mlr3proba
mlr3proba is shedding weight as its survival work moves into sibling packages
Comparison · Analytics
textrecipes vs tidypredict
A side-by-side editorial comparison of textrecipes and tidypredict — release velocity, themes, recent moves, and the top alternatives to consider.
textrecipes vs tidypredict: 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 tidypredict?
tidypredict now translates the gradient-boosting libraries people actually deploy
tidypredict converts fitted R models into SQL and dplyr expressions so predictions can run inside a database instead of in R. The 1.1.0 release added rpart, CatBoost, and LightGBM, with full objective and tree-type coverage for the boosted models. That followed 1.0.0, which broke random-forest output into a single formula, added glmnet, and cut fit-translation time for xgboost, partykit, and ranger.
textrecipes vs tidypredict: 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.
tidypredict
0.0ANALYTICS
tidypredict now translates the gradient-boosting libraries people actually deploy
◆ Current state
tidypredict converts fitted R models into SQL and dplyr expressions so predictions can run inside a database instead of in R. The 1.1.0 release added rpart, CatBoost, and LightGBM, with full objective and tree-type coverage for the boosted models. That followed 1.0.0, which broke random-forest output into a single formula, added glmnet, and cut fit-translation time for xgboost, partykit, and ranger.
◆ Where it's heading
The package's value scales directly with how many model types it can translate, and the recent work has concentrated on the tree ensembles that dominate tabular modelling in practice. Coverage now extends past what parsnip wraps, since raw CatBoost models are supported alongside parsnip and bonsai ones with an explicit escape hatch for categorical features. Performance work on the translation step suggests the models being converted have grown large enough for that to matter.
◆ Prediction
With the major boosting libraries covered, the remaining gap is what happens to preprocessing, so tighter integration with recipes or orbital for translating whole workflows is the natural next step.
Alternatives to textrecipes and tidypredict
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 tidypredict.
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 tidypredict alternatives →
Recent activity from textrecipes and tidypredict
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 5mo agotidypredicttidypredict 1.1.0 adds CatBoost, LightGBM, and rpart support ⚡
- 8mo agotidypredicttidypredict 1.0.1 fixes base_score extraction for xgboost 3
- 8mo agotidypredicttidypredict 1.0.0 unifies random forest output and adds glmnet
- 1y agotextrecipesHashing and TF-IDF steps can emit sparse vectors ⚡
- 1y agotextrecipesstep_textfeatures() sped up; clean_levels NA bug fixed
- 1y agotidypredicttidypredict 0.5.1 exports internals for the orbital package
- 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
- 3y agotidypredicttidypredict 0.5 hands maintenance to a new maintainer
- 4y agotidypredicttidypredict 0.4.9 relicenses to MIT and fixes SQL generation
Frequently asked questions
What is the difference between textrecipes and tidypredict?
They serve adjacent needs but don't currently overlap on shipped themes. textrecipes and tidypredict 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 tidypredict?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. textrecipes and tidypredict 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 tidypredict?
Top tidypredict alternatives in Analytics are ranked by recent ship velocity. Browse the "tidypredict alternatives" section above for the current picks, or visit /alternatives/tidypredict for the full list with editorial commentary on each.