Association Rules: An Overview

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dc.contributor.author Mcnicholas, Paul en_US
dc.contributor.author Zhao, Yanchang en_US
dc.contributor.editor Yanchang Zhao, Chengqi Zhang, and Longbing Cao en_US
dc.date.accessioned 2010-07-13T08:46:47Z
dc.date.available 2010-07-13T08:46:47Z
dc.date.issued 2009 en_US
dc.identifier 2009005764 en_US
dc.identifier.citation Mcnicholas Paul and Zhao Yanchang 2009, 'Association Rules: An Overview', in http://dx.doi.org/10.4018/978-1-60566-404-0 (ed.), Information Science Reference - IGI Global, USA, pp. 1-10. en_US
dc.identifier.issn 978-1-60566-404-0 en_US
dc.identifier.other B1 en_US
dc.identifier.uri http://hdl.handle.net/10453/12438
dc.description.abstract Association rules present one of the most versatile techniques for the analysis of binary data, with applications in areas as diverse as retail, bioinformatics, and sociology. In this chapter, the origin of association rules is discussed along with the functions by which association rules are traditionally characterised. Following the formal definition of an association rule, these functions a?? support, confidence and lift a?? are defined and various methods of rule generation are presented, spanning 15 years of development. There is some discussion about negations and negative association rules and an analogy between association rules and 2??2 tables is outlined. Pruning methods are discussed, followed by an overview of measures of interestingness. Finally, the post-mining stage of the association rule paradigm is put in the context of the preceding stages of the mining process. en_US
dc.language en_US
dc.publisher IGI Global en_US
dc.relation.isbasedon http://dx.doi.org/10.4018/978-1-60566-404-0 en_US
dc.title Association Rules: An Overview en_US
dc.parent Post-Mining of Association Rules: Techniques for Effective Knowledge Extraction en_US
dc.journal.volume en_US
dc.journal.number en_US
dc.publocation USA en_US
dc.identifier.startpage 1 en_US
dc.identifier.endpage 10 en_US
dc.cauo.name FEIT.School of Systems, Management and Leadership en_US
dc.conference Verified OK en_US
dc.for 120402 en_US
dc.personcode 0000062599 en_US
dc.personcode 998488 en_US
dc.percentage 100 en_US
dc.classification.name Engineering Design Knowledge en_US
dc.classification.type FOR-08 en_US
dc.edition 1 en_US
dc.custom en_US
dc.date.activity en_US
dc.location.activity en_US
dc.description.keywords NA en_US
dc.staffid en_US
dc.staffid 998488 en_US


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