churon
churon is spending its entire release history getting a Rust ONNX binding through CRAN.
A side-by-side editorial comparison of cubist and rfm — release velocity, themes, recent moves, and the top alternatives to consider.
The R port of Quinlan's Cubist gets reproducibility fixes, not new modelling
Cubist is the R interface to Quinlan's rule-based regression model, wrapping the original C sources behind an R API and feeding the tidymodels rules package. The 0.6.0 release adds a strip_time_stamps control that removes date, time and duration information from model output, and now errors rather than silently misbehaving when a date or date-time column is passed. Error reporting moves from base stop() and warning() to cli.
A customer segmentation package that went quiet for six years and returned with dependency hygiene
rfm computes recency, frequency and monetary segmentation for customer analytics in R. The feature surface was set early: 0.1.0 shipped a Shiny app and customer-level input, 0.2.0 added default segments and median statistics, 0.2.1 added user-specified score thresholds and returnable plot objects. Then nothing for nearly six years. Version 0.4.0 in April 2026 fixes a missing-column error and a customer id fault, and moves plotly and gganimate from Suggests to Imports.
Cubist is the R interface to Quinlan's rule-based regression model, wrapping the original C sources behind an R API and feeding the tidymodels rules package. The 0.6.0 release adds a strip_time_stamps control that removes date, time and duration information from model output, and now errors rather than silently misbehaving when a date or date-time column is passed. Error reporting moves from base stop() and warning() to cli.
The direction is custodial: this is a mature algorithm with a stable definition, so the work is making a decades-old C codebase behave predictably inside a modern R workflow. The reproducibility thread is the clearest one — embedded timestamps mean two identical models compare as different objects, which breaks caching, testing and any workflow that hashes results. Alongside it runs slow C hygiene, from keyword symbol overwrites in 0.5.0 to unused-variable warnings in 0.6.0.
Expect continued small maintenance releases tracking CRAN compiler requirements and the needs of the rules package, with no change to the modelling algorithm itself.
rfm computes recency, frequency and monetary segmentation for customer analytics in R. The feature surface was set early: 0.1.0 shipped a Shiny app and customer-level input, 0.2.0 added default segments and median statistics, 0.2.1 added user-specified score thresholds and returnable plot objects. Then nothing for nearly six years. Version 0.4.0 in April 2026 fixes a missing-column error and a customer id fault, and moves plotly and gganimate from Suggests to Imports.
The 0.4.0 release says more about maintenance posture than about product direction — the version jump past 0.3.x with only two bug fixes and a dependency reshuffle suggests a package being brought back to a releasable state rather than resuming development. Promoting plotly and gganimate to Imports makes the visualization stack mandatory, which is a heavier install in exchange for a simpler code path. The core RFM computation itself has not changed in this window.
The entries show a package returning from dormancy rather than pursuing a roadmap, so further small fixes are more likely than new segmentation capability.
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 cubist or rfm.
churon is spending its entire release history getting a Rust ONNX binding through CRAN.
firatheme woke up after four years and started fixing what ggplot2 changed underneath it.
bagyo reached CRAN as a Philippine tropical cyclone dataset, with its tags stamped out of order.
rainette rebuilt its Reinert clustering in 0.2.0, tuned it in 0.3.0, and has coasted since.
questionr's survey helpers are finished; recent releases only keep pace with R-devel.
washdata is a fixed survey dataset; eight years of releases have changed only its packaging.
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Analytics. cubist and rfm 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. cubist and rfm 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 cubist alternatives in Analytics are ranked by recent ship velocity. Browse the "cubist alternatives" section above for the current picks, or visit /alternatives/cubist for the full list with editorial commentary on each.
Top rfm alternatives in Analytics are ranked by recent ship velocity. Browse the "rfm alternatives" section above for the current picks, or visit /alternatives/rfm for the full list with editorial commentary on each.