Jonathan Crabbé, Yao Zhang, William Zame, Mihaela van der Schaar
TL;DR该论文提出了一种使用 Meijer G 函数的黑盒函数连续全局解释算法来解决机器学习模型可解释性问题,通过实验结果证明该算法可以高度准确地表示特征和特征交互的相对重要性。
Abstract
machine learning has proved its ability to produce accurate models but the
deployment of these models outside the machine learning community has been
hindered by the difficulties of interpreting these models. Thi