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I have some concerns related to the use of nntool in MATLAB toolbox. Following links like this, I have found that nntool by default normalizes the inputs to the range [-1 1]. So I am a bit concerned, I created a neural network with tansig activation in the first layer and logsig activation in the output layer. I manually normalized the outputs to the range of [0 1] in the data and fed it to nntool.

Now my question is does nntool further normalizes it to the range [-1 1]. If it does then it is not correct, the output of logsig cannot be in the range of [-1 1].

I am using the newfit function like this

load house_dataset;
net = newfit(houseInputs,houseTargets,20);

Any suggestions?

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closed as off-topic by kjetil b halvorsen, Michael Chernick, Siong Thye Goh, user158565, jpmuc Jun 5 at 8:21

This question appears to be off-topic. The users who voted to close gave this specific reason:

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nntool has a large number of tunable parameters, refer to the documentation for more details. In particular section Preprocessing and Postprocessing deals with different types of pre- and postprocessing techniques which are available in the toolbox.

When you look at the newfit definition you can find such information:

Purpose Create fitting network

Syntax net = newfit(P,T,S,TF,BTF,BLF,PF,IPF,OPF,DDF)

Description newfit(P,T,S,TF,BTF,BLF,PF,IPF,OPF,DDF) takes the following:

(...)

IPF Row cell array of input processing functions. Default is {'fixunknowns','remconstantrows','mapminmax'}.

OPF Row cell array of output processing functions. Default is {'remconstantrows','mapminmax'}

(...)

So you can simply change them to IPF={'fixunknowns','remconstantrows'} and OPF={'remconstantrows'} to turn the min-max mapping off.

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