tidytext
Finished, widely taught, and shipping roxygen fixes.
A side-by-side editorial comparison of broom and probably — release velocity, themes, recent moves, and the top alternatives to consider.
broom's release calendar is now set by CRAN checks, not by new tidiers.
broom converts model objects from across R's statistical ecosystem into tidy data frames. Four of its last six releases exist purely to resolve R CMD check warnings and errors on r-devel or to absorb upstream package changes. Maintainership passed to Emil Hvitfeldt at 1.0.11.
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.
broom converts model objects from across R's statistical ecosystem into tidy data frames. Four of its last six releases exist purely to resolve R CMD check warnings and errors on r-devel or to absorb upstream package changes. Maintainership passed to Emil Hvitfeldt at 1.0.11.
Carrying hundreds of tidier methods for model classes it does not own, broom's workload is dominated by other projects' breaking changes and CRAN's evolving checks. New tidier coverage has largely migrated to the packages that define the models, leaving broom as a compatibility surface.
Expect the cadence to stay reactive, with releases triggered by r-devel check failures and upstream API shifts rather than expanded model coverage.
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.
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 broom or probably.
Finished, widely taught, and shipping roxygen fixes.
Text features finally stay sparse all the way to the model.
workflowsets keeps widening what counts as a model worth comparing.
The tidymodels pipeline grew a third stage, and it happens after the model runs.
Posit's MLOps package went quiet for two years, then came back to keep up with recipes.
patchwork stopped being a ggplot composer and became a page composer.
See all broom alternatives → · See all probably alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. broom and probably 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. broom and probably 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 broom alternatives in Analytics are ranked by recent ship velocity. Browse the "broom alternatives" section above for the current picks, or visit /alternatives/broom for the full list with editorial commentary on each.
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.