← Back to home
Comparison · Analytics

dggridR vs kernelshap

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

dggridR vs kernelshap: at a glance

FeaturedggridRkernelshap
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesdiscrete-global-grids, spatial-indexing, geospatial, hexagonal-gridsshap, model explainability, sampling algorithms, numerical correctness
Last editorial update50m ago2h ago
WebsiteVisit →Visit →

What is dggridR?

A discrete global grid generator grew cell traversal and became a usable spatial index.

dggridR builds discrete global grids — icosahedral tessellations of the Earth into equal-area hexagonal or triangular cells — by wrapping the DGGRID C++ engine. The 4.1.0 release adds dgneighbors, dgchildren and dgparent for moving between adjacent cells and across resolutions, plus dgpoints_to_cells and dgbin_points for mapping and aggregating point data into cells. New aperture 7 and mixed-aperture ISEA43H grid types arrive alongside them.

Read the full dggridR trajectory →

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 →

dggridR vs kernelshap: editorial side-by-side

D
dggridR
ANALYTICS
0.0

A discrete global grid generator grew cell traversal and became a usable spatial index.

◆ Current state

dggridR builds discrete global grids — icosahedral tessellations of the Earth into equal-area hexagonal or triangular cells — by wrapping the DGGRID C++ engine. The 4.1.0 release adds dgneighbors, dgchildren and dgparent for moving between adjacent cells and across resolutions, plus dgpoints_to_cells and dgbin_points for mapping and aggregating point data into cells. New aperture 7 and mixed-aperture ISEA43H grid types arrive alongside them.

◆ Where it's heading

The package changed hands in effect as well as in code: the 4.0.0 engine update to DGGRID v9.0b and the first real test suite were contributed by Sebastian Krantz, who also maintains the upstream engine fork, and 4.1.0's feature burst followed two weeks later. The direction of that burst is unmistakable — away from generating grids for plotting and toward using them as an indexing structure that point data gets binned into and navigated through.

◆ Prediction

Expect the cell hierarchy functions to extend to non-hexagonal apertures and multi-level traversal, closing the remaining gaps against established global indexing systems.

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.

Alternatives to dggridR and kernelshap

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 dggridR or kernelshap.

See all dggridR alternatives → · See all kernelshap alternatives →

Recent activity from dggridR and kernelshap

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

  1. 3mo agodggridRCell neighbors, parents and children make the grid navigable
  2. 3mo agodggridRBundled DGGRID engine updated to v9.0b with a test suite
  3. 3mo agodggridRMaster merged into development ahead of the 4.0 work
  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 agokernelshapFaster on plain data.frames

Frequently asked questions

What is the difference between dggridR and kernelshap?

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

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

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

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.