How to determine the neuron in LVQ

Dear all
I have one question, now i'm using LVQ to classify fruits but i confuse to determine the neuron that I must use. I have matrix, rows = 15 and the column = 60, the class = 3. How many neuron I must use.
Thank you

 Accepted Answer

[ I N ] = size(input) % [15 60]
[ O N ] = size(target) % [ 3 60 ]
For lvqnet net.divideFcn = ''. Therefore,
Ntrn = N %60 Training examples
Ntrneq = N*O %180 Training equations
For a single hidden layer with H units
Nw = (I+O)*H % No. of unknown weights to estimate
For a robust design desire Ntrneq >> Nw. or H << Hub where
Hub -1 + ceil( Ntrneq/(I+O)) % 9
Since H << Hub is not possible, try reducing I and/or increasing N (e.g., adding noisy copies of the originals and making H as small as possible.
You may also wish to investigate 10-fold cross-validation and/or another type of classifier (e.g., patternnet or newrb).
Hope this helps.
Thank you for formally accepting my answer
Greg

1 Comment

Thank you for your answer, but i' still confuse with it. Is there any equations to determine the number of neuron that we use? Thank you

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on 9 May 2014

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on 10 May 2014

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