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e2tree vs forrel

A side-by-side editorial comparison of e2tree and forrel — release velocity, themes, recent moves, and the top alternatives to consider.

e2tree vs forrel: at a glance

Featuree2treeforrel
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesexplainable-ai, ensemble-methods, decision-trees, r-packageforensic genetics, kinship analysis, simulation, parallel computing
Last editorial update1h ago1d ago
WebsiteVisit →Visit →

What is e2tree?

The explainable-ensemble-tree package now measures whether its own explanations are faithful.

e2tree builds a single interpretable tree that approximates a fitted ensemble, working from the proximity structure the ensemble induces between observations. The 1.0.0 release added the piece that had been missing: a Goodness of Interpretability index quantifying how well the approximating tree reconstructs the ensemble's own proximity matrix, with a permutation test for significance. Interactive visualisation and a C++ backend with OpenMP parallelism arrived alongside, and support now spans ranger and CatBoost as well as the original targets.

Read the full e2tree trajectory →

What is forrel?

forrel is getting faster at the simulations forensic kinship work actually spends its time on.

forrel handles forensic pedigree analysis: kinship likelihood ratios, profile simulation, relationship checking, and missing person calculations. Version 1.9.0 synced with pedtools 2.11.0's loop handling, which the release notes credit with enabling complex pedigrees that were previously intractable, and moved profileSim() to mirai for parallelism. It also added fEstimate() for inbreeding coefficients and parentChildLikelihood() as a fast path for the simplest case.

Read the full forrel trajectory →

e2tree vs forrel: editorial side-by-side

E
e2tree
ANALYTICS
0.0

The explainable-ensemble-tree package now measures whether its own explanations are faithful.

◆ Current state

e2tree builds a single interpretable tree that approximates a fitted ensemble, working from the proximity structure the ensemble induces between observations. The 1.0.0 release added the piece that had been missing: a Goodness of Interpretability index quantifying how well the approximating tree reconstructs the ensemble's own proximity matrix, with a permutation test for significance. Interactive visualisation and a C++ backend with OpenMP parallelism arrived alongside, and support now spans ranger and CatBoost as well as the original targets.

◆ Where it's heading

Development has moved from producing an explanation to defending it. The GoI index and its permutation test change the package's claim from here is a tree that resembles your ensemble to here is how closely it resembles it and whether that could have happened by chance — the question a reviewer asks of any surrogate model. Around that, the work is engineering: the proximity matrix construction moved from R-level parallel loops into C++ with thread-level parallelism, and recent releases have been absorbing the awkwardness of supporting multiple ensemble backends, where a multi-class CatBoost objective returns a score matrix where a vector was expected. Interactive visNetwork output and standalone HTML export point at explanations meant to be shared rather than only inspected.

◆ Prediction

Given how much recent effort has gone into per-backend adapters, expect further work on ensemble compatibility; the entries do not indicate whether the interpretability index is heading toward comparing surrogate trees against each other.

F
forrel
ANALYTICS
0.0

forrel is getting faster at the simulations forensic kinship work actually spends its time on.

◆ Current state

forrel handles forensic pedigree analysis: kinship likelihood ratios, profile simulation, relationship checking, and missing person calculations. Version 1.9.0 synced with pedtools 2.11.0's loop handling, which the release notes credit with enabling complex pedigrees that were previously intractable, and moved profileSim() to mirai for parallelism. It also added fEstimate() for inbreeding coefficients and parentChildLikelihood() as a fast path for the simplest case.

◆ Where it's heading

Two long threads run through the window. One is making the common operations cheap: faster simulations through reorganized likelihood calculations, a dedicated parent-child path, dropped map attribute preservation, log-likelihoods to avoid underflow in kinshipLR(). The other is making relationship checking presentable, with checkPairwise() growing ggplot2 and plotly output, verbal relationship descriptions, and bootstrap p-values. Reference data is maintained alongside both, with the FORCE SNP panel completed and an X-chromosomal counterpart added.

◆ Prediction

With profileSim() on mirai and the loop handling synced, the next likely step is extending mirai parallelism to the other simulation-heavy functions such as exclusionPower() and the bootstrap in checkPairwise().

Alternatives to e2tree and forrel

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 e2tree or forrel.

See all e2tree alternatives → · See all forrel alternatives →

Recent activity from e2tree and forrel

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

  1. 1mo agoforrelmirai parallelism and faster profile simulation
  2. 3mo agoe2treeCatBoost multi-class and loss-function handling repaired
  3. 4mo agoe2treeA significance-tested measure of explanation fidelity
  4. 1y agoforrelFORCE SNP panel completed and X-chromosomal set added
  5. 1y agoe2treeranger models supported
  6. 1y agoforrelrankProfiles() and access to special lumping
  7. 1y agoforrelacrossComps argument and readFam() unexported
  8. 1y agoforrelcheckPairwise() overhauled with p-values and new plot backends
  9. 2y agoforrelFamilias interoperability split into pedFamilias

Frequently asked questions

What is the difference between e2tree and forrel?

They serve adjacent needs but don't currently overlap on shipped themes. e2tree and forrel 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 e2tree better than forrel?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. e2tree and forrel 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 e2tree?

Top e2tree alternatives in Analytics are ranked by recent ship velocity. Browse the "e2tree alternatives" section above for the current picks, or visit /alternatives/e2tree for the full list with editorial commentary on each.

What are the best alternatives to forrel?

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