Semi-Automatic Visual Subgroup Mining using VIKAMINE

Простая страница элемента
dc.creatorAtzmueller,Martin
dc.creatorPuppe,Frank
dc.date2005
dc.date.accessioned2024-02-06T12:53:54Z
dc.date.available2024-02-06T12:53:54Z
dc.descriptionVisual mining methods enable the direct integration of the user to overcome major problems of automatic data mining methods, e.g., the presentation of uninteresting results, lack of acceptance of the discovered findings, or limited confidence in these. We present a novel subgroup mining approach for explorative and descriptive data mining implemented in the VIKAMINE system. We propose several integrated visualization methods to support subgroup mining. Furthermore, we describe three case studies using data from fielded systems in the medical domain.
dc.formattext/html
dc.identifierhttps://doi.org/10.3217/jucs-011-11-1752
dc.identifierhttps://lib.jucs.org/article/28499/
dc.identifier.urihttps://openrepository.mephi.ru/handle/123456789/8874
dc.languageen
dc.publisherJournal of Universal Computer Science
dc.relationinfo:eu-repo/semantics/altIdentifier/eissn/0948-6968
dc.relationinfo:eu-repo/semantics/altIdentifier/pissn/0948-695X
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rightsJ.UCS License
dc.sourceJUCS - Journal of Universal Computer Science 11(11): 1752-1765
dc.subjectsubgroup mining
dc.subjectvisualization
dc.subjectdata analysis
dc.subjectdata mining
dc.titleSemi-Automatic Visual Subgroup Mining using VIKAMINE
dc.typeResearch Article
Файлы
Коллекции