Classification based on textured image

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);