Abstract
By inspiration of immune computational intelligence, a novel association rule mining algorithm based immune clonal and cluster was proposed. Aim at the efficiency problem of association rules mining,raw data is regarded as antigen and candidate pattern is regarded as antibody. enhancing the antibody’s affinity maturation rate and improving the support of candidate patterns through the cluster competition operation. The simulation and real application illustrate this algorithm can increase the convergence velocity and advance veracity of the association rule, and has the remarkable quality of the global and local research reliability.
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Xu, X., Wang, S. (2010). A Novel Association Rule Mining Based on Immune Computational Intelligence . In: Li, K., Jia, L., Sun, X., Fei, M., Irwin, G.W. (eds) Life System Modeling and Intelligent Computing. ICSEE LSMS 2010 2010. Lecture Notes in Computer Science(), vol 6330. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15615-1_32
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DOI: https://doi.org/10.1007/978-3-642-15615-1_32
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