通过Shapley加性解释增强基于回归的多项式混沌展开的可解释性
Enhancing the explainability of regression-based polynomial chaos expansion by Shapley additive explanations
Reliability Engineering and System Safety · 2022
被引 72
ABS 3
- Pramudita Satria Palar 通讯
- Lavi Rizki Zuhal
- Koji Shimoyama
不确定性量化代理模型机器学习可解释性敏感性分析计算数学