mlr3proba
mlr3proba is shedding weight as its survival work moves into sibling packages
A side-by-side editorial comparison of mlr3viz and workflowsets — release velocity, themes, recent moves, and the top alternatives to consider.
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.
workflowsets keeps widening what counts as a model worth comparing.
workflowsets holds a grid of preprocessor and model combinations and evaluates all of them under one call to workflow_map(). The releases in view widen that grid — clustering specifications via tidyclust, censored regression via an eval_time argument, case weights — and fill in the accessors around it with collect_notes(), collect_extracts() and fit_best(). The long-running pull_*() deprecation finally reached the error stage in 1.1.1.
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.
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.
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.
workflowsets holds a grid of preprocessor and model combinations and evaluates all of them under one call to workflow_map(). The releases in view widen that grid — clustering specifications via tidyclust, censored regression via an eval_time argument, case weights — and fill in the accessors around it with collect_notes(), collect_extracts() and fit_best(). The long-running pull_*() deprecation finally reached the error stage in 1.1.1.
The package's job is comparison, so its direction is set by what tidymodels can express: every time a new model paradigm lands elsewhere, workflowsets has to learn to rank it. Clustering was the largest of those steps because it has no outcome column to score against. Alongside that runs a slower cleanup — named-only optional arguments, type checking on inputs, informative errors when someone passes a workflow set to fit() — that reads as a package hardening after its API settled.
Expect the tailor postprocessors that workflows added in 1.3.0 to need representation here next, since a workflow set that cannot vary the postprocessor cannot compare calibration choices.
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 workflowsets.
mlr3proba is shedding weight as its survival work moves into sibling packages
mlr3tuning is rebuilding its async machinery under a stable public surface
timetk swallowed anomalize whole, then went quiet for two years
modelbased is turning marginal effects into a full contrast grammar
easystats' parameters package absorbs one more model class every few weeks
A finished Bayesian model-comparison package in pure maintenance mode
See all mlr3viz alternatives → · See all workflowsets alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. 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.
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.
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.
Top workflowsets alternatives in Analytics are ranked by recent ship velocity. Browse the "workflowsets alternatives" section above for the current picks, or visit /alternatives/workflowsets for the full list with editorial commentary on each.