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Interpret When Possible:A Tree-Based Hybrid Framework for Interpretable Classification

Yifan Li Shuhan Qi Lei Cui Chao Xing Lei Zhang Xuan Wang

大数据挖掘与分析（英文版）2026，Vol.9Issue(1)：263-283,21.

大数据挖掘与分析（英文版）2026，Vol.9Issue(1)：263-283,21.DOI:10.26599/BDMA.2025.9020055

Interpret When Possible:A Tree-Based Hybrid Framework for Interpretable Classification

Yifan Li ¹Shuhan Qi ¹Lei Cui ¹Chao Xing ²Lei Zhang ³Xuan Wang¹

作者信息

1. School of Computer Science and Technology,Harbin Institute of Technology,Shenzhen 518000,China||Guangdong Provincial Key Laboratory of Novel Security Intelligence Technologies,Shenzhen 518000,China
2. Shenzhen Zhice Technology Co.,Ltd.,Shenzhen 518000,China
3. Pengcheng Laboratory,Shenzhen 518000,China
折叠

摘要

关键词

interpretable machine learning/Decision Trees(DTs)/classification

Key words

interpretable machine learning/Decision Trees(DTs)/classification

引用本文复制引用

Yifan Li,Shuhan Qi,Lei Cui,Chao Xing,Lei Zhang,Xuan Wang..Interpret When Possible:A Tree-Based Hybrid Framework for Interpretable Classification[J].大数据挖掘与分析（英文版）,2026,9(1):263-283,21.

基金项目

This research was funded by the Guangdong Provincial Key Laboratory of Novel Security Intelligence Technologies(No.2022B1212010005),the National Natural Science Foundation of China(No.62376073),the Natural Science Foundation of Guangdong(No.2024A1515030024),and the Colleges and Universities Stable Support Project of Shenzhen(No.GXWD20220811173149002). （No.2022B1212010005）

大数据挖掘与分析（英文版）

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