Classification based on textured image

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Need help! IS this the right way to do classification? I cant seem to get the right labels out...
Code:
data = importdata('LDA data2.mat')%LDA data2 is training data with labels
features=data(:,1:end-1); %split data without labels
lable=data(:,end); %get the labels
handles.lable = lable;
ldaClass = classify(features,features,lable);
%-----------------------Cross Validation----------------------------------- split_assignments = cross_val_split(14,size(handles.lableimage,1));
for i=1:1:14
ldaClasses = reshape(ldaClass,359,476);
training_set = ldaClasses(find(split_assignments(:,i)==0),:);
test_set = handles.lableimage(find(split_assignments(:,i)==1),:);
% determine weights from the training set
phi_train=[training_set(:,1).^(0) training_set(:,1).^(1)];
w=pinv(phi_train)*training_set(:,2);
phi_test=[test_set(:,1).^(0) test_set(:,1).^(1)];
% apply learned weights to the test set and compute MSE
MSE(i)=sum((test_set(:,2)-phi_test*w).^2)/size(test_set,1);
end
data2 = importdata('LDA data3.mat') %LDA data3 is data from the picture I want to classify
features2=data2(:,1:end-1);
ldaClass2 = classify(features2,features2,ldaClass);

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