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e2tree (development version)

S3 class system overhaul

  • e2tree class now properly listed as first in the class vector (c("e2tree", "list")).
  • New S3 methods for e2tree: predict(), fitted(), residuals().
  • predict.e2tree() replaces ePredTree() as the standard prediction interface. For regression, returns a data frame with fit and sd (node-level standard deviation). For classification, returns a data frame with fit, accuracy, and score.
  • fitted.e2tree() returns fitted values for training data.
  • residuals.e2tree() returns residuals for regression E2Trees.
  • methods(class = "e2tree") now shows: as.rpart, e2splits, fitted, nodes, plot, predict, print, residuals, summary.
  • methods(class = "eValidation") now shows: measures, plot, print, proximity, summary.

Accessor functions (new)

  • nodes(): Extract tree node data frame from an e2tree object, with optional terminal filter.
  • e2splits(): Extract split and categorical split information.
  • measures(): Extract validation measures from an eValidation object.
  • proximity(): Extract proximity matrices (ensemble, e2tree, or both) from an eValidation object.

Coercion methods (new)

  • as.rpart(): Generic and method for converting e2tree to rpart format.
  • as.party(): Method for converting e2tree to partykit's constparty format (registered conditionally when partykit is installed). Produces proper bar plots in terminal nodes for classification trees.
  • rpart2Tree() retained for backward compatibility with a deprecation note.

Validation framework improvements

  • eValidation() gains a test argument: "mantel" (Mantel test only), "measures" (divergence/similarity measures only), or "both" (default). This allows choosing between association testing and agreement testing.
  • print.eValidation(), summary.eValidation(), and plot.eValidation() updated to handle all three test modes gracefully.

Variable importance improvements

  • vimp(): Auto-detects classification/regression from the e2tree object; type argument now optional.
  • Fixed incorrect y-axis label ("Variance" instead of "Variable") in variable importance plots.
  • Regression variable importance bars now sorted by importance (previously unsorted).
  • Consistent column naming (Variable, MeanImpurityDecrease) across classification and regression.
  • Internal logic refactored into .vimp_classification() and .vimp_regression().

Documentation

  • All man page titles standardized to Title Case.
  • \dontrun{} replaced with \donttest{} in all examples; interactive-only examples wrapped in if (interactive()).
  • Examples updated to use accessor functions and predict() instead of direct $ access.
  • New vignette e2tree-introduction covering classification, regression, validation (Mantel test, divergence measures, LoI decomposition), and comparison with partykit/stablelearner.
  • ePredTree() documentation updated with deprecation note pointing to predict.e2tree().

Package infrastructure

  • Added partykit, knitr, rmarkdown to Suggests.
  • Added VignetteBuilder: knitr to DESCRIPTION.
  • e2tree object now stores fitted.values, y, and data for S3 method support.
  • Conditional .onLoad hook for registering as.party.e2tree when partykit is loaded.

e2tree 1.0.0

New functions

  • goi(): Goodness of Interpretability (GoI) index measuring how well the E2Tree-estimated proximity matrix reconstructs the original ensemble proximity matrix.
  • goi_perm(): Permutation test for the GoI index to assess statistical significance.
  • goi_analysis(): Combined GoI analysis returning both the observed statistic and permutation results.
  • plot.goi_perm(): Plot method for goi_perm objects displaying the permutation distribution.
  • plot_e2tree_vis(): Interactive E2Tree visualization using visNetwork with draggable nodes, zoom/pan, and multiple layout options.
  • plot_e2tree_click(): Interactive E2Tree plot in the R graphics device with click-to-inspect node details.
  • save_e2tree_html(): Save an interactive visNetwork tree plot as a standalone HTML file.
  • print_e2tree_summary(): Print a formatted summary of an e2tree object.

Performance improvements

  • createDisMatrix: C++ backend (CoOccurrences.cpp) with OpenMP thread-level parallelism replaces the R-level foreach/doParallel loop; co-occurrence normalization also moved to C++.
  • e2tree: vectorized Wt computation using vapply; simplified internal get_classes helper.
  • ePredTree: split rules are now pre-parsed once (parse_all_splits + apply_split_rule), eliminating repeated regex/eval(parse()) calls during prediction.
  • vimp: three group_by operations consolidated into one; eval/parse removed.
  • split: ordSplit and catSplit vectorized with outer().
  • eImpurity: single-step integer matrix conversion.

Bug fixes

  • Fixed Rcpp type conversion (NumericVector + static_cast<int>) for ranger compatibility (ranger returns double columns for tree node assignments).
  • Fixed ePredTree returning character instead of double for regression trees.
  • Fixed bare filter() call in proximity_longer.R causing namespace conflict with dplyr.
  • Added missing NAMESPACE imports for graphics, grDevices, and utils.

Internal changes

  • New aaa_utils.R with shared internal helpers: e2_variance(), get_ensemble_type(), check_package().
  • Refactored eValidation, eImpurity, and eStoppingRules for consistency and performance.

e2tree 0.2.0

  • Added support for 'ranger' models
  • Several improvements in e2tree plots

e2tree 0.1.2

e2tree 0.1.1

e2tree 0.0.0.9000

  • Added a NEWS.md file to track changes to the package.