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hoardr vs xplainfi

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

hoardr vs xplainfi: at a glance

Featurehoardrxplainfi
SectorAnalyticsAnalytics
Velocity score0.02.5
Sparks · 30d00
Top themescaching, r-package, ropensci, infrastructuremlr3, feature-importance, interpretability, statistical-inference
Last editorial update58m ago7h ago
WebsiteVisit →Visit →

What is hoardr?

A cache-directory helper that has shipped nothing but CRAN-triggered patches for seven years.

hoardr manages local cache directories for other R packages — where files go, how they are keyed, whether they exist. It underpins caching in several rOpenSci data clients. The last functional additions were in 2018; everything since is a patch issued because CRAN reported a test failure or the maintainer changed.

Read the full hoardr 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 →

hoardr vs xplainfi: editorial side-by-side

H
hoardr
ANALYTICS
0.0

A cache-directory helper that has shipped nothing but CRAN-triggered patches for seven years.

◆ Current state

hoardr manages local cache directories for other R packages — where files go, how they are keyed, whether they exist. It underpins caching in several rOpenSci data clients. The last functional additions were in 2018; everything since is a patch issued because CRAN reported a test failure or the maintainer changed.

◆ Where it's heading

This is infrastructure that has reached its final shape. Three of the last three releases were reactive: two responses to CRAN test-failure notifications, one to a maintainer handover. The single behavioural change in that stretch — forward slashes in paths on every operating system — is a consistency fix for downstream packages rather than a feature. Its release cadence is set by CRAN's checks, not by demand.

◆ Prediction

Expect the next release to be triggered by another CRAN check failure rather than by new functionality, matching every release since 2018.

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 hoardr 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 hoardr or xplainfi.

See all hoardr alternatives → · See all xplainfi alternatives →

Recent activity from hoardr and xplainfi

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

  1. 21d 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 agohoardrPaths use forward slashes on every platform
  6. 2y agohoardrTest-only patch for a CRAN failure
  7. 3y agohoardrPatch release for maintainer handover
  8. 7y agohoardrFixes cache paths leaking between HoardClient instances
  9. 7y agohoardrFile-existence checks and full-path cache configuration
  10. 9y agohoardrCRAN disk-writing policy compliance

Frequently asked questions

What is the difference between hoardr 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 hoardr 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 hoardr?

Top hoardr alternatives in Analytics are ranked by recent ship velocity. Browse the "hoardr alternatives" section above for the current picks, or visit /alternatives/hoardr 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.