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Comparison · Analytics

mlr3filters vs modelbased

A side-by-side editorial comparison of mlr3filters and modelbased — release velocity, themes, recent moves, and the top alternatives to consider.

mlr3filters vs modelbased: at a glance

Featuremlr3filtersmodelbased
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesfeature-selection, mlr3, machine-learning, r-statseasystats, marginal-effects, contrasts, mixed-models
Last editorial update3h ago1h ago
WebsiteVisit →Visit →

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.

Read the full mlr3filters trajectory →

What is modelbased?

modelbased is turning marginal effects into a full contrast grammar

modelbased computes marginal means, contrasts, and slopes from fitted models, and it ships every one to two months with a consistent shape: new comparison types, broader model support, and steady renaming toward clearer vocabulary. The recent arc runs from marginal effects inequality measures through inequality ratios to an omnibus global test and a post_process argument for multi-step comparisons. Argument names have been settled along the way, with trend becoming slope and an alias left behind.

Read the full modelbased trajectory →

mlr3filters vs modelbased: editorial side-by-side

M
mlr3filters
ANALYTICS
0.0

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.

M
modelbased
ANALYTICS
0.0

modelbased is turning marginal effects into a full contrast grammar

◆ Current state

modelbased computes marginal means, contrasts, and slopes from fitted models, and it ships every one to two months with a consistent shape: new comparison types, broader model support, and steady renaming toward clearer vocabulary. The recent arc runs from marginal effects inequality measures through inequality ratios to an omnibus global test and a post_process argument for multi-step comparisons. Argument names have been settled along the way, with trend becoming slope and an alias left behind.

◆ Where it's heading

The package is building a compositional vocabulary rather than a fixed menu — contrasts of average slopes, contrasts across two numeric predictors, inequality summaries across all outcome categories, and now user-supplied post-processing of comparisons. Support quietly widens underneath, covering nestedLogit, brms finite mixtures, and offsets under population and average estimation. Plotting gets attention in proportion to how often these results are presented rather than tabulated, including collapse_by_group() for showing averaged raw data under mixed-model fits.

◆ Prediction

With post_process and omnibus tests both landed, the likely next step is making these composed comparisons easier to report — formatting or plotting methods for the multi-step results rather than new comparison types.

Alternatives to mlr3filters and modelbased

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 modelbased.

See all mlr3filters alternatives → · See all modelbased alternatives →

Recent activity from mlr3filters and modelbased

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

  1. 1mo agomodelbasedmodelbased 0.16.0 adds post-processing and omnibus contrast tests
  2. 3mo agomodelbasedmodelbased 0.15.0 contrasts average slopes across numeric predictors
  3. 3mo agomlr3filtersFilter dictionary listing now uses prototypes
  4. 5mo agomodelbasedmodelbased 0.14.0 renames trend to slope and adds collapse_by_group()
  5. 8mo agomodelbasedmodelbased 0.13.1 adds marginal group-level estimates and as.data.frame()
  6. 11mo agomlr3filtersBoruta handles logical, factor and ordered features
  7. 11mo agomodelbasedmodelbased 0.13.0 adds inequality ratios and slope marginalization
  8. 1y agomodelbasedmodelbased 0.12.0 introduces marginal effects inequality measures
  9. 2y agomlr3filtersBoruta and univariate Cox filters added
  10. 3y agomlr3filtersMissing-value tagging and wider CarScore feature support
  11. 3y agomlr3filtersMissing-value checks and featureless learner defaults
  12. 3y agomlr3filtersSurvival CAR score filter and pipeline documentation

Frequently asked questions

What is the difference between mlr3filters and modelbased?

They serve adjacent needs but don't currently overlap on shipped themes. mlr3filters and modelbased 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 modelbased?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. mlr3filters and modelbased 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 modelbased?

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