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?
Sahar abdalah
le 8 Avr 2015
Réponse acceptée
Plus de réponses (3)
James Tursa
le 8 Avr 2015
NormRows = sqrt(sum(Ypred.*Ypred,2));
Ynorm = bsxfun(@rdivide,abs(Ypred),NormRows);
3 commentaires
Tubi
le 10 Mar 2018
If I want to use this code for my work, any way should I use to cite/reference?
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.
Sahar abdalah
le 9 Avr 2015
c4ndc
le 12 Août 2017
0 votes
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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