MATLAB: Neural Network – inverted pre-processing functions

neural networkspreprocessing functions

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!

Best Answer

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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