Neural Network - inverted pre-processing functions
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Emiliano Rosso
le 24 Nov 2015
Commenté : Emiliano Rosso
le 25 Nov 2015
I know that using preprocessing functions have to transform the output of the neural network to their original values using:
P = inputs;
t = targets;
[pn, Mins, maxp, tn, mint, maxt] = premnmx (p, t);
net = train (net, pn, tn);
an = sim (net, pn);
postmnmx a = (an, mint, maxt);
I would like to know if using fitnet with new preprocessing functions integrated into the neural network ('mapminmax', 'processpca', 'mapstd') for the training and calculating the output of a new data set using:
newoutputs = net (newinputs);
I still have to convert and reconvert the new data or the transformation is performed automatically.
Is there any difference if I use:
new outputs = net (newinputs);
instead of:
newoutputs = sim (net, newinputs);
?
Thank you!
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Greg Heath
le 25 Nov 2015
Modifié(e) : Greg Heath
le 25 Nov 2015
Why are you wasting time on a question that you can answer yourself by simply running the example in
help fitnet
To better answer your problem add
max(abs(t-y))
Hope this helps.
Greg
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