title: Scikit - 3D feature array for SVM
body: <p>I am trying to train an SVM in scikit. I am following the example and tried to adjust it to my 3d feature vectors. 
  I tried the example from the page <a href="http://scikit-learn.org/stable/modules/svm.html" rel="nofollow">http://scikit-learn.org/stable/modules/svm.html</a>
  and it ran through. While bugfixing I came back to the tutorial setup and found this:</p>
  
  <pre><code>X = [[0, 0], [1, 1],[2,2]]
  y = [0, 1,1]
  clf = svm.SVC()
  clf.fit(X, y) 
  </code></pre>
  
  <p>works while </p>
  
  <pre><code>X = [[0, 0,0], [1, 1,1],[2,2,2]]
  y = [0, 1,1]
  clf = svm.SVC()
  clf.fit(X, y)
  </code></pre>
  
  <p>fails with:
  <code>ValueError: X.shape[1] = 2 should be equal to 3, the number of features at training time</code></p>
  
  <p>what is wrong here? It's only one additional dimension...
  Thanks,
  El</p>