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Comparison · Analytics

hardhat vs mlr3filters

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

Shared themes:r-statsmachine-learning

hardhat vs mlr3filters: at a glance

Featurehardhatmlr3filters
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themestidymodels, r-stats, machine-learning, infrastructurefeature-selection, mlr3, machine-learning, r-stats
Last editorial update1h ago1h ago
WebsiteVisit →Visit →

What is hardhat?

hardhat keeps adding the contracts tidymodels needs next

hardhat is the infrastructure layer under tidymodels, defining the preprocessing and extraction contracts other packages implement. Its releases read as a list of new generics and vector classes: extract_postprocessor(), extract_fit_time(), extract_tailor(), and a quantile_pred() class for quantile-regression output. The newest release is narrow warning and missing-value handling in mold().

Read the full hardhat trajectory →

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 →

hardhat vs mlr3filters: editorial side-by-side

H
hardhat
ANALYTICS
0.0

hardhat keeps adding the contracts tidymodels needs next

◆ Current state

hardhat is the infrastructure layer under tidymodels, defining the preprocessing and extraction contracts other packages implement. Its releases read as a list of new generics and vector classes: extract_postprocessor(), extract_fit_time(), extract_tailor(), and a quantile_pred() class for quantile-regression output. The newest release is narrow warning and missing-value handling in mold().

◆ Where it's heading

Each addition here lands ahead of a user-facing feature elsewhere in tidymodels — the postprocessor and tailor generics precede the postprocessing workflow, quantile_pred() precedes quantile prediction in parsnip. The package's own surface stays deliberately small and its cadence follows what the rest of the stack is about to need.

◆ Prediction

Expect further extraction generics and prediction-type classes as tidymodels builds out postprocessing, with hardhat's own API remaining thin.

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.

Alternatives to hardhat and mlr3filters

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 hardhat or mlr3filters.

See all hardhat alternatives → · See all mlr3filters alternatives →

Recent activity from hardhat and mlr3filters

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

  1. 3mo agomlr3filtersFilter dictionary listing now uses prototypes
  2. 4mo agohardhatmold() warning and quantile missing-value fixes
  3. 11mo agomlr3filtersBoruta handles logical, factor and ordered features
  4. 11mo agohardhatextract_tailor() generic added
  5. 1y agohardhatquantile_pred() class for quantile regression output
  6. 2y agohardhatextract_postprocessor() and extract_fit_time() generics
  7. 2y agomlr3filtersBoruta and univariate Cox filters added
  8. 2y agohardhatDocumentation topic renamed at CRAN's request
  9. 3y agohardhatMulti-outcome prediction helpers and one-hot factor encoding
  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 hardhat and mlr3filters?

Both compete on the same themes — r-stats, machine-learning — within Analytics. hardhat and mlr3filters 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 hardhat better than mlr3filters?

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

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

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.