tidytext
Finished, widely taught, and shipping roxygen fixes.
A side-by-side editorial comparison of mlr3cluster and patchwork — release velocity, themes, recent moves, and the top alternatives to consider.
mlr3cluster went from a handful of clusterers to covering the field
mlr3cluster supplies clustering learners to the mlr3 framework. Over three releases it added roughly a dozen learners — CLARA, k-prototypes, spectral, then a batch of nine covering finite mixtures, spherical and directional families, self-organising maps, spatio-temporal DBSCAN and robust trimmed clustering. The newest release fixes predict-time behaviour across the hierarchical learners.
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.
mlr3cluster supplies clustering learners to the mlr3 framework. Over three releases it added roughly a dozen learners — CLARA, k-prototypes, spectral, then a batch of nine covering finite mixtures, spherical and directional families, self-organising maps, spatio-temporal DBSCAN and robust trimmed clustering. The newest release fixes predict-time behaviour across the hierarchical learners.
The package is at the tail end of a coverage push, and the emphasis has shifted from adding algorithms to making the ones it has behave correctly at prediction time — cutting trees at the current k, reclustering coresets, failing informatively on unsupported metric combinations. That is the normal sequence after a rapid expansion.
Expect further predict-path corrections and parameter-set alignment across the newly added learners before any more algorithms arrive.
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 mlr3cluster 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 mlr3cluster 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. mlr3cluster 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. mlr3cluster 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 mlr3cluster alternatives in Analytics are ranked by recent ship velocity. Browse the "mlr3cluster alternatives" section above for the current picks, or visit /alternatives/mlr3cluster 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.