A New Fuzzy Classification Method Based Estimation of Distribution Algorithm
Xiaoxia Gao, Weigang Huo · IC3T '12 Proceedings of the 2012 International Conference on Convergence Computer Technology · 2012
In order to improve fuzzy classification model's accuracy and interpretability, a fuzzy classification method based on estimation of distribution algorithm was presented. It first constructs initial fuzzy rule set using Apriori principle in the field of data mining, then builds fuzzy classification model by extracting rule from initial fuzzy rule set automatically through Pittsburgh-style binary coding method and UMDA (Univariate Marginal Distribution Algorithm) estimation of distribution algorithm. Simulation experiment on benchmark datasets show that the proposed approach has better performance than fuzzy classification model based on genetic algorithm.