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AN EFFICIENT APPROACH FOR THE IMPLEMENTATION OF FP TREE

Frequent pattern mining is one of the most common mining techniques to identify the frequent patterns in large data sets. The Apriori algorithm is one algorithm very efficient for mining frequent patterns. But the drawback is it generates a number of candidate item sets. The FP tree is a frequent pattern technique without candidate item set generation. We have proposed an approach for improving the performance of the FP tree using the parameter average support count.