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discrim vs mlr3mbo

A side-by-side editorial comparison of discrim and mlr3mbo — release velocity, themes, recent moves, and the top alternatives to consider.

discrim vs mlr3mbo: at a glance

Featurediscrimmlr3mbo
SectorAnalyticsAnalytics
Velocity score0.02.5
Sparks · 30d00
Top themestidymodels, discriminant analysis, parsnip extension, classificationbayesian-optimization, mlr3, hyperparameter-tuning, r-stats
Last editorial update2h ago1h ago
WebsiteVisit →Visit →

What is discrim?

discrim settled into a thin engine shim after handing its model definitions to parsnip.

discrim is the parsnip extension for discriminant analysis, exposing linear, quadratic, flexible and regularized variants through the tidymodels interface. Its model definition functions moved into parsnip itself in 0.2.0, leaving this package as the engine and prediction layer. The two most recent releases are a documentation fix and a single prediction bug.

Read the full discrim trajectory →

What is mlr3mbo?

mlr3mbo picked its defaults from a benchmark study, not from taste

mlr3mbo does model-based and Bayesian optimisation for mlr3. Its 1.0.0 release added a dictionary of pre-built acquisition-function optimisers and, more consequentially, replaced the default surrogate, acquisition function and optimiser settings with values derived from a large-scale benchmark study. The releases since are corrections to the acquisition-optimiser path exposed by that new default configuration.

Read the full mlr3mbo trajectory →

discrim vs mlr3mbo: editorial side-by-side

D
discrim
ANALYTICS
0.0

discrim settled into a thin engine shim after handing its model definitions to parsnip.

◆ Current state

discrim is the parsnip extension for discriminant analysis, exposing linear, quadratic, flexible and regularized variants through the tidymodels interface. Its model definition functions moved into parsnip itself in 0.2.0, leaving this package as the engine and prediction layer. The two most recent releases are a documentation fix and a single prediction bug.

◆ Where it's heading

The package built out method coverage early, adding quadratic discriminant analysis in 0.1.2, the sda and sparsediscrim engines in 0.1.3 and case weights in 1.0.0, then stopped growing. Handing definitions upstream to parsnip in 0.2.0 confirmed the shape: discrim is where engines are wired, not where the API lives. Cadence since 2022 is roughly one small fix a year.

◆ Prediction

Nothing in the entries points to new methods or engines; the next release is most likely another CRAN or prediction-path fix.

M
mlr3mbo
ANALYTICS
2.5

mlr3mbo picked its defaults from a benchmark study, not from taste

◆ Current state

mlr3mbo does model-based and Bayesian optimisation for mlr3. Its 1.0.0 release added a dictionary of pre-built acquisition-function optimisers and, more consequentially, replaced the default surrogate, acquisition function and optimiser settings with values derived from a large-scale benchmark study. The releases since are corrections to the acquisition-optimiser path exposed by that new default configuration.

◆ Where it's heading

The package has moved from a toolkit that expected users to assemble a Bayesian optimisation loop into one with a defensible default loop, and the recent fixes — warm-start sizing on multi-objective archives, silently discarded terminators, stale x_domain values — are the consequences of more people running the default path.

◆ Prediction

Expect continued hardening of the acquisition-optimiser classes rather than new acquisition functions.

Alternatives to discrim and mlr3mbo

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 discrim or mlr3mbo.

See all discrim alternatives → · See all mlr3mbo alternatives →

Recent activity from discrim and mlr3mbo

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

  1. 23d agomlr3mboAcquisition optimiser fixes for warm starts and archives
  2. 3mo agomlr3mboDictionary lookup and restart-limit fixes
  3. 4mo agomlr3mborush 1.0.0 compatibility and Surrogate$check()
  4. 5mo agomlr3mbomlr3mbo 1.0.0 ships benchmark-derived default settings
  5. 8mo agodiscrimFix for FDA models failing at prediction time
  6. 10mo agomlr3mbomlr3learners 0.13.0 compatibility
  7. 11mo agodiscrimDocumentation links updated to stay on CRAN
  8. 11mo agomlr3mboMaintainer change and mlr3pipelines 0.9.0 upkeep
  9. 4y agodiscrimCase weights enabled for flexible and linear discriminant models
  10. 4y agodiscrimModel definitions moved upstream into parsnip
  11. 5y agodiscrimsda and sparsediscrim engines added for LDA and QDA
  12. 5y agodiscrimdiscrim_quad() added; package relicensed to MIT

Frequently asked questions

What is the difference between discrim and mlr3mbo?

They serve adjacent needs but don't currently overlap on shipped themes. mlr3mbo is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.

Is discrim better than mlr3mbo?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. mlr3mbo is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.

What are the best alternatives to discrim?

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

What are the best alternatives to mlr3mbo?

Top mlr3mbo alternatives in Analytics are ranked by recent ship velocity. Browse the "mlr3mbo alternatives" section above for the current picks, or visit /alternatives/mlr3mbo for the full list with editorial commentary on each.