What is the use of the target matrix and how do i create one?

Question

We are developing a neural network for classification there are 72 signals and there are 100 samples of each signal. We have extracted 49 parameters from each signal. What should my target matrix contain

Prashant Kumar · Accepted Answer

The current neural network classification function is PATTERNNET (replacing the obsolete NEWPR). The syntax of the target matrix for N I-dimensional column inputs that are to be assigned into into 1 of c classes is N c-dimensional {0,1} unit vectors from the unit matrix eye(c).
 
 [ I N ] = size(input)
 [ c N ] = size(target)
The transformation between the true class index row vector and the corresponding target matrix is
target       = full(ind2vec(trueclassind)) 
trueclassind = ind2vec(target)
Therefore, if the classifier output is
 output = target+ randn(1,N)
the estimated classindex and error vectors are
 estclassind = vec2ind(output)
 error       = estclassind~=trueclassind
 Nerr        = sum(error)
 PctErr      = 100*Nerr/N
1. Test the above code with N = 9,
 classind = [ 9 7 5 3 1 8 6 4 2 ]
2. See the online documentation
 help patternnet
 doc patternnet
3. Search both the NEWSGROUP and ANSWERS for my examples
 greg patternnet

What is the use of the target matrix and how do i create one?

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