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cubist vs discretefdr

A side-by-side editorial comparison of cubist and discretefdr — release velocity, themes, recent moves, and the top alternatives to consider.

Shared themes:r-package

cubist vs discretefdr: at a glance

Featurecubistdiscretefdr
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesmachine-learning, rule-based-models, tidymodels, reproducibilitymultiple-testing, false-discovery-rate, discrete-statistics, r-package
Last editorial update1h ago3h ago
WebsiteVisit →Visit →

What is cubist?

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.

Read the full cubist trajectory →

What is discretefdr?

The discrete-data FDR package is being pared into one piece of a larger multiple-testing suite.

DiscreteFDR implements false discovery rate procedures adapted for discrete test statistics, where the standard continuous-case corrections are conservative. It now covers a discrete Benjamini-Yekutieli procedure alongside the Benjamini-Hochberg variants it started with, including adaptive versions. Its datasets and test-result classes have been moved out into companion packages, so it increasingly does one job and defers the rest.

Read the full discretefdr trajectory →

cubist vs discretefdr: editorial side-by-side

C
cubist
ANALYTICS
0.0

The R port of Quinlan's Cubist gets reproducibility fixes, not new modelling

◆ Current state

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.

◆ Where it's heading

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.

◆ Prediction

Expect continued small maintenance releases tracking CRAN compiler requirements and the needs of the rules package, with no change to the modelling algorithm itself.

D
discretefdr
ANALYTICS
0.0

The discrete-data FDR package is being pared into one piece of a larger multiple-testing suite.

◆ Current state

DiscreteFDR implements false discovery rate procedures adapted for discrete test statistics, where the standard continuous-case corrections are conservative. It now covers a discrete Benjamini-Yekutieli procedure alongside the Benjamini-Hochberg variants it started with, including adaptive versions. Its datasets and test-result classes have been moved out into companion packages, so it increasingly does one job and defers the rest.

◆ Where it's heading

The direction is decomposition into a suite. The amnesia dataset went to DiscreteDatasets, summary output now interoperates with the DiscreteTestResults class from DiscreteTests, and match.pvals() stopped being exported — each release trims something that belongs elsewhere. What remains gets methodological additions at a slow, deliberate cadence, with performance work on the step-up procedures that dominate cost when the number of tests is large. Recent activity is maintenance: replacing deprecated calls the package still made of its own siblings. This is a mature statistical package whose release notes are short because the methods underneath them are settled.

◆ Prediction

Expect further alignment with the companion packages rather than new procedures, since the last substantive release was already about interoperating with DiscreteTests classes and the most recent one about clearing deprecations.

Alternatives to cubist and discretefdr

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 discretefdr.

See all cubist alternatives → · See all discretefdr alternatives →

Recent activity from cubist and discretefdr

Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.

  1. 3mo agodiscretefdrDeprecated internal calls replaced
  2. 5mo agocubiststrip_time_stamps makes fitted models reproducible
  3. 9mo agocubistCubist 0.5.1
  4. 1y agocubistCubist 0.5.0
  5. 1y agodiscretefdrDiscrete Benjamini-Yekutieli procedure added
  6. 1y agodiscretefdrDatasets split out and step-up procedures sped up
  7. 2y agocubistCubist 0.4.4
  8. 4y agocubistCubist 0.4.0

Frequently asked questions

What is the difference between cubist and discretefdr?

Both compete on the same themes — r-package — within Analytics. cubist and discretefdr 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 cubist better than discretefdr?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. cubist and discretefdr 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.

What are the best alternatives to cubist?

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.

What are the best alternatives to discretefdr?

Top discretefdr alternatives in Analytics are ranked by recent ship velocity. Browse the "discretefdr alternatives" section above for the current picks, or visit /alternatives/discretefdr for the full list with editorial commentary on each.