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tidyclust vs workflowsets

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

Shared themes:clusteringtidymodels

tidyclust vs workflowsets: at a glance

Featuretidyclustworkflowsets
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themestidyclust, clustering, tidymodels, dbscantidymodels, model-comparison, clustering, tuning
Last editorial update45m ago1h ago
WebsiteVisit →Visit →

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 →

What is workflowsets?

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.

Read the full workflowsets trajectory →

tidyclust vs workflowsets: editorial side-by-side

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.

W
workflowsets
ANALYTICS
0.0

workflowsets keeps widening what counts as a model worth comparing.

◆ Current state

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.

◆ Where it's heading

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.

◆ Prediction

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.

Alternatives to tidyclust and workflowsets

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 tidyclust or workflowsets.

See all tidyclust alternatives → · See all workflowsets alternatives →

Recent activity from tidyclust and workflowsets

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

  1. 1mo agotidyclusttidyclust 0.3.2 fixes k_means() on sparse predictors
  2. 1mo agotidyclusttidyclust 0.3.1 stops same-named metrics silently merging
  3. 2mo agotidyclusttidyclust 0.3.0 adds DBSCAN, Gaussian mixture, and mean shift models
  4. 1y agoworkflowsetscollect_extracts() added; pull_*() functions now error
  5. 1y agotidyclusttidyclust 0.2.4 switches distance calculations to philentropy
  6. 2y agotidyclusttidyclust 0.2.3 resolves a clustMixType reverse-dependency issue
  7. 2y agotidyclusttidyclust 0.2.2 resolves a ClusterR reverse-dependency issue
  8. 2y agoworkflowsetsCensored regression evaluation; eval_time breaks positional args
  9. 3y agoworkflowsetsClustering models enter workflow sets via tidyclust
  10. 4y agoworkflowsetsCase weights supported across a workflow set
  11. 4y agoworkflowsetsUpdate models and recipes across a set; mixed inputs accepted
  12. 5y agoworkflowsetsextract_*() supersedes pull_*() across tidymodels

Frequently asked questions

What is the difference between tidyclust and workflowsets?

Both compete on the same themes — clustering, tidymodels — within Analytics. tidyclust and workflowsets are shipping at a similar cadence (velocity 0.0 vs 0.0, both within Sparkpulse's "active" band). See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.

Is tidyclust better than workflowsets?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. tidyclust and workflowsets are shipping at a similar cadence (velocity 0.0 vs 0.0, both within Sparkpulse's "active" band). For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.

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.

What are the best alternatives to workflowsets?

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.