Feature-Specific Coefficients of Determination in Tree Ensembles
<|reference_start|>Feature-Specific Coefficients of Determination in Tree Ensembles: Tree ensemble methods provide promising predictions with models difficult to interpret. Recent introduction of Shapley values for individualized feature contributions, accompanied with several fast computing algorithms for predicted values, shows intriguing results. However, individualizing coefficients of determination, aka $R^2$, for each feature is challenged by the underlying quadratic losses, although these coefficients allow us to comparatively assess single feature's contribution to tree ensembles. Here we propose an efficient algorithm, Q-SHAP, that reduces the computational complexity to polynomial time when calculating Shapley values related to quadratic losses. Our extensive simulation studies demonstrate that this approach not only enhances computational efficiency but also improves estimation accuracy of feature-specific coefficients of determination.<|reference_end|>
@article{jiang2024feature-specific,
    title={Feature-Specific Coefficients of Determination in Tree Ensembles},
    author={Zhongli Jiang, Dabao Zhang, Min Zhang},
    journal={arXiv preprint arXiv:2407.03515},
    year={2024},
    archivePrefix={arXiv},
    eprint={2407.03515},
    primaryClass={stat.ML cs.LG}
}