Apriori Optimization Algorithm Based on Equivalence Class
Jie Ma · Jisuanji gongcheng · 2010
This paper introduces the principle of the Apriori algorithm which is the classical algorithm of association rules mining,and proposes an improved Apriori algorithm――Equivalence class-Apriori(Ec-Apriori) algorithm which aims at the disadvantage of Apriori algorithm.It adopts a partition method and partitions the database into some independent databases according to the support of frequent 1-itemsets.It generates the candidate itemsets by adopting equivalence class in separate databases and optimizes the join operation,and simplifies the account of support by bit object,so it is more efficient.Experimental result shows that the Ec-Apriori algorithm outperforms Apriori algorithm,and gets a good practicality.