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Comparison · Analytics
mlr3filters vs mlr3measures
A side-by-side editorial comparison of mlr3filters and mlr3measures — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:mlr3machine-learningr-stats
mlr3filters vs mlr3measures: at a glance
What is mlr3filters?
mlr3filters grows one feature-selection filter at a time
mlr3filters provides feature-filter methods to mlr3. Its releases follow a consistent shape: one or two new filters, broader feature-type support on existing ones, and error-message work. Boruta and a univariate Cox filter arrived in 0.8.0; 0.9.0 extended Boruta to logical, factor and ordered features and moved param_set to an active binding.
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.
mlr3filters vs mlr3measures: editorial side-by-side
mlr3filters
0.0ANALYTICS
mlr3filters grows one feature-selection filter at a time
◆ Current state
mlr3filters provides feature-filter methods to mlr3. Its releases follow a consistent shape: one or two new filters, broader feature-type support on existing ones, and error-message work. Boruta and a univariate Cox filter arrived in 0.8.0; 0.9.0 extended Boruta to logical, factor and ordered features and moved param_set to an active binding.
◆ Where it's heading
This is incremental infrastructure that tracks mlr3's own conventions — cli printing, prototype-based dictionaries, featureless learners as defaults — while slowly widening which data types each filter accepts. Nothing in the recent history suggests a change of scope.
◆ Prediction
Expect another filter or two plus continued feature-type broadening, keeping pace with mlr3 core conventions.
mlr3measures
0.0ANALYTICS
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 mlr3filters 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 mlr3filters or mlr3measures.
textrecipes
Text features finally stay sparse all the way to the model.
probably
The package that made calibration a step instead of an afterthought.
workflowsets
workflowsets keeps widening what counts as a model worth comparing.
workflows
The tidymodels pipeline grew a third stage, and it happens after the model runs.
vetiver
Posit's MLOps package went quiet for two years, then came back to keep up with recipes.
See all mlr3filters alternatives → · See all mlr3measures alternatives →
Recent activity from mlr3filters and mlr3measures
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 3mo agomlr3filtersFilter dictionary listing now uses prototypes
- 3mo agomlr3measuresWeighted AUC and weighted confusion-matrix measures
- 8mo agomlr3measuresObservation-wise loss for bbrier and logloss
- 11mo agomlr3filtersBoruta handles logical, factor and ordered features
- 11mo agomlr3measuresrse, rsq, rrse and rae deprecated; bias measures corrected
- 1y agomlr3measureslinex, pinball and Mu AUC measures added
- 2y agomlr3measuresgmean, gpr and multiclass MCC added
- 2y agomlr3filtersBoruta and univariate Cox filters added
- 3y agomlr3filtersMissing-value tagging and wider CarScore feature support
- 3y agomlr3filtersMissing-value checks and featureless learner defaults
- 3y agomlr3filtersSurvival CAR score filter and pipeline documentation
- 4y agomlr3measuresObservation-wise loss functions introduced
Frequently asked questions
What is the difference between mlr3filters and mlr3measures?
Both compete on the same themes — mlr3, machine-learning, r-stats — within Analytics. mlr3filters 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 mlr3filters better than mlr3measures?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. mlr3filters 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 mlr3filters?
Top mlr3filters alternatives in Analytics are ranked by recent ship velocity. Browse the "mlr3filters alternatives" section above for the current picks, or visit /alternatives/mlr3filters 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.