← Back to home
Comparison · Analytics

mlr3proba vs stacks

A side-by-side editorial comparison of mlr3proba and stacks — release velocity, themes, recent moves, and the top alternatives to consider.

Shared themes:r-package

mlr3proba vs stacks: at a glance

Featuremlr3probastacks
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesmlr3, survival-analysis, probabilistic-learning, dependency-maintenancetidymodels, ensembling, parallel-processing, future-framework
Last editorial update1h ago1h ago
WebsiteVisit →Visit →

What is mlr3proba?

mlr3proba is shedding weight as its survival work moves into sibling packages

mlr3proba provides probabilistic supervised learning for mlr3 — survival analysis, density estimation, and the measures that go with them. Recent releases are almost entirely upkeep: a distr6 fork to work around an upstream problem, an ooplah fix, a predict-type correction, and registration in mlr_reflections$loaded_packages. The one deletion is telling, with LearnerDensPenalized removed after pendensity left CRAN.

Read the full mlr3proba 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 →

mlr3proba vs stacks: editorial side-by-side

M
mlr3proba
ANALYTICS
0.0

mlr3proba is shedding weight as its survival work moves into sibling packages

◆ Current state

mlr3proba provides probabilistic supervised learning for mlr3 — survival analysis, density estimation, and the measures that go with them. Recent releases are almost entirely upkeep: a distr6 fork to work around an upstream problem, an ooplah fix, a predict-type correction, and registration in mlr_reflections$loaded_packages. The one deletion is telling, with LearnerDensPenalized removed after pendensity left CRAN.

◆ Where it's heading

The package is being pared back rather than extended. Its README now points at survdistr and mlr3cmprsk as matured alternatives for parts of what it covers, which reads as scope being handed off, while the Cox proportional-hazards autoplot arrived from mlr3viz in the other direction. Several fixes exist to route around dependencies that broke or disappeared, which is the recurring cost of building on a long chain of specialized CRAN packages.

◆ Prediction

The dependency churn suggests more consolidation — further reliance on survdistr and mlr3cmprsk, and more learners retired when the package underneath them goes unmaintained.

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 mlr3proba 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 mlr3proba or stacks.

See all mlr3proba alternatives → · See all stacks alternatives →

Recent activity from mlr3proba and stacks

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

  1. 2mo agomlr3probamlr3proba 0.8.10 registers itself in the mlr3 loaded-packages registry
  2. 4mo agomlr3probamlr3proba 0.8.9 drops LearnerDensPenalized after pendensity left CRAN
  3. 5mo agomlr3probamlr3proba 0.8.8
  4. 5mo agomlr3probamlr3proba 0.8.7
  5. 9mo agomlr3probamlr3proba 0.8.5
  6. 10mo agomlr3probamlr3proba 0.8.4 takes over the Cox proportional-hazards autoplot
  7. 1y agostacksstacks 1.1.1 re-released to clear a CRAN check note
  8. 1y agostacksstacks 1.1.0 completes the move to future-based parallelism
  9. 2y agostacksstacks 1.0.5 fixes butchered stack size inflation
  10. 2y agostacksstacks 1.0.4 introduces future-based parallel processing
  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 mlr3proba and stacks?

Both compete on the same themes — r-package — within Analytics. mlr3proba and stacks 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 mlr3proba better than stacks?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. mlr3proba and stacks 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 mlr3proba?

Top mlr3proba alternatives in Analytics are ranked by recent ship velocity. Browse the "mlr3proba alternatives" section above for the current picks, or visit /alternatives/mlr3proba 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.