tidytext
Finished, widely taught, and shipping roxygen fixes.
A side-by-side editorial comparison of mlr3fselect and patchwork — release velocity, themes, recent moves, and the top alternatives to consider.
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.
patchwork stopped being a ggplot composer and became a page composer.
patchwork assembles plots into compositions with arithmetic operators, and the 1.x line has steadily hardened that grammar: guide and axis collection, free() to exempt a plot from alignment, inset_element() for overlays, and list-like behaviour so lapply() and length() work on a patchwork. Version 1.3.0 added native gt table support. The two releases since are a load-time warning fix and a compatibility pass for the next ggplot2 release.
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.
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.
Expect the ensemble result API to keep gaining analysis helpers, with async execution treated as the default rather than an option.
patchwork assembles plots into compositions with arithmetic operators, and the 1.x line has steadily hardened that grammar: guide and axis collection, free() to exempt a plot from alignment, inset_element() for overlays, and list-like behaviour so lapply() and length() work on a patchwork. Version 1.3.0 added native gt table support. The two releases since are a load-time warning fix and a compatibility pass for the next ggplot2 release.
The centre of gravity is shifting from alignment mechanics to composition scope. Early releases were almost entirely bug fixes against grid and ggplot2 internals — strip placement, fixed aspect ratios, guide merging. Recent ones add object types and escape hatches instead. Between feature cycles the package is in maintenance defined by ggplot2's release calendar, which is what 1.3.1 is in its entirety.
Expect wrap_table() to grow beyond gt to other table objects, and expect the next substantive release to be triggered by a ggplot2 internals change rather than by a patchwork roadmap.
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 patchwork.
Finished, widely taught, and shipping roxygen fixes.
Text features finally stay sparse all the way to the model.
The package that made calibration a step instead of an afterthought.
workflowsets keeps widening what counts as a model worth comparing.
The tidymodels pipeline grew a third stage, and it happens after the model runs.
Posit's MLOps package went quiet for two years, then came back to keep up with recipes.
See all mlr3fselect alternatives → · See all patchwork alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. mlr3fselect and patchwork 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. mlr3fselect and patchwork 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.
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.
Top patchwork alternatives in Analytics are ranked by recent ship velocity. Browse the "patchwork alternatives" section above for the current picks, or visit /alternatives/patchwork for the full list with editorial commentary on each.