“An algorithm for frequent item set based on Apriori: SFIT”

Association rules are the main technique for data mining. The Apriori algorithm is a classical algorithm in mining association rules. With the time a number of changes proposed in Apriori to enhance the performance in term of time and number of database passes. For the two bottlenecks of frequent item sets mining: the large multitude of candidate 2-itemsets, the poor efficiency of counting their support. This paper main focus lies in the generation of frequent patterns which is the most important task in explanation of the fundamentals of association rule mining. This is done by analyzing the implementations of the well known association rule mining algorithms Apriori and Proposed algorithm Set operation for Frequent Item using Transaction database.