title: Plot scikit-learn (sklearn) SVM decision boundary / surface
body: <p>I am currently performing multi class SVM with linear kernel using python's scikit library. 
  The sample training data and testing data are as given below:</p>
  
  <p>Model data:</p>
  
  <pre><code>x = [[20,32,45,33,32,44,0],[23,32,45,12,32,66,11],[16,32,45,12,32,44,23],[120,2,55,62,82,14,81],[30,222,115,12,42,64,91],[220,12,55,222,82,14,181],[30,222,315,12,222,64,111]]
  y = [0,0,0,1,1,2,2]
  </code></pre>
  
  <p>I want to plot the decision boundary and visualize the datasets. Can someone please help to plot this type of data.</p>
  
  <p>The data given above is just mock data so feel free to change the values.
  It would be helpful if at least if you could suggest the steps that are to followed. 
  Thanks in advance</p>