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Comparison · Analytics
mlr3measures vs probably
A side-by-side editorial comparison of mlr3measures and probably — release velocity, themes, recent moves, and the top alternatives to consider.
mlr3measures vs probably: at a glance
What is mlr3measures?
mlr3measures is systematically retrofitting sample weights across every metric
mlr3measures is the metric library behind mlr3. Recent releases follow two threads: adding measures — linex, pinball, Mu AUC, gmean, gpr, mcc — and retrofitting sample_weights support across the existing ones, reaching AUC and the confusion-matrix family in 1.3.0. Along the way 1.1.0 deprecated four regression measures and corrected the bias definitions.
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.
mlr3measures vs probably: editorial side-by-side
mlr3measures
0.0ANALYTICS
mlr3measures is systematically retrofitting sample weights across every metric
◆ Current state
mlr3measures is the metric library behind mlr3. Recent releases follow two threads: adding measures — linex, pinball, Mu AUC, gmean, gpr, mcc — and retrofitting sample_weights support across the existing ones, reaching AUC and the confusion-matrix family in 1.3.0. Along the way 1.1.0 deprecated four regression measures and corrected the bias definitions.
◆ Where it's heading
The library is maturing rather than growing: weighted evaluation and observation-wise loss functions are being brought to metrics that already existed, which is what downstream weighted-resampling and per-observation analysis need. The deprecations suggest the maintainers are willing to remove measures they consider ill-defined rather than keep them for compatibility.
◆ Prediction
Expect sample_weights and observation-wise variants to reach the remaining measures that lack them.
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 mlr3measures 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 mlr3measures or probably.
textrecipes
Text features finally stay sparse all the way to the model.
workflowsets
workflowsets keeps widening what counts as a model worth comparing.
workflows
The tidymodels pipeline grew a third stage, and it happens after the model runs.
vetiver
Posit's MLOps package went quiet for two years, then came back to keep up with recipes.
patchwork
patchwork stopped being a ggplot composer and became a page composer.
See all mlr3measures alternatives → · See all probably alternatives →
Recent activity from mlr3measures and probably
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 3mo agomlr3measuresWeighted AUC and weighted confusion-matrix measures
- 8mo agomlr3measuresObservation-wise loss for bbrier and logloss
- 10mo agoprobablyConformal objects gain required_pkgs() and butcher methods
- 11mo agomlr3measuresrse, rsq, rrse and rae deprecated; bias measures corrected
- 1y agoprobablyggplot2 test updates and a clearer validation-set error
- 1y agoprobablyCalibration internals refactored; isotonic bootstrap bug fixed
- 1y agomlr3measureslinex, pinball and Mu AUC measures added
- 2y agomlr3measuresgmean, gpr and multiclass MCC added
- 2y agoprobablyFix grouping sensitivity to variable type
- 3y agoprobablySplit conformal and conformal quantile regression added
- 3y agoprobablyCalibration and conformal inference arrive in tidymodels ⚡
- 4y agomlr3measuresObservation-wise loss functions introduced
Frequently asked questions
What is the difference between mlr3measures and probably?
They serve adjacent needs but don't currently overlap on shipped themes. mlr3measures 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 mlr3measures better than probably?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. mlr3measures 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 mlr3measures?
Top mlr3measures alternatives in Analytics are ranked by recent ship velocity. Browse the "mlr3measures alternatives" section above for the current picks, or visit /alternatives/mlr3measures 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.