← Back to home
Comparison · Analytics

kernelshap vs n2kanalysis

A side-by-side editorial comparison of kernelshap and n2kanalysis — release velocity, themes, recent moves, and the top alternatives to consider.

kernelshap vs n2kanalysis: at a glance

Featurekernelshapn2kanalysis
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesshap, model explainability, sampling algorithms, numerical correctnessbiodiversity-monitoring, inla, bayesian-models, s3-storage
Last editorial update4h 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 n2kanalysis?

n2kanalysis has spent eight years wiring INLA models to an S3 bucket.

n2kanalysis is the analysis framework behind INBO's nature monitoring networks, wrapping INLA model fitting with a manifest-driven pipeline whose intermediate objects live in S3. Capability has arrived in discrete lumps: hurdle models with imputation and a manifest-to-bash converter in 0.3.1, SPDE spatial elements in INLA models in 0.4.0, and in 0.4.1 a connect_inbo_s3() function that makes temporary credentials available to the R functions.

Read the full n2kanalysis trajectory →

kernelshap vs n2kanalysis: 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.

N
n2kanalysis
ANALYTICS
0.0

n2kanalysis has spent eight years wiring INLA models to an S3 bucket.

◆ Current state

n2kanalysis is the analysis framework behind INBO's nature monitoring networks, wrapping INLA model fitting with a manifest-driven pipeline whose intermediate objects live in S3. Capability has arrived in discrete lumps: hurdle models with imputation and a manifest-to-bash converter in 0.3.1, SPDE spatial elements in INLA models in 0.4.0, and in 0.4.1 a connect_inbo_s3() function that makes temporary credentials available to the R functions.

◆ Where it's heading

Development is slow, institutional, and driven by the modeling needs of specific monitoring programmes rather than a product roadmap. The pattern across the window is a new model class when the ecology requires one, then a stretch of infrastructure work around storage, credentials and pipeline efficiency. The 0.4.1 release is characteristic — a credentials helper, better result retrieval, more tests and a code-style pass, with no modeling change at all. Much of the early history is recorded only as merge-commit titles, so the release record thins out the further back it goes.

◆ Prediction

Expect the next substantive release to add another INLA model variant as a monitoring programme needs it, with S3 and credential handling continuing to absorb the maintenance effort in between.

Alternatives to kernelshap and n2kanalysis

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 n2kanalysis.

See all kernelshap alternatives → · See all n2kanalysis alternatives →

Recent activity from kernelshap and n2kanalysis

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

  1. 4mo agon2kanalysisconnect_inbo_s3() exposes temporary credentials to R
  2. 1y agokernelshapKernel weight bug fixed; parallelism moves to doFuture
  3. 1y agokernelshapSampling permutation SHAP with standard errors
  4. 1y agon2kanalysisINLA models with SPDE elements supported
  5. 1y agokernelshapBackground data now optional; ranger survival support
  6. 2y agokernelshapFactor-valued predictions dropped
  7. 2y agokernelshapadditive_shap() explains additive models exactly
  8. 2y agon2kanalysisfit_model() made more efficient
  9. 2y agokernelshapFaster on plain data.frames
  10. 3y agon2kanalysisHurdle models with imputation added
  11. 7y agon2kanalysisImputed data handling improvements
  12. 7y agon2kanalysisINLA models consolidated onto a single class

Frequently asked questions

What is the difference between kernelshap and n2kanalysis?

They serve adjacent needs but don't currently overlap on shipped themes. kernelshap and n2kanalysis 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 n2kanalysis?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. kernelshap and n2kanalysis 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 n2kanalysis?

Top n2kanalysis alternatives in Analytics are ranked by recent ship velocity. Browse the "n2kanalysis alternatives" section above for the current picks, or visit /alternatives/n2kanalysis for the full list with editorial commentary on each.