Machine-learning interpretability techniques for seismic performance assessment of infrastructure systems
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TL;DR: In this article, interpretable machine learning approaches such as partial dependence plots, accumulated local effects, and Shapely additive explanations are used to understand the behavior and predictions of the machine-learning model.
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About: This article is published in Engineering Structures. The article was published on 01 Jan 2022. and is currently open access. The article focuses on the topics: Interpretability & Computer science.
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