Association Rules Mining Based on Simulated Annealing Immune Programming Algorithm

Association rules mining is an important problem of data mining, in this paper we propose a association rules mining algorithm based on the simulated annealing immune programming algorithm which combines each character of the simulated annealing algorithm and immune programming algorithm. Through the theoretical analysis and the experiment we can find that this algorithm has better robustness and the global and local ability of search, thus it can quickly, effectively excavate more association rules which meet the conditions.