Analysis of Various Multiobjective Genetic Approaches in Association Rule Mining

Data mining is used now days by companies with a strong consumer focus. It enables these companies to know the relationships among "internal" factors such as, product positioning, price or staff skills, and "external" factors such as indicators, economic, competition, and customer demographics. The overall aim of the data mining process is to extract information from a data set and transform it into an understandable structure for further use. In this paper, the multi-objective genetic approach for the result Comparison of Pittsburgh and Michigan approach using multi-objective genetic algorithm has been proposed, and it is shown that using Pittsburgh approach is much better than the Michigan approach.