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mlr3viz vs stacks

A side-by-side editorial comparison of mlr3viz and stacks — release velocity, themes, recent moves, and the top alternatives to consider.

Shared themes:r-package

mlr3viz vs stacks: at a glance

Featuremlr3vizstacks
SectorAnalyticsAnalytics
Velocity score2.50.0
Sparks · 30d00
Top themesmlr3, visualization, ggplot2, roc-curvestidymodels, ensembling, parallel-processing, future-framework
Last editorial update1h ago1h ago
WebsiteVisit →Visit →

What is mlr3viz?

mlr3viz keeps the ecosystem's plots working while the plots themselves move out

mlr3viz supplies autoplot methods across mlr3 objects — learners, resample and benchmark results, tuning instances, ensemble feature-selection results. Recent releases are mostly defensive: suppressing ggplot2::fortify() warnings on ROC and PRC curves, pinning legend order so plots are deterministic across ggplot2 environments, and tracking mlr3 1.7.2. A visible piece of scope also left, with the LearnerSurvCoxPH plot moving to mlr3proba.

Read the full mlr3viz trajectory →

What is stacks?

Model stacking in tidymodels, quietly migrating off foreach and onto future

stacks builds ensembles from tidymodels tuning results, and its release history is dominated by one long project: replacing foreach-based parallelism with the future framework. That transition completed in 1.1.0, where foreach backends began being ignored with a warning and the minimum R version rose to 4.1. Releases are infrequent and small, with the most recent being a CRAN re-submission rather than a change.

Read the full stacks trajectory →

mlr3viz vs stacks: editorial side-by-side

M
mlr3viz
ANALYTICS
2.5

mlr3viz keeps the ecosystem's plots working while the plots themselves move out

◆ Current state

mlr3viz supplies autoplot methods across mlr3 objects — learners, resample and benchmark results, tuning instances, ensemble feature-selection results. Recent releases are mostly defensive: suppressing ggplot2::fortify() warnings on ROC and PRC curves, pinning legend order so plots are deterministic across ggplot2 environments, and tracking mlr3 1.7.2. A visible piece of scope also left, with the LearnerSurvCoxPH plot moving to mlr3proba.

◆ Where it's heading

The package is being narrowed toward generic plotting infrastructure while learner-specific plots migrate to the packages that own those learners. What it does add is access rather than new charts — passing parameters through to precrec::autoplot(), better hints when the wrong autoplot type is requested, and a confidence-interval plot for mlr3inferr. Determinism across ggplot2 versions has become a recurring concern, which is what happens when a visualization package is depended on by documentation and tests.

◆ Prediction

Following the Cox proportional-hazards precedent, further learner-specific plots are likely to move to their owning packages, leaving mlr3viz with the cross-cutting result objects.

S
stacks
ANALYTICS
0.0

Model stacking in tidymodels, quietly migrating off foreach and onto future

◆ Current state

stacks builds ensembles from tidymodels tuning results, and its release history is dominated by one long project: replacing foreach-based parallelism with the future framework. That transition completed in 1.1.0, where foreach backends began being ignored with a warning and the minimum R version rose to 4.1. Releases are infrequent and small, with the most recent being a CRAN re-submission rather than a change.

◆ Where it's heading

The package is mature and its remaining work is compatibility rather than capability — tracking the parallelism story across tidymodels, keeping object sizes sane after butchering and reloading, and staying aligned with recipes deprecations. The augment() method added for vetiver compatibility shows the same instinct: fit into the surrounding ecosystem rather than grow independently of it. Nothing in the visible history suggests new ensembling methods are being pursued.

◆ Prediction

With the future migration finished, the next release is most likely maintenance keeping pace with tune and recipes rather than anything users would notice.

Alternatives to mlr3viz and stacks

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 mlr3viz or stacks.

See all mlr3viz alternatives → · See all stacks alternatives →

Recent activity from mlr3viz and stacks

Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.

  1. 18d agomlr3vizmlr3viz 0.11.1 pins legend order for deterministic plots
  2. 5mo agomlr3vizmlr3viz 0.11.0 quiets ggplot2 fortify warnings on ROC curves
  3. 1y agomlr3vizmlr3viz 0.10.1 passes plotting parameters through to precrec
  4. 1y agostacksstacks 1.1.1 re-released to clear a CRAN check note
  5. 1y agostacksstacks 1.1.0 completes the move to future-based parallelism
  6. 1y agomlr3vizmlr3viz 0.10.0 adds a LearnerSurvCoxPH plot
  7. 2y agostacksstacks 1.0.5 fixes butchered stack size inflation
  8. 2y agomlr3vizmlr3viz 0.9.0 adds EnsembleFSResult plots
  9. 2y agostacksstacks 1.0.4 introduces future-based parallel processing
  10. 2y agomlr3vizmlr3viz 0.8.0 tracks paradox 1.0.0
  11. 2y agostacksstacks 1.0.3 clears recipes deprecations and a type-check bug
  12. 3y agostacksstacks 1.0.2 adds an augment() method for vetiver compatibility

Frequently asked questions

What is the difference between mlr3viz and stacks?

Both compete on the same themes — r-package — within Analytics. mlr3viz is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.

Is mlr3viz better than stacks?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. mlr3viz is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.

What are the best alternatives to mlr3viz?

Top mlr3viz alternatives in Analytics are ranked by recent ship velocity. Browse the "mlr3viz alternatives" section above for the current picks, or visit /alternatives/mlr3viz for the full list with editorial commentary on each.

What are the best alternatives to stacks?

Top stacks alternatives in Analytics are ranked by recent ship velocity. Browse the "stacks alternatives" section above for the current picks, or visit /alternatives/stacks for the full list with editorial commentary on each.