XING Zong-yi, ZHANG Yong, HOU Yuan-long, et al. Design of Interpretable and Precise Fuzzy Classification System Based on Fuzzy Clustering and Genetic Algorithm[J]. Acta Electronica Sinica, 2006, 34(1): 83-88.
DOI:
XING Zong-yi, ZHANG Yong, HOU Yuan-long, et al. Design of Interpretable and Precise Fuzzy Classification System Based on Fuzzy Clustering and Genetic Algorithm[J]. Acta Electronica Sinica, 2006, 34(1): 83-88.DOI:
Design of Interpretable and Precise Fuzzy Classification System Based on Fuzzy Clustering and Genetic Algorithm
An approach of constructing interpretable and precise fuzzy classification system based on fuzzy clustering and genetic algorithm is proposed.First
the precision index is defined
and the necessary conditions of interpretability are analyzed.Second
the number of fuzzy rules is determined by cluster validity indices
and the initial fuzzy classification system is identified using a fuzzy clustering algorithm.Subsequently
the method of merging similar fuzzy sets is used to enhance the interpretability of the initial model.A genetic algorithm is used to improve the precision of the model.The process continues iteratively until the stop criteria are satisfied.The proposed approach is applied to the Iris benchmark classification problem