Parameter Optimization Based on Genetic Algorithm in the Research of Equivalent Pruning Effect on Fuzzy Decision Tree

Yan Jun Dong; Tian Zhen Liu

doi:10.4028/www.scientific.net/AMR.756-759.3809

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 756-759Parameter Optimization Based on Genetic Algorithm...

Parameter Optimization Based on Genetic Algorithm in the Research of Equivalent Pruning Effect on Fuzzy Decision Tree

Abstract:

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.

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Periodical:

Advanced Materials Research (Volumes 756-759)

Pages:

3809-3813

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.756-759.3809

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Online since:

September 2013

Authors:

Yan Jun Dong, Tian Zhen Liu

Keywords:

Classification Accuracy, Fuzzy Decision Tree, Genetic Algorithm (GA), Post Pruning, Tree Size

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References

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