Optimized Fuzzy Decision Tree Using Genetic Algorithm

Author(s):  
Myung Won Kim ◽  
Joung Woo Ryu
2013 ◽  
Vol 756-759 ◽  
pp. 3809-3813 ◽  
Author(s):  
Yan Jun Dong ◽  
Tian Zhen Liu

for a parameter α that played an important role in the course of fuzzy decision tree creation ,there exists a specific interval, within which gradual increasing of the parameter α may have the same effect as the crisp decision tree post pruning on the size and test accuracy, and there exists a optimum value of α within this specific interval, When α gets the value, can make the fuzzy decision tree reach its performance optimal. To obtain α optimum value , this paper proposed a method of optimizing parameter based on genetic algorithm and proved the validity of the method through comparing with the relative experiment.


Author(s):  
Chin-Teng Lin ◽  
I-Fang Chung ◽  
Her-Chang Pu ◽  
Tsern-Huei Lee ◽  
Jyh-Yeong Chang

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