A Novel Approach for Reducing the Candidate Item Sets and Large Item Sets by Fuzzy Mining Association Rule

In this era of modern computing world, there are many fuzzy association algorithms is developed and still lots of work have to performed in this area. Some already proposed algorithm reduces data sets or space complexity and some reduces the time complexity and so on. Our proposed algorithms reduce the space complexity by reducing the candidate item sets and large item sets from data sets. We use the row count technique in fuzzy association rules.