How do i denormalize the data after i have used the "normalize" function?
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Hi,
I have normalized my data using the formula given and now i need to renormalize it to the original version, not (0,1) or (-1,1). What function do i use? Pls help! i couldnt find a "denormalize" function anywhere!
%Data needs to be normalized
inputs = normalize(inputs);
targets = normalize(targets);
inputs2020 = normalize(inputs2020);
targets2020 = normalize(targets2020);
7 个评论
Star Strider
2020-3-7
If you used the default 'zscore', you would have to have saved the mean and standard deviation (std) of your data first in order to ‘denormalise’ it. If you did not do that, likely all hope is lost.
It is always appropriate to save all the original data so reversing a potentially irreversible process is not necessary.
CLHE
2020-3-7
Star Strider
2020-3-7
Then do not bother with the denormalisation and just use the original data.
CLHE
2020-3-7
dpb
2020-3-7
If z=(x-mu)/s, then x=z*s+mu
It can make quite a bit of difference in the result if do not standardize inputs if they (the inputs) are of markedly differing amplitudes. As the "More About" section of thd documenation for normalize says, using it scales the data to a zero mean and variance of 1 for all variables, retaining shape. This can aid quite a lot in numerical calculations where otherwise differences can become insiginficant of one variable to another or apparent importance owing to magnitude alone.
It would seem to have been a convenience for the user if normalize had also the ability to return the needed parameters when called as optional additional outputs or if rescale had the option to convert back from z-scores besides just the linear scaling it does.
I'd never used either; it's so trivial an operation always just code it inline so had to go look up what each actually did as implemented...
Star Strider
2020-3-7
@CLHE —
The neural network information is new. To denormalise the results of the neural network, multiply them by the standard deviation and then add the mean.
dpb
2020-3-7
Isn't the output rescaled back to the same units as the original? I've not used the ML NN models/don't have the TB so not sure how they actually work in that regards...
采纳的回答
John D'Errico
2020-3-7
编辑：John D'Errico
2020-3-7
You can't. Well, you can, but only if you do what you need in advance.
X = 1:5
X =
1 2 3 4 5
normalize(X)
ans =
-1.2649 -0.63246 0 0.63246 1.2649
normalize(2*X)
ans =
-1.2649 -0.63246 0 0.63246 1.2649
Can you see that normaize produces exactly the same result for both X and 2*X? If so, then you must surely understand that merely from the normalized data, you can never recover the original data.
You absolutely need to save the transformation parameters for how the data was normalized. Otherwise, denormalization is impossible.
However, if we store the normalization parameters, then recovery is possible.
mu = mean(X);
S = std(X);
Xnorm = (X - mu)/S
Xnorm =
-1.2649 -0.63246 0 0.63246 1.2649
Xnorm*S + mu
ans =
1 2 3 4 5
As you see, Xnorm is the same thing as what normalize produced, but now we can recover X from Xnorm.
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