Associative classification approaches : review and comparison

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dc.contributor.authorAbdelhamid, Neda
dc.contributor.authorThabtah, Fadi
dc.date.accessioned2020-02-13T09:15:16Z
dc.date.available2020-02-13T09:15:16Z
dc.date.copyright2014en_US
dc.date.issued2014
dc.descriptionThis review is not available at CUD collection. The version of scholarly record of this Review is published in Journal of Information and Knowledge Management (2014), available online at: https://doi.org/10.1142/S0219649214500270.en_US
dc.description.abstractAssociative classification (AC) is a promising data mining approach that integrates classification and association rule discovery to build classification models (classifiers). In the last decade, several AC algorithms have been proposed such as Classification based Association (CBA), Classification based on Predicted Association Rule (CPAR), Multi-class Classification using Association Rule (MCAR), Live and Let Live (L3) and others. These algorithms use different procedures for rule learning, rule sorting, rule pruning, classifier building and class allocation for test cases. This paper sheds the light and critically compares common AC algorithms with reference to the abovementioned procedures. Moreover, data representation formats in AC mining are discussed along with potential new research directions. © 2014 World Scientific Publishing Co.en_US
dc.identifier.citationAbdelhamid, N., & Thabtah, F. (2014). Associative classification approaches: Review and comparison. Journal of Information and Knowledge Management, 13(3). https://doi.org/10.1142/S0219649214500270en_US
dc.identifier.issn02196492
dc.identifier.urihttp://dx.doi.org/10.1142/S0219649214500270
dc.identifier.urihttps://hdl.handle.net/20.500.12519/140
dc.language.isoenen_US
dc.publisherWorld Scientific Publishing Co. Pte Ltden_US
dc.relationAuthors Affiliations: Abdelhamid, N., Computing and Informatics Department, De Montfort University, Leicester, United Kingdom; Thabtah, F., Ebusiness Department, Canadian University of Dubai, Dubai, United Arab Emirates
dc.relation.ispartofseriesJournal of Information and Knowledge Management;Vol. 13, no. 3
dc.rightsPermission to reuse abstract has been secured from World Scientific Publishing Co. Pte Ltd.
dc.rights.holderCopyright : 2014 World Scientific Publishing Co.
dc.subjectAssociative classificationen_US
dc.subjectclassificationen_US
dc.subjectData miningen_US
dc.subjectPredictionen_US
dc.subjectPruningen_US
dc.subjectRule learningen_US
dc.subjectRule sortingen_US
dc.titleAssociative classification approaches : review and comparisonen_US
dc.typeReviewen_US
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