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April 24, 2015Journal of Computational and Theoretical Nanoscience

Association Rule Mining Based on Bat Algorithm

Kamel Eddine Heraguemi Nadjet Kamel Habiba Drias

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Abstract

In this paper, we propose a bat-based algorithm (BA) for association rule mining (ARM Bat). Our algorithm aims to maximize the fitness function to generate the best rules in the defined dataset starting from a specific minimum support and minimum confidence. The efficiency of our proposed algorithm is tested on several generic datasets with different number of transactions and items. The results are compared to FPgrowth algorithm results on the same datasets. ARM bat algorithm perform better than the FPgrowth algorithm in term of computation speed and memory usage,

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Cite This Study

Heraguemi et al. (2015) studied this question.

synapsesocial.com/papers/6a72f351d33c10ecfecf2b35 https://doi.org/10.1166/jctn.2015.3873

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