rnaturalearth
rnaturalearth finished its sp exit and is now optimising how the data actually arrives.
Comparison · Analytics
mlr3learners vs rstanarm
A side-by-side editorial comparison of mlr3learners and rstanarm — release velocity, themes, recent moves, and the top alternatives to consider.
mlr3learners vs rstanarm: at a glance
What is mlr3learners?
mlr3learners spends its releases absorbing upstream churn
mlr3learners wraps the standard model packages — ranger, xgboost, glmnet, kknn — for mlr3. Its recent history is dominated by upstream events rather than its own plans: kknn was pulled from CRAN and its learners removed in 0.11.0, then restored in 0.12.0 when the package returned. The newest release absorbs glmnet 5.0 while adding a predict_raw flag across all learners and probit support to logistic regression.
What is rstanarm?
rstanarm is community-maintained now, tracking Stan and lme4 rather than adding models.
2.32.2 is entirely infrastructure and dependency work: formula machinery migrated from lme4 to reformulas, `r_eff` no longer computed for loo by default, the Stan R packages repo replaced by R-Universe, rstantools adopted to fix build and export errors, and CRAN NOTE cleanups — contributed largely by four first-time contributors. 2.32.1 and 2.26.1 follow the same pattern, tracking rstan syntax and adding `posterior::as_draws()` support. The last release with substantive modelling content is 2.21.1, which changed how default priors are determined and flipped `autoscale` to FALSE outside default priors.
mlr3learners vs rstanarm: editorial side-by-side
mlr3learners
0.0ANALYTICS
mlr3learners spends its releases absorbing upstream churn
◆ Current state
mlr3learners wraps the standard model packages — ranger, xgboost, glmnet, kknn — for mlr3. Its recent history is dominated by upstream events rather than its own plans: kknn was pulled from CRAN and its learners removed in 0.11.0, then restored in 0.12.0 when the package returned. The newest release absorbs glmnet 5.0 while adding a predict_raw flag across all learners and probit support to logistic regression.
◆ Where it's heading
The package's job is insulation, and the changelog shows what that costs — compatibility-only releases interleaved with small capability additions that expose more of each upstream model. The direction of travel is toward giving users access to the raw upstream objects rather than hiding them.
◆ Prediction
Expect the next release to track another upstream version bump, with incremental exposure of learner-specific fields continuing alongside.
rstanarm
0.0ANALYTICS
rstanarm is community-maintained now, tracking Stan and lme4 rather than adding models.
◆ Current state
2.32.2 is entirely infrastructure and dependency work: formula machinery migrated from lme4 to reformulas, `r_eff` no longer computed for loo by default, the Stan R packages repo replaced by R-Universe, rstantools adopted to fix build and export errors, and CRAN NOTE cleanups — contributed largely by four first-time contributors. 2.32.1 and 2.26.1 follow the same pattern, tracking rstan syntax and adding `posterior::as_draws()` support. The last release with substantive modelling content is 2.21.1, which changed how default priors are determined and flipped `autoscale` to FALSE outside default priors.
◆ Where it's heading
The package has moved from feature development into ecosystem maintenance, and the contributor list shows why it survives: outside developers keep it compiling against a moving Stan, lme4 and CRAN. The `as_draws()` support and the reformulas migration both point the same way — rstanarm increasingly consumes shared infrastructure (posterior, reformulas, rstantools) instead of carrying its own.
◆ Prediction
Expect the next release to track another upstream change — rstan, reformulas or CRAN policy — rather than add model families. The pre-fit model surface looks settled.
Alternatives to mlr3learners and rstanarm
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 mlr3learners or rstanarm.
writexl
writexl spent nine years refusing to do formatting, then shipped all of it in 2.0.0.
rgbif
rgbif is steadily pushing users off paged searching and onto real downloads.
taxa
taxa started a ground-up rewrite in 2021 and has published almost nothing since.
rotl
rotl's whole release history is keeping name matching honest against a moving taxonomy.
taxize
taxize spends its releases absorbing other people's API changes, one dead source at a time.
See all mlr3learners alternatives → · See all rstanarm alternatives →
Recent activity from mlr3learners and rstanarm
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 2mo agomlr3learnerspredict_raw across all learners, plus probit and ranger internals
- 8mo agomlr3learnersxgboost 3.1.2.1 compatibility
- 9mo agomlr3learnersUncertainty estimation methods for ranger regression
- 10mo agorstanarmrstanarm 2.32.2 migrates formula machinery to reformulas
- 10mo agomlr3learnersDevelopment snapshot: LDA test adjustment
- 1y agomlr3learnerskknn learners restored after returning to CRAN
- 1y agomlr3learnerskknn learners removed after CRAN archival
- 2y agorstanarmrstanarm 2.32.1 fixes unit_vector error, enables LTO
- 2y agorstanarmrstanarm 2.26.1 adopts new rstan syntax and as_draws()
- 4y agorstanarmrstanarm 2.21.3 fixes loo() and adds stan_jm offsets
- 6y agorstanarmrstanarm 2.21.1 changes default prior behaviour
Frequently asked questions
What is the difference between mlr3learners and rstanarm?
They serve adjacent needs but don't currently overlap on shipped themes. mlr3learners and rstanarm 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 mlr3learners better than rstanarm?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. mlr3learners and rstanarm 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 mlr3learners?
Top mlr3learners alternatives in Analytics are ranked by recent ship velocity. Browse the "mlr3learners alternatives" section above for the current picks, or visit /alternatives/mlr3learners for the full list with editorial commentary on each.
What are the best alternatives to rstanarm?
Top rstanarm alternatives in Analytics are ranked by recent ship velocity. Browse the "rstanarm alternatives" section above for the current picks, or visit /alternatives/rstanarm for the full list with editorial commentary on each.