← Back to home
Comparison · Analytics

mlr3viz vs parameters

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

Shared themes:r-package

mlr3viz vs parameters: at a glance

Featuremlr3vizparameters
SectorAnalyticsAnalytics
Velocity score2.50.0
Sparks · 30d00
Top themesmlr3, visualization, ggplot2, roc-curveseasystats, model-parameters, standardization, mixed-models
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 parameters?

easystats' parameters package absorbs one more model class every few weeks

parameters extracts and formats coefficients from an enormous range of R model objects, and its releases read as a running ledger of that range expanding — lavaan and lavaan.mi, survey, lcmm, glmmTMB, fixest, marginaleffects, ordinal. Recent versions ship roughly monthly with a mix of new support, new arguments, and fixes for label handling and standard errors. The most consequential recent change is behavioral: post-hoc standardization no longer standardizes the intercept, setting it and its inferential statistics to NA.

Read the full parameters trajectory →

mlr3viz vs parameters: 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.

P
parameters
ANALYTICS
0.0

easystats' parameters package absorbs one more model class every few weeks

◆ Current state

parameters extracts and formats coefficients from an enormous range of R model objects, and its releases read as a running ledger of that range expanding — lavaan and lavaan.mi, survey, lcmm, glmmTMB, fixest, marginaleffects, ordinal. Recent versions ship roughly monthly with a mix of new support, new arguments, and fixes for label handling and standard errors. The most consequential recent change is behavioral: post-hoc standardization no longer standardizes the intercept, setting it and its inferential statistics to NA.

◆ Where it's heading

The package's job is to be the universal adapter for model output, so its roadmap is effectively set by what the R modelling ecosystem produces. Two threads are visible beyond coverage: getting standard errors right for awkward cases such as frailty terms and robust vcov matrices, and getting labels right when factors are converted on the fly or character variables appear in a formula. Interoperability inside easystats keeps tightening, with equivalence_test() gaining methods for modelbased objects.

◆ Prediction

Given the cadence, the next release will most likely add another model class alongside label and standard-error fixes rather than change how the package works.

Alternatives to mlr3viz and parameters

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 parameters.

See all mlr3viz alternatives → · See all parameters alternatives →

Recent activity from mlr3viz and parameters

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

  1. 18d agomlr3vizmlr3viz 0.11.1 pins legend order for deterministic plots
  2. 1mo agoparametersparameters 0.29.2 extends lavaan support and fixes label dropping
  3. 2mo agoparametersparameters 0.29.1 adds a cluster argument and fixes vcov handling
  4. 3mo agoparametersparameters 0.29.0 stops standardizing the intercept in post-hoc methods
  5. 5mo agomlr3vizmlr3viz 0.11.0 quiets ggplot2 fortify warnings on ROC curves
  6. 8mo agoparametersparameters 0.28.3 adds Kenward-Roger and Satterthwaite for glmmTMB
  7. 11mo agoparametersparameters 0.28.2 updates tests for the latest fixest release
  8. 11mo agoparametersparameters 0.28.1 adds robust standard errors for glmmTMB
  9. 1y agomlr3vizmlr3viz 0.10.1 passes plotting parameters through to precrec
  10. 1y agomlr3vizmlr3viz 0.10.0 adds a LearnerSurvCoxPH plot
  11. 2y agomlr3vizmlr3viz 0.9.0 adds EnsembleFSResult plots
  12. 2y agomlr3vizmlr3viz 0.8.0 tracks paradox 1.0.0

Frequently asked questions

What is the difference between mlr3viz and parameters?

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 parameters?

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 parameters?

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