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Comparison · Analytics
mlr3fselect vs textrecipes
A side-by-side editorial comparison of mlr3fselect and textrecipes — release velocity, themes, recent moves, and the top alternatives to consider.
mlr3fselect vs textrecipes: at a glance
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.
What is textrecipes?
Text features finally stay sparse all the way to the model.
textrecipes supplies the recipes steps for turning text into model-ready columns: tokenizing, hashing, term frequency, TF-IDF, and word embeddings. Version 1.1.0 added a sparse argument to step_dummy_hash(), step_texthash(), step_tf() and step_tfidf() so they emit sparse vectors. The releases before it are a long consistency pass — keep_original_cols on every step that creates columns, informative errors on name collisions, tunable arguments documented, integer rather than double output where integers are what is meant.
mlr3fselect vs textrecipes: editorial side-by-side
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.
textrecipes
0.0ANALYTICS
Text features finally stay sparse all the way to the model.
◆ Current state
textrecipes supplies the recipes steps for turning text into model-ready columns: tokenizing, hashing, term frequency, TF-IDF, and word embeddings. Version 1.1.0 added a sparse argument to step_dummy_hash(), step_texthash(), step_tf() and step_tfidf() so they emit sparse vectors. The releases before it are a long consistency pass — keep_original_cols on every step that creates columns, informative errors on name collisions, tunable arguments documented, integer rather than double output where integers are what is meant.
◆ Where it's heading
Two forces drive this package. One is memory: text produces wide, mostly-zero matrices, and the sparse work is the direct answer, landing in the same period that workflows learned to fit and predict on dgCMatrix input. The other is upstream churn — the tweets tokenizer was deprecated because tokenizers deprecated it, the politeness feature disappeared when textfeatures left Suggests. The package's own agenda is consistency; its release timing belongs to its dependencies.
◆ Prediction
Expect the sparse argument to spread to the remaining column-producing steps, since only four of them have it, and expect more steps to be reworked as recipes' own sparse-data support matures.
Alternatives to mlr3fselect and textrecipes
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 mlr3fselect or textrecipes.
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.
patchwork
patchwork stopped being a ggplot composer and became a page composer.
See all mlr3fselect alternatives → · See all textrecipes alternatives →
Recent activity from mlr3fselect and textrecipes
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 2mo agomlr3fselectEmpty-selection rows removable from ensemble results
- 8mo agomlr3fselectFaster objective evaluation and always_included roles
- 1y agomlr3fselectAsynchronous feature selection arrives with FSelectorAsync ⚡
- 1y agotextrecipesHashing and TF-IDF steps can emit sparse vectors ⚡
- 1y agotextrecipesstep_textfeatures() sped up; clean_levels NA bug fixed
- 1y agomlr3fselectEmbedded ensemble selection and result combination
- 1y agomlr3fselectInternal tuning callback added
- 1y agomlr3fselectmlr3 0.21.0 compatibility and archive slimming
- 2y agotextrecipestextfeatures dependency dropped; politeness feature removed
- 2y agotextrecipesuntokenize and normalization return factors
- 2y agotextrecipeskeep_original_cols everywhere; hashing column order fixed
- 3y agotextrecipesTunable arguments documented; name collisions now error
Frequently asked questions
What is the difference between mlr3fselect and textrecipes?
They serve adjacent needs but don't currently overlap on shipped themes. mlr3fselect and textrecipes 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 mlr3fselect better than textrecipes?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. mlr3fselect and textrecipes 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 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.
What are the best alternatives to textrecipes?
Top textrecipes alternatives in Analytics are ranked by recent ship velocity. Browse the "textrecipes alternatives" section above for the current picks, or visit /alternatives/textrecipes for the full list with editorial commentary on each.