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USE OF RADIUS WEIGHTED MEAN TO CLUSTER 2-CLASS DATA

dc.citation.epage759en_US
dc.citation.issue10en_US
dc.citation.spage757en_US
dc.citation.volume30en_US
dc.citation.woscount5
dc.contributor.authorYANG, CYen_US
dc.contributor.authorLIN, JCen_US
dc.contributor.department交大名義發表zh_TW
dc.contributor.department資訊工程學系zh_TW
dc.contributor.departmentNational Chiao Tung Universityen_US
dc.contributor.departmentDepartment of Computer Scienceen_US
dc.date.accessioned2014-12-08T15:03:59Z
dc.date.available2014-12-08T15:03:59Z
dc.date.issued1994-05-12en_US
dc.description.abstractA new method using the radius weighted mean to cluster two-class data is proposed. Experiments show that the clustering results are good, the computation is fast, and the method is easy to implement. The method can be applied to block truncation coding, codebook generation, and decision tree construction.en_US
dc.identifier.doi10.1049/el:19940516en_US
dc.identifier.issn0013-5194en_US
dc.identifier.journalELECTRONICS LETTERSen_US
dc.identifier.urihttp://dx.doi.org/10.1049/el:19940516en_US
dc.identifier.urihttps://ir.lib.nycu.edu.tw/handle/11536/2492
dc.identifier.wosnumberWOS:A1994NQ48100010
dc.language.isoen_USen_US
dc.subjectBLOCK CODESen_US
dc.subjectPATTERN RECOGNITIONen_US
dc.subjectVECTOR QUANTIZATIONen_US
dc.titleUSE OF RADIUS WEIGHTED MEAN TO CLUSTER 2-CLASS DATAen_US
dc.typeArticleen_US

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