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Comparison · Analytics
mlr3viz vs see
A side-by-side editorial comparison of mlr3viz and see — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:ggplot2
mlr3viz vs see: at a glance
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.
What is see?
see grows wherever easystats adds a diagnostic, one plot method at a time.
see is the visualization layer for the easystats ecosystem, supplying plot() methods for performance, parameters and datawizard objects. Each release adds methods for whatever those packages shipped — prior predictive checks, DAG diagrams, factor-analysis graphs — alongside steady theme and geom refinement.
mlr3viz vs see: editorial side-by-side
mlr3viz
2.5ANALYTICS
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.
see
0.0ANALYTICS
see grows wherever easystats adds a diagnostic, one plot method at a time.
◆ Current state
see is the visualization layer for the easystats ecosystem, supplying plot() methods for performance, parameters and datawizard objects. Each release adds methods for whatever those packages shipped — prior predictive checks, DAG diagrams, factor-analysis graphs — alongside steady theme and geom refinement.
◆ Where it's heading
Growth here is downstream-driven rather than self-directed: see expands to cover new diagnostics as easystats produces them. Running alongside that is a sustained investment in presentation control — theme arguments on plot methods, elements that scale with base_size — which suits users embedding these plots in documents rather than glancing at them interactively.
◆ Prediction
Expect new plot methods to keep arriving in step with performance and parameters releases, with continued theming work rather than any change in the package's scope.
Alternatives to mlr3viz and see
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 see.
mlr3proba
mlr3proba is shedding weight as its survival work moves into sibling packages
mlr3tuning
mlr3tuning is rebuilding its async machinery under a stable public surface
timetk
timetk swallowed anomalize whole, then went quiet for two years
modelbased
modelbased is turning marginal effects into a full contrast grammar
parameters
easystats' parameters package absorbs one more model class every few weeks
Recent activity from mlr3viz and see
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 18d agomlr3vizmlr3viz 0.11.1 pins legend order for deterministic plots
- 1mo agoseesee 0.14.1 adds plots for prior checks and grouped means
- 2mo agoseesee 0.14.0 renders factor loadings as node-edge graphs
- 5mo agomlr3vizmlr3viz 0.11.0 quiets ggplot2 fortify warnings on ROC curves
- 6mo agoseesee 0.13.0 fixes reversed plot sorting, adds theme arguments
- 11mo agoseesee 0.12.0 extends normality checks to psych factor models
- 1y agomlr3vizmlr3viz 0.10.1 passes plotting parameters through to precrec
- 1y agoseesee 0.11.0 scales theme elements with base_size
- 1y agoseesee 0.10.0 plots random-effect group levels for mixed models
- 1y agomlr3vizmlr3viz 0.10.0 adds a LearnerSurvCoxPH plot
- 2y agomlr3vizmlr3viz 0.9.0 adds EnsembleFSResult plots
- 2y agomlr3vizmlr3viz 0.8.0 tracks paradox 1.0.0
Frequently asked questions
What is the difference between mlr3viz and see?
Both compete on the same themes — ggplot2 — 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 see?
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 see?
Top see alternatives in Analytics are ranked by recent ship velocity. Browse the "see alternatives" section above for the current picks, or visit /alternatives/see-r for the full list with editorial commentary on each.