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Is there any RBF neural network function available for classification problem?

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Hi,
As far as I know, the neural network pattern recognition tool does not supply the radial basis network algorithm. Is there any RBF neural network function available in Matlab for classification problem?
Many thanks!
Betty

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Greg Heath
Greg Heath el 16 de Mayo de 2012
help newrb
doc newrb
Search the newsgroup using
heath newrb
Hope this helps.
Greg
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Moore betty
Moore betty el 17 de Mayo de 2012
Thanks for your help.
As for function newrb, it seems that it is used only for approximating a function in Matlab , do you know if the newrb function could be used to classify a dataset? Since I am new to neural network, hope you could give me some suggestions. Many thanks!
Betty

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Más respuestas (3)

Richard
Richard el 16 de Mayo de 2012
Hi - I think the free Netlab toolbox has code for radial basis function networks: http://www1.aston.ac.uk/eas/research/groups/ncrg/resources/netlab/
  1 comentario
Moore betty
Moore betty el 17 de Mayo de 2012
Thanks for your information!
I have download the toolbox, it has many useful codes though I still cannot find how to use rbf network for classification.
Thank you all the same!!
Best Regards
Betty

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Greg Heath
Greg Heath el 17 de Mayo de 2012
108 results for
heath newrb classification
Hope this elps.
Greg
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Moore betty
Moore betty el 20 de Mayo de 2012
Hi, thanks for your help!
I have searched for your answer, I still have a question that PCTerrval (the validation data missclassification error rate) you mentioned as performance goal for classification, cannot be found in Matlab. Does that mean I have coding this part in function newrb by myself?
Hope for your reply!
Many thanks!

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Greg Heath
Greg Heath el 21 de Mayo de 2012
Yes.
1. Divide the data
2. Normalize or standardize the training set
3. Use the training set statistics (min/max or mean/std) to normalize the trn and val sets.
4. NEWRB does not consider val or tst data. Training stops when either Hmax or MSEtrngoal is reached. I typically use Hmax <= (Ntrn-1)*O/(I+O+1) and MSEtrngoal ~ 0.01*mean(var(t'))
5. Train multiple designs with different values of spread
6. Record the trn/val/tst MSEs and PCTerrs.
7. Choose the design with the best nontraining performance
8. Searching with heath newrb close clear should yield code examples.
Hope this helps.
Greg

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