mlr3mbo
mlr3mbo picked its defaults from a benchmark study, not from taste
Comparison · Analytics
discrim vs scales
A side-by-side editorial comparison of discrim and scales — release velocity, themes, recent moves, and the top alternatives to consider.
discrim vs scales: at a glance
What is discrim?
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.
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.
discrim vs scales: editorial side-by-side
discrim
0.0ANALYTICS
discrim settled into a thin engine shim after handing its model definitions to parsnip.
◆ Current state
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.
◆ Where it's heading
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.
◆ Prediction
Nothing in the entries points to new methods or engines; the next release is most likely another CRAN or prediction-path fix.
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 discrim 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 discrim 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 discrim alternatives → · See all scales alternatives →
Recent activity from discrim and scales
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 8mo agodiscrimFix for FDA models failing at prediction time
- 11mo agodiscrimDocumentation links updated to stay on CRAN
- 1y agoscalesscales 1.4.0 opens range training to custom classes
- 2y agoscalesscales 1.3.0 makes timespans first-class on axes
- 3y agoscalesscales 1.2.1 re-documents to fix .Rd HTML issues
- 4y agodiscrimCase weights enabled for flexible and linear discriminant models
- 4y agoscalesscales 1.2.0 fixes currency sign order and adds scale_cut
- 4y agodiscrimModel definitions moved upstream into parsnip
- 5y agodiscrimsda and sparsediscrim engines added for LDA and QDA
- 5y agodiscrimdiscrim_quad() added; package relicensed to MIT ⚡
- 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 discrim and scales?
They serve adjacent needs but don't currently overlap on shipped themes. discrim 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 discrim better than scales?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. discrim 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 discrim?
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.
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.