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mlr3cluster vs mlr3measures

A side-by-side editorial comparison of mlr3cluster and mlr3measures — release velocity, themes, recent moves, and the top alternatives to consider.

Shared themes:mlr3machine-learningr-stats

mlr3cluster vs mlr3measures: at a glance

Featuremlr3clustermlr3measures
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesclustering, mlr3, machine-learning, r-statsmetrics, mlr3, machine-learning, r-stats
Last editorial update1h ago1h ago
WebsiteVisit →Visit →

What is mlr3cluster?

mlr3cluster went from a handful of clusterers to covering the field

mlr3cluster supplies clustering learners to the mlr3 framework. Over three releases it added roughly a dozen learners — CLARA, k-prototypes, spectral, then a batch of nine covering finite mixtures, spherical and directional families, self-organising maps, spatio-temporal DBSCAN and robust trimmed clustering. The newest release fixes predict-time behaviour across the hierarchical learners.

Read the full mlr3cluster trajectory →

What is mlr3measures?

mlr3measures is systematically retrofitting sample weights across every metric

mlr3measures is the metric library behind mlr3. Recent releases follow two threads: adding measures — linex, pinball, Mu AUC, gmean, gpr, mcc — and retrofitting sample_weights support across the existing ones, reaching AUC and the confusion-matrix family in 1.3.0. Along the way 1.1.0 deprecated four regression measures and corrected the bias definitions.

Read the full mlr3measures trajectory →

mlr3cluster vs mlr3measures: editorial side-by-side

M
mlr3cluster
ANALYTICS
0.0

mlr3cluster went from a handful of clusterers to covering the field

◆ Current state

mlr3cluster supplies clustering learners to the mlr3 framework. Over three releases it added roughly a dozen learners — CLARA, k-prototypes, spectral, then a batch of nine covering finite mixtures, spherical and directional families, self-organising maps, spatio-temporal DBSCAN and robust trimmed clustering. The newest release fixes predict-time behaviour across the hierarchical learners.

◆ Where it's heading

The package is at the tail end of a coverage push, and the emphasis has shifted from adding algorithms to making the ones it has behave correctly at prediction time — cutting trees at the current k, reclustering coresets, failing informatively on unsupported metric combinations. That is the normal sequence after a rapid expansion.

◆ Prediction

Expect further predict-path corrections and parameter-set alignment across the newly added learners before any more algorithms arrive.

M
mlr3measures
ANALYTICS
0.0

mlr3measures is systematically retrofitting sample weights across every metric

◆ Current state

mlr3measures is the metric library behind mlr3. Recent releases follow two threads: adding measures — linex, pinball, Mu AUC, gmean, gpr, mcc — and retrofitting sample_weights support across the existing ones, reaching AUC and the confusion-matrix family in 1.3.0. Along the way 1.1.0 deprecated four regression measures and corrected the bias definitions.

◆ Where it's heading

The library is maturing rather than growing: weighted evaluation and observation-wise loss functions are being brought to metrics that already existed, which is what downstream weighted-resampling and per-observation analysis need. The deprecations suggest the maintainers are willing to remove measures they consider ill-defined rather than keep them for compatibility.

◆ Prediction

Expect sample_weights and observation-wise variants to reach the remaining measures that lack them.

Alternatives to mlr3cluster and mlr3measures

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 mlr3cluster or mlr3measures.

See all mlr3cluster alternatives → · See all mlr3measures alternatives →

Recent activity from mlr3cluster and mlr3measures

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

  1. 1mo agomlr3clusterHierarchical learners now honour k at prediction time
  2. 2mo agomlr3clusterNine new clustering learners in one release
  3. 3mo agomlr3measuresWeighted AUC and weighted confusion-matrix measures
  4. 5mo agomlr3clusterCLARA, k-prototypes and spectral clustering learners added
  5. 6mo agomlr3clusterTyped error classes and probabilistic EM assignments
  6. 8mo agomlr3measuresObservation-wise loss for bbrier and logloss
  7. 8mo agomlr3clusterHDBSCAN gains cluster_selection_epsilon
  8. 11mo agomlr3measuresrse, rsq, rrse and rae deprecated; bias measures corrected
  9. 1y agomlr3clusterMclust learner brought in line with paradox conventions
  10. 1y agomlr3measureslinex, pinball and Mu AUC measures added
  11. 2y agomlr3measuresgmean, gpr and multiclass MCC added
  12. 4y agomlr3measuresObservation-wise loss functions introduced

Frequently asked questions

What is the difference between mlr3cluster and mlr3measures?

Both compete on the same themes — mlr3, machine-learning, r-stats — within Analytics. mlr3cluster and mlr3measures 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 mlr3cluster better than mlr3measures?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. mlr3cluster and mlr3measures 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 mlr3cluster?

Top mlr3cluster alternatives in Analytics are ranked by recent ship velocity. Browse the "mlr3cluster alternatives" section above for the current picks, or visit /alternatives/mlr3cluster for the full list with editorial commentary on each.

What are the best alternatives to mlr3measures?

Top mlr3measures alternatives in Analytics are ranked by recent ship velocity. Browse the "mlr3measures alternatives" section above for the current picks, or visit /alternatives/mlr3measures for the full list with editorial commentary on each.