Multi-label classification and extracting predicted class hierarchies


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BRUCKER, Florian, Fernando BENITES DE AZEVEDO E SOUZA, Elena SAPOZHNIKOVA, 2011. Multi-label classification and extracting predicted class hierarchies. In: Pattern Recognition. 44(3), pp. 724-738. ISSN 0031-3203. Available under: doi: 10.1016/j.patcog.2010.09.010

@article{Brucker2011Multi-2997, title={Multi-label classification and extracting predicted class hierarchies}, year={2011}, doi={10.1016/j.patcog.2010.09.010}, number={3}, volume={44}, issn={0031-3203}, journal={Pattern Recognition}, pages={724--738}, author={Brucker, Florian and Benites de Azevedo e Souza, Fernando and Sapozhnikova, Elena} }

<rdf:RDF xmlns:dcterms="" xmlns:dc="" xmlns:rdf="" xmlns:bibo="" xmlns:dspace="" xmlns:foaf="" xmlns:void="" xmlns:xsd="" > <rdf:Description rdf:about=""> <dcterms:bibliographicCitation>Publ. in: Pattern Recognition 44 (2011), 3, pp. 724-738</dcterms:bibliographicCitation> <dc:contributor>Benites de Azevedo e Souza, Fernando</dc:contributor> <dcterms:title>Multi-label classification and extracting predicted class hierarchies</dcterms:title> <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/> <dc:rights>terms-of-use</dc:rights> <dc:creator>Brucker, Florian</dc:creator> <foaf:homepage rdf:resource="http://localhost:8080/jspui"/> <dspace:isPartOfCollection rdf:resource=""/> <dcterms:isPartOf rdf:resource=""/> <dcterms:issued>2011</dcterms:issued> <dc:contributor>Sapozhnikova, Elena</dc:contributor> <dcterms:rights rdf:resource=""/> <dc:language>eng</dc:language> <dc:creator>Benites de Azevedo e Souza, Fernando</dc:creator> <dcterms:abstract xml:lang="eng">This paper investigates hierarchy extraction from results of multi-label classification (MC). MC deals with instances labeled by multiple classes rather than just one, and the classes are often hierarchically organized. Usually multi-label classifiers rely on a predefined class hierarchy. A much less investigated approach is to suppose that the hierarchy is unknown and to infer it automatically. In this setting, the proposed system classifies multi-label data and extracts a class hierarchy from multi-label predictions. It is based on a combination of a novel multi-label extension of the fuzzy Adaptive Resonance Associative Map (ARAM) neural network with an association rule learner.</dcterms:abstract> <dcterms:available rdf:datatype="">2011-03-23T10:15:41Z</dcterms:available> <dc:contributor>Brucker, Florian</dc:contributor> <bibo:uri rdf:resource=""/> <dc:date rdf:datatype="">2011-03-23T10:15:41Z</dc:date> <dc:creator>Sapozhnikova, Elena</dc:creator> </rdf:Description> </rdf:RDF>

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