How to denormalize the output

Hello all,

I need your help to solve my problem.

I used the 'normalize' command to prepare my dataset for Deep Learning.

data_normalized = normalize(data, 'range', [-1 1]) ;

Do you have any idea how I can just denormalize my output at the end?

I don't know how to use "mapminmax" instead of "normalize" for neural networks.

Now I wanted to denormalize my prediction again. I have a problem doing this. Could you please help me on this?

I would be very grateful to you guys.

Thank you in advance.

I looked up in MATLAB documentation that 'range' or 'rescale' is calculated using the following function.

Xrescaled=a+[X-minXmaxX-minX](b-a) .

My code is :

a = (YPred_mat+1)./2
b = (max(YPred_mat)-min(YPred_mat));
YPred_denormalized = (b.*a1)+ min(YPred_mat);

Thanks.

Answer 1

[Star Strider]

Assuming that the normalisation was by z-score, if the mean and standard deviation of the original data were calculated and saved, then de-normalising them would be straightforward:

data_denormed = (data_zscore * data_standard_deviation) + data_mean;

If those data were not saved, then all is lost.

.

[Sam Kalho]

thanks a lot.

[Star Strider]

As always, my pleasure!