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censored vs mlr3measures

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

Shared themes:r-stats

censored vs mlr3measures: at a glance

Featurecensoredmlr3measures
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themessurvival-analysis, tidymodels, parsnip, enginesmetrics, mlr3, machine-learning, r-stats
Last editorial update4h ago1h ago
WebsiteVisit →Visit →

What is censored?

censored keeps survival models aligned with parsnip's shifting prediction contracts

censored supplies survival-analysis engines to parsnip, and its release history is dominated by staying in step with the rest of tidymodels rather than shipping independent features. The 0.2.0 and 0.3.0 releases added engines and prediction types; everything since has been contract alignment — quantile prediction format, hardhat test adaptation, flexsurv preparation.

Read the full censored 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 →

censored vs mlr3measures: editorial side-by-side

C
censored
ANALYTICS
0.0

censored keeps survival models aligned with parsnip's shifting prediction contracts

◆ Current state

censored supplies survival-analysis engines to parsnip, and its release history is dominated by staying in step with the rest of tidymodels rather than shipping independent features. The 0.2.0 and 0.3.0 releases added engines and prediction types; everything since has been contract alignment — quantile prediction format, hardhat test adaptation, flexsurv preparation.

◆ Where it's heading

The package is settling into a downstream role where parsnip and hardhat set the interface and censored implements it for censored regression. Breaking changes arrive from upstream, not from new ideas here. The substantive engine work — aorsf, flexsurvspline, glmnet multi_predict — is behind it, and recent cycles are thin.

◆ Prediction

Expect the next releases to track further parsnip prediction-type changes rather than add engines; the entries do not show new survival methods in progress.

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 censored 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 censored or mlr3measures.

See all censored alternatives → · See all mlr3measures alternatives →

Recent activity from censored and mlr3measures

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

  1. 3mo agomlr3measuresWeighted AUC and weighted confusion-matrix measures
  2. 4mo agocensoredcensored 0.3.4
  3. 8mo agomlr3measuresObservation-wise loss for bbrier and logloss
  4. 11mo agomlr3measuresrse, rsq, rrse and rae deprecated; bias measures corrected
  5. 1y agocensoredQuantile prediction format follows new parsnip requirements
  6. 1y agomlr3measureslinex, pinball and Mu AUC measures added
  7. 2y agomlr3measuresgmean, gpr and multiclass MCC added
  8. 2y agocensoredSurvival probabilities at infinite evaluation times now computed
  9. 2y agocensoredcensored 0.3.1
  10. 2y agocensoredmulti_predict() for all glmnet prediction types; aorsf predicts time
  11. 3y agocensoredeval_time replaces time; matrix fitting for censored regression
  12. 4y agomlr3measuresObservation-wise loss functions introduced

Frequently asked questions

What is the difference between censored and mlr3measures?

Both compete on the same themes — r-stats — within Analytics. censored 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 censored better than mlr3measures?

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

Top censored alternatives in Analytics are ranked by recent ship velocity. Browse the "censored alternatives" section above for the current picks, or visit /alternatives/censored 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.