Comparative Analysis of Association Rule Mining Algorithms in Mining Frequent Patterns

Sinthuja M, Dr. Puviarasan N, Dr. Aruna P


Finding frequent patterns in a huge transaction database has wide scope in research. Here in this paper we consider three of the algorithms in an association rule namely Apriori, Predictive Apriori and FP-Growth algorithm. Experiments are done to compare the result of these three algorithms with distinct datasets and present the result. Based on the results, we find that FP-Growth algorithm is more worthwhile than the Predictive Apriori and Apriori algorithms as time consumption is low and the need for candidate patterns is done away.


Apriori; Association Rule Mining Algorithm; Data mining; FP-tree; Minimum support; Predictive Apriori; Predictive Accuracy; Pruning

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