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Updated: May 21, 2025

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用不同的方法生成的分子机器学习模型的比较解释,用于计算Shapley值

Alec Lamens1, Jürgen Bajorath1,2

  • 1Department of Life Science Informatics and Data Science, B-IT, LIMES Program Unit Chemical Biology and Medicinal Chemistry, Rheinische Friedrich-Wilhelms-Universität, Friedrich-Hirzebruch-Allee 5/6, D-53115, Bonn, Germany.

Molecular informatics
|March 20, 2025
PubMed
概括

可解释的人工智能 (XAI) 方法用于特征归属显示不一致的结果. 通过比较Shapley值变量,发现了不同的特征重要性分布,突出显示了机器学习解释中需要进行一致性检查的必要性.

关键词:
谢普利的价值是什么意思方法的近似方法.复合活动预测预测.属性属性 属性属性 属性属性 属性属性机器学习是机器学习.模型解释 模型解释

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