mlr3proba
mlr3proba is shedding weight as its survival work moves into sibling packages
Comparison · Analytics
tidyposterior vs workflows
A side-by-side editorial comparison of tidyposterior and workflows — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:tidymodels
tidyposterior vs workflows: at a glance
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.
What is workflows?
The tidymodels pipeline grew a third stage, and it happens after the model runs.
workflows bundles a preprocessor and a model into one object that tidymodels can fit, tune and extract from. Version 1.3.0 added a post stage backed by the tailor package, wired through every generic a workflow supports — augment, tidy, tunable, tune_args, required_pkgs and parameter extraction. Version 1.2.0 added sparse data support so fit() and predict() accept dgCMatrix and sparse tibbles. Earlier releases in view are boundary tightening: erroring on unknown model modes, on trained recipes, and on silently ignored formula offsets.
tidyposterior vs workflows: editorial side-by-side
tidyposterior
0.0ANALYTICS
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.
workflows
0.0ANALYTICS
The tidymodels pipeline grew a third stage, and it happens after the model runs.
◆ Current state
workflows bundles a preprocessor and a model into one object that tidymodels can fit, tune and extract from. Version 1.3.0 added a post stage backed by the tailor package, wired through every generic a workflow supports — augment, tidy, tunable, tune_args, required_pkgs and parameter extraction. Version 1.2.0 added sparse data support so fit() and predict() accept dgCMatrix and sparse tibbles. Earlier releases in view are boundary tightening: erroring on unknown model modes, on trained recipes, and on silently ignored formula offsets.
◆ Where it's heading
The object is filling out into a complete pipeline description rather than a preprocessing-plus-model pair. Postprocessing is the structural addition — calibration and threshold selection were previously done by hand after prediction, outside anything tidymodels could tune or record — and the fact that it arrived integrated with tunable() and tune_args() rather than as a standalone step is the point. The rest of the arc is the steady tidymodels habit of converting silent guesses into errors.
◆ Prediction
Expect tailor postprocessors to spread through tune and workflowsets next, since the parameter and tuning generics were wired up first, and expect sparse support to extend to more engines after lightgbm.
Alternatives to tidyposterior and workflows
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 tidyposterior or workflows.
mlr3viz
mlr3viz keeps the ecosystem's plots working while the plots themselves move out
mlr3tuning
mlr3tuning is rebuilding its async machinery under a stable public surface
timetk
timetk swallowed anomalize whole, then went quiet for two years
modelbased
modelbased is turning marginal effects into a full contrast grammar
parameters
easystats' parameters package absorbs one more model class every few weeks
See all tidyposterior alternatives → · See all workflows alternatives →
Recent activity from tidyposterior and workflows
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 11mo agoworkflowsWorkflows gain a postprocessing stage via tailor ⚡
- 1y agotidyposteriortidyposterior 1.0.1.9000 prepares for an upcoming ggplot2 release
- 1y agoworkflowsSparse matrices work through fit() and predict()
- 2y agoworkflowsaugment() aligns with parsnip; censored regression supported
- 2y agotidyposteriortidyposterior 1.0.1 fixes a test broken under R-devel
- 3y agoworkflowsRegister tuning generics unconditionally
- 3y agoworkflowsMissing parsnip extensions now error early; unsupervised specs supported
- 3y agoworkflowsMode guessing removed; silent offset handling now errors
- 4y agotidyposteriortidyposterior 1.0.0 modernizes internals to pivot_longer and testthat 3e
- 5y agotidyposteriortidyposterior 0.1.0 adds perf_mod() methods for tune and workflowsets
- 6y agotidyposteriortidyposterior 0.0.3 returns tibbles and adds a formula override
- 7y agotidyposteriortidyposterior 0.0.2 removes example RData files for CRAN
Frequently asked questions
What is the difference between tidyposterior and workflows?
Both compete on the same themes — tidymodels — within Analytics. tidyposterior and workflows are shipping at a similar cadence (velocity 0.0 vs 0.0, both within Sparkpulse's "active" band). See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.
Is tidyposterior better than workflows?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. tidyposterior and workflows are shipping at a similar cadence (velocity 0.0 vs 0.0, both within Sparkpulse's "active" band). For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.
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.
What are the best alternatives to workflows?
Top workflows alternatives in Analytics are ranked by recent ship velocity. Browse the "workflows alternatives" section above for the current picks, or visit /alternatives/workflows-r for the full list with editorial commentary on each.