mlr3proba
mlr3proba is shedding weight as its survival work moves into sibling packages
Comparison · Analytics
textrecipes vs tidyclust
A side-by-side editorial comparison of textrecipes and tidyclust — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:tidymodels
textrecipes vs tidyclust: at a glance
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.
What is tidyclust?
tidyclust just tripled the model types it can fit, and handed finalization back to tune
tidyclust brings clustering into the tidymodels interface, and 0.3.0 was the release where its model coverage stopped being k-means and hierarchical clustering. DBSCAN and HDBSCAN, Gaussian mixtures, and mean shift all arrived at once as proper clustering specifications. The two releases since have been bug fixes on the metric and sparse-data paths, which is the usual pattern after a large surface addition.
textrecipes vs tidyclust: editorial side-by-side
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.
tidyclust
0.0ANALYTICS
tidyclust just tripled the model types it can fit, and handed finalization back to tune
◆ Current state
tidyclust brings clustering into the tidymodels interface, and 0.3.0 was the release where its model coverage stopped being k-means and hierarchical clustering. DBSCAN and HDBSCAN, Gaussian mixtures, and mean shift all arrived at once as proper clustering specifications. The two releases since have been bug fixes on the metric and sparse-data paths, which is the usual pattern after a large surface addition.
◆ Where it's heading
The package is converging with the rest of tidymodels rather than maintaining a parallel API: finalize_model_tidyclust() and finalize_workflow_tidyclust() are deprecated because tune::finalize_model() and tune::finalize_workflow() now handle cluster_spec objects natively. That removes the last place where clustering needed its own version of a shared verb. With density-based and model-based clustering now present, the interface has to cover model families with genuinely different assumptions than the centroid methods it started with.
◆ Prediction
The recent fixes to cluster_metric_set() labeling and custom-metric authoring suggest evaluation is the current focus, so metrics suited to density-based clusters are the likely next addition.
Alternatives to textrecipes and tidyclust
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 textrecipes or tidyclust.
mlr3viz
mlr3viz keeps the ecosystem's plots working while the plots themselves move out
mlr3tuning
mlr3tuning is rebuilding its async machinery under a stable public surface
timetk
timetk swallowed anomalize whole, then went quiet for two years
modelbased
modelbased is turning marginal effects into a full contrast grammar
parameters
easystats' parameters package absorbs one more model class every few weeks
See all textrecipes alternatives → · See all tidyclust alternatives →
Recent activity from textrecipes and tidyclust
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 1mo agotidyclusttidyclust 0.3.2 fixes k_means() on sparse predictors
- 1mo agotidyclusttidyclust 0.3.1 stops same-named metrics silently merging
- 2mo agotidyclusttidyclust 0.3.0 adds DBSCAN, Gaussian mixture, and mean shift models ⚡
- 1y agotextrecipesHashing and TF-IDF steps can emit sparse vectors ⚡
- 1y agotidyclusttidyclust 0.2.4 switches distance calculations to philentropy
- 1y agotextrecipesstep_textfeatures() sped up; clean_levels NA bug fixed
- 2y agotidyclusttidyclust 0.2.3 resolves a clustMixType reverse-dependency issue
- 2y agotidyclusttidyclust 0.2.2 resolves a ClusterR reverse-dependency issue
- 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 textrecipes and tidyclust?
Both compete on the same themes — tidymodels — within Analytics. textrecipes and tidyclust 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 textrecipes better than tidyclust?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. textrecipes and tidyclust 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 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.
What are the best alternatives to tidyclust?
Top tidyclust alternatives in Analytics are ranked by recent ship velocity. Browse the "tidyclust alternatives" section above for the current picks, or visit /alternatives/tidyclust for the full list with editorial commentary on each.