Provided by: International Journal of Recent Technology and Engineering (IJRTE)
Topic: Data Management
Date Added: Sep 2013
Association rules usually found out the relationship between different data entities in given data set and moreover it is very much important task of data mining. Basically, association rule mining is a multi-objective problem, instead of a single objective problem. A multi-objective genetic algorithm approach using Pittsburgh technique is introduced in this paper for discovering the interesting association rules with multiple criteria i.e. support, confidence and simplicity and complexity with genetic algorithm. In this paper, the authors have discussed the results on various datasets and show effectiveness of the new proposed algorithm.