Data mining is the technique of discovering the new patterns in large data sets with reference to various methods at the intersection of statistics, machine learning and database systems. Computer science and statistics are the interdisciplinary subfield of data mining. The overall goal of data mining is to extort information from a data set and renew or reframe the information into a structure. Association rule is a research area in the field of data searching for frequent and using the criteria support to find frequently the items appear in the data and confidence to identify the most important relationships. In focus of this paper is to find maximal frequent itemset using a new algorithm called maximal Frequent Itemset using Prime algorithm. Most of the association rule algorithms are used to find the minimal frequent item set, and then with the help minimal frequent item set derive the maximal frequent item set. But it consumes lot of time. So to overcome this problem a new approach Maximal Frequent Itemset using Prime algorithm is proposed to find the maximal frequent item set directly. The proposed method is efficient in finding the maximal frequent item set.
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