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General Information
Prof. Wael Badawy
Department of Computing and Information Systems Umm Al Qura University, Canada
I'm happy to take on the position of editor in chief of IJCTE. We encourage authors to submit papers concerning any branch of computer theory and engineering.
IJCTE 2014 Vol.6(2): 135-140 ISSN: 1793-8201
DOI: 10.7763/IJCTE.2014.V6.851

Associative Classification Based on Incremental Mining (ACIM)

Mohammed H. Alnababteh, M. Alfyoumi, A. Aljumah, and J. Ababneh
Abstract—Associative classification (AC) is an approach in data mining that uses association rule to build classification systems that are easy to interpret by end-user. When different data operations (adding, deleting, updating) are applied against certain training data set, the majority of current AC algorithms must scan the complete training dataset again to update the results (classifier) in order to reflect change caused by such operations. This paper deals with data insertion issue within the incremental learning in AC mining. Particularly, we modified a known AC algorithm called CBA to treat one aspect of the incremental data problem which is data insertion. The new algorithm called Associative Classification based on Incremental Mining (ACIM). Experimental results against six data sets from UCI data repository showed that the proposed incremental algorithm reduces the computational time if compared to CBA, and almost derives the same accuracy of it.

Index Terms—Associative classification, CBA, data mining, Incremental mining.

M. H. Alnababteh, M. Alfyoumi, and A. Aljumah are with the Salman Bin Abdulaziz University, Kharj, KSA (e-mail: nababteh@gmail.com, fayomi66@yahoo.com, aljumah88@hotmail.com).
J. Ababneh is with the World Islamic Sciences and Education University, Amman, Jordan (e-mail: ababnehjafar@yahoo.com, jafar.ababneh@wise.edu.jo).


Cite:Mohammed H. Alnababteh, M. Alfyoumi, A. Aljumah, and J. Ababneh, "Associative Classification Based on Incremental Mining (ACIM)," International Journal of Computer Theory and Engineering vol. 6, no. 2, pp. 135-140, 2014.

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