打开你的黑箱分类器。
Open your black box classifier.
作者信息
Lisboa Paulo Jorge Gomes
机构信息
Data Science Research Centre, School of Computing and Mathematics Liverpool John Moores University Liverpool UK.
出版信息
Healthc Technol Lett. 2023 Aug 29;11(4):210-212. doi: 10.1049/htl2.12050. eCollection 2024 Aug.
Abstract
A priority for machine learning in healthcare and other high stakes applications is to enable end-users to easily interpret individual predictions. This opinion piece outlines recent developments in interpretable classifiers and methods to open black box models.
摘要
在医疗保健和其他高风险应用中，机器学习的一个优先事项是让终端用户能够轻松解释单个预测结果。这篇观点文章概述了可解释分类器和打开黑箱模型方法的最新进展。
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