tidytext
Finished, widely taught, and shipping roxygen fixes.
Comparison · Analytics
discrim vs probably
A side-by-side editorial comparison of discrim and probably — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:tidymodels
discrim vs probably: 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 probably?
The package that made calibration a step instead of an afterthought.
probably started as a small utility for class predictions and equivocal zones, and version 1.0.0 turned it into tidymodels' calibration and uncertainty package: cal_plot_*, cal_estimate_*, cal_validate_* and cal_apply across binary, multiclass and regression problems, plus conformal prediction intervals. Since then the work has been consolidation — a large internal refactor with no API change, split conformal and conformal quantile regression, bound_prediction(), and required_pkgs() and butcher methods so conformal objects can be deployed and stripped.
discrim vs probably: 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.
probably
0.0ANALYTICS
The package that made calibration a step instead of an afterthought.
◆ Current state
probably started as a small utility for class predictions and equivocal zones, and version 1.0.0 turned it into tidymodels' calibration and uncertainty package: cal_plot_*, cal_estimate_*, cal_validate_* and cal_apply across binary, multiclass and regression problems, plus conformal prediction intervals. Since then the work has been consolidation — a large internal refactor with no API change, split conformal and conformal quantile regression, bound_prediction(), and required_pkgs() and butcher methods so conformal objects can be deployed and stripped.
◆ Where it's heading
The recent releases are about making these objects survive leaving the session. butcher and required_pkgs() methods are what a model needs to be pinned, containerised and served, and their arrival alongside workflows adding a tailor postprocessing stage and vetiver adding probably support points the same way: calibration is being moved out of analysis scripts and into the deployed pipeline. The cal_*_none() reference implementations are the tell that calibration is now something people tune rather than apply once.
◆ Prediction
Expect the calibration functions to be reachable directly from a tuned workflow's postprocessing stage rather than applied to predictions afterwards, following the tailor integration that workflows just shipped.
Alternatives to discrim and probably
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 probably.
textrecipes
Text features finally stay sparse all the way to the model.
workflowsets
workflowsets keeps widening what counts as a model worth comparing.
workflows
The tidymodels pipeline grew a third stage, and it happens after the model runs.
vetiver
Posit's MLOps package went quiet for two years, then came back to keep up with recipes.
patchwork
patchwork stopped being a ggplot composer and became a page composer.
See all discrim alternatives → · See all probably alternatives →
Recent activity from discrim and probably
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 8mo agodiscrimFix for FDA models failing at prediction time
- 10mo agoprobablyConformal objects gain required_pkgs() and butcher methods
- 11mo agodiscrimDocumentation links updated to stay on CRAN
- 1y agoprobablyggplot2 test updates and a clearer validation-set error
- 1y agoprobablyCalibration internals refactored; isotonic bootstrap bug fixed
- 2y agoprobablyFix grouping sensitivity to variable type
- 3y agoprobablySplit conformal and conformal quantile regression added
- 3y agoprobablyCalibration and conformal inference arrive in tidymodels ⚡
- 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 probably?
Both compete on the same themes — tidymodels — within Analytics. discrim and probably 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 probably?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. discrim and probably 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 probably?
Top probably alternatives in Analytics are ranked by recent ship velocity. Browse the "probably alternatives" section above for the current picks, or visit /alternatives/probably for the full list with editorial commentary on each.