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dc.contributor.authorLiau, CJen_US
dc.contributor.authorLiu, DRen_US
dc.date.accessioned2014-12-08T15:47:12Z-
dc.date.available2014-12-08T15:47:12Z-
dc.date.issued1999en_US
dc.identifier.isbn3-540-66490-4en_US
dc.identifier.issn0302-9743en_US
dc.identifier.urihttp://hdl.handle.net/11536/31669-
dc.description.abstractIn this paper, we investigate the extraction of fuzzy rules from data tables based on possibility theory. A possibilistic decision language is used to represent the extracted fuzzy rules. The algorithm for rule extraction is presented and the complexity analysis is carried out. Since the results of the rule induction process strongly depend on the representation language, we also discuss some approach for dynamic adjustment of the language based on the data.en_US
dc.language.isoen_USen_US
dc.titleA logical approach to fuzzy data analysisen_US
dc.typeArticle; Proceedings Paperen_US
dc.identifier.journalPRINCIPLES OF DATA MINING AND KNOWLEDGE DISCOVERYen_US
dc.citation.volume1704en_US
dc.citation.spage412en_US
dc.citation.epage417en_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:000170570600051-
顯示於類別:會議論文