Improving bagging performance through multi-algorithm ensembles

DOI10.1007/S11704-012-1163-6zbMath1251.68189OpenAlexW2006550254MaRDI QIDQ1762211

Jaideep Srivastava, Kuo-Wei Hsu

Publication date: 15 November 2012

Published in: Frontiers of Computer Science (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11704-012-1163-6

zbMATH Keywords

classificationdiversitybaggingensemble

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Pattern recognition, speech recognition (68T10)

Uses Software

• UCI-ml
• C4.5
• bootlib

Cites Work

• Bagging predictors
• Measures of diversity in classifier ensembles and their relationship with the ensemble accuracy
• Analyzing bagging
• Using diversity of errors for selecting members of a committee classifier
• Combining Pattern Classifiers
• Random forests
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