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xplaineff 0.1.0

• Package renamed to xplaineff for CRAN submission (no issue).
• AleStrategy categorical splits now apply ordered-prefix partitions consistently in fitted trees and display category sets for those splits (no issue).
• AleStrategy now accepts a bare prediction function as model in the default ALE prediction path (no issue).
• AleStrategy split search now skips ALE effect components with numerically zero heterogeneity while keeping all split candidate features available (no issue).
• AleStrategy and PdStrategy now prune negligible effect components during split search while preserving all split candidate features and full effect grids (no issue).
• AleStrategy and PdStrategy now default to auto precompute engine selection while keeping explicit cpp and r engines as compatibility options (no issue).
• AleStrategy now supports categorical_split = "exhaustive" for level-set searches over categorical ALE split candidates while retaining ordered-prefix splits as the default (no issue).
• AleStrategy split search now uses the bias-corrected self-gain ranking objective for ALE self-feature splits (no issue).
• AleStrategy now uses only the selected split’s objective rows when multiple ALE split candidates tie (no issue).
• calculate_ale() and calculate_ale_fast() now preserve fractional interval bounds for integer features and restore shared prediction scratch data between features (no issue).
• calculate_ale_fast() now normalizes custom predict_fun outputs like the R ALE path and errors on prediction length mismatches (no issue).
• calculate_pd() now routes custom predict_fun calls through the cached R-side PD stack to avoid slow data-frame reconstruction in the C++ stacker (no issue).
• calculate_pd() now uses a row-major full-ICE prediction layout for native ranger regression models under pd_engine = "auto" (no issue).
• compute_ice_r() now preserves fractional grid values for cached integer features in the PD R backend (no issue).
• default_predict_fun() now uses direct regression prediction paths for native ranger, native and mlr3 rpart, and native and mlr3 xgboost models when no custom predict_fun is supplied. It also skips redundant feature subsetting for already aligned prediction data (no issue).
• extract_split_info() keeps categorical split level sets out of the default summary table (no issue).
• extract_split_info() now omits internal split timings by default and can include them with include_timing = TRUE (no issue).
• PdStrategy now avoids redundant re-centering for already centered full-grid PD matrices and uses a cache-friendly exact split-search layout (no issue).
• PdStrategy now supports categorical_split = "exhaustive" for level-set searches over categorical PD split candidates while retaining one-vs-rest as the default and guarding large level counts with max_exhaustive_levels (no issue).
• plot_tree_pd() now displays categorical split conditions as category sets instead of equality labels (no issue).
• plot_tree_pd() now names returned node plots with actual tree node ids instead of depth-local positions (no issue).
• prepare_split_data_pd() now infers effect features from precomputed PD/ICE results when feature_set is omitted and still uses all non-target columns as split candidates (no issue).

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.