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mlr3proba vs mlr3tuning

A side-by-side editorial comparison of mlr3proba and mlr3tuning — release velocity, themes, recent moves, and the top alternatives to consider.

Shared themes:mlr3r-package

mlr3proba vs mlr3tuning: at a glance

Featuremlr3probamlr3tuning
SectorAnalyticsAnalytics
Velocity score0.02.5
Sparks · 30d00
Top themesmlr3, survival-analysis, probabilistic-learning, dependency-maintenancemlr3, hyperparameter-tuning, async-optimization, callbacks
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 mlr3tuning?

mlr3tuning is rebuilding its async machinery under a stable public surface

mlr3tuning provides hyperparameter optimization for the mlr3 ecosystem, and its recent history is dominated by the asynchronous tuning path: archive freezing, callback stages around queue evaluation, and version-locked compatibility with the rush backend. Releases pair a small feature with several fixes and an explicit compatibility line naming the mlr3 or rush version they track. The most recent release drops all workarounds for older rush versions, which suggests that dependency has stabilized enough to require rather than accommodate.

Read the full mlr3tuning trajectory →

mlr3proba vs mlr3tuning: 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.

M
mlr3tuning
ANALYTICS
2.5

mlr3tuning is rebuilding its async machinery under a stable public surface

◆ Current state

mlr3tuning provides hyperparameter optimization for the mlr3 ecosystem, and its recent history is dominated by the asynchronous tuning path: archive freezing, callback stages around queue evaluation, and version-locked compatibility with the rush backend. Releases pair a small feature with several fixes and an explicit compatibility line naming the mlr3 or rush version they track. The most recent release drops all workarounds for older rush versions, which suggests that dependency has stabilized enough to require rather than accommodate.

◆ Where it's heading

Two things are being tidied at once. The async archive is converging on a consistent data.table representation across batch and async variants, so results are shaped the same regardless of how tuning ran. Separately, the package is becoming a better ecosystem citizen — unioning tuner properties on load instead of overwriting them, removing its callbacks on unload, and raising informative errors from AutoTuner accessors on an untrained model. Both are the marks of a package used as a dependency more than as a destination.

◆ Prediction

With rush pinned to 1.2.0 and the compatibility shims gone, the next release is likely to expose more of the async path through callbacks rather than change the tuning interface.

Alternatives to mlr3proba and mlr3tuning

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 mlr3tuning.

See all mlr3proba alternatives → · See all mlr3tuning alternatives →

Recent activity from mlr3proba and mlr3tuning

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

  1. 18d agomlr3tuningmlr3tuning 1.6.1 stops clobbering other packages' tuner properties
  2. 2mo agomlr3probamlr3proba 0.8.10 registers itself in the mlr3 loaded-packages registry
  3. 4mo agomlr3probamlr3proba 0.8.9 drops LearnerDensPenalized after pendensity left CRAN
  4. 4mo agomlr3tuningmlr3tuning 1.6.0 aligns archive column order across tuning classes
  5. 5mo agomlr3probamlr3proba 0.8.8
  6. 5mo agomlr3probamlr3proba 0.8.7
  7. 8mo agomlr3tuningmlr3tuning 1.5.1 tracks xgboost 3.1.2.1
  8. 8mo agomlr3tuningmlr3tuning 1.5.0 adds queue evaluation stages to async callbacks
  9. 9mo agomlr3probamlr3proba 0.8.5
  10. 10mo agomlr3probamlr3proba 0.8.4 takes over the Cox proportional-hazards autoplot
  11. 1y agomlr3tuningmlr3tuning 1.4.0 unifies logging under a base mlr3 logger
  12. 1y agomlr3tuningmlr3tuning 1.3.0 adds a frozen async archive and leaner worker storage

Frequently asked questions

What is the difference between mlr3proba and mlr3tuning?

Both compete on the same themes — mlr3, r-package — within Analytics. mlr3tuning 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 mlr3proba better than mlr3tuning?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. mlr3tuning 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 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 mlr3tuning?

Top mlr3tuning alternatives in Analytics are ranked by recent ship velocity. Browse the "mlr3tuning alternatives" section above for the current picks, or visit /alternatives/mlr3tuning for the full list with editorial commentary on each.