billboarder
An htmlwidget whose release notes are mostly billboard.js version bumps, quiet since 2021.
A side-by-side editorial comparison of embed and yardstick — release velocity, themes, recent moves, and the top alternatives to consider.
embed keeps adding encoding steps while shedding its deep-learning dependencies
embed supplies recipes steps that turn categorical predictors into numeric representations — likelihood encoding, UMAP projection, string-distance collapsing. The 1.1.x line made UMAP arguments tunable and moved keras and tensorflow out of hard dependencies; 1.2.0 added analytical likelihood encoding with partial pooling and retired step_feature_hash() in favor of textrecipes.
yardstick made fairness metrics a first-class part of tidymodels evaluation
yardstick supplies the metrics tidymodels evaluates models with. Its recent history is metric expansion into areas the package did not originally cover - survival analysis, model fairness, and in 1.4.0 a batch of regression and classification metrics filling remaining gaps - alongside a long deprecation cycle that finally turned errors on in 1.4.0.
embed supplies recipes steps that turn categorical predictors into numeric representations — likelihood encoding, UMAP projection, string-distance collapsing. The 1.1.x line made UMAP arguments tunable and moved keras and tensorflow out of hard dependencies; 1.2.0 added analytical likelihood encoding with partial pooling and retired step_feature_hash() in favor of textrecipes.
Two quiet directions run through these releases. One is making the steps tunable rather than fixed, so they participate properly in tidymodels grids. The other is boundary maintenance: heavy dependencies pushed to Suggests, overlapping steps handed to the package that owns them. Recent releases are thin and fix-driven.
Expect further consolidation with textrecipes over which package owns which encoding step, and continued upkeep against xgboost and uwot releases rather than new step families.
yardstick supplies the metrics tidymodels evaluates models with. Its recent history is metric expansion into areas the package did not originally cover - survival analysis, model fairness, and in 1.4.0 a batch of regression and classification metrics filling remaining gaps - alongside a long deprecation cycle that finally turned errors on in 1.4.0.
The direction is coverage plus extensibility. Rather than adding fairness metrics one at a time, 1.3.0 shipped new_groupwise_metric() so group-aware metrics can be defined for the problem at hand, which is the more durable contribution. The parallel thread is removing hidden state: the event_first global option, deprecated in 0.0.7, took until 1.4.0 to become an error.
Expect the groupwise constructor to attract more fairness definitions than the three shipped, and the developer-facing metric creation helpers deprecated in 1.2.0 to be removed next; core metric coverage now looks close to complete.
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 embed or yardstick.
An htmlwidget whose release notes are mostly billboard.js version bumps, quiet since 2021.
bbotk is generalizing from an optimizer toolkit into an evaluation framework.
bayesplot keeps widening its posterior-check catalogue while absorbing each ggplot2 break.
Contribution-driven maintenance on a package whose last structural change was magick support.
pins keeps adding a storage backend per release while retiring its original API
tsibble shipped one release in five and a half years - the data structure is finished
See all embed alternatives → · See all yardstick alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — tidymodels — within Analytics. embed and yardstick 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. embed and yardstick 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 embed alternatives in Analytics are ranked by recent ship velocity. Browse the "embed alternatives" section above for the current picks, or visit /alternatives/embed for the full list with editorial commentary on each.
Top yardstick alternatives in Analytics are ranked by recent ship velocity. Browse the "yardstick alternatives" section above for the current picks, or visit /alternatives/yardstick for the full list with editorial commentary on each.