论文标题
使用基于替代模型的树木的沙普利计算
Shapley Computations Using Surrogate Model-Based Trees
论文作者
论文摘要
由于其理想的特性，与Shapley相关的技术已成为全球和本地解释工具的关注。但是，他们使用条件期望的计算在计算上是昂贵的。文献中建议的近似方法有局限性。本文提出了基于条件期望的基于替代模型的树来计算沙普利和塑造值。仿真研究表明，所提出的算法可以提高准确性，统一全球沙普利和摇摆的解释，而阈值方法为折衷运行时间和准确性提供了一种方法。
Shapley-related techniques have gained attention as both global and local interpretation tools because of their desirable properties. However, their computation using conditional expectations is computationally expensive. Approximation methods suggested in the literature have limitations. This paper proposes the use of a surrogate model-based tree to compute Shapley and SHAP values based on conditional expectation. Simulation studies show that the proposed algorithm provides improvements in accuracy, unifies global Shapley and SHAP interpretation, and the thresholding method provides a way to trade-off running time and accuracy.
