Association Rule Mining Based on Hybrid Whale Optimization Algorithm

Association Rule Mining(ARM) is one of the most significant and active research areas in data mining. Recently, Whale Optimization Algorithm (WOA) has been successfully applied field mining, however, it easily falls into local optimum. Therefore, an improved WOA based adaptive parameter strategy Levy Flight mechanism (LWOA) to mine association rules. Meanwhile, a hybrid that blends two algorithms balance exploration exploitation phases put forward, is, grey wolf optimization algorithm (GWO), artificial bee colony (ABC) cuckoo search (CS) are devoted improving convergence LWOA. The approach performs global finds rules sets by modeling rule mining task as multi-objective problem simultaneously meets support, confidence, lift, certain factor, which examined on multiple sets. Experimental results verify proposed method better performance compared other involved paper.