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Comparison · Analytics
parallelDist vs treeshap
A side-by-side editorial comparison of parallelDist and treeshap — release velocity, themes, recent moves, and the top alternatives to consider.
parallelDist vs treeshap: at a glance
What is parallelDist?
parallelDist is in pure preservation mode — one build fix every few years.
parallelDist computes distance matrices across threads in C++ via RcppParallel and Armadillo. The feature set has been settled since 0.2.3 in 2018, which added hamming distance and cosine similarity; everything after that is compatibility work. The most recent release, 0.2.7, exists only to drop a C++11 pin that newer Armadillo versions no longer tolerate.
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.
parallelDist vs treeshap: editorial side-by-side
parallelDist
0.0ANALYTICS
parallelDist is in pure preservation mode — one build fix every few years.
◆ Current state
parallelDist computes distance matrices across threads in C++ via RcppParallel and Armadillo. The feature set has been settled since 0.2.3 in 2018, which added hamming distance and cosine similarity; everything after that is compatibility work. The most recent release, 0.2.7, exists only to drop a C++11 pin that newer Armadillo versions no longer tolerate.
◆ Where it's heading
The package is being kept installable, not developed. The three most recent releases are a toolchain pin removal, a DESCRIPTION field removal, and a coercion change inherited from proxy — none originate from user-facing intent. Gaps of three to four years between releases are the norm now, and each one is triggered by something upstream breaking rather than by a roadmap.
◆ Prediction
The next release will almost certainly be another compatibility fix timed to whatever Armadillo, Rcpp or CRAN check policy changes next. Nothing in the entries points to new distance measures or API work.
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 parallelDist 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 parallelDist or treeshap.
geodist
geodist stays dependency-free and fast, and warns you when 'cheap' distances stop being honest.
errors
errors keeps making uncertainty print the way each scientific field expects.
CMAQ
CMAQ went global in v5.5, and has been patching that surface ever since.
enpls
enpls has not changed its statistics since 2016 — only its website, twice.
grex
grex is a lookup table with a version number — it ships when the annotation moves.
See all parallelDist alternatives → · See all treeshap alternatives →
Recent activity from parallelDist and treeshap
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 3mo agotreeshapGPBoost support lands; xgboost adapter repaired
- 10mo agoparallelDistparallelDist 0.2.7 drops the C++11 pin for newer Armadillo
- 2y agotreeshapFixes broken lightgbm.unify examples
- 2y agotreeshapMulti-output model explanations added
- 2y agotreeshapFirst CRAN release consolidates the unify() adapters ⚡
- 4y agoparallelDistparallelDist 0.2.6: LazyData removed, vignette font swapped
- 4y agoparallelDistparallelDist 0.2.5 changes cosine distance to 1-x
- 7y agoparallelDistparallelDist 0.2.4 fixes the Solaris build
- 7y agoparallelDistparallelDist 0.2.3 adds hamming and cosine measures
- 7y agoparallelDistparallelDist 0.2.2
Frequently asked questions
What is the difference between parallelDist and treeshap?
They serve adjacent needs but don't currently overlap on shipped themes. parallelDist 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 parallelDist better than treeshap?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. parallelDist 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 parallelDist?
Top parallelDist alternatives in Analytics are ranked by recent ship velocity. Browse the "parallelDist alternatives" section above for the current picks, or visit /alternatives/paralleldist 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.