Generating Optimized Association Rule for Big Data Using GA and MLMS - Sultana, Arsha; Madhavi, S (International Journal of Computer Sciences and Engineering, 2025)
For mining association rule different algorithms are used such as Apriori, tree based algorithm which take too much computerized time to accomplish all the frequent items. These obstacles are eliminated by using GA and MLMS and also improving the performance. In this method used a multi level minimum support of data table as 0 and 1. Genetic algorithm is indiscriminate search algorithm model based on natural selection, works in an iteration manner and is very adequate in large amount of data. Genetic algorithm is implemented in Hadoop to reduce computation cost. Hadoop supports for manipulating large data and operate them in parallel manner for better performance. The optimal frequent items are access that satisfies fitness, support and confidence.