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e2tree vs invasimapr

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

e2tree vs invasimapr: at a glance

Featuree2treeinvasimapr
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesexplainable-ai, ensemble-methods, decision-trees, r-packageinvasion ecology, species traits, biodiversity, research software
Last editorial update1h ago3h 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 invasimapr?

invasimapr halved its install size and became citable; the science stayed put.

invasimapr estimates species invasiveness and site invasibility from trait, environmental and resident-community data, exposing a traits → competition → invasion-fitness pipeline behind seven high-level wrappers. Its three releases are all packaging and standards work: a first citable archive in June 2026, then a maturity release bringing it in line with the B-Cubed software development guide. The one behavioral addition in that release is an opt-in standardise_inputs argument on compute_invasion_fitness(), off by default.

Read the full invasimapr trajectory →

e2tree vs invasimapr: 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.

I
invasimapr
ANALYTICS
0.0

invasimapr halved its install size and became citable; the science stayed put.

◆ Current state

invasimapr estimates species invasiveness and site invasibility from trait, environmental and resident-community data, exposing a traits → competition → invasion-fitness pipeline behind seven high-level wrappers. Its three releases are all packaging and standards work: a first citable archive in June 2026, then a maturity release bringing it in line with the B-Cubed software development guide. The one behavioral addition in that release is an opt-in standardise_inputs argument on compute_invasion_fitness(), off by default.

◆ Where it's heading

The pressure is toward being installable and auditable rather than more capable — install slimmed from roughly 100 MB to 56 MB, R CMD check warnings and notes resolved, sp moved to Suggests, a Darwin Core-aligned data dictionary added, and a Zenodo concept DOI with CITATION.cff, codemeta.json and .zenodo.json. The package moves in lockstep with its B-Cubed sibling dissmapr, tagged within minutes of each other at both 0.1.0 and 0.2.1, which points at project-level standards deadlines rather than independent release decisions. Trait dispersion metrics and scenario exploration remain on the roadmap.

◆ Prediction

Standards compliance is now complete and the roadmap names functional trait dispersion metrics and scenario exploration tools, so the next release is the first that can plausibly be about invasion ecology rather than packaging.

Alternatives to e2tree and invasimapr

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 invasimapr.

See all e2tree alternatives → · See all invasimapr alternatives →

Recent activity from e2tree and invasimapr

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

  1. 1mo agoinvasimaprVersion bump; notes identical to 0.2.0
  2. 1mo agoinvasimaprB-Cubed standards alignment; install slimmed to 56 MB
  3. 1mo agoinvasimaprinvasimapr v0.1.0: First citable release
  4. 3mo agoe2treeCatBoost multi-class and loss-function handling repaired
  5. 4mo agoe2treeA significance-tested measure of explanation fidelity
  6. 1y agoe2treeranger models supported

Frequently asked questions

What is the difference between e2tree and invasimapr?

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

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

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