Author 
Topic: Neural Network With Genetic Algorithm Plzzz help 

zaza_thegreat 
Posted: 26Jan11 20:19 



im trying to generate weight vector for a certain neural network i have a file of inputs and their output (x1 : number , x2: number o: number) hidden layer activation function is sigmoid output layer activation function is linear
anyway this isnt the problem the problem is i do calculate he output of the chromosome and get its error for each set of i/o from the file and then i get MSE = 1/2 sum(myoutput  files_output)^2 i make the fitness evaluation 1/mse to be able to minimize then xover with prob 0.7 and mutation with prob 0.2 with generalized replacement i never manage to get MSE below 45,000 which is enormously large what is my problem is it with the fitness or the neural calculation is wrong please guys i need your help !!



Nikola 
Posted: 31Jan11 02:20 



Try with
MSE = (1 / n) * sum((myoutput  files_output)^2)
where n is the number of training examples (sets of i/o, if you will). 

