Modification of Random Forest Based Approach for Streaming Data with Concept Drift

DOI10.14529/mmp160408zbMath1442.68210OpenAlexW2558750332MaRDI QIDQ4692062

Denis Nikolaevich Sidorov, Alekseĭ Vital'evich Zhukov

Publication date: 26 October 2018

Published in: Bulletin of the South Ural State University. Series "Mathematical Modelling, Programming and Computer Software" (Search for Journal in Brave)

Full work available at URL: http://mathnet.ru/eng/vyuru346

zbMATH Keywords

classificationdecision treeconcept driftrandom forestensemble learning

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05)

Related Items (1)

A suite of intelligent tools for early detection and prevention of blackouts in power interconnections

Uses Software

• UCI-ml

Cites Work

• Bagging predictors
• Incremental Learning Extremely Random Forest Classifier for Online Learning*
• Random Forests and Kernel Methods
• Knowledge Discovery from Data Streams
• Extremely randomized trees
• Random forests

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