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How can I normalize data between 0 and 1 ? I want to use logsig...

Asked by Platon on 13 May 2013

All is in the question: I want to use logsig as a transfer function for the hidden neurones so I have to normalize data between 0 and 1. The mapminmax function in NN tool box normalize data between -1 and 1 so it does not correspond to what I'm looking for.




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2 Answers

Answer by José-Luis on 15 May 2013
Accepted answer
 bla = 100.*randn(1,10)
 norm_data = (bla - min(bla)) / ( max(bla) - min(bla) )


Platon on 15 May 2013

Thank you for your response. But if I do the normalization manually and train the NN with the normalized data, how can I test the net with new data? normalize them before simulation? if so how can I de-normalize the output calculated from unseen data? It seems complicated (mapminmax do all the stuff automatically)

José-Luis on 15 May 2013

Yes, provided you use the same normalization bounds (the min and max of both datasets). To rescale, please look at the below code.

bla = 100.*randn(1,10)
minVal = min(bla);
maxVal = max(bla);
norm_data = (bla - minVal) / ( maxVal - minVal )
your_original_data = minVal + norm_data.*(maxVal - minVal)
Answer by Jurgen on 15 May 2013
NDATA = mat2gray(DATA);



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