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Comparison · Analytics
kernelshap vs shapviz
A side-by-side editorial comparison of kernelshap and shapviz — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:shapmodel explainabilityr package
kernelshap vs shapviz: at a glance
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.
What is shapviz?
shapviz refines its SHAP plots release by release while chasing ggplot2's moving target.
shapviz turns SHAP values from XGBoost, LightGBM, H2O, kernelshap and other sources into standard diagnostic plots — importance, dependence, waterfall, force and interaction. Recent work is plot ergonomics: shared y-axis control across dependence plots, a bar view for interaction values, and axis collection via patchwork. The two most recent releases are pure compatibility and bug fixes.
kernelshap vs shapviz: editorial side-by-side
kernelshap
0.0ANALYTICS
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.
shapviz
0.0ANALYTICS
shapviz refines its SHAP plots release by release while chasing ggplot2's moving target.
◆ Current state
shapviz turns SHAP values from XGBoost, LightGBM, H2O, kernelshap and other sources into standard diagnostic plots — importance, dependence, waterfall, force and interaction. Recent work is plot ergonomics: shared y-axis control across dependence plots, a bar view for interaction values, and axis collection via patchwork. The two most recent releases are pure compatibility and bug fixes.
◆ Where it's heading
Two threads run in parallel here. One is visual refinement converging on conventions from Python's shap — the 0.10.0 notes openly float switching share_y to TRUE to match it. The other is connector maintenance, keeping pace with H2O, XGBoost 1.x and 2.x, shapr and permshap as each changes. Neither thread adds new explanation methods; shapviz's job is presentation, and it is being polished rather than extended.
◆ Prediction
Expect share_y = TRUE to become the default and further ggplot2 4.x fallout, with connector updates arriving as the upstream SHAP packages release.
Alternatives to kernelshap and shapviz
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 shapviz.
geoarrow-r
geoarrow tracks the GeoArrow spec and otherwise just keeps compiling
n2khab
n2khab keeps retracting interpretations of habitat data it can't actually support
tidypolars
tidypolars is grinding toward complete dplyr coverage, one supported function at a time
OneSampleMR
OneSampleMR found that argument order in a formula was silently changing its estimates
bpbounds
bpbounds found the same swapped-cell bug twice and clamped its bounds back into range
See all kernelshap alternatives → · See all shapviz alternatives →
Recent activity from kernelshap and shapviz
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 10mo agoshapvizggplot 4.0 compatibility fix
- 1y agokernelshapKernel weight bug fixed; parallelism moves to doFuture
- 1y agoshapvizFixes duplicated bars in sv_interaction()
- 1y agokernelshapSampling permutation SHAP with standard errors ⚡
- 1y agoshapvizggplot2 and patchwork dependency bumps
- 1y agoshapvizShared y-axis control and bar-style interaction plots
- 1y agoshapvizH2O random forests gain TreeSHAP support
- 1y agoshapvizFixes a broken vignette link
- 1y agokernelshapBackground data now optional; ranger survival support
- 2y agokernelshapFactor-valued predictions dropped
- 2y agokernelshapadditive_shap() explains additive models exactly
- 2y agokernelshapFaster on plain data.frames
Frequently asked questions
What is the difference between kernelshap and shapviz?
Both compete on the same themes — shap, model explainability, r package — within Analytics. kernelshap and shapviz 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 shapviz?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. kernelshap and shapviz 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 shapviz?
Top shapviz alternatives in Analytics are ranked by recent ship velocity. Browse the "shapviz alternatives" section above for the current picks, or visit /alternatives/shapviz for the full list with editorial commentary on each.