A logical approach to fuzzy data analysis

dc.citation.epage	417	en_US
dc.citation.spage	412	en_US
dc.citation.volume	1704	en_US
dc.contributor.author	Liau, CJ	en_US
dc.contributor.author	Liu, DR	en_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.department	Department of Information Management and Finance	en_US
dc.date.accessioned	2014-12-08T15:47:12Z
dc.date.available	2014-12-08T15:47:12Z
dc.date.issued	1999	en_US
dc.description.abstract	In 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.identifier.isbn	3-540-66490-4	en_US
dc.identifier.issn	0302-9743	en_US
dc.identifier.journal	PRINCIPLES OF DATA MINING AND KNOWLEDGE DISCOVERY	en_US
dc.identifier.uri	https://ir.lib.nycu.edu.tw/handle/11536/31669
dc.identifier.wosnumber	WOS:000170570600051
dc.language.iso	en_US	en_US
dc.title	A logical approach to fuzzy data analysis	en_US
dc.type	Article; Proceedings Paper	en_US

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