nflreadr
The nflverse data loader, whose releases are dictated by the NFL calendar and CRAN's archive policy
Comparison · Analytics
e2tree vs reliaplotr
A side-by-side editorial comparison of e2tree and reliaplotr — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
e2tree vs reliaplotr: at a glance
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.
What is reliaplotr?
The Weibull plotting package renamed itself, then handed its charts to AI assistants.
ReliaPlotR draws interactive reliability plots with plotly — probability plots, contour plots, Duane and reliability growth charts, accelerated life testing plots by stress level, mean cumulative function curves for repairable systems, and exposure plots. It was WeibullR.plotly until late 2025, and the rename tracked a real widening of scope rather than just a label change. The current release adds tidy extractors that turn fitted model objects into data frames, and an MCP server exposing five of its fit and plot functions as tools.
e2tree vs reliaplotr: editorial side-by-side
e2tree
0.0ANALYTICS
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.
reliaplotr
0.0ANALYTICS
The Weibull plotting package renamed itself, then handed its charts to AI assistants.
◆ Current state
ReliaPlotR draws interactive reliability plots with plotly — probability plots, contour plots, Duane and reliability growth charts, accelerated life testing plots by stress level, mean cumulative function curves for repairable systems, and exposure plots. It was WeibullR.plotly until late 2025, and the rename tracked a real widening of scope rather than just a label change. The current release adds tidy extractors that turn fitted model objects into data frames, and an MCP server exposing five of its fit and plot functions as tools.
◆ Where it's heading
The package has been following its analysis siblings function for function: as accelerated life testing and repairable systems modelling landed in the wider suite, the matching plot types appeared here, and when the growth-analysis package shipped an MCP server, this one followed two weeks later. The tidy extractors point the same way — a plotting package that can also return parameter estimates, goodness-of-fit metrics, and confidence bounds as tidy frames is one designed to be consumed programmatically, by a pipeline or an assistant, not only read on screen. Overlaying multiple model fits on a single plot has been a recurring request answered across several releases.
◆ Prediction
Expect the tidy extractor and MCP tool surfaces to keep expanding together, since each new plot type in the suite now implies both a chart and a machine-readable version of what it shows.
Alternatives to e2tree and reliaplotr
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 reliaplotr.
susier
Fine-mapping workhorse susieR spends its releases hunting null-effect trimming bugs
UCell
A rank-based gene signature scorer that has grown by adapting to whatever object format single-cell R uses next
detectseparation
A diagnostic package that generalized past its own name, then learned to say which kind of separation it found
brglm2
A bias-reduction package reaches 1.0 by adding an estimator built for high-dimensional logistic regression
bayestools
The JAGS toolkit under RoBMA, shipping the standardization machinery its downstream rewrite needed
See all e2tree alternatives → · See all reliaplotr alternatives →
Recent activity from e2tree and reliaplotr
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 2mo agoreliaplotrTidy model extractors plus five plotting tools over MCP ⚡
- 2mo agoreliaplotrNHPP plots switch to the mean cumulative function
- 3mo agoe2treeCatBoost multi-class and loss-function handling repaired
- 4mo agoreliaplotrAccelerated life testing and repairable systems plots added
- 4mo agoe2treeA significance-tested measure of explanation fidelity ⚡
- 8mo agoreliaplotrDuane plots gain confidence bounds
- 9mo agoreliaplotrReliaPlotR v0.4.1
- 10mo agoreliaplotrRenamed from WeibullR.plotly to ReliaPlotR
- 1y agoe2treeranger models supported
Frequently asked questions
What is the difference between e2tree and reliaplotr?
Both compete on the same themes — r-package — within Analytics. e2tree and reliaplotr 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 reliaplotr?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. e2tree and reliaplotr 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 reliaplotr?
Top reliaplotr alternatives in Analytics are ranked by recent ship velocity. Browse the "reliaplotr alternatives" section above for the current picks, or visit /alternatives/reliaplotr for the full list with editorial commentary on each.