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Comparison · Analytics

tern.rbmi vs xplainfi

A side-by-side editorial comparison of tern.rbmi and xplainfi — release velocity, themes, recent moves, and the top alternatives to consider.

tern.rbmi vs xplainfi: at a glance

Featuretern.rbmixplainfi
SectorAnalyticsAnalytics
Velocity score0.02.5
Sparks · 30d00
Top themespharmaverse, multiple-imputation, cran-maintenance, tabulationmlr3, feature-importance, interpretability, statistical-inference
Last editorial update2h ago2h ago
WebsiteVisit →Visit →

What is tern.rbmi?

Reference-based multiple imputation tables, shipping only what CRAN checks demand.

tern.rbmi renders the output of {rbmi} reference-based multiple imputation analyses into tern tables for clinical reporting. Its three most recent releases exist to satisfy CRAN: restricting vignette builds to gcc, adding V8 to Suggests, and a plain resubmission. No user-facing functionality has changed in the visible window.

Read the full tern.rbmi trajectory →

What is xplainfi?

xplainfi treats feature importance as an estimate with error bars, not a number.

xplainfi implements feature importance methods for mlr3 — perturbation-based PFI, CFI and RFI, refit-based LOCO and WVIM, and SAGE. Its defining choice is that importance scores come with inference attached: several confidence-interval methods, including the Nadeau-Bengio correction and a distribution-free option added in 1.1.0. It declared itself released at 1.0.0 in January 2026.

Read the full xplainfi trajectory →

tern.rbmi vs xplainfi: editorial side-by-side

T
tern.rbmi
ANALYTICS
0.0

Reference-based multiple imputation tables, shipping only what CRAN checks demand.

◆ Current state

tern.rbmi renders the output of {rbmi} reference-based multiple imputation analyses into tern tables for clinical reporting. Its three most recent releases exist to satisfy CRAN: restricting vignette builds to gcc, adding V8 to Suggests, and a plain resubmission. No user-facing functionality has changed in the visible window.

◆ Where it's heading

This is a thin adapter package and behaves like one — it moves when CRAN or an upstream dependency forces it to. Between 2022 and 2024 the feed shows only version bumps, and the 2025 releases are packaging concerns rather than analysis changes.

◆ Prediction

Expect the next release to be triggered by a CRAN check failure or an {rbmi} update rather than by new tabulation features.

X
xplainfi
ANALYTICS
2.5

xplainfi treats feature importance as an estimate with error bars, not a number.

◆ Current state

xplainfi implements feature importance methods for mlr3 — perturbation-based PFI, CFI and RFI, refit-based LOCO and WVIM, and SAGE. Its defining choice is that importance scores come with inference attached: several confidence-interval methods, including the Nadeau-Bengio correction and a distribution-free option added in 1.1.0. It declared itself released at 1.0.0 in January 2026.

◆ Where it's heading

Two lines of work run in parallel. The statistical side keeps adding inference options — variance corrections, conditional predictive impact, and the Lei et al. observation-wise loss-difference test — while the computational side attacks the cost of refit-based methods, most recently with a batch_size argument that parallelises refits and a default of one refit per resampling iteration. Support for pre-trained learners in 1.1.0 removes the refit requirement entirely in some workflows.

◆ Prediction

The stated reasoning that budget is better spent on resampling iterations than repeated refits suggests n_repeats may be removed from WVIM and LOCO outright, as the release notes hint.

Alternatives to tern.rbmi and xplainfi

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 tern.rbmi or xplainfi.

See all tern.rbmi alternatives → · See all xplainfi alternatives →

Recent activity from tern.rbmi and xplainfi

Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.

  1. 20d agoxplainfiRefits parallelise; repeated refits deprioritised in favour of resampling
  2. 5mo agoxplainfiPre-trained learners supported; distribution-free inference added
  3. 6mo agoxplainfiVersion bumped to mark the package as released
  4. 9mo agoxplainfiConfidence intervals arrive for feature importance scores
  5. 1y agotern.rbmiVignette built only under gcc
  6. 1y agotern.rbmiV8 added to Suggests
  7. 1y agotern.rbmiCRAN resubmission with dependency and workflow updates
  8. 3y agotern.rbmi2022_10_13
  9. 4y agotern.rbmi2022_08_16
  10. 4y agotern.rbmi2022_06_09: [skip vbump] (#31)

Frequently asked questions

What is the difference between tern.rbmi and xplainfi?

They serve adjacent needs but don't currently overlap on shipped themes. xplainfi 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 tern.rbmi better than xplainfi?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. xplainfi 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 tern.rbmi?

Top tern.rbmi alternatives in Analytics are ranked by recent ship velocity. Browse the "tern.rbmi alternatives" section above for the current picks, or visit /alternatives/tern-rbmi for the full list with editorial commentary on each.

What are the best alternatives to xplainfi?

Top xplainfi alternatives in Analytics are ranked by recent ship velocity. Browse the "xplainfi alternatives" section above for the current picks, or visit /alternatives/xplainfi for the full list with editorial commentary on each.