title: How to obtain features' weights
body: <p>I am dealing with highly imbalanced data set and my idea is to obtain values of feature weights from my <em>libSVM</em> model. As for now I am OK with the linear kernel, where I can obtain feature weights, but when I am using <code>rbf</code> or <code>poly</code>, I fail to reach my objective.</p>
  
  <p>Here I am using <code>sklearn</code> for my model and it's easy to obtain feature weights for linear kernel using <code>.coef_</code>. Can anyone help me to do same thing for <code>rbf</code> or <code>poly</code>? What I've tried to do so far is given below:</p>
  
  <pre><code>svr = SVC(C=10, cache_size=200, class_weight='auto', coef0=0.0, degree=3.0, gamma=0.12,kernel='rbf', max_iter=-1, probability=True, random_state=0,shrinking=True, tol=0.001, verbose=False)
  clf = svr.fit(data_train,target_train)
  print clf.coef_
  </code></pre>