mlr3proba
mlr3proba is shedding weight as its survival work moves into sibling packages
A side-by-side editorial comparison of probably and vetiver — release velocity, themes, recent moves, and the top alternatives to consider.
The package that made calibration a step instead of an afterthought.
probably started as a small utility for class predictions and equivocal zones, and version 1.0.0 turned it into tidymodels' calibration and uncertainty package: cal_plot_*, cal_estimate_*, cal_validate_* and cal_apply across binary, multiclass and regression problems, plus conformal prediction intervals. Since then the work has been consolidation — a large internal refactor with no API change, split conformal and conformal quantile regression, bound_prediction(), and required_pkgs() and butcher methods so conformal objects can be deployed and stripped.
Posit's MLOps package went quiet for two years, then came back to keep up with recipes.
vetiver versions, deploys and monitors models: it pins a model, generates a plumber API around it, and writes the Dockerfile to run it. The visible release stream is bug fixes to plumber file generation, one prototype endpoint, and then a two-year gap between 0.2.5 in November 2023 and 0.2.6 in October 2025. The two releases since that gap are compatibility work — recipes' new input data prototype, support for probably, and all versions of xgboost.
probably started as a small utility for class predictions and equivocal zones, and version 1.0.0 turned it into tidymodels' calibration and uncertainty package: cal_plot_*, cal_estimate_*, cal_validate_* and cal_apply across binary, multiclass and regression problems, plus conformal prediction intervals. Since then the work has been consolidation — a large internal refactor with no API change, split conformal and conformal quantile regression, bound_prediction(), and required_pkgs() and butcher methods so conformal objects can be deployed and stripped.
The recent releases are about making these objects survive leaving the session. butcher and required_pkgs() methods are what a model needs to be pinned, containerised and served, and their arrival alongside workflows adding a tailor postprocessing stage and vetiver adding probably support points the same way: calibration is being moved out of analysis scripts and into the deployed pipeline. The cal_*_none() reference implementations are the tell that calibration is now something people tune rather than apply once.
Expect the calibration functions to be reachable directly from a tuned workflow's postprocessing stage rather than applied to predictions afterwards, following the tailor integration that workflows just shipped.
vetiver versions, deploys and monitors models: it pins a model, generates a plumber API around it, and writes the Dockerfile to run it. The visible release stream is bug fixes to plumber file generation, one prototype endpoint, and then a two-year gap between 0.2.5 in November 2023 and 0.2.6 in October 2025. The two releases since that gap are compatibility work — recipes' new input data prototype, support for probably, and all versions of xgboost.
The feature era ended before this window opened. Deploying to SageMaker, generating Docker files, storing renv lockfiles in model metadata and supporting keras, luz and recipes all landed in 0.2.1 and 0.2.2; nothing since has extended what vetiver does. What it does now is track the rest of tidymodels — when recipes gains a prototype API or probably becomes something a workflow can contain, vetiver adds a line. That is a package holding its position rather than advancing it.
The entries do not support a confident prediction of new capability. On this pattern the next release tracks another tidymodels change, most likely the postprocessing stage that workflows added in 1.3.0.
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 probably or vetiver.
mlr3proba is shedding weight as its survival work moves into sibling packages
mlr3viz keeps the ecosystem's plots working while the plots themselves move out
mlr3tuning is rebuilding its async machinery under a stable public surface
timetk swallowed anomalize whole, then went quiet for two years
modelbased is turning marginal effects into a full contrast grammar
easystats' parameters package absorbs one more model class every few weeks
See all probably alternatives → · See all vetiver alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — tidymodels — within Analytics. probably and vetiver 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.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. probably and vetiver 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.
Top probably alternatives in Analytics are ranked by recent ship velocity. Browse the "probably alternatives" section above for the current picks, or visit /alternatives/probably for the full list with editorial commentary on each.
Top vetiver alternatives in Analytics are ranked by recent ship velocity. Browse the "vetiver alternatives" section above for the current picks, or visit /alternatives/vetiver-r for the full list with editorial commentary on each.