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dc.contributor.authorLi, Han-Linen_US
dc.contributor.authorHuang, Yao-Hueien_US
dc.contributor.authorChen, Ming-Hsienen_US
dc.date.accessioned2014-12-08T15:25:34Z-
dc.date.available2014-12-08T15:25:34Z-
dc.date.issued2010en_US
dc.identifier.isbn978-3-642-13922-2en_US
dc.identifier.issn0302-9743en_US
dc.identifier.urihttp://hdl.handle.net/11536/17966-
dc.description.abstractThis study proposes an effective method called DIAMOND to classify biological and medical data. Given a set of objects with some classes, DIAMOND separates the objects into different cubes, where each cube is assigned to a class. Via the union of these cubes, we utilize mixed integer programs to induce classification rules with better rates of accuracy, support and compactness. Two practical data sets, one of HSV patient results and the other of Iris flower, are tested to illustrate the advantages of DIAMOND over some current methods.en_US
dc.language.isoen_USen_US
dc.subjectDIAMONDen_US
dc.subjectInteger Programen_US
dc.subjectClassification rulesen_US
dc.titleA DIAMOND Method for Classifying Biological Dataen_US
dc.typeArticleen_US
dc.identifier.journalMEDICAL BIOMETRICS, PROCEEDINGSen_US
dc.citation.volume6165en_US
dc.citation.spage104en_US
dc.citation.epage114en_US
dc.contributor.department資訊管理與財務金融系 註:原資管所+財金所zh_TW
dc.contributor.departmentDepartment of Information Management and Financeen_US
dc.identifier.wosnumberWOS:000280516800011-
Appears in Collections:Conferences Paper