Mining for Optimised Data Using Clustering Along with Fuzzy Association Rules and Genetic Algorithms

Data mining also known as knowledge discovery in databases has been recognized as a promising newarea for database research. The proposed work in this paper is about optimizing the data with clusteringand fuzzy association rules using multi-objective genetic algorithms. This algorithm is implemented in twophases. In the first phase it optimizes the data to reduce the number of comparisons using clustering. Inthe second phase it is implemented with multi-objective genetic algorithms to find the optimum number offuzzy association rules using threshold value and fitness function