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dc.date.accessioned2007-09-28T10:09:30Z
dc.date.available2007-09-28T10:09:30Z
dc.date.issued2007-09-28T10:09:30Z
dc.identifier.uriurn:nbn:de:hebis:34-2007092819260
dc.identifier.urihttp://hdl.handle.net/123456789/2007092819260
dc.format.extent362330 bytes
dc.format.mimetypeapplication/pdf
dc.language.isoeng
dc.subjectEvolutionary Computationeng
dc.subjectData Miningeng
dc.subjectData-Mining-Cupeng
dc.subjectDMC 2007eng
dc.subjectEvolutionary Algorithmeng
dc.subjectGenetic Algorithmeng
dc.subjectLearning Classifier Systemeng
dc.subjectClassifier Systemeng
dc.subject.ddc004
dc.titleEvolving Classifiers - Evolutionary Algorithms in Data Miningeng
dc.typeTechnischer Report
dcterms.abstractData mining means to summarize information from large amounts of raw data. It is one of the key technologies in many areas of economy, science, administration and the internet. In this report we introduce an approach for utilizing evolutionary algorithms to breed fuzzy classifier systems. This approach was exercised as part of a structured procedure by the students Achler, Göb and Voigtmann as contribution to the 2006 Data-Mining-Cup contest, yielding encouragingly positive results.eng
dcterms.accessRightsopen access
dcterms.creatorWeise, Thomas
dcterms.creatorAchler, Stefan
dcterms.creatorGöb, Martin
dcterms.creatorVoigtmann, Christian
dcterms.creatorZapf, Michael
dcterms.isPartOfKasseler Informatikschriftenger
dcterms.isPartOf2007, 4ger
dc.description.everythingData-Mining-Cup 2007eng
dc.subject.ccsG.3
dc.subject.ccsI.2.4
dc.subject.ccsI.2.6
dc.subject.ccsI.5.0
dc.subject.ccsJ.1


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