mlr3proba
mlr3proba is shedding weight as its survival work moves into sibling packages
Comparison · Analytics
ggraph vs probably
A side-by-side editorial comparison of ggraph and probably — release velocity, themes, recent moves, and the top alternatives to consider.
ggraph vs probably: at a glance
What is ggraph?
ggraph has settled into ggplot2 compatibility duty
ggraph provides the grammar of graphics for network and tree data. Its recent releases are compatibility and bug-fix work — a collapse fix in get_edges() alongside ggplot2 v4.0.0 upkeep, and before that a pipe rollback. The last release with real content was 2.2.0, a long list of layout and edge-geom corrections.
What is probably?
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.
ggraph vs probably: editorial side-by-side
ggraph
0.0ANALYTICS
ggraph has settled into ggplot2 compatibility duty
◆ Current state
ggraph provides the grammar of graphics for network and tree data. Its recent releases are compatibility and bug-fix work — a collapse fix in get_edges() alongside ggplot2 v4.0.0 upkeep, and before that a pipe rollback. The last release with real content was 2.2.0, a long list of layout and edge-geom corrections.
◆ Where it's heading
The feature surface looks finished and the maintenance is about keeping it working under a moving ggplot2. The one architectural move in this window — pushing dendrogram layout into compiled code to escape R's recursion limits, back in 2.1.0 — was about scaling existing features, not adding new ones.
◆ Prediction
Expect the next release to follow ggplot2 4.0.0 rather than introduce layouts or edge geoms.
probably
0.0ANALYTICS
The package that made calibration a step instead of an afterthought.
◆ Current state
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.
◆ Where it's heading
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.
◆ Prediction
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.
Alternatives to ggraph and probably
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 ggraph or probably.
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 ggraph alternatives → · See all probably alternatives →
Recent activity from ggraph and probably
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 10mo agoprobablyConformal objects gain required_pkgs() and butcher methods
- 11mo agoggraphget_edges() collapse fix and ggplot2 v4 upkeep
- 1y agoprobablyggplot2 test updates and a clearer validation-set error
- 1y agoprobablyCalibration internals refactored; isotonic bootstrap bug fixed
- 2y agoggraphNative pipe usage rolled back
- 2y agoggraphLayout precision and edge geom fixes across the package
- 2y agoprobablyFix grouping sensitivity to variable type
- 3y agoprobablySplit conformal and conformal quantile regression added
- 3y agoprobablyCalibration and conformal inference arrive in tidymodels ⚡
- 3y agoggraphBinned edge scales and compiled dendrogram layouts
- 5y agoggraphC++11 pinned to fix std::random_shuffle deprecation
- 5y agoggraphFaceting and edge geom bug fixes
Frequently asked questions
What is the difference between ggraph and probably?
They serve adjacent needs but don't currently overlap on shipped themes. ggraph 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.
Is ggraph better than probably?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. ggraph 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.
What are the best alternatives to ggraph?
Top ggraph alternatives in Analytics are ranked by recent ship velocity. Browse the "ggraph alternatives" section above for the current picks, or visit /alternatives/ggraph for the full list with editorial commentary on each.
What are the best alternatives to probably?
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.