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A Novel Immune Optimization with Shuffled Frog Leaping Algorithm - A Parallel Approach for Unsupervised Data Clustering
2016
International Journal of Computer Applications
Data clustering is one of the data mining task, it is used to group the data objects according to their similarity. It is an optimization problem to find optimal results apply the proposed parallel approach called P-AISFLA. This hybrid algorithm is developed by utilizing the benefits of both social and immune mechanisms. The social algorithm Shuffled Frog Leaping Algorithm is a new parameter free population based algorithm combined with Clonal selection algorithm CSA. This hybrid algorithm
doi:10.5120/ijca2016909423
fatcat:wmeflcbfffcwbc742pi5dp4biu