Multi-label classification via multi-target regression on data streams

DOI10.1007/s10994-016-5613-5zbMath1455.68178OpenAlexW2582292785WikidataQ59411202 ScholiaQ59411202MaRDI QIDQ1699623

Panče Panov, Aljaž Osojnik, Sašo Džeroski

Publication date: 23 February 2018

Published in: Machine Learning (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10994-016-5613-5

zbMATH Keywords

multi-label classificationdata stream miningmulti-target regression

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Online algorithms; streaming algorithms (68W27)

Related Items (3)

Multi-label classification via multi-target regression on data streams ⋮ Incremental predictive clustering trees for online semi-supervised multi-target regression ⋮ Dynamic principal projection for cost-sensitive online multi-label classification

Uses Software

• MOA
• VFML

Cites Work

• Unnamed Item
• Learning model trees from evolving data streams
• Multilabel classification via calibrated label ranking
• Decision trees for hierarchical multi-label classification
• Using model trees for classification
• Multi-target regression via input space expansion: treating targets as inputs
• Multi-label classification via multi-target regression on data streams
• Combining instance-based learning and logistic regression for multilabel classification
• Knowledge Discovery from Data Streams
• A Comparison of Alternative Tests of Significance for the Problem of $m$ Rankings

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