Application of Weighted Particle Swarm Optimization in Association Rule Mining
نویسندگان
چکیده
Determination of the threshold values of support and confidence, affect the quality of association rule mining up to a great extent. Focus of my study is to apply weighted PSO for evaluating threshold values for support and confidence. The particle swarm optimization algorithm first searches for the optimum fitness value of each particle and then finds corresponding support and confidence as minimal threshold values after the data are transformed into binary values. The proposed method is verified by applying the Food Mart 2000 database of Microsoft SQL Server 2000. I am expecting that the particle swarm optimization algorithm will suggest suitable threshold values and obtain quality rules as per the previous works [1].
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