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Comparison · Analytics
kernelshap vs treeshap
A side-by-side editorial comparison of kernelshap and treeshap — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:shapmodel explainabilityr package
kernelshap vs treeshap: 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 treeshap?
treeshap keeps widening its tree-model coverage while the SHAP math stays put.
treeshap computes exact SHAP values for tree ensembles in R, reaching each modelling framework through a per-framework unify() adapter. Since returning to CRAN in 2023 it has added GPBoost, ranger survival forests and multi-output models to that adapter layer. Four releases in three years, each dominated by adapter work contributed by users of one specific framework.
kernelshap vs treeshap: 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.
treeshap
0.0ANALYTICS
treeshap keeps widening its tree-model coverage while the SHAP math stays put.
◆ Current state
treeshap computes exact SHAP values for tree ensembles in R, reaching each modelling framework through a per-framework unify() adapter. Since returning to CRAN in 2023 it has added GPBoost, ranger survival forests and multi-output models to that adapter layer. Four releases in three years, each dominated by adapter work contributed by users of one specific framework.
◆ Where it's heading
The direction is breadth of model support rather than new explanation methods: every release since the first CRAN submission adds or repairs a unify() backend. Maintenance is community-driven, with named contributors fixing the framework they personally use. Nothing in these entries points at work on the SHAP algorithms themselves.
◆ Prediction
Expect the next release to add or repair another unify() adapter as a contributor brings their own framework, rather than to change how explanations are computed.
Alternatives to kernelshap and treeshap
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 treeshap.
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 treeshap alternatives →
Recent activity from kernelshap and treeshap
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 3mo agotreeshapGPBoost support lands; xgboost adapter repaired
- 1y agokernelshapKernel weight bug fixed; parallelism moves to doFuture
- 1y agokernelshapSampling permutation SHAP with standard errors ⚡
- 1y agokernelshapBackground data now optional; ranger survival support
- 2y agokernelshapFactor-valued predictions dropped
- 2y agokernelshapadditive_shap() explains additive models exactly
- 2y agotreeshapFixes broken lightgbm.unify examples
- 2y agokernelshapFaster on plain data.frames
- 2y agotreeshapMulti-output model explanations added
- 2y agotreeshapFirst CRAN release consolidates the unify() adapters ⚡
Frequently asked questions
What is the difference between kernelshap and treeshap?
Both compete on the same themes — shap, model explainability, r package — within Analytics. kernelshap and treeshap 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 treeshap?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. kernelshap and treeshap 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 treeshap?
Top treeshap alternatives in Analytics are ranked by recent ship velocity. Browse the "treeshap alternatives" section above for the current picks, or visit /alternatives/treeshap for the full list with editorial commentary on each.