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可解释机器学习:黑盒模型可解释性理解指南 = Interpretable machine learning:a guide for making black box models interpretable

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Bibliographic Details
Main Authors: (Molnar, Christoph) 莫尔纳 (Molnar, Christoph) ((德)Christoph Molnar著)
Group Author: 朱明超 (译)
Published: 电子工业出版社
Publisher Address: 北京
Publication Dates: 2021
Literature type: Book
Language: Chinese
Subjects:
Carrier Form: ⅩⅥ,,230页: 图 ; 24cm
ISBN: 978-7-121-40606-5
Index Number: TP181
CLC: TP181-34
Call Number: TP181-34/4822
Contents: 博文视点
有书目(第227-230页)
本书探索了可解释性的概念,介绍了简单的、可解释的模型,例如决策树、决策规则和线性回归,重点介绍了解释黑盒模型的、与模型无关的方法,如特征重要性和累积局部效应,以及用Shapley