compositional.mle
An MLE package rebuilt around composable solvers, then renamed to match.
Comparison · Analytics
hubEvals vs hubPredEvalsData
A side-by-side editorial comparison of hubEvals and hubPredEvalsData — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:forecast-evaluationepidemiologyhubverse
hubEvals vs hubPredEvalsData: at a glance
What is hubEvals?
Forecast-hub scoring that learned to handle joint, sample-based predictions.
hubEvals scores model output from collaborative forecasting hubs, wrapping scoringutils and translating hubverse formats into forecast objects it can evaluate. The package has moved quickly from a thin translation layer to something that handles every output type the hubverse defines — quantile, mean, median, nominal and ordinal pmf, and samples. The most recent releases are almost entirely about the failure modes of relative skill scoring rather than about new metrics.
What is hubPredEvalsData?
The pipeline turning hub forecasts into dashboard-ready evaluation data.
hubPredEvalsData generates the scored evaluation data that hubverse prediction dashboards read, driven by a predevals-config.yml and scoring through hubEvals underneath. It is the youngest package in this part of the stack and the fastest-moving in configuration terms, having already passed a breaking 1.0.0 and a schema-versioned feature addition. Its output contract is a scores.csv file consumed downstream, which shapes what its releases care about.
hubEvals vs hubPredEvalsData: editorial side-by-side
hubEvals
2.5ANALYTICS
Forecast-hub scoring that learned to handle joint, sample-based predictions.
◆ Current state
hubEvals scores model output from collaborative forecasting hubs, wrapping scoringutils and translating hubverse formats into forecast objects it can evaluate. The package has moved quickly from a thin translation layer to something that handles every output type the hubverse defines — quantile, mean, median, nominal and ordinal pmf, and samples. The most recent releases are almost entirely about the failure modes of relative skill scoring rather than about new metrics.
◆ Where it's heading
Two threads dominate. The first is coverage of output types, which reached its widest point with sample-based and compound scoring. The second, and the one occupying every recent release, is making relative skill degrade gracefully: single-model input, comparison groups with one model, and groups missing the requested baseline have each been converted from a cryptic upstream abort into a defined result. That pattern — inherited scoringutils errors being caught and given hub-specific meaning — is the clearest signal of where this package adds value.
◆ Prediction
Expect continued work smoothing scoringutils error surfaces into hub-aware behaviour, and performance attention on relative skill, which was explicitly optimised in the latest release.
hubPredEvalsData
0.0ANALYTICS
The pipeline turning hub forecasts into dashboard-ready evaluation data.
◆ Current state
hubPredEvalsData generates the scored evaluation data that hubverse prediction dashboards read, driven by a predevals-config.yml and scoring through hubEvals underneath. It is the youngest package in this part of the stack and the fastest-moving in configuration terms, having already passed a breaking 1.0.0 and a schema-versioned feature addition. Its output contract is a scores.csv file consumed downstream, which shapes what its releases care about.
◆ Where it's heading
Each release widens what the config file can express — round selection, then scale transformations with per-target overrides, then target labelling pulled from the hub's own task metadata. The pattern is consistent: capability that already exists in hubEvals gets a declarative surface here so hub maintainers configure it rather than write code. Recent attention to byte-stable output ordering shows the file is being treated as a reproducible artifact, not just a report.
◆ Prediction
Expect the config schema to keep absorbing hubEvals capabilities as declarative options, with continued attention to making scores.csv reproducible and diffable between runs.
Alternatives to hubEvals and hubPredEvalsData
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 hubEvals or hubPredEvalsData.
nabla
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snowflakeauth
Eight months from first release to keyring caching and workload identity.
kwb.geosalz
A research-project workflow package where the interesting work is in the plumbing.
cyclocomp
A cyclomatic complexity checker that ships once every couple of years, and lands when it does.
revdbayes
Extreme value sampling in pure upkeep mode, mostly answering to Rcpp and CRAN.
See all hubEvals alternatives → · See all hubPredEvalsData alternatives →
Recent activity from hubEvals and hubPredEvalsData
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 24d agohubEvalsScored-forecast counts and faster relative skill
- 1mo agohubEvalsDisaggregated relative skill no longer aborts the whole call
- 1mo agohubPredEvalsDataTarget names pulled from hub metadata; scores.csv made byte-stable
- 1mo agohubEvalsSingle-model scoring returns relative skill of 1 instead of erroring
- 2mo agohubPredEvalsDataVersioned target data with an as_of column no longer fails scoring
- 2mo agohubPredEvalsDataScale transformations become configurable per target
- 4mo agohubPredEvalsDataMulti-round hub support via a required rounds_idx property (breaking)
- 5mo agohubEvalsSample output types and multivariate compound scoring ⚡
- 6mo agohubEvalsScoring on transformed scales via transform arguments
- 11mo agohubEvalsFirst release: score_model_out() and the scoringutils bridge
Frequently asked questions
What is the difference between hubEvals and hubPredEvalsData?
Both compete on the same themes — forecast-evaluation, epidemiology, hubverse — within Analytics. hubEvals 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 hubEvals better than hubPredEvalsData?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. hubEvals 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 hubEvals?
Top hubEvals alternatives in Analytics are ranked by recent ship velocity. Browse the "hubEvals alternatives" section above for the current picks, or visit /alternatives/hubevals for the full list with editorial commentary on each.
What are the best alternatives to hubPredEvalsData?
Top hubPredEvalsData alternatives in Analytics are ranked by recent ship velocity. Browse the "hubPredEvalsData alternatives" section above for the current picks, or visit /alternatives/hubpredevalsdata for the full list with editorial commentary on each.