A neural network algorithm for semi-supervised node label learning from unbalanced data

DOI10.1016/j.neunet.2013.01.021zbMath1293.68222DBLPjournals/nn/FrascaBRV13OpenAlexW1964602337WikidataQ30600354 ScholiaQ30600354MaRDI QIDQ2510813

Matteo Re, Marco Frasca, Giorgio Valentini, Alberto Bertoni

Publication date: 4 August 2014

Published in: Neural Networks (Search for Journal in Brave)

Full work available at URL: http://hdl.handle.net/2434/219468

zbMATH Keywords

Hopfield neural networkslearning from unbalanced datanode label predictionsemi-supervised learning in graphs

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Graph labelling (graceful graphs, bandwidth, etc.) (05C78) Genetics and epigenetics (92D10)

Related Items (1)

Imbalanced classification in sparse and large behaviour datasets

Uses Software

• SHOGUN
• BioGRID
• GeneMANIA

Cites Work

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