title: Interpretation of SVM commands
body: <p>I have trained an SVM model on load_digits() dataset that is part of Sklearn package.It is a multiclass classification problem with 10 classes. Below is my classifier state</p>
  
  <pre><code>svmclf=SVC(kernel='linear',decision_function_shape='ovr',C=1,gamma=1, max_iter=2000)
  </code></pre>
  
  <p>As I am using 'ovr' decision function shape, the model built 10 classifiers. The model gave me 385 support vectors. Are these support vectors are the repository of total support vectors of individual classifier? if so, is there a command that will help me to figure out the support vectors for each classifier individually?</p>
  
  <pre><code>In:svmclf.support_vectors_.shape 
  Out:(385,65)
  </code></pre>
  
  <p>Can you also please advise what is the interpretation of the output of below commands</p>
  
  <pre><code>svmclf.coef_
  svmclf.dual_coef_
  </code></pre>
  
  <p>The shape of svmclf.coef_ is (45,64). I assumed the shape to be (10,64), as we have 10 classifiers and each classifier has (1,64) weight vector.</p>