svm2.asv

function accuracy = svm2(n1,n2,i)
arr = [1 6 11 16 21];
n1 = arr(n1);
n2 = arr(n2);

load eegdata
%11/21 0%
%% first
task1 = data{n1}{4};
t = [];
for i = 1:1:5
t = [t ; task1(i,:)];
end
for i = 1:1:5
set{i} = reshape(t(i,:),100,25);
end
f1 = [];
for i =1:1:5
f1 =[f1; getfeatures(set{i})];
end
%% second
task2 = data{n2}{4};
t = [];
for i = 1:1:5
t = [t ; task2(i,:)];
end
for i = 1:1:5
set{i} = reshape(t(i,:),100,25);
end
f2 = [];
for i =1:1:5
f2 =[f2; getfeatures(set{i})];
end
t1 = [1 1 1 1 1];
t2 = [2 2 2 2 2];

P = [f1 f2]';
%LVQ
Tc = [t1 t1 t1 t1 t1 t2 t2 t2 t2 t2]';
T = ind2vec(Tc);
targets = full(T);
%SVM

model = svmtrain(Tc,P, '-s 1 -t 0 -d 9 -c 2 -q');
[predict_label, accuracy, dec_values] = svmpredict(Tc,P, model); % test the training data
accuracy = accuracy(1);