imbalanced-learn
The resampling companion to scikit-learn now ships mostly to stay compatible with it.
A side-by-side editorial comparison of recipes and rsample — release velocity, themes, recent moves, and the top alternatives to consider.
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.
tidymodels' resampling package is retiring its old splitters for sliding windows.
rsample is at 1.3.2, a small release covering spatialsample interoperability and a soft deprecation of the lag argument on initial_time_split(). The more consequential work sits behind it: 1.3.1 added internal_calibration_split() and a calibration() accessor so tune can fit a preprocessor and a post-processor on separate parts of the analysis set, and 1.3.0 superseded rolling_origin() with the sliding_* family.
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.
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.
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.
rsample is at 1.3.2, a small release covering spatialsample interoperability and a soft deprecation of the lag argument on initial_time_split(). The more consequential work sits behind it: 1.3.1 added internal_calibration_split() and a calibration() accessor so tune can fit a preprocessor and a post-processor on separate parts of the analysis set, and 1.3.0 superseded rolling_origin() with the sliding_* family.
Two threads run through the window. Time-based resampling is migrating from rolling_origin() to sliding_window(), sliding_index() and sliding_period(), while validation_split() and its relatives have moved from soft deprecation to warning in favour of the three-way initial_validation_split(). Alongside that, rsample is growing infrastructure other tidymodels packages consume rather than user-facing splitters.
Given that validation_split() and friends now warn and initial_time_split()'s lag argument is soft-deprecated, the next release most likely escalates those deprecations rather than adding a resampling scheme.
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 recipes or rsample.
The resampling companion to scikit-learn now ships mostly to stay compatible with it.
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See all recipes alternatives → · See all rsample alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — tidymodels, deprecations, r-language — within ai-assistants. recipes and rsample 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.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. recipes and rsample 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.
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.
Top rsample alternatives in ai-assistants are ranked by recent ship velocity. Browse the "rsample alternatives" section above for the current picks, or visit /alternatives/rsample for the full list with editorial commentary on each.