning 1.5.0 adds queue evaluation stages to async callbacks
  5. 1y agotidyposteriortidyposterior 1.0.1.9000 prepares for an upcoming ggplot2 release
  6. 1y agomlr3tuningmlr3tuning 1.4.0 unifies logging under a base mlr3 logger
  7. 1y agomlr3tuningmlr3tuning 1.3.0 adds a frozen async archive and leaner worker storage
  8. 2y agotidyposteriortidyposterior 1.0.1 fixes a test broken under R-devel
  9. 4y agotidyposteriortidyposterior 1.0.0 modernizes internals to pivot_longer and testthat 3e
  10. 5y agotidyposteriortidyposterior 0.1.0 adds perf_mod() methods for tune and workflowsets
  11. 6y agotidyposteriortidyposterior 0.0.3 returns tibbles and adds a formula override
  12. 7y agotidyposteriortidyposterior 0.0.2 removes example RData files for CRAN

Frequently asked questions

What is the difference between mlr3tuning and tidyposterior?

Both compete on the same themes — r-package — within Analytics. mlr3tuning 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 mlr3tuning better than tidyposterior?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. mlr3tuning 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 mlr3tuning?

Top mlr3tuning alternatives in Analytics are ranked by recent ship velocity. Browse the "mlr3tuning alternatives" section above for the current picks, or visit /alternatives/mlr3tuning for the full list with editorial commentary on each.

What are the best alternatives to tidyposterior?

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