mlr3mbo
mlr3mbo picked its defaults from a benchmark study, not from taste
A side-by-side editorial comparison of desirability2 and Fulcrum — release velocity, themes, recent moves, and the top alternatives to consider.
| Feature | desirability2 | Fulcrum |
|---|---|---|
| Sector | Analytics | Analytics |
| Velocity score | 0.0 | 6.3 |
| Sparks · 30d | 0 | 0 |
| Top themes | tidymodels, multi-objective optimization, model selection, desirability functions | field-data-collection, esri-arcgis, offline-maps, on-device-inference |
| Last editorial update | 1h ago | 17h ago |
| Website | Visit → | — |
desirability2 is making multi-metric model selection a first-class tidymodels step.
desirability2 implements desirability functions, which map several metrics onto a common 0-1 scale so they can be combined into a single objective. The package is young: three releases, the first of which only added a NEWS file. Its substance arrived in 0.1.0 with hooks into tidymodels' tune package.
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.
desirability2 implements desirability functions, which map several metrics onto a common 0-1 scale so they can be combined into a single objective. The package is young: three releases, the first of which only added a NEWS file. Its substance arrived in 0.1.0 with hooks into tidymodels' tune package.
The direction is integration rather than standalone use. Version 0.1.0 added select_best_desirability() and show_best_desirability() to resolve a tuning run against several metrics at once; 0.2.0 exported make_desirability_cols() so other packages can build on it and made data-driven limits the default, removing the need to state ranges by hand. Both releases move work from the user into the package.
The exported helper and the developer-facing desirability() API point to adoption by other tidymodels packages as the next step rather than new functionality here.
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 desirability2 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 desirability2 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 desirability2 alternatives in Analytics are ranked by recent ship velocity. Browse the "desirability2 alternatives" section above for the current picks, or visit /alternatives/desirability2 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.