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.