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kernelshap vs posteriordb-r

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

Shared themes:r package

kernelshap vs posteriordb-r: at a glance

Featurekernelshapposteriordb-r
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesshap, model explainability, sampling algorithms, numerical correctnessbayesian inference, stan, benchmark data, r package
Last editorial update1h ago1h ago
WebsiteVisit →Visit →

What is kernelshap?

kernelshap makes permutation SHAP practical past eight features, then fixes the kernel weights it had wrong.

kernelshap computes model-agnostic SHAP values in R through Kernel SHAP, permutation SHAP and an exact additive explainer. Version 0.8.0 added a sampling permutation-SHAP algorithm with standard errors and early stopping, lifting the practical feature ceiling past what the exact method allows. Version 0.9.0 then corrected a bug in how kernel weights were computed — exact Kernel SHAP now agrees with exact permutation SHAP — and moved parallelism from foreach to doFuture.

Read the full kernelshap trajectory →

What is posteriordb-r?

posteriordb's R client ships a test-file fix and nothing else.

posteriordb-r is the R interface to the posteriordb collection of reference Bayesian posteriors, used for benchmarking inference algorithms. The single release in view fixes Stan syntax in test files. Neither the posterior collection nor the client API changes.

Read the full posteriordb-r trajectory →

kernelshap vs posteriordb-r: editorial side-by-side

K
kernelshap
ANALYTICS
0.0

kernelshap makes permutation SHAP practical past eight features, then fixes the kernel weights it had wrong.

◆ Current state

kernelshap computes model-agnostic SHAP values in R through Kernel SHAP, permutation SHAP and an exact additive explainer. Version 0.8.0 added a sampling permutation-SHAP algorithm with standard errors and early stopping, lifting the practical feature ceiling past what the exact method allows. Version 0.9.0 then corrected a bug in how kernel weights were computed — exact Kernel SHAP now agrees with exact permutation SHAP — and moved parallelism from foreach to doFuture.

◆ Where it's heading

Two concerns drive this package: making exact methods reach further, and being demonstrably right. The first shows in the additive explainer, the optional background dataset and the sampling permutation algorithm; the second in unit tests written against Python's shap, credited fixes from outside contributors, and a willingness to ship a correctness fix that changes numbers people have already published. Speed work runs continuously underneath — direct solves replacing the Moore-Penrose pseudo-inverse, roughly 10% less memory.

◆ Prediction

The 0.6.0 and 0.7.0 notes each promised a stable 1.0.0 that has not arrived; with the weighting bug fixed and parallelism reworked, a 1.0 release is the most plausible next step.

P
posteriordb-r
ANALYTICS
0.0

posteriordb's R client ships a test-file fix and nothing else.

◆ Current state

posteriordb-r is the R interface to the posteriordb collection of reference Bayesian posteriors, used for benchmarking inference algorithms. The single release in view fixes Stan syntax in test files. Neither the posterior collection nor the client API changes.

◆ Where it's heading

One patch-level entry gives little to read. What it does say is that upkeep here tracks Stan's evolving syntax rather than the database's contents — the client's job is to stay compatible with the language the reference models are written in. Whether the collection itself is growing is not visible from this feed.

◆ Prediction

Expect further compatibility patches as Stan syntax deprecations land; the entries give no signal on new posteriors or API changes.

Alternatives to kernelshap and posteriordb-r

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 kernelshap or posteriordb-r.

See all kernelshap alternatives → · See all posteriordb-r alternatives →

Recent activity from kernelshap and posteriordb-r

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

  1. 9mo agoposteriordb-rStan syntax fixes in test files
  2. 1y agokernelshapKernel weight bug fixed; parallelism moves to doFuture
  3. 1y agokernelshapSampling permutation SHAP with standard errors
  4. 1y agokernelshapBackground data now optional; ranger survival support
  5. 2y agokernelshapFactor-valued predictions dropped
  6. 2y agokernelshapadditive_shap() explains additive models exactly
  7. 2y agokernelshapFaster on plain data.frames

Frequently asked questions

What is the difference between kernelshap and posteriordb-r?

Both compete on the same themes — r package — within Analytics. kernelshap and posteriordb-r 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 kernelshap better than posteriordb-r?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. kernelshap and posteriordb-r 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 kernelshap?

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

What are the best alternatives to posteriordb-r?

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