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Error Histogram in Artifical Neural Network Skewed - cause of poor success rate?

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I am running a Artificial Neural Network algorithm in Matlab using the following code that is found here :
train_target = zeros(40,200);
for row = 1 : size(train_target, 1)
col = 5*(row-1)+1;
train_target(row, col:col+4) = 1;
%%%%%%%%Creating Network and Training Them %%%%%%%%%%%
rand('seed', 491218382)
net = patternnet([90]);
net.divideFcn = 'divideint';
net.divideParam.trainRatio =100/100;%%only training
net.divideParam.valRatio = 00/100;
net.divideParam.testRatio = 00/100;
for i=2:2%%%set the activation function linear for the output layer
net.layers{i}.transferFcn = 'purelin';
% Train network
[net,tr] = trainrp(net,train_images,train_target);
My success rate is stuck to around 20% at best case. I also found that the Error Histogram is skewed like this:
Can you tell me what might be the issue that is causing the poor success rate?
As a background:
1. I have 40 subjects, with 5 images per subjects (= total of 200 Training images)
2. I used PCA to extract the features from the images.
3. I then ran the code using the test images that was projected as per the PCA algorithm.
Any help is greatly appreciated!

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