An Innovative Potential on Rule Optimization using Fuzzy Artificial Bee Colony
نویسنده
چکیده
This study adapted an improved algorithm based on Artifical Bee Colony Optimization. It is not possible to justify that all the rules generated by fuzzy based apriori algorithm produce optimum result. Thus optimization of the result generated was carried out by Fuzzy Apriori algorithm using Fuzzy Artifical Bee Colony Optimization (FABCO), it's worth noting that a significant findings were revealed. FABCO is used for optimization of rules to get the best classification accuracy. The proposed method was compared with the traditional Artifical bee colony optimization and the particle swarm optimization. The current work proved a better classification performance compared to un-pruned rules.
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