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- W1967012136 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." @default.
- W1967012136 created "2016-06-24" @default.
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- W1967012136 date "2013-09-01" @default.
- W1967012136 modified "2023-09-27" @default.
- W1967012136 title "Parameter Optimization Based on Genetic Algorithm in the Research of Equivalent Pruning Effect on Fuzzy Decision Tree" @default.
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- W1967012136 doi "https://doi.org/10.4028/www.scientific.net/amr.756-759.3809" @default.
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