boosting machine." Annals of statistics (2001): 1189-1232. • Goldstein, Alex, et al. "Peeking inside the black box: Visualizing statistical learning with plots of individual conditional expectation." Journal of Computational and Graphical Statistics 24.1 (2015): 44-65. • Hooker, Giles, and Lucas Mentch. "Please Stop Permuting Features: An Explanation and Alternatives." arXiv preprint arXiv:1905.03151 (2019). • Apley, Daniel W., and Jingyu Zhu. "Visualizing the effects of predictor variables in black box supervised learning models." Journal of the Royal Statistical Society: Series B (Statistical Methodology) 82.4 (2020): 1059-1086. • Molnar, Christoph. "Interpretable machine learning. A Guide for Making Black Box Models Explainable." (2019). https://christophm.github.io/interpretable-ml-book/. • 森下光之助. 「機械学習を解釈する技術〜予測力と説明力を両立する実践テ クニック」. 技術評論社. (2021). (宣伝) https://is.gd/nkYPPG