How to normalize values in a matrix to be between 0 and 1?
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I have a matrix Ypred that contain negative values and I want to normalize this matrix between 0 and 1
Ypred=[-0.9630 -1.0107 -1.0774
-1.2075 -1.4164 -1.2135
-1.0237 -1.0082 -1.0714
-1.0191 -1.3686 -1.2105];
I'm new in matlab, please help me, there is a matlab function or toolbox that can do this? thanks
2 commentaires
James Tursa
le 8 Avr 2015
Modifié(e) : James Tursa
le 8 Avr 2015
What do you mean by "normalize"? Divide by the max value in the matrix and make all values positive? Do this by columns or rows? Divide by norm of columns or rows? Or what?
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Jos (10584)
le 8 Avr 2015
Modifié(e) : Jos (10584)
le 8 Avr 2015
This can be simply done in a two step process
- subtract the minimum
- divide by the new maximum
normA = A - min(A(:))
normA = normA ./ max(normA(:)) % *
note that A(:) makes A into a long list of values. Otherwise min(A) would not return a single value ... Try fro yourself!
- Edited after comment ...
2 commentaires
Jos (10584)
le 8 Avr 2015
Sorry! The second line of code is wrong ;-) It should read
normA = normA ./ max(normA(:))
Plus de réponses (3)
James Tursa
le 8 Avr 2015
NormRows = sqrt(sum(Ypred.*Ypred,2));
Ynorm = bsxfun(@rdivide,abs(Ypred),NormRows);
3 commentaires
John D'Errico
le 10 Mar 2018
Modifié(e) : John D'Errico
le 10 Mar 2018
Why would you need a citation? If you truly want a citation, just cite MATLAB itself, or perhaps the doc page for bsxfun, but it seems a bit silly to need a citation for a simple code fragment.
Tubi
le 22 Mar 2018
Many Thanks John, I believe you are right in your suggestion since they are mostly common MATLAB commands and functions.
Sahar abdalah
le 9 Avr 2015
2 commentaires
James Tursa
le 9 Avr 2015
Use whichever is appropriate for your problem. Jos and I are both trying to interpret what you want, but without any background about the problem you are solving it is a bit of a guessing game at our end.
c4ndc
le 12 Août 2017
Hello, What is the name of this norm in the accepted answer? (Euclidean, Frobenius etc.)
1 commentaire
Jan
le 12 Août 2017
Please post comments to answers in the section for the comments. You message is not an answer.
The accepted answer does not contain a norm at all, but a "normalization". A matrix norm would reply a scalar, the normalization replies a matrix with the same size, but with shifted and scaled values.
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