title: Scikits-learn svm SVC simple issue
body: <p>I have a problem which I solved, but I want to know if i am right.</p>
  
  <p>on scikit's learn documentation regarding SVM SVC, there is an example to manage unbalanced data by using weights in classes.</p>
  
  <p>they put an example where the classes weight are informed in svm.SVC()</p>
  
  <pre><code>    wclf = svm.SVC(kernel='linear', class_weight={1: 10})
  </code></pre>
  
  <p>but if a reproduce this command on source code, i get the following error:</p>
  
  <pre><code>    wclf = svm.SVC(kernel='linear', class_weight={1: 10})
      TypeError: __init__() got an unexpected keyword argument 'class_weight'
  </code></pre>
  
  <p>But if put the classes_weight on fit() function the problem is solved:</p>
  
  <pre><code>    wclf.fit(X, y, class_weight={1: 10})
  </code></pre>
  
  <p>am I right about this? did anybody ever had this problem?</p>