rsample
tidymodels' resampling package is retiring its old splitters for sliding windows.
Comparison · ai-assistants
mlr3 vs recipes
A side-by-side editorial comparison of mlr3 and recipes — release velocity, themes, recent moves, and the top alternatives to consider.
mlr3 vs recipes: at a glance
What is mlr3?
mlr3 is hardening the seams where its abstractions meet real learners
Releases arrive every few weeks and read as a systematic audit of the Learner interface. Recent versions added a native_model binding and a predict_raw flag so users can reach the underlying package's model and raw prediction, gave encapsulated learners a wall-clock deadline alongside the existing timeout, and removed the deprecated Task$divide(). A run of fixes addresses correctness at the boundary - factor level ordering that inverted binary probabilities, fallback learners losing state, misaligned probability columns.
What is recipes?
tidymodels' preprocessing engine learned sparsity, then settled into deprecations.
recipes is at 1.3.3, whose entire changelog is one suggested-package declaration. The substantive release in the window is 1.2.0, which taught recipe, prep and bake to work with sparse tibbles and sparse matrices, added a sparse argument to eight dummy and indicator steps, and made seventeen more steps preserve sparsity they receive. Since then the work has been deprecations and bug fixes.
mlr3 vs recipes: editorial side-by-side
mlr3
0.0AI-ASSISTANTS
mlr3 is hardening the seams where its abstractions meet real learners
◆ Current state
Releases arrive every few weeks and read as a systematic audit of the Learner interface. Recent versions added a native_model binding and a predict_raw flag so users can reach the underlying package's model and raw prediction, gave encapsulated learners a wall-clock deadline alongside the existing timeout, and removed the deprecated Task$divide(). A run of fixes addresses correctness at the boundary - factor level ordering that inverted binary probabilities, fallback learners losing state, misaligned probability columns.
◆ Where it's heading
The framework is maturing from wrapping models to being accountable for what happens when wrapping goes wrong. Structured Mlr3Error and Mlr3Warning classes, conditions stored on the learner log, and messages replaced by conditions all point at making failures programmatically inspectable rather than printed. In parallel, escape hatches to the upstream model are being formalised instead of left to users digging into internals.
◆ Prediction
Expect the remaining deprecated surface to follow Task$divide() out, and further work on encapsulation and fallback behaviour, which is where most recent fixes have clustered. The raw and native_model accessors suggest more of the upstream model will be surfaced deliberately.
recipes
0.0AI-ASSISTANTS
tidymodels' preprocessing engine learned sparsity, then settled into deprecations.
◆ Current state
recipes is at 1.3.3, whose entire changelog is one suggested-package declaration. The substantive release in the window is 1.2.0, which taught recipe, prep and bake to work with sparse tibbles and sparse matrices, added a sparse argument to eight dummy and indicator steps, and made seventeen more steps preserve sparsity they receive. Since then the work has been deprecations and bug fixes.
◆ Where it's heading
The direction is consolidation of a large step catalogue rather than growth. step_select and step_nnmf have entered deprecation, arguments across nine steps moved from strings and vars() calls to bare names, and all steps now require the same four arguments. The sparse work stands as the last structural change; what follows tidies the surface around it.
◆ Prediction
With step_select mid-deprecation and step_nnmf newly deprecated in favour of step_nnmf_sparse, the next release most likely advances those deprecations rather than adding steps.
Alternatives to mlr3 and recipes
Other ai-assistants 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 mlr3 or recipes.
imbalanced-learn
The resampling companion to scikit-learn now ships mostly to stay compatible with it.
parsnip
parsnip added a whole new regression type, then wired R models to JAX and PyTorch
Mem0
Mem0 splits agent memory from user memory, then spends a week hardening the plumbing
Pictory
Every post is a comparison page, and Pictory is always the answer.
DocsBot AI
DocsBot now lets an AI agent administer DocsBot, not just answer with it
See all mlr3 alternatives → · See all recipes alternatives →
Recent activity from mlr3 and recipes
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 2mo agomlr3Fallback learner state and probability alignment fixes
- 2mo agomlr3Encapsulated learners gain a deadline; Task$divide() removed
- 2mo agorecipesDeclares mixOmics as a suggested package
- 4mo agorecipesstep_nnmf() deprecated in favour of step_nnmf_sparse()
- 4mo agomlr3Raw upstream predictions preserved; binary probability fix
- 5mo agomlr3Log messages replaced with conditions
- 5mo agomlr3native_model accessor and structured warning/error logs
- 8mo agomlr3Mlr3Error and Mlr3Warning classes introduced
- 1y agorecipesFixes tune_args() with tuned parsnip arguments
- 1y agorecipesBare-name arguments across nine steps; step_select() deprecated
- 1y agorecipesFixes sparsity steps applied to derived variables
- 1y agorecipesSparse tibbles and sparse matrices supported end to end ⚡
Frequently asked questions
What is the difference between mlr3 and recipes?
They serve adjacent needs but don't currently overlap on shipped themes. mlr3 and recipes 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 mlr3 better than recipes?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. mlr3 and recipes 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 ai-assistants products to evaluate alongside.
What are the best alternatives to mlr3?
Top mlr3 alternatives in ai-assistants are ranked by recent ship velocity. Browse the "mlr3 alternatives" section above for the current picks, or visit /alternatives/mlr3 for the full list with editorial commentary on each.
What are the best alternatives to recipes?
Top recipes alternatives in ai-assistants are ranked by recent ship velocity. Browse the "recipes alternatives" section above for the current picks, or visit /alternatives/recipes for the full list with editorial commentary on each.