how can I teach glcm features with SVM

How can I train with the GLM-specific svm algorithm for brain tumor

[Ahmet Gürbüz]

Example

>> filename='C:\MATLAB\R2017a\bin\dataset\';
>> a=gorsel(filename,0);
    0.0002    8.6622    0.0341

      0.0001    8.9730    0.0279

      0.0001    9.2377    0.0244

      0.0001    9.4267    0.0239

      0.0001    9.5962    0.0217

      0.0001    9.6768    0.0207

      0.0001    9.7512    0.0199

      0.0001    9.7999    0.0193

      0.0001    9.7608    0.0161

      0.0001    9.7153    0.0146

      0.0001    9.6964    0.0156

      0.0001    9.7230    0.0177

      0.0001    9.7560    0.0198

      0.0001    9.8653    0.0178

      0.0001    9.8902    0.0169

[Ahmet Gürbüz]

.m

function [output]=gorsel(i,indis)
  for artis=indis:15
       filename1 = ['C:\MATLAB\R2017a\bin\dataset\' num2str(artis,'%d') '.jpg'];
       input=imread(filename1);
        % figure,imshow(input);
        j=imnoise(input,'salt & pepper',0.02);%image noise
          k=medfilt2(j);%median filter
         filename2 = ['C:\MATLAB\R2017a\bin\Median\median' num2str(artis,'%d') '.jpg'];
         imwrite(k,filename2);
         i=imread(filename2);
         level=graythresh(i);
         bw=imbinarize(i,level);
         filename3= ['C:\MATLAB\R2017a\bin\Otsu\otsu' num2str(artis,'%d') '.jpg'];
         imwrite(bw,filename3);%otsu algorithm
      output=GLCMFeatures(bw); %glcm features for otsu algorithm image
      output=struct2array(output);
      disp(output);

     end

end

[Walter Roberson]

It is recommended that you use fullfile() instead of those concatenations of strings.

[Ahmet Gürbüz]

how can ı do it