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Alternatives · analytics tools
kernelshap alternatives
The best kernelshap alternatives in analytics tools, ranked by Sparkpulse's velocity_score.
Updated Aug 15, 2026
Looking for the best alternatives to kernelshap? Sparkpulse tracks and ranks 12 alternatives in analytics tools by shipping velocity — how frequently each ships meaningful updates, verified from official changelogs. For reference, kernelshap shipped 0 meaningful updates in the last 30 days and carries a velocity score of 0.0 out of 10 in 2026. The alternatives below are ranked the same way, so you're comparing real release momentum, not marketing claims.
About 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.
Velocity 0.0 · Last update 50m ago
Top 12 alternatives to kernelshap
Ranked by recent ship velocity. Tap any card for the full editorial breakdown, or pivot to a head-to-head.
ANALYTICS
dbt-core spent a day backporting one deprecation warning across eight EOL branches — the message is: upgrade.
ANALYTICS
After the 836-commit 0.92 release, OpenObserve is quietly moving its MCP server into the free tier
ANALYTICS
A Bayesian real-time CFR estimator that now ships stratified fits and posterior-predictive checks
ANALYTICS
camtrapdp has become a full read-edit-write toolkit for camera trap datasets, then went quiet
ANALYTICS
spatstat's inference layer builds out determinantal and cluster process fitting
ANALYTICS
The geometry layer under spatstat, steadily absorbing 3D patterns and missing-data semantics
ANALYTICS
spatstat's simulation engine pushes point process generation into three dimensions
ANALYTICS
Clinical-table typesetting for R, closing the gap between R output and regulatory Word documents
ANALYTICS
monitOS relicenses to MIT, the clearest signal in a sparse Novartis release feed.
ANALYTICS
filtro moves to S7 and multiplies its feature-scoring methods in a single release.
ANALYTICS
modeltime.resample exists to keep backtesting working as tidymodels shifts underneath it.
kernelshap vs alternatives — shipping velocity at a glance
Velocity score (0–10) and meaningful releases shipped in the last 30 days, from official changelogs. Higher = shipping faster.
| Product | Velocity | Sparks · 30d | Focus areas | Latest release |
|---|---|---|---|---|
| kernelshap (baseline) | 0.0 | 0 | shapmodel explainabilitysampling algorithms | Sampling permutation SHAP with standard errors |
| Basedash | 7.5 | 1 | ai-analystprescriptive-analyticsembedded-bi | Introducing Tasks: your operations, on autopilot |
| dbt Core | 7.5 | 0 | analytics-engineeringdeprecationbackports | — |
| OpenObserve | 6.3 | 1 | observabilitymcpopen-source | v0.92.0 adds synthetic monitoring, workflows, and AI observability |
| cfrnow | 5.0 | 0 | epidemiologybayesian-modellingcfr-estimation | First release: real-time CFR from a Bayesian mixture-cure model |
| camtrapdp | 2.5 | 0 | camera trapsbiodiversity datar | camtrapdp 0.4.0 closes the read-edit-write loop for Camtrap DP |
| spatstat.model | 2.5 | 0 | spatial-statisticspoint-processesmodel-fitting | — |
| spatstat.geom | 2.5 | 0 | spatial-statisticscomputational-geometryr-package | — |
| spatstat.random | 2.5 | 0 | spatial-statisticspoint-processessimulation | Three-dimensional point process simulation arrives |
| clinify | 2.5 | 0 | clinical-trialsr-packagedocument-generation | — |
| monitOS | 0.0 | 0 | clinical trialsoverall survivalnovartis | — |
| filtro | 0.0 | 0 | feature selectiontidymodelss7 | Five new filter scores and the move to S7 |
| modeltime.resample | 0.0 | 0 | time seriescross-validationtidymodels | — |
The 12 best kernelshap alternatives, in depth
1. Basedash · velocity 7.5
Basedash is done answering questions about your data — it now wants to tell you what to do next.
Over the last 30 days Basedash shipped 1 meaningful update vs kernelshap's 0, most recently “Introducing Tasks: your operations, on autopilot”. Its velocity score of 7.5/10 blends that with longer-term release cadence.
Where kernelshap leans on shap, model explainability and sampling algorithms, Basedash focuses on ai analyst, prescriptive analytics and embedded bi.
Over the last 30 days Basedash has been shipping faster than kernelshap — a point in its favour if release momentum matters to you.
Full Basedash trajectory → · Compare kernelshap vs Basedash →
2. dbt Core · velocity 7.5
Dbt-core spent a day backporting one deprecation warning across eight EOL branches — the message is: upgrade.
Its velocity score of 7.5/10 reflects longer-term release cadence.
Where kernelshap leans on shap, model explainability and sampling algorithms, dbt Core focuses on analytics engineering, deprecation and backports.
dbt Core and kernelshap have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.
Full dbt Core trajectory → · Compare kernelshap vs dbt Core →
3. OpenObserve · velocity 6.3
After the 836-commit 0.92 release, OpenObserve is quietly moving its MCP server into the free tier.
Over the last 30 days OpenObserve shipped 1 meaningful update vs kernelshap's 0, most recently “v0.92.0 adds synthetic monitoring, workflows, and AI observability”. Its velocity score of 6.3/10 blends that with longer-term release cadence.
Where kernelshap leans on shap, model explainability and sampling algorithms, OpenObserve focuses on observability, mcp and open source.
Over the last 30 days OpenObserve has been shipping faster than kernelshap — a point in its favour if release momentum matters to you.
Full OpenObserve trajectory → · Compare kernelshap vs OpenObserve →
4. cfrnow · velocity 5.0
A Bayesian real-time CFR estimator that now ships stratified fits and posterior-predictive checks.
Its velocity score of 5.0/10 reflects longer-term release cadence; its most recent meaningful update was “First release: real-time CFR from a Bayesian mixture-cure model”.
Where kernelshap leans on shap, model explainability and sampling algorithms, cfrnow focuses on epidemiology, bayesian modelling and cfr estimation.
cfrnow and kernelshap have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.
5. camtrapdp · velocity 2.5
Camtrapdp has become a full read-edit-write toolkit for camera trap datasets, then went quiet.
Its velocity score of 2.5/10 reflects longer-term release cadence; its most recent meaningful update was “camtrapdp 0.4.0 closes the read-edit-write loop for Camtrap DP”.
Where kernelshap leans on shap, model explainability and sampling algorithms, camtrapdp focuses on camera traps, biodiversity data and r.
camtrapdp and kernelshap have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.
Full camtrapdp trajectory → · Compare kernelshap vs camtrapdp →
6. spatstat.model · velocity 2.5
Spatstat's inference layer builds out determinantal and cluster process fitting.
Its velocity score of 2.5/10 reflects longer-term release cadence.
Where kernelshap leans on shap, model explainability and sampling algorithms, spatstat.model focuses on spatial statistics, point processes and model fitting.
spatstat.model and kernelshap have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.
Full spatstat.model trajectory → · Compare kernelshap vs spatstat.model →
7. spatstat.geom · velocity 2.5
The geometry layer under spatstat, steadily absorbing 3D patterns and missing-data semantics.
Its velocity score of 2.5/10 reflects longer-term release cadence.
Where kernelshap leans on shap, model explainability and sampling algorithms, spatstat.geom focuses on spatial statistics, computational geometry and r package.
spatstat.geom and kernelshap have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.
Full spatstat.geom trajectory → · Compare kernelshap vs spatstat.geom →
8. spatstat.random · velocity 2.5
Spatstat's simulation engine pushes point process generation into three dimensions.
Its velocity score of 2.5/10 reflects longer-term release cadence; its most recent meaningful update was “Three-dimensional point process simulation arrives”.
Where kernelshap leans on shap, model explainability and sampling algorithms, spatstat.random focuses on spatial statistics, point processes and simulation.
spatstat.random and kernelshap have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.
Full spatstat.random trajectory → · Compare kernelshap vs spatstat.random →
9. clinify · velocity 2.5
Clinical-table typesetting for R, closing the gap between R output and regulatory Word documents.
Its velocity score of 2.5/10 reflects longer-term release cadence.
Where kernelshap leans on shap, model explainability and sampling algorithms, clinify focuses on clinical trials, r package and document generation.
clinify and kernelshap have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.
10. monitOS · velocity 0.0
MonitOS relicenses to MIT, the clearest signal in a sparse Novartis release feed.
Its velocity score of 0.0/10 reflects longer-term release cadence.
Where kernelshap leans on shap, model explainability and sampling algorithms, monitOS focuses on clinical trials, overall survival and novartis.
monitOS and kernelshap have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.
11. filtro · velocity 0.0
Filtro moves to S7 and multiplies its feature-scoring methods in a single release.
Its velocity score of 0.0/10 reflects longer-term release cadence; its most recent meaningful update was “Five new filter scores and the move to S7”.
Where kernelshap leans on shap, model explainability and sampling algorithms, filtro focuses on feature selection, tidymodels and s7.
filtro and kernelshap have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.
12. modeltime.resample · velocity 0.0
Modeltime.resample exists to keep backtesting working as tidymodels shifts underneath it.
Its velocity score of 0.0/10 reflects longer-term release cadence.
Where kernelshap leans on shap, model explainability and sampling algorithms, modeltime.resample focuses on time series, cross validation and tidymodels.
modeltime.resample and kernelshap have shipped at a similar pace over the last 30 days, so the decision comes down to fit and feature depth.
Full modeltime.resample trajectory → · Compare kernelshap vs modeltime.resample →
Frequently asked questions
What are the best alternatives to kernelshap?
The top kernelshap alternatives we currently track in analytics tools are Basedash, dbt Core, OpenObserve, cfrnow, camtrapdp, ranked by recent ship velocity.
How is this list of kernelshap alternatives ranked?
Alternatives are ranked by Sparkpulse's velocity_score — release cadence + 30-day spark count + sector-relative ship rate.
Can I compare kernelshap directly with one of these alternatives?
Yes — every card has a "Compare with kernelshap" link to a side-by-side /compare page.