ANALYTICS
mlr3mbo picked its defaults from a benchmark study, not from taste
Alternatives · analytics tools
probably alternatives
The best probably alternatives in analytics tools, ranked by Sparkpulse's velocity_score.
Updated Aug 13, 2026
Looking for the best alternatives to probably? Sparkpulse tracks and ranks 12 alternatives in analytics tools by shipping velocity — how frequently each ships meaningful updates, verified from official changelogs. For reference, probably shipped 0 meaningful updates in the last 30 days and carries a velocity score of 0.0 out of 10 in 2026. The alternatives below are ranked the same way, so you're comparing real release momentum, not marketing claims.
About 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.
Velocity 0.0 · Last update 49m ago
Top 12 alternatives to probably
Ranked by recent ship velocity. Tap any card for the full editorial breakdown, or pivot to a head-to-head.
ANALYTICS
loo keeps rewriting the diagnostics Bayesian modellers read off model comparison
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Finished, widely taught, and shipping roxygen fixes.
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Text features finally stay sparse all the way to the model.
ANALYTICS
workflowsets keeps widening what counts as a model worth comparing.
ANALYTICS
The tidymodels pipeline grew a third stage, and it happens after the model runs.
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Posit's MLOps package went quiet for two years, then came back to keep up with recipes.
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patchwork stopped being a ggplot composer and became a page composer.
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mlr3fselect turned feature selection into an asynchronous, distributable job
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lime survives on compatibility patches years after its research moment
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mlr3measures is systematically retrofitting sample weights across every metric
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mlr3cluster went from a handful of clusterers to covering the field
probably vs alternatives — shipping velocity at a glance
Velocity score (0–10) and meaningful releases shipped in the last 30 days, from official changelogs. Higher = shipping faster.
| Product | Velocity | Sparks · 30d | Focus areas | Latest release |
|---|---|---|---|---|
| probably (baseline) | 0.0 | 0 | calibrationconformal-inferencetidymodels | Calibration and conformal inference arrive in tidymodels |
| mlr3mbo | 2.5 | 0 | bayesian-optimizationmlr3hyperparameter-tuning | mlr3mbo 1.0.0 ships benchmark-derived default settings |
| loo | 2.5 | 0 | bayesiancross-validationstan | loo_compare returns a data.frame with new uncertainty columns |
| tidytext | 0.0 | 0 | text-miningtidyversetopic-models | — |
| textrecipes | 0.0 | 0 | text-processingtidymodelsrecipes | Hashing and TF-IDF steps can emit sparse vectors |
| workflowsets | 0.0 | 0 | tidymodelsmodel-comparisonclustering | Clustering models enter workflow sets via tidyclust |
| workflows | 0.0 | 0 | tidymodelspipelinespostprocessing | Workflows gain a postprocessing stage via tailor |
| vetiver | 0.0 | 0 | mlopsmodel-deploymenttidymodels | — |
| patchwork | 0.0 | 0 | ggplot2compositiontables | gt tables become first-class patchwork objects |
| mlr3fselect | 0.0 | 0 | feature-selectionmlr3machine-learning | Asynchronous feature selection arrives with FSelectorAsync |
| lime | 0.0 | 0 | interpretabilitymachine-learningr-stats | — |
| mlr3measures | 0.0 | 0 | metricsmlr3machine-learning | — |
| mlr3cluster | 0.0 | 0 | clusteringmlr3machine-learning | Nine new clustering learners in one release |
The 12 best probably alternatives, in depth
1. mlr3mbo · velocity 2.5
Mlr3mbo picked its defaults from a benchmark study, not from taste.
Its velocity score of 2.5/10 reflects longer-term release cadence; its most recent meaningful update was “mlr3mbo 1.0.0 ships benchmark-derived default settings”.
Where probably leans on calibration, conformal inference and tidymodels, mlr3mbo focuses on bayesian optimization, mlr3 and hyperparameter tuning.
mlr3mbo and probably have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.
2. loo · velocity 2.5
Loo keeps rewriting the diagnostics Bayesian modellers read off model comparison.
Its velocity score of 2.5/10 reflects longer-term release cadence; its most recent meaningful update was “loo_compare returns a data.frame with new uncertainty columns”.
Where probably leans on calibration, conformal inference and tidymodels, loo focuses on bayesian, cross validation and stan.
loo and probably have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.
3. tidytext · velocity 0.0
Finished, widely taught, and shipping roxygen fixes.
Its velocity score of 0.0/10 reflects longer-term release cadence.
Where probably leans on calibration, conformal inference and tidymodels, tidytext focuses on text mining, tidyverse and topic models.
tidytext and probably have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.
4. textrecipes · velocity 0.0
Text features finally stay sparse all the way to the model.
Its velocity score of 0.0/10 reflects longer-term release cadence; its most recent meaningful update was “Hashing and TF-IDF steps can emit sparse vectors”.
Where probably leans on calibration, conformal inference and tidymodels, textrecipes focuses on text processing, tidymodels and recipes.
textrecipes and probably have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.
Full textrecipes trajectory → · Compare probably vs textrecipes →
5. workflowsets · velocity 0.0
Workflowsets keeps widening what counts as a model worth comparing.
Its velocity score of 0.0/10 reflects longer-term release cadence; its most recent meaningful update was “Clustering models enter workflow sets via tidyclust”.
Where probably leans on calibration, conformal inference and tidymodels, workflowsets focuses on tidymodels, model comparison and clustering.
workflowsets and probably have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.
Full workflowsets trajectory → · Compare probably vs workflowsets →
6. workflows · velocity 0.0
The tidymodels pipeline grew a third stage, and it happens after the model runs.
Its velocity score of 0.0/10 reflects longer-term release cadence; its most recent meaningful update was “Workflows gain a postprocessing stage via tailor”.
Where probably leans on calibration, conformal inference and tidymodels, workflows focuses on tidymodels, pipelines and postprocessing.
workflows and probably have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.
Full workflows trajectory → · Compare probably vs workflows →
7. vetiver · velocity 0.0
Posit's MLOps package went quiet for two years, then came back to keep up with recipes.
Its velocity score of 0.0/10 reflects longer-term release cadence.
Where probably leans on calibration, conformal inference and tidymodels, vetiver focuses on mlops, model deployment and tidymodels.
vetiver and probably have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.
8. patchwork · velocity 0.0
Patchwork stopped being a ggplot composer and became a page composer.
Its velocity score of 0.0/10 reflects longer-term release cadence; its most recent meaningful update was “gt tables become first-class patchwork objects”.
Where probably leans on calibration, conformal inference and tidymodels, patchwork focuses on ggplot2, composition and tables.
patchwork and probably have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.
Full patchwork trajectory → · Compare probably vs patchwork →
9. mlr3fselect · velocity 0.0
Mlr3fselect turned feature selection into an asynchronous, distributable job.
Its velocity score of 0.0/10 reflects longer-term release cadence; its most recent meaningful update was “Asynchronous feature selection arrives with FSelectorAsync”.
Where probably leans on calibration, conformal inference and tidymodels, mlr3fselect focuses on feature selection, mlr3 and machine learning.
mlr3fselect and probably have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.
Full mlr3fselect trajectory → · Compare probably vs mlr3fselect →
10. lime · velocity 0.0
Lime survives on compatibility patches years after its research moment.
Its velocity score of 0.0/10 reflects longer-term release cadence.
Where probably leans on calibration, conformal inference and tidymodels, lime focuses on interpretability, machine learning and r stats.
lime and probably have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.
11. mlr3measures · velocity 0.0
Mlr3measures is systematically retrofitting sample weights across every metric.
Its velocity score of 0.0/10 reflects longer-term release cadence.
Where probably leans on calibration, conformal inference and tidymodels, mlr3measures focuses on metrics, mlr3 and machine learning.
mlr3measures and probably have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.
Full mlr3measures trajectory → · Compare probably vs mlr3measures →
12. mlr3cluster · velocity 0.0
Mlr3cluster went from a handful of clusterers to covering the field.
Its velocity score of 0.0/10 reflects longer-term release cadence; its most recent meaningful update was “Nine new clustering learners in one release”.
Where probably leans on calibration, conformal inference and tidymodels, mlr3cluster focuses on clustering, mlr3 and machine learning.
mlr3cluster and probably have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.
Full mlr3cluster trajectory → · Compare probably vs mlr3cluster →
Frequently asked questions
What are the best alternatives to probably?
The top probably alternatives we currently track in analytics tools are mlr3mbo, loo, tidytext, textrecipes, workflowsets, ranked by recent ship velocity.
How is this list of probably alternatives ranked?
Alternatives are ranked by Sparkpulse's velocity_score — release cadence + 30-day spark count + sector-relative ship rate.
Can I compare probably directly with one of these alternatives?
Yes — every card has a "Compare with probably" link to a side-by-side /compare page.