Why this classification doesn`t work for tumor brain classification?

in bellow code I have used strcmpi for comparing but it doesn`t compare according the features extractions, any one help?

signal1 = img2(:,:);

[cA1,cH1,cV1,cD1] = dwt2(signal1,'db4');
[cA2,cH2,cV2,cD2] = dwt2(cA1,'db4');
[cA3,cH3,cV3,cD3] = dwt2(cA2,'db4');

DWT_feat = [cA3,cH3,cV3,cD3];
G = pca(DWT_feat);
whos DWT_feat;
whos G;
g = graycomatrix(G);
stats = graycoprops(g,'Contrast Correlation Energy Homogeneity');
Contrast = stats.Contrast;
Correlation = stats.Correlation;
Energy = stats.Energy;
Homogeneity = stats.Homogeneity;
Mean = mean2(G);
Standard_Deviation = std2(G);
Entropy = entropy(G);
RMS = mean2(rms(G));
Skewness = skewness(img);
Variance = mean2(var(double(G)));
a = sum(double(G(:)));
Smoothness = 1-(1/(1+a));
Kurtosis = kurtosis(double(G(:)));
Skewness = skewness(double(G(:)));
% Inverse Difference Movement
m = size(G,1);
n = size(G,2);
in_diff = 0;
for i = 1:m
    for j = 1:n
        temp = G(i,j)./(1+(i-j).^2);
        in_diff = in_diff+temp;
    end
end
IDM = double(in_diff);


%% Classification
feat = [Contrast,Correlation,Energy,Homogeneity, Mean, Standard_Deviation, Entropy, RMS, Variance, Smoothness, Kurtosis, Skewness, IDM];

load Trainset.mat 
xdata = meas;
 group = label;
 species = fitcsvm(xdata,group,'HyperparameterOptimizationOptions',struct('showplot',true),'kernelfunction', 'linear','KernelScale',0.5);
 species = fitcsvm(xdata,group,'HyperparameterOptimizationOptions',struct('showplot',true));
 if strcmpi(species,'MALIGNANT')
     helpdlg(' Malignant Tumor ');
     disp(' Malignant Tumor ');
 elseif strcmpi(species,'BENIGN')
     helpdlg(' Benign Tumor ');
     disp(' Benign Tumor ');
 else
     helpdlg('not clear')
 end