BP网络的过拟合现象满足的测不准关系式

UNCERTAINTY RELATION SUITED TO OVERFITTING OF BP NEURAL NETWORK 

揭示了在 BP网络建模过程中 ,出现“过拟合”现象时网络学习能力与推广能力之间满足的一般测不准关系式 ;通过数值模拟试验确定出测不准关系式中的“过拟合”参数的取值范围及其与函数类的复杂性的关系 ;指出函数类的复杂性可用复相关系数来表示 ;给出应用 BP网络对实际问题的建模过程中 ,为了避免出现“过拟合”现象 ,提高网络推广能力的“过拟合”

A general uncertainty relation between learning ability and generalization ability suited to overfitting was revealed in the modeling of BP neural network. Tests of numerical simulation were carried out to determine the field of values of overfitting parameter in the uncertainty relation, and the relations between the value assignment of parameters and the complexity of function category, which can be represented with the aid of complex correlation coefficient. An overfitting discriminant which improves the generalization ability of network was also presented for freeing of overfitting in the modeling of cases using BP neural network.