qshap - Fast Calculation of Feature Contributions in Boosting Trees
Computes feature-specific R-squared (R2) contributions for
boosting tree models using a Shapley-value-based decomposition
of the total R-squared in polynomial time. Supports models
fitted with 'XGBoost', 'LightGBM', and 'CatBoost', with
optimized backend-specific implementations and cached tree
summaries suitable for large-scale problems. Multiple
visualization tools are included for interpreting and
communicating feature contributions. The methodology is
described in Jiang, Zhang, and Zhang (2025)
<doi:10.48550/arXiv.2407.03515>. Optional 'CatBoost' support
uses the R package 'catboost', which is not distributed on
CRAN; installation instructions and released binaries are
provided by the CatBoost project at
<https://catboost.ai/docs/en/concepts/r-installation>.
