title: How to solve the NaN value in SVM classifier?
body: <p>I use libsvm toolbox to classify multiple class dataset. In my case,
  I have 9 classes. The following is my code:</p>
  
  <pre><code>model = ovrtrainBot(trainLabel, trainData, type);
  
  [predict_label, accuracy, decis_values] = ovrpredictBot(testLabel, testData, model);
  </code></pre>
  
  <p>I set kernel type to <code>"1"</code>, which is polynomial, since I found
  this will give the best classification accuracy. But the problem is 
  the parameter <code>accuracy</code> gives all <code>NaN</code> values in its 3rd row. The 
  parameter <code>"accuracy"</code> shown as follows:</p>
  
  <pre><code>63.63%  92.56% 92.56%  92.56%  92.56%  92.56%   92.56%   92.56%   92.56%
  0.3636  0.0744  0.0744 0.0744  0.0744  0.0744   0.0744   0.0744   0.0744
  NaN      NaN      NaN     NaN     NaN     NaN     NaN      NaN    NaN 
  </code></pre>
  
  <p>If I use kernel <code>t = 0(linear)</code>, the 3rd row of accuracy will all have values, but the classification accuracy is much lower than I use <code>kernel t=1</code>.</p>
  
  <p>Can anyone give me a help to fix the problem?</p>