"aarti gehani" wrote in message <email@example.com>... > I am not clear with the right selection of spread constant in RBFN. > > When I selected spread constant = 0.1, the performance goal was reached but the error was large but when I selected spread constant = 10, the performance goal was not reached and error was very small. > > Can anyone tell me that if I consider spread constant = 10, then the results will be correct?
Glossing over minute details:
1. Standardize your inputs and targets using zscore (zeromean/unitvariance) 2. Randomly divide your data into a training set, a hold out validation set and a test set. 3. Set a training goal of MSEtrngoal = 0.01*mean(var(ttrn')) 4. Loop over 10 or more spread value candidates. 5. Choose the best net using MSEval 6. If unsatisfactory, go back to 4, otherwise 5. Obtain a final evaluation on the validation set choice using the test set. 7. If unsatisfactory, go back to 2