An optimization of association rule mining for large database using K- map and Genetic Algorithm: A review

In the field of data mining association rule is a very popular and efficient technique while it has different technique such as classification, clustering, sequential pattern etc to extract or optimize the large database. The main aim of data mining is to find an effective or an optimized set of data from the big database. An association rulesmining technique is used in various applications such as in banking, department stores etc. The Genetic Algorithm (GA) system can expect the rules which include negative attributes in the created rules mutually more than one attribute in resulting part. In this paper, we explore a review to optimize association rules using K- map and genetic algorithm (GA).