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dcterms:bibliographicCitation <http://dblp.uni-trier.de/rec/bibtex/conf/gecco/JacquesTDJD13>
dc:creator <https://dblp.l3s.de/d2r/resource/authors/Clarisse_Dhaenens>
dc:creator <https://dblp.l3s.de/d2r/resource/authors/David_Delerue>
dc:creator <https://dblp.l3s.de/d2r/resource/authors/Julie_Jacques>
dc:creator <https://dblp.l3s.de/d2r/resource/authors/Julien_Taillard>
dc:creator <https://dblp.l3s.de/d2r/resource/authors/Laetitia_Jourdan>
foaf:homepage <http://dx.doi.org/doi.org%2F10.1145%2F2463372.2463432>
foaf:homepage <https://doi.org/10.1145/2463372.2463432>
dc:identifier DBLP conf/gecco/JacquesTDJD13 (xsd:string)
dc:identifier DOI doi.org%2F10.1145%2F2463372.2463432 (xsd:string)
dcterms:issued 2013 (xsd:gYear)
rdfs:label The benefits of using multi-objectivization for mining pittsburgh partial classification rules in imbalanced and discrete data. (xsd:string)
foaf:maker <https://dblp.l3s.de/d2r/resource/authors/Clarisse_Dhaenens>
foaf:maker <https://dblp.l3s.de/d2r/resource/authors/David_Delerue>
foaf:maker <https://dblp.l3s.de/d2r/resource/authors/Julie_Jacques>
foaf:maker <https://dblp.l3s.de/d2r/resource/authors/Julien_Taillard>
foaf:maker <https://dblp.l3s.de/d2r/resource/authors/Laetitia_Jourdan>
swrc:pages 543-550 (xsd:string)
dcterms:partOf <https://dblp.l3s.de/d2r/resource/publications/conf/gecco/2013>
owl:sameAs <http://bibsonomy.org/uri/bibtexkey/conf/gecco/JacquesTDJD13/dblp>
owl:sameAs <http://dblp.rkbexplorer.com/id/conf/gecco/JacquesTDJD13>
rdfs:seeAlso <http://dblp.uni-trier.de/db/conf/gecco/gecco2013.html#JacquesTDJD13>
rdfs:seeAlso <https://doi.org/10.1145/2463372.2463432>
swrc:series <https://dblp.l3s.de/d2r/resource/conferences/gecco>
dc:title The benefits of using multi-objectivization for mining pittsburgh partial classification rules in imbalanced and discrete data. (xsd:string)
dc:type <http://purl.org/dc/dcmitype/Text>
rdf:type swrc:InProceedings
rdf:type foaf:Document