training multi dimensional features using newff or newpr
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Hello there,
I am trying to train my a neural network using newff. My features are muti dimensional, i.e. having 13 columns and 20 rows against one sample. I have 100 samples of input. Is it possible that I train NN with these features without reducing their dimensions? If possible than how? matlab allows one sample per column so I put all 13 feature-columns of one sample together in one column which I suppose is effceting my results.
would anyone suggest anyother way to tackle this problem? thanks in advance.
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Greg Heath
2012-6-23
If the N input vectors are I-dimensional and the N output vectors are O-dimensional the training matrices have sizes
[ I N ] = size(input)
[ O N ] = size(target)
To design a single hidden layer MLPNN with I-H-O node topology
net = newff(input,target,H);
Hope this helps.
Greg
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