An Ensemble Learning Approach Based on Missing-Valued Tables

DOI10.1007/978-3-319-25783-9_28zbMath1444.68164OpenAlexW2407494999MaRDI QIDQ3300272

Akira Notsu, Katsuhiro Honda, Taro Miyazaki, Seiki Ubukata, Masahiro Inuiguchi

Publication date: 28 July 2020

Published in: Lecture Notes in Computer Science (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-3-319-25783-9_28

zbMATH Keywords

rough setsincomplete dataensemble learningmissing attribute valuesMLEM2

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Reasoning under uncertainty in the context of artificial intelligence (68T37)

Uses Software

• UCI-ml

Cites Work

• Unnamed Item
• Bagging predictors
• Rough set approach to incomplete information systems
• Generalized probabilistic approximations of incomplete data
• Rough sets
• Rough Sets and Current Trends in Computing
• Random forests

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