alexa EVALUATING THE PERFORMANCE OF ASSOCIATION RULE MINING
ISSN: 1948-1432

Journal of Global Research in Computer Sciences
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Research Article

EVALUATING THE PERFORMANCE OF ASSOCIATION RULE MINING ALGORITHMS

K.Vanitha*1, R.Santhi2
  1. Department of Computer Studies, Saranathan College of Engineering, Trichy,India
  2. Department of Computer Studies. Saranathan College of Engineering, Trichy,India
Corresponding Author: K.Vanitha, E-mail: [email protected]
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Abstract

Association rule mining is one of the most popular data mining methods. However, mining association rules often results in a very large number of found rules, leaving the analyst with the task to go through all the rules and discover interesting ones. In this paper, we present the performance comparison of Apriori and FP-growth algorithms. The performance is analyzed based on the execution time for different number of instances and confidence in Super market data set. These algorithms are presented together with some experimental data. Our performance study shows that the FP-growth method is efficient and scalable and is about an order of magnitude faster than the Apriori algorithm

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