Self Organizing Maps
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Hi,
I use the neural network toolbox of Matlab R2010a (not Kohonen somtoolbox). I use SOM to classify water radiances spectra. I cannot find in the plot tools how to represent each neuron with his reference vector (prototype spectrum), which is a statistical mean of all the spectra captured by the neuron.
Thank you for your help!
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Accepted Answer
Mark Hudson Beale
on 27 Apr 2011
The prototype pattern for each neuron is its weight vector. To see all the neurons' weight vectors:
net.IW
Each row represents the prototype vector for a different neuron.
These row/prototype vectors are what are shown in PLOTSOMPOS graphically, if the network has two or fewer inputs.
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Preetisha Kaur
on 21 Jun 2011
Hi there...I want to use SOM to classify a 124 X 26 data set into 3 clusters. I am struggling with the same. I want to know how to define the number of neurons for the layers in newsom command, also how can I make sure that the resultant clusters are 3 in numbers? Could you please help...
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