No abstract

Abstract-Association rules mining in large databases is a core topic of data mining. Discovering these associations is beneficial to the correct and appropriate decision made by decision makers. Discovering frequent item sets is the key process in association rule mining. One of the challenges in developing association rules mining algorithms is the extremely large number of rules generated which makes the algorithms inefficient and makes it difficult for the end users to comprehend the generated rules. In this paper we proposed efficient fuzzy association rule mining technique to find all co-occurrence relationships among data items. The proposed method which allows considerably reduced the search space with discover the frequent item set and finding fuzzy sets for quantitative attributes in a database and finally employs techniques for mining of Fuzzy Associate Rules Mining (FARM).