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Finished, widely taught, and shipping roxygen fixes.
Comparison · Analytics
hardhat vs mlr3fselect
A side-by-side editorial comparison of hardhat and mlr3fselect — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-statsmachine-learning
hardhat vs mlr3fselect: at a glance
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().
What is mlr3fselect?
mlr3fselect turned feature selection into an asynchronous, distributable job
mlr3fselect runs feature selection for mlr3. The defining change in this window is 1.4.0, which introduced FSelectorAsync and the asynchronous instance classes, letting searches run without a synchronous batch loop. Around it sit ensemble feature selection work — fastVoteR ranking, embedded ensemble selection, result combination — and performance work on objective evaluation.
hardhat vs mlr3fselect: editorial side-by-side
hardhat
0.0ANALYTICS
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.
mlr3fselect
0.0ANALYTICS
mlr3fselect turned feature selection into an asynchronous, distributable job
◆ Current state
mlr3fselect runs feature selection for mlr3. The defining change in this window is 1.4.0, which introduced FSelectorAsync and the asynchronous instance classes, letting searches run without a synchronous batch loop. Around it sit ensemble feature selection work — fastVoteR ranking, embedded ensemble selection, result combination — and performance work on objective evaluation.
◆ Where it's heading
Two threads run in parallel: scaling the search itself through async execution and the rush backend, and making ensemble selection results easier to analyse via Pareto fronts, knee points and now removal of empty result rows. The rush backward-compatibility shim was dropped in 1.6.0, so the async path is now the assumed one.
◆ Prediction
Expect the ensemble result API to keep gaining analysis helpers, with async execution treated as the default rather than an option.
Alternatives to hardhat and mlr3fselect
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 mlr3fselect.
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 hardhat alternatives → · See all mlr3fselect alternatives →
Recent activity from hardhat and mlr3fselect
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 2mo agomlr3fselectEmpty-selection rows removable from ensemble results
- 4mo agohardhatmold() warning and quantile missing-value fixes
- 8mo agomlr3fselectFaster objective evaluation and always_included roles
- 11mo agohardhatextract_tailor() generic added
- 1y agomlr3fselectAsynchronous feature selection arrives with FSelectorAsync ⚡
- 1y agohardhatquantile_pred() class for quantile regression output
- 1y agomlr3fselectEmbedded ensemble selection and result combination
- 1y agomlr3fselectInternal tuning callback added
- 1y agomlr3fselectmlr3 0.21.0 compatibility and archive slimming
- 2y agohardhatextract_postprocessor() and extract_fit_time() generics
- 2y agohardhatDocumentation topic renamed at CRAN's request
- 3y agohardhatMulti-outcome prediction helpers and one-hot factor encoding
Frequently asked questions
What is the difference between hardhat and mlr3fselect?
Both compete on the same themes — r-stats, machine-learning — within Analytics. hardhat and mlr3fselect 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 mlr3fselect?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. hardhat and mlr3fselect 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 mlr3fselect?
Top mlr3fselect alternatives in Analytics are ranked by recent ship velocity. Browse the "mlr3fselect alternatives" section above for the current picks, or visit /alternatives/mlr3fselect for the full list with editorial commentary on each.