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Comparison · Analytics
loo vs mlr3learners
A side-by-side editorial comparison of loo and mlr3learners — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-stats
loo vs mlr3learners: at a glance
What is loo?
loo keeps rewriting the diagnostics Bayesian modellers read off model comparison
loo computes leave-one-out cross-validation and model comparison for Bayesian models in the Stan ecosystem. Two releases in this window changed what users actually read: 2.7.0 replaced the fixed Pareto-k thresholds with sample-size-dependent ones and dropped the middle category, and 2.10.0 reshaped loo_compare's output into a data.frame with new uncertainty columns. The releases between are diagnostic robustness fixes and moment-matching corrections.
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.
loo vs mlr3learners: editorial side-by-side
loo
2.5ANALYTICS
loo keeps rewriting the diagnostics Bayesian modellers read off model comparison
◆ Current state
loo computes leave-one-out cross-validation and model comparison for Bayesian models in the Stan ecosystem. Two releases in this window changed what users actually read: 2.7.0 replaced the fixed Pareto-k thresholds with sample-size-dependent ones and dropped the middle category, and 2.10.0 reshaped loo_compare's output into a data.frame with new uncertainty columns. The releases between are diagnostic robustness fixes and moment-matching corrections.
◆ Where it's heading
The package is being brought in line with the current PSIS literature rather than extended with new features, and the practical effect is that the numbers practitioners quote in papers keep changing meaning. Work is increasingly delegated to posterior for shared computations, and the project has added contributor process, benchmarks and a published AI contribution policy.
◆ Prediction
Expect further work on comparison diagnostics — the p_worse and diag_* columns are new enough that their defaults and documentation will likely be revised next.
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.
Alternatives to loo and mlr3learners
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 loo or mlr3learners.
textrecipes
Text features finally stay sparse all the way to the model.
probably
The package that made calibration a step instead of an afterthought.
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.
See all loo alternatives → · See all mlr3learners alternatives →
Recent activity from loo and mlr3learners
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 20d agoloopsis_smooth_tail revert and simplify arg restored
- 1mo agolooloo_compare returns a data.frame with new uncertainty columns ⚡
- 2mo agomlr3learnerspredict_raw across all learners, plus probit and ranger internals
- 7mo agolooStacking overflow fixes and posterior-based ESS
- 8mo agomlr3learnersxgboost 3.1.2.1 compatibility
- 9mo agomlr3learnersUncertainty estimation methods for ranger regression
- 10mo agomlr3learnersDevelopment snapshot: LDA test adjustment
- 1y agomlr3learnerskknn learners restored after returning to CRAN
- 1y agomlr3learnerskknn learners removed after CRAN archival
- 2y agolooMore robust Pareto-k diagnostics and moment matching
- 2y agolooPareto-k thresholds now depend on sample size ⚡
- 3y agolooLOO predictive metrics and CRPS scoring functions
Frequently asked questions
What is the difference between loo and mlr3learners?
Both compete on the same themes — r-stats — within Analytics. loo is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.
Is loo better than mlr3learners?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. loo is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.
What are the best alternatives to loo?
Top loo alternatives in Analytics are ranked by recent ship velocity. Browse the "loo alternatives" section above for the current picks, or visit /alternatives/loo for the full list with editorial commentary on each.
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.