An algorithm for mining maximum frequent itemsets based on FP-tree

Mining maximum frequent itemsets is a key problem in many data mining applications. In order to overcome the drawbacks in previous maximum itemsets algorithm based on Apriori, a lot of approaches for mining maximum frequent itemsets were proposed, which include much more algorithm for mining maximum frequent itemsets based on FP-Tree, but few focus on frequent count of node in FP-Tree. A algorithm——USDMFIA (using set to mining maximum frequent itemsets algorithm )for mining maximum frequent itemsets based on frequent count of node and set theory through analyzing FP-Tree structure is proposed. A comparative and analysis to previous methods show that the algorithm is efficient.