mlr3mbo
mlr3mbo picked its defaults from a benchmark study, not from taste
A side-by-side editorial comparison of discrim and Fulcrum — release velocity, themes, recent moves, and the top alternatives to consider.
| Feature | discrim | Fulcrum |
|---|---|---|
| Sector | Analytics | Analytics |
| Velocity score | 0.0 | 6.3 |
| Sparks · 30d | 0 | 0 |
| Top themes | tidymodels, discriminant analysis, parsnip extension, classification | field-data-collection, esri-arcgis, offline-maps, on-device-inference |
| Last editorial update | 1h ago | 17h ago |
| Website | Visit → | — |
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.
Fulcrum's mobile train is all Esri migration cleanup, with on-device inference quietly changing format.
Fulcrum ships iOS, Android, and web releases on a near-weekly cadence, and this stretch is dominated by mapping work following the Google Maps retirement announced for September. Recent builds upgraded to ArcGIS SDK 300.0.0, moved the web map engine to current ArcGIS and deck.gl versions, and worked through the resulting stability issues — basemap loading, location resolution, black map screens, panning and zooming performance. The most consequential change is easy to miss: ONNX support for on-device machine learning inference was removed in favor of a new INFERENCE format that reads labels from an uploaded labels.txt.
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.
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.
Nothing in the entries points to new methods or engines; the next release is most likely another CRAN or prediction-path fix.
Fulcrum ships iOS, Android, and web releases on a near-weekly cadence, and this stretch is dominated by mapping work following the Google Maps retirement announced for September. Recent builds upgraded to ArcGIS SDK 300.0.0, moved the web map engine to current ArcGIS and deck.gl versions, and worked through the resulting stability issues — basemap loading, location resolution, black map screens, panning and zooming performance. The most consequential change is easy to miss: ONNX support for on-device machine learning inference was removed in favor of a new INFERENCE format that reads labels from an uploaded labels.txt.
This is a platform consolidation being paid down one point release at a time. Having committed to Esri, Fulcrum is absorbing the instability that came with it, and each release reads as fixes to symptoms of the same migration. Underneath, the offline and field-capture story continues to get real attention — downloaded offline map layers can now be updated in place, and Photo FastFill moved to background processing so it no longer blocks editing.
Expect the release notes to stay fix-dominated through the September Google Maps cutoff, with the migration-related map defects tapering after it passes. Photo FastFill leaving early access is the most likely next substantive item.
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 Fulcrum.
mlr3mbo picked its defaults from a benchmark study, not from taste
loo keeps rewriting the diagnostics Bayesian modellers read off model comparison
mlr3fselect turned feature selection into an asynchronous, distributable job
lime survives on compatibility patches years after its research moment
mlr3measures is systematically retrofitting sample weights across every metric
mlr3cluster went from a handful of clusterers to covering the field
See all discrim alternatives → · See all Fulcrum alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. Fulcrum is currently shipping more aggressively (velocity 6.3 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.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. Fulcrum is currently shipping more aggressively (velocity 6.3 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.
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.
Top Fulcrum alternatives in Analytics are ranked by recent ship velocity. Browse the "Fulcrum alternatives" section above for the current picks, or visit /alternatives/fulcrum for the full list with editorial commentary on each.