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mlr3viz vs tidyclust

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

Shared themes:r-package

mlr3viz vs tidyclust: at a glance

Featuremlr3viztidyclust
SectorAnalyticsAnalytics
Velocity score2.50.0
Sparks · 30d00
Top themesmlr3, visualization, ggplot2, roc-curvestidyclust, clustering, tidymodels, dbscan
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 tidyclust?

tidyclust just tripled the model types it can fit, and handed finalization back to tune

tidyclust brings clustering into the tidymodels interface, and 0.3.0 was the release where its model coverage stopped being k-means and hierarchical clustering. DBSCAN and HDBSCAN, Gaussian mixtures, and mean shift all arrived at once as proper clustering specifications. The two releases since have been bug fixes on the metric and sparse-data paths, which is the usual pattern after a large surface addition.

Read the full tidyclust trajectory →

mlr3viz vs tidyclust: 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.

T
tidyclust
ANALYTICS
0.0

tidyclust just tripled the model types it can fit, and handed finalization back to tune

◆ Current state

tidyclust brings clustering into the tidymodels interface, and 0.3.0 was the release where its model coverage stopped being k-means and hierarchical clustering. DBSCAN and HDBSCAN, Gaussian mixtures, and mean shift all arrived at once as proper clustering specifications. The two releases since have been bug fixes on the metric and sparse-data paths, which is the usual pattern after a large surface addition.

◆ Where it's heading

The package is converging with the rest of tidymodels rather than maintaining a parallel API: finalize_model_tidyclust() and finalize_workflow_tidyclust() are deprecated because tune::finalize_model() and tune::finalize_workflow() now handle cluster_spec objects natively. That removes the last place where clustering needed its own version of a shared verb. With density-based and model-based clustering now present, the interface has to cover model families with genuinely different assumptions than the centroid methods it started with.

◆ Prediction

The recent fixes to cluster_metric_set() labeling and custom-metric authoring suggest evaluation is the current focus, so metrics suited to density-based clusters are the likely next addition.

Alternatives to mlr3viz and tidyclust

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 tidyclust.

See all mlr3viz alternatives → · See all tidyclust alternatives →

Recent activity from mlr3viz and tidyclust

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

  1. 18d agomlr3vizmlr3viz 0.11.1 pins legend order for deterministic plots
  2. 1mo agotidyclusttidyclust 0.3.2 fixes k_means() on sparse predictors
  3. 1mo agotidyclusttidyclust 0.3.1 stops same-named metrics silently merging
  4. 2mo agotidyclusttidyclust 0.3.0 adds DBSCAN, Gaussian mixture, and mean shift models
  5. 5mo agomlr3vizmlr3viz 0.11.0 quiets ggplot2 fortify warnings on ROC curves
  6. 1y agomlr3vizmlr3viz 0.10.1 passes plotting parameters through to precrec
  7. 1y agotidyclusttidyclust 0.2.4 switches distance calculations to philentropy
  8. 1y agomlr3vizmlr3viz 0.10.0 adds a LearnerSurvCoxPH plot
  9. 2y agotidyclusttidyclust 0.2.3 resolves a clustMixType reverse-dependency issue
  10. 2y agomlr3vizmlr3viz 0.9.0 adds EnsembleFSResult plots
  11. 2y agotidyclusttidyclust 0.2.2 resolves a ClusterR reverse-dependency issue
  12. 2y agomlr3vizmlr3viz 0.8.0 tracks paradox 1.0.0

Frequently asked questions

What is the difference between mlr3viz and tidyclust?

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 tidyclust?

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 tidyclust?

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