Description: 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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传递函数为线性函数_特例验证\Combin.m
...........................\Criterion_value.m
...........................\GMDH_main.m
...........................\network_search.m
...........................\PE_AIC.m
...........................\Sym_Combin.m
...........................\sym_representation.m
...........................\variable_Combin.m
...........................\variable_select.m
...........................\X.xls
...........................\Y.xls
...........................\说明.txt
传递函数为线性函数_特例验证
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