mlr3mbo
mlr3mbo picked its defaults from a benchmark study, not from taste
Comparison · Analytics
discrim vs fable
A side-by-side editorial comparison of discrim and fable — release velocity, themes, recent moves, and the top alternatives to consider.
discrim vs fable: 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 fable?
fable keeps widening its model shelf, one econometric class at a time
fable is the tidyverts forecasting engine, and its releases are almost entirely about which model families it can express. The 0.4.x line added the vector-error-correction and VARIMA classes plus impulse-response methods; 0.5.0 adds fractional differencing via ARFIMA. Between those, the releases are CRAN-check patches and documentation passes.
discrim vs fable: 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.
fable
0.0ANALYTICS
fable keeps widening its model shelf, one econometric class at a time
◆ Current state
fable is the tidyverts forecasting engine, and its releases are almost entirely about which model families it can express. The 0.4.x line added the vector-error-correction and VARIMA classes plus impulse-response methods; 0.5.0 adds fractional differencing via ARFIMA. Between those, the releases are CRAN-check patches and documentation passes.
◆ Where it's heading
The package is closing the gap with the older forecast package's model coverage while keeping the tidy model-specification grammar. Each substantive release is a new model class plus the generate()/IRF() plumbing to make it behave like the existing ones. Maintenance releases cluster around CRAN policy and ggplot2/tsibble compatibility rather than internal rewrites.
◆ Prediction
Expect the next substantive release to add another model class or extend generate()/IRF() coverage to the classes that still lack them, rather than change the modelling interface.
Alternatives to discrim and fable
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 fable.
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 fable alternatives →
Recent activity from discrim and fable
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 6mo agofablefable adds ARFIMA and fractional differencing ⚡
- 8mo agodiscrimFix for FDA models failing at prediction time
- 11mo agodiscrimDocumentation links updated to stay on CRAN
- 1y agofableIndexing and generate() fixes for VECM models
- 1y agofableVECM and VARIMA models land, plus IRF for VAR and ARIMA ⚡
- 2y agofablePatch for C++ R header changes
- 2y agofableCRAN check patch with generate() fixes
- 3y agofableTSLM forecasts gain Student's t intervals
- 4y agodiscrimCase weights enabled for flexible and linear discriminant models
- 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 ⚡
Frequently asked questions
What is the difference between discrim and fable?
They serve adjacent needs but don't currently overlap on shipped themes. discrim and fable 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 fable?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. discrim and fable 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 fable?
Top fable alternatives in Analytics are ranked by recent ship velocity. Browse the "fable alternatives" section above for the current picks, or visit /alternatives/fable for the full list with editorial commentary on each.