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kernelshap vs redist

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

kernelshap vs redist: at a glance

Featurekernelshapredist
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesshap, model explainability, sampling algorithms, numerical correctnessr, redistricting, monte-carlo, sampling
Last editorial update6h ago52m 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 redist?

redist keeps rewriting the sampler underneath a district-drawing API it has held stable since 4.0.

redist simulates redistricting plans via sequential Monte Carlo, merge-split MCMC and short-burst optimization, and it is the analysis tool behind a good deal of published districting work. The user-facing shape was set by 4.0.1's constraint interface and the split of metrics into the redistmetrics package; since then the changes are in the algorithms. The most consequential recent one replaces the SMC label-counting adjustment with a backward kernel that removes approximation error outright.

Read the full redist trajectory →

kernelshap vs redist: 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.

R
redist
ANALYTICS
0.0

redist keeps rewriting the sampler underneath a district-drawing API it has held stable since 4.0.

◆ Current state

redist simulates redistricting plans via sequential Monte Carlo, merge-split MCMC and short-burst optimization, and it is the analysis tool behind a good deal of published districting work. The user-facing shape was set by 4.0.1's constraint interface and the split of metrics into the redistmetrics package; since then the changes are in the algorithms. The most consequential recent one replaces the SMC label-counting adjustment with a backward kernel that removes approximation error outright.

◆ Where it's heading

The direction is toward exactness and throughput at once — the new kernel is described as both eliminating approximation error and costing far less computation, and successive releases keep adding parallelism, most recently to the flip algorithm. Feature growth has moved into the optimization side, where short-burst gained multiple independent scorers and a Pareto frontier. The release notes are not a reliable ledger: 4.3.1 ships the identical text as 4.3.0.

◆ Prediction

Expect the remaining single-threaded algorithms to gain the chains-style parallelism that flip just received, following the pattern SMC established several releases ago.

Alternatives to kernelshap and redist

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 redist.

See all kernelshap alternatives → · See all redist alternatives →

Recent activity from kernelshap and redist

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

  1. 6mo agoredistParallel chains for redist_flip()
  2. 6mo agoredistPatch release reusing the 4.3.0 notes
  3. 10mo agoredistSMC backward kernel removes label-counting approximation error
  4. 1y agokernelshapKernel weight bug fixed; parallelism moves to doFuture
  5. 1y agokernelshapSampling permutation SHAP with standard errors
  6. 1y agokernelshapBackground data now optional; ranger survival support
  7. 2y agokernelshapFactor-valued predictions dropped
  8. 2y agokernelshapadditive_shap() explains additive models exactly
  9. 2y agoredistMulti-objective short-burst search with Pareto frontier
  10. 2y agokernelshapFaster on plain data.frames
  11. 3y agoredistredist_ci interface and faster loop-erased random walk
  12. 4y agoredistredist_constr() unifies constraints and admits user-defined ones

Frequently asked questions

What is the difference between kernelshap and redist?

They serve adjacent needs but don't currently overlap on shipped themes. kernelshap and redist 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 redist?

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

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