paleobuddy
paleobuddy can now simulate trait-dependent diversification, not just birth-death.
A side-by-side editorial comparison of enpls and shapviz — release velocity, themes, recent moves, and the top alternatives to consider.
enpls has not changed its statistics since 2016 — only its website, twice.
enpls implements ensemble partial least squares regression, with variants for feature selection, outlier detection and model applicability. Across the six most recent releases there is not one change to the modeling code. They cover a documentation website, a website URL change, a font stack, code indentation, a CI service, and most recently a GitHub Actions migration with an R CMD check note fix.
shapviz refines its SHAP plots release by release while chasing ggplot2's moving target.
shapviz turns SHAP values from XGBoost, LightGBM, H2O, kernelshap and other sources into standard diagnostic plots — importance, dependence, waterfall, force and interaction. Recent work is plot ergonomics: shared y-axis control across dependence plots, a bar view for interaction values, and axis collection via patchwork. The two most recent releases are pure compatibility and bug fixes.
enpls implements ensemble partial least squares regression, with variants for feature selection, outlier detection and model applicability. Across the six most recent releases there is not one change to the modeling code. They cover a documentation website, a website URL change, a font stack, code indentation, a CI service, and most recently a GitHub Actions migration with an R CMD check note fix.
The statistical work finished around version 5.6, which added cross-validation fold control and fixed component selection when the maximum was left unspecified. Everything since has kept the package installable and its docs online. The 2025 release arriving the same day as sibling package grex, with the same two fixes, confirms the pattern: these are maintainer sweeps across a portfolio, not attention to enpls specifically.
The next release will almost certainly be another CRAN or tooling fix. Six consecutive infrastructure-only releases across nine years give no basis for expecting new methods.
shapviz turns SHAP values from XGBoost, LightGBM, H2O, kernelshap and other sources into standard diagnostic plots — importance, dependence, waterfall, force and interaction. Recent work is plot ergonomics: shared y-axis control across dependence plots, a bar view for interaction values, and axis collection via patchwork. The two most recent releases are pure compatibility and bug fixes.
Two threads run in parallel here. One is visual refinement converging on conventions from Python's shap — the 0.10.0 notes openly float switching share_y to TRUE to match it. The other is connector maintenance, keeping pace with H2O, XGBoost 1.x and 2.x, shapr and permshap as each changes. Neither thread adds new explanation methods; shapviz's job is presentation, and it is being polished rather than extended.
Expect share_y = TRUE to become the default and further ggplot2 4.x fallout, with connector updates arriving as the upstream SHAP packages release.
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 enpls or shapviz.
paleobuddy can now simulate trait-dependent diversification, not just birth-death.
geodist stays dependency-free and fast, and warns you when 'cheap' distances stop being honest.
errors keeps making uncertainty print the way each scientific field expects.
CMAQ went global in v5.5, and has been patching that surface ever since.
grex is a lookup table with a version number — it ships when the annotation moves.
protr's feature set is finished; the work now is surviving Bioconductor's churn.
See all enpls alternatives → · See all shapviz alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. enpls and shapviz 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.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. enpls and shapviz 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.
Top enpls alternatives in Analytics are ranked by recent ship velocity. Browse the "enpls alternatives" section above for the current picks, or visit /alternatives/enpls for the full list with editorial commentary on each.
Top shapviz alternatives in Analytics are ranked by recent ship velocity. Browse the "shapviz alternatives" section above for the current picks, or visit /alternatives/shapviz for the full list with editorial commentary on each.