mlr3mbo
mlr3mbo picked its defaults from a benchmark study, not from taste
Comparison · Analytics
desirability2 vs scales
A side-by-side editorial comparison of desirability2 and scales — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r
desirability2 vs scales: 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 scales?
scales keeps widening what ggplot2 can put on an axis.
scales supplies the breaks, labels and transformations behind ggplot2's axes and legends. Unlike much of the tidyverse infrastructure around it, it still ships genuine feature work each release: native timespan handling in 1.3.0, then custom range-training classes and label_glue() in 1.4.0.
desirability2 vs scales: 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.
scales
0.0ANALYTICS
scales keeps widening what ggplot2 can put on an axis.
◆ Current state
scales supplies the breaks, labels and transformations behind ggplot2's axes and legends. Unlike much of the tidyverse infrastructure around it, it still ships genuine feature work each release: native timespan handling in 1.3.0, then custom range-training classes and label_glue() in 1.4.0.
◆ Where it's heading
The arc runs toward extensibility and type coverage. First came built-in support for awkward types like difftime and hms; 1.4.0 inverts that by letting any third-party class participate in range training simply by implementing range() or levels(). Labelling is getting more expressive rather than merely more numerous.
◆ Prediction
Expect continued type-support and labelling work, with extension points that let downstream packages plug in their own classes instead of scales enumerating every one.
Alternatives to desirability2 and scales
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 scales.
loo
loo keeps rewriting the diagnostics Bayesian modellers read off model comparison
mlr3fselect
mlr3fselect turned feature selection into an asynchronous, distributable job
lime
lime survives on compatibility patches years after its research moment
mlr3measures
mlr3measures is systematically retrofitting sample weights across every metric
mlr3cluster
mlr3cluster went from a handful of clusterers to covering the field
See all desirability2 alternatives → · See all scales alternatives →
Recent activity from desirability2 and scales
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 11mo agodesirability2make_desirability_cols() exported; data-driven limits on by default
- 1y agodesirability2Desirability-based model selection added for tune ⚡
- 1y agoscalesscales 1.4.0 opens range training to custom classes
- 2y agoscalesscales 1.3.0 makes timespans first-class on axes
- 3y agodesirability2NEWS.md added to track package changes
- 3y agoscalesscales 1.2.1 re-documents to fix .Rd HTML issues
- 4y agoscalesscales 1.2.0 fixes currency sign order and adds scale_cut
- 6y agoscalesscales 1.1.1 fixes palette inversion and adds oob_keep()
- 6y agoscalesscales 1.1.0 reorganises breaks and labels into a naming scheme
Frequently asked questions
What is the difference between desirability2 and scales?
Both compete on the same themes — r — within Analytics. desirability2 and scales 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.
Is desirability2 better than scales?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. desirability2 and scales 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.
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 scales?
Top scales alternatives in Analytics are ranked by recent ship velocity. Browse the "scales alternatives" section above for the current picks, or visit /alternatives/scales-r for the full list with editorial commentary on each.