Multi-label semi-supervised classification through optimum-path forest

DOI10.1016/j.ins.2018.06.067zbMath1441.68202OpenAlexW2811215564MaRDI QIDQ2200531

Willian P. Amorim, Alexandre Xavier Falcão, João Paulo Papa

Publication date: 22 September 2020

Published in: Information Sciences (Search for Journal in Brave)

Full work available at URL: http://hdl.handle.net/11449/164684

zbMATH Keywords

semi-supervised learningmulti-label assignmentoptimum-path forest classifiers

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Learning and adaptive systems in artificial intelligence (68T05)

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Uses Software

• ML-KNN

Cites Work

• A nature-inspired approach to speed up optimum-path forest clustering and its application to intrusion detection in computer networks
• ML-KNN: A lazy learning approach to multi-label learning
• Robust path-based spectral clustering
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