function noiseResults = noiseVal(d, l, params)


[rows cols] = size(d);

noiseResults = [];

for j = 1:cols
    noise = d;
    for i = 1:rows
        r = rand();
        r = r*2;
        r = r + .5;
        
        noise(i,j) = noise(i,j) + r;
    end
    
    %% train the SVM
    model = svmtrain(l, d, params);

    %% test the SVM
    [predicted_label, accuracy, dec_values] = svmpredict(l, noise, model, '');

    %mserr = crossVal(10, l, d, params);
    
    noiseResults = [noiseResults [j;accuracy(2)]];%;mean(mserr);std(mserr)]];
end