Study on Apriori Algorithm and FP-Growth Algorithm in Association Rule Mining

Kyi Zar Nyunt, Wint Aye Khaing, Thida Win


Data mining is a technique dedicated to data analysis and understanding and to reveal the knowledge contained in data. It has become one of the important goals of the application of information technology in the future. Association rule mining is the technique that can discover set of frequent items in a transaction. The paper highlight about apriori algorithm and fp-growth algorithm in association rule mining and compare the performance between them. Apriori algorithm discovers the itemset which is frequent and generates candidate itemset. Fp-growth discovers the frequent itemsets without candidate itemset generation.

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