I'm using a Learning Vector Quantization network (LVQ) to classify data collected for deep brain stimulation.
The training data set size is 70X69 and target size 2X68.
my code body is : net = newlvq(minmax(ptr),10,[.5 .5]);
net.trainParam.epochs=50;net = train(net,ptr, ttr);
trout = sim(net,ptr); perftrain = perform(net,trout,ttr); etrain=ttr-trout; msetrain= mse(etrain);
Now the problem is , I could not get accuracy error more than 60% . I am using 100 repeated 10 fold cross validation. Also, Is there anything wrong with the code?
How do you know how many neurons to use in the competitive layer?How many epochs should you use?
How do you know that the LVQ is trained well? Please respond. I need it urgently. Thanks