mlr3viz
mlr3viz keeps the ecosystem's plots working while the plots themselves move out
A side-by-side editorial comparison of finetune and mlr3proba — release velocity, themes, recent moves, and the top alternatives to consider.
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.
mlr3proba is shedding weight as its survival work moves into sibling packages
mlr3proba provides probabilistic supervised learning for mlr3 — survival analysis, density estimation, and the measures that go with them. Recent releases are almost entirely upkeep: a distr6 fork to work around an upstream problem, an ooplah fix, a predict-type correction, and registration in mlr_reflections$loaded_packages. The one deletion is telling, with LearnerDensPenalized removed after pendensity left CRAN.
finetune provides the racing and simulated-annealing alternatives to grid search in tidymodels. The core algorithms have been stable since 1.0.x; what has changed is everything around them — censored regression support arriving with a tune release, weighted resampling estimates preserved through racing, and a breaking move to named-only optional arguments.
This is a package operating downstream of tune, adopting whatever the shared resampling machinery grows next rather than proposing new search strategies. The 1.3.0 weighting work is a clear example: tune changed how resampling estimates are computed, and finetune's job was to not lose the weights during racing. Error messages and input checks are the steady internal theme.
Expect the next release to absorb whatever tune changes about metric collection or resampling weights; nothing in the entries points to a new search algorithm.
mlr3proba provides probabilistic supervised learning for mlr3 — survival analysis, density estimation, and the measures that go with them. Recent releases are almost entirely upkeep: a distr6 fork to work around an upstream problem, an ooplah fix, a predict-type correction, and registration in mlr_reflections$loaded_packages. The one deletion is telling, with LearnerDensPenalized removed after pendensity left CRAN.
The package is being pared back rather than extended. Its README now points at survdistr and mlr3cmprsk as matured alternatives for parts of what it covers, which reads as scope being handed off, while the Cox proportional-hazards autoplot arrived from mlr3viz in the other direction. Several fixes exist to route around dependencies that broke or disappeared, which is the recurring cost of building on a long chain of specialized CRAN packages.
The dependency churn suggests more consolidation — further reliance on survdistr and mlr3cmprsk, and more learners retired when the package underneath them goes unmaintained.
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 mlr3proba.
mlr3viz keeps the ecosystem's plots working while the plots themselves move out
mlr3tuning is rebuilding its async machinery under a stable public surface
timetk swallowed anomalize whole, then went quiet for two years
modelbased is turning marginal effects into a full contrast grammar
easystats' parameters package absorbs one more model class every few weeks
A finished Bayesian model-comparison package in pure maintenance mode
See all finetune alternatives → · See all mlr3proba alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — survival-analysis — within Analytics. finetune and mlr3proba 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.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. finetune and mlr3proba 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.
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.
Top mlr3proba alternatives in Analytics are ranked by recent ship velocity. Browse the "mlr3proba alternatives" section above for the current picks, or visit /alternatives/mlr3proba for the full list with editorial commentary on each.