easystats
The easystats meta-package is install tooling wrapped around a relicensed ecosystem.
Comparison · Analytics
desirability2 vs themis
A side-by-side editorial comparison of desirability2 and themis — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:tidymodelsr
desirability2 vs themis: at a glance
What is desirability2?
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.
What is themis?
themis is back to adding real resampling algorithms after a documentation-heavy stretch.
themis supplies recipes steps for handling class imbalance in tidymodels. The 1.0.x line was consumed by documentation accuracy, message translation and internal consistency work. Version 1.1.0 returns to substance with two new under-sampling methods.
desirability2 vs themis: editorial side-by-side
desirability2
0.0ANALYTICS
desirability2 is making multi-metric model selection a first-class tidymodels step.
◆ Current state
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.
◆ Where it's heading
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.
◆ Prediction
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.
themis
2.5ANALYTICS
themis is back to adding real resampling algorithms after a documentation-heavy stretch.
◆ Current state
themis supplies recipes steps for handling class imbalance in tidymodels. The 1.0.x line was consumed by documentation accuracy, message translation and internal consistency work. Version 1.1.0 returns to substance with two new under-sampling methods.
◆ Where it's heading
The package grows by adding algorithms rather than restructuring itself. tomek() was rewritten to handle multiple classes and drop the unbalanced dependency, case weights arrived at 1.0.0, and cluster-centroid and condensed-nearest-neighbour under-sampling arrive now — each shipped as both a recipes step and a direct-implementation function.
◆ Prediction
Expect further under- and over-sampling methods in the same paired form, as the package fills out coverage of the standard class-imbalance literature.
Alternatives to desirability2 and themis
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 themis.
discrim
discrim settled into a thin engine shim after handing its model definitions to parsnip.
dbparser
dbparser shed its database and CSV writers to become just a DrugBank parser.
crosstalk
crosstalk is frozen infrastructure: four releases in five years, mostly CRAN upkeep.
cmdstanr
cmdstanr keeps adding fast approximations beside full HMC, and fighting Windows toolchains.
comtradr
comtradr's 1.0 line is a long tail of patches against a brittle UN trade API.
See all desirability2 alternatives → · See all themis alternatives →
Recent activity from desirability2 and themis
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 10d agothemisthemis 1.1.0 adds cluster-centroid and CNN under-sampling
- 11mo agodesirability2make_desirability_cols() exported; data-driven limits on by default
- 1y agodesirability2Desirability-based model selection added for tune ⚡
- 1y agothemisthemis 1.0.3 corrects resampling direction in documentation
- 2y agothemisthemis 1.0.2 makes internal consistency and speed changes
- 3y agodesirability2NEWS.md added to track package changes
- 3y agothemisthemis 1.0.1 fixes upsampling errors when none is needed
- 4y agothemisthemis 1.0.0 adds case weights to up- and down-sampling
- 4y agothemisthemis 0.2.2 rewrites tomek() for multiclass, drops a dependency
Frequently asked questions
What is the difference between desirability2 and themis?
Both compete on the same themes — tidymodels, r — within Analytics. themis 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 desirability2 better than themis?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. themis 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 desirability2?
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.
What are the best alternatives to themis?
Top themis alternatives in Analytics are ranked by recent ship velocity. Browse the "themis alternatives" section above for the current picks, or visit /alternatives/themis for the full list with editorial commentary on each.