← Back to home
Comparison · Analytics

kernelshap vs xts

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

kernelshap vs xts: at a glance

Featurekernelshapxts
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesshap, model explainability, sampling algorithms, numerical correctnessr, time-series, finance, c-api
Last editorial update6h ago53m 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 xts?

xts is finished software, and its releases now track R's C API more than user requests.

xts is the time-series class underpinning much of R's financial stack, and it behaves like infrastructure: the visible releases are bug fixes, plotting repairs and conformance work. A recurring thread is removing calls R no longer considers public — SET_TYPEOF in 0.14.0 and 0.14.1, then ATTRIB() and SET_ATTRIB() in 0.14.2. Feature additions are rare and small, the last cluster being open-ended time-of-day subsetting and na.fill performance in 0.13.0.

Read the full xts trajectory →

kernelshap vs xts: 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.

X
xts
ANALYTICS
0.0

xts is finished software, and its releases now track R's C API more than user requests.

◆ Current state

xts is the time-series class underpinning much of R's financial stack, and it behaves like infrastructure: the visible releases are bug fixes, plotting repairs and conformance work. A recurring thread is removing calls R no longer considers public — SET_TYPEOF in 0.14.0 and 0.14.1, then ATTRIB() and SET_ATTRIB() in 0.14.2. Feature additions are rare and small, the last cluster being open-ended time-of-day subsetting and na.fill performance in 0.13.0.

◆ Where it's heading

Two forces drive releases. R core keeps narrowing its public C API, and xts keeps rewriting internals to stay inside it; separately, ggplot-era changes elsewhere in the ecosystem surface plotting bugs that get fixed one report at a time. Nearly every entry credits an outside reporter, which is what maintenance of a dependency this widely used looks like.

◆ Prediction

Further C API conformance work is the safest expectation, since two consecutive releases have each removed a different non-API entry point and R has continued tightening that boundary.

Alternatives to kernelshap and xts

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 xts.

See all kernelshap alternatives → · See all xts alternatives →

Recent activity from kernelshap and xts

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

  1. 5mo agoxtsmulti.panel plots beyond 8 columns; SET_TYPEOF removed from C
  2. 5mo agoxtsATTRIB removed from C; rollapply.xts accepts vector widths
  3. 1y agokernelshapKernel weight bug fixed; parallelism moves to doFuture
  4. 1y agokernelshapSampling permutation SHAP with standard errors
  5. 1y agokernelshapBackground data now optional; ranger survival support
  6. 2y agokernelshapFactor-valued predictions dropped
  7. 2y agoxtsMulti-panel event lines; first SET_TYPEOF replacement
  8. 2y agoxtstclass changes now alter index values; log-scale y-axis added
  9. 2y agokernelshapadditive_shap() explains additive models exactly
  10. 2y agokernelshapFaster on plain data.frames
  11. 3y agoxtsUpdate path for pre-0.12 objects missing index attributes
  12. 3y agoxtsOpen-ended time-of-day subsetting; fast scalar na.fill

Frequently asked questions

What is the difference between kernelshap and xts?

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

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

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