title: Multi-Class SVM( one versus all)
body: <p>I know that LIBSVM only allows one-vs-one classification when it comes to multi-class SVM. However, I would like to tweak it a bit to perform one-against-all classification. I have tried to perform one-against-all below. Is this the correct approach?</p>
  
  <p>The code:</p>
  
  <pre><code>TrainLabel;TrainVec;TestVec;TestLaBel;
  u=unique(TrainLabel);
  N=length(u);
  if(N&gt;2)
      itr=1;
      classes=0;
      while((classes~=1)&amp;&amp;(itr&lt;=length(u)))
          c1=(TrainLabel==u(itr));
          newClass=c1;
          model = svmtrain(TrainLabel, TrainVec, '-c 1 -g 0.00154'); 
          [predict_label, accuracy, dec_values] = svmpredict(TestLabel, TestVec, model);
          itr=itr+1;
      end
  itr=itr-1;
  end
  </code></pre>
  
  <p>I might have done some mistakes. I would like to hear some feedback. Thanks.</p>
  
  <p>Second Part: 
  As grapeot said : 
  I need to do Sum-pooling (or voting as a simplified solution) to come up with the final answer. I am not sure how to do it. I need some help on it; I saw the python file but still not very sure. I need some help.</p>