mlr3proba
mlr3proba is shedding weight as its survival work moves into sibling packages
Comparison · Analytics
finetune vs parameters
A side-by-side editorial comparison of finetune and parameters — release velocity, themes, recent moves, and the top alternatives to consider.
finetune vs parameters: at a glance
What is finetune?
finetune tracks tune's evolving contracts more than it advances racing itself
finetune provides the racing and simulated-annealing alternatives to grid search in tidymodels. The core algorithms have been stable since 1.0.x; what has changed is everything around them — censored regression support arriving with a tune release, weighted resampling estimates preserved through racing, and a breaking move to named-only optional arguments.
What is parameters?
easystats' parameters package absorbs one more model class every few weeks
parameters extracts and formats coefficients from an enormous range of R model objects, and its releases read as a running ledger of that range expanding — lavaan and lavaan.mi, survey, lcmm, glmmTMB, fixest, marginaleffects, ordinal. Recent versions ship roughly monthly with a mix of new support, new arguments, and fixes for label handling and standard errors. The most consequential recent change is behavioral: post-hoc standardization no longer standardizes the intercept, setting it and its inferential statistics to NA.
finetune vs parameters: editorial side-by-side
finetune
0.0ANALYTICS
finetune tracks tune's evolving contracts more than it advances racing itself
◆ Current state
finetune provides the racing and simulated-annealing alternatives to grid search in tidymodels. The core algorithms have been stable since 1.0.x; what has changed is everything around them — censored regression support arriving with a tune release, weighted resampling estimates preserved through racing, and a breaking move to named-only optional arguments.
◆ Where it's heading
This is a package operating downstream of tune, adopting whatever the shared resampling machinery grows next rather than proposing new search strategies. The 1.3.0 weighting work is a clear example: tune changed how resampling estimates are computed, and finetune's job was to not lose the weights during racing. Error messages and input checks are the steady internal theme.
◆ Prediction
Expect the next release to absorb whatever tune changes about metric collection or resampling weights; nothing in the entries points to a new search algorithm.
parameters
0.0ANALYTICS
easystats' parameters package absorbs one more model class every few weeks
◆ Current state
parameters extracts and formats coefficients from an enormous range of R model objects, and its releases read as a running ledger of that range expanding — lavaan and lavaan.mi, survey, lcmm, glmmTMB, fixest, marginaleffects, ordinal. Recent versions ship roughly monthly with a mix of new support, new arguments, and fixes for label handling and standard errors. The most consequential recent change is behavioral: post-hoc standardization no longer standardizes the intercept, setting it and its inferential statistics to NA.
◆ Where it's heading
The package's job is to be the universal adapter for model output, so its roadmap is effectively set by what the R modelling ecosystem produces. Two threads are visible beyond coverage: getting standard errors right for awkward cases such as frailty terms and robust vcov matrices, and getting labels right when factors are converted on the fly or character variables appear in a formula. Interoperability inside easystats keeps tightening, with equivalence_test() gaining methods for modelbased objects.
◆ Prediction
Given the cadence, the next release will most likely add another model class alongside label and standard-error fixes rather than change how the package works.
Alternatives to finetune and parameters
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 finetune or parameters.
mlr3viz
mlr3viz keeps the ecosystem's plots working while the plots themselves move out
mlr3tuning
mlr3tuning is rebuilding its async machinery under a stable public surface
timetk
timetk swallowed anomalize whole, then went quiet for two years
modelbased
modelbased is turning marginal effects into a full contrast grammar
tidyposterior
A finished Bayesian model-comparison package in pure maintenance mode
See all finetune alternatives → · See all parameters alternatives →
Recent activity from finetune and parameters
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 1mo agoparametersparameters 0.29.2 extends lavaan support and fixes label dropping
- 2mo agoparametersparameters 0.29.1 adds a cluster argument and fixes vcov handling
- 3mo agoparametersparameters 0.29.0 stops standardizing the intercept in post-hoc methods
- 3mo agofinetuneRacing preserves tune's assessment-set weighting
- 8mo agoparametersparameters 0.28.3 adds Kenward-Roger and Satterthwaite for glmmTMB
- 11mo agoparametersparameters 0.28.2 updates tests for the latest fixest release
- 11mo agoparametersparameters 0.28.1 adds robust standard errors for glmmTMB
- 1y agofinetuneMaintenance release; magrittr pipe replaced with base pipe
- 2y agofinetuneCensored regression models can be raced and annealed
- 3y agofinetuneKeep-up release for tune and dplyr; .config alignment fixed
- 3y agofinetuneRacing results filter to fully resampled configurations
- 3y agofinetuneInformative error when resamples are too few for racing
Frequently asked questions
What is the difference between finetune and parameters?
They serve adjacent needs but don't currently overlap on shipped themes. finetune and parameters 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 finetune better than parameters?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. finetune and parameters 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 finetune?
Top finetune alternatives in Analytics are ranked by recent ship velocity. Browse the "finetune alternatives" section above for the current picks, or visit /alternatives/finetune for the full list with editorial commentary on each.
What are the best alternatives to parameters?
Top parameters alternatives in Analytics are ranked by recent ship velocity. Browse the "parameters alternatives" section above for the current picks, or visit /alternatives/parameters-r for the full list with editorial commentary on each.