R: size ANN training input

by Andrea_Viano :: Rate this Message:

Some parts of this message have been removed. Learn more about Nabble's security policy.

Thank you Fabio,

I used a backpropagation method and I used activation sigmoid function.

Is it maybe for that I have to normalize?

Andrea

Da: Fábio Blessa [mailto:fabioblessa@...]
Inviato: mercoledì 2 novembre 2011 19.23
A: FANN General and development discussion
Oggetto: Re: [Fann-general] size ANN training input

Normalization you mean?
Does it depends on the training algorithm? Having your data normalized is a good practice.

On Nov 2, 2011 2:49 PM, "Andrea_Viano" <viano@...> wrote:

Hi,

Is there anyone that knows why training inputs of an ANN have to be less than 1 to have a convergence? I tried with my regular input( 10000,or 8 etc), and I had a very high and constant error. If I divided training inputs to reach numbers close to the unity I could find a solution of my ANN.

Can you help me to solve this problem?

Thanks

Andrea

Ing. Andrea Viano

Industry Division

CFD Engineering S.r.l.

Headquarters

Piazza della Vittoria, 7/2A - 16123 Genova (Italy)

Phone +39-010-8540050 - Fax +39-010-8631199

------------------------------------------------------------------------------
RSA® Conference 2012
Save $700 by Nov 18
Register now!
http://p.sf.net/sfu/rsa-sfdev2dev1
_______________________________________________
Fann-general mailing list
Fann-general@...
https://lists.sourceforge.net/lists/listinfo/fann-general

------------------------------------------------------------------------------
RSA(R) Conference 2012
Save $700 by Nov 18
Register now
http://p.sf.net/sfu/rsa-sfdev2dev1
_______________________________________________
Fann-general mailing list
Fann-general@...
https://lists.sourceforge.net/lists/listinfo/fann-general

« Return to Thread: size ANN training input