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mutagen vs treeshap

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

mutagen vs treeshap: at a glance

Featuremutagentreeshap
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesdata-manipulation, tidyverse, stata-port, r-packageshap, model explainability, tree ensembles, r package
Last editorial update56m ago7h ago
WebsiteVisit →Visit →

What is mutagen?

A young package porting Stata's egen row-wise helpers to the tidyverse, one function per release

mutagen provides row-wise column-generation helpers for R data frames in the spirit of Stata's egen — gen_rowmean(), gen_rowsum(), gen_rowsd(), gen_rownonmiss() and about a dozen siblings. It reached 0.5.0 within three months of its first release, adding two or three functions each time. The most recent release adds gen_coldiff() and renames two functions to fit the naming scheme.

Read the full mutagen trajectory →

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.

Read the full treeshap trajectory →

mutagen vs treeshap: editorial side-by-side

M
mutagen
ANALYTICS
0.0

A young package porting Stata's egen row-wise helpers to the tidyverse, one function per release

◆ Current state

mutagen provides row-wise column-generation helpers for R data frames in the spirit of Stata's egen — gen_rowmean(), gen_rowsum(), gen_rowsd(), gen_rownonmiss() and about a dozen siblings. It reached 0.5.0 within three months of its first release, adding two or three functions each time. The most recent release adds gen_coldiff() and renames two functions to fit the naming scheme.

◆ Where it's heading

The package is filling out a known surface rather than discovering one: the reference implementation exists in Stata, so development is a matter of working through the list. Alongside that, the naming convention is still settling — gen_rowmatch became gen_rowany, gen_percent became gen_colpercent, gen_na_listcol became gen_listcol_na — which is normal for a pre-1.0 package but means callers should expect further renames. Contributions are arriving from several first-time contributors.

◆ Prediction

The gen_col* prefix has only two members against a dozen gen_row* functions, so column-wise coverage is the obvious gap; expect it to fill before the naming stabilises for a 1.0.

T
treeshap
ANALYTICS
0.0

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 mutagen 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 mutagen or treeshap.

See all mutagen alternatives → · See all treeshap alternatives →

Recent activity from mutagen and treeshap

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

  1. 3mo agotreeshapGPBoost support lands; xgboost adapter repaired
  2. 8mo agomutagengen_coldiff() added; two functions renamed for consistency
  3. 9mo agomutagengen_rowsum() and gen_rowsd() added
  4. 9mo agomutagengen_rownonmiss() and gen_rowall() added
  5. 9mo agomutagenRow mean, median and missingness helpers; gen_rowmatch renamed
  6. 11mo agomutagenFirst release with the row-wise gen_* family
  7. 2y agotreeshapFixes broken lightgbm.unify examples
  8. 2y agotreeshapMulti-output model explanations added
  9. 2y agotreeshapFirst CRAN release consolidates the unify() adapters

Frequently asked questions

What is the difference between mutagen and treeshap?

They serve adjacent needs but don't currently overlap on shipped themes. mutagen 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 mutagen better than treeshap?

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

Top mutagen alternatives in Analytics are ranked by recent ship velocity. Browse the "mutagen alternatives" section above for the current picks, or visit /alternatives/mutagen-r 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.