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gmdh_example
GMDH_main为GMDH主函数;
variable_Combin为输入层初始变量选为x1,x1^2,x1*x2,x2^2,x2时的输入变量矩阵值
variable_select计算X_train训练输入数据,Y_train训练输出数据,X_test测试输入数据,Y_test测试输出数据
Combin为求变量的两两组合
Sym_Combin为求符号变量的两两组合
PE_AIC求每层各神经元的参数估计W,及训练数据在参数估计后估计的输出out_train,测试数据在参数估计后的估计输出out_test,还有与实际比较的误差平方和PESS, 以及准则值AIC
sym_representation求最终的输入输出符号表达式
Criterion_value求准则值
(GMDH_main main function for the GMDH variable_Combin initial variables chosen for the input layer, x1, x1 ^ 2, x1* x2, x2 ^ 2, x2 the value of the input variable matrix calculation X_train variable_select training input data, Y_train training output data, X_test test input data, Y_test for the sake of the test output data Combin pairwise combination of variables for the sake of symbolic variables Sym_Combin pairwise combinations PE_AIC neurons find each parameter estimation of the W, and after the training data is estimated in the estimation of output out_train, test data After the parameter estimates of the output estimated out_test, also compared with the actual sum of squared errors PESS, as well as the final criterion value AIC sym_representation seek the input and output values of symbolic expressions Criterion_value find criteria)
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