权衡与局限性

这部分内容有帮助吗？

参考文献

“Why Should I Trust You?”: Explaining the Predictions of Any Classifier, Marco Tulio Ribeiro, Sameer Singh, Carlos Guestrin, 2016 Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (ACM) DOI: 10.1145/2939672.2939778 - 介绍了LIME算法，用于对黑盒模型预测进行局部、可解释的解释。
A Unified Approach to Interpreting Model Predictions, Scott M. Lundberg, Su-In Lee, 2017 Advances in Neural Information Processing Systems 30 (NIPS 2017), Vol. 30 DOI: 10.48550/arXiv.1705.07874 - 提出了SHAP（SHapley Additive exPlanations），一个基于Shapley值的统一模型预测解释框架。
On the (In)fidelity and Sensitivity of Explanations, Chih-Kuan Yeh, Cheng-Yu Hsieh, Arun Sai Suggala, David I. Inouye, Pradeep Ravikumar, 2019 Advances in Neural Information Processing Systems 32 (NeurIPS 2019) DOI: 10.48550/arXiv.1901.09392 - 研究了局部解释方法的可靠性，强调了保真度（忠实性）和敏感度（稳定性）问题。
Explaining Individual Predictions When Features Are Dependent: A Step-by-Step Guide to the Conditional SHAP Approach, Kjersti Aas, Martin Jullum, Anders Løland, 2021 Machine Learning: ECML PKDD 2021 Workshops, Vol. 12975 (Springer, Cham) DOI: 10.1007/978-3-030-80279-0_8 - 介绍了在SHAP解释中处理特征依赖的方法，这是一个常见难题。